{"id":17435706,"url":"https://github.com/zjukg/KG-LLM-Papers","last_synced_at":"2025-03-01T08:32:39.848Z","repository":{"id":174570290,"uuid":"652420569","full_name":"zjukg/KG-LLM-Papers","owner":"zjukg","description":"[Paper List] Papers integrating knowledge graphs (KGs) and large language models (LLMs)","archived":false,"fork":false,"pushed_at":"2025-01-03T16:12:53.000Z","size":290,"stargazers_count":1716,"open_issues_count":6,"forks_count":129,"subscribers_count":55,"default_branch":"main","last_synced_at":"2025-02-18T10:02:33.945Z","etag":null,"topics":["awesome","awesome-kg","awesome-llm","awsome-list","commonsense","gpt","knowledge","knowledge-graph","language-models","large-language-models","llm","nlp","paper-list","prompt","survey"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/zjukg.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-06-12T03:26:14.000Z","updated_at":"2025-02-18T08:57:12.000Z","dependencies_parsed_at":"2023-10-20T10:56:28.772Z","dependency_job_id":"e8ae9e75-af84-4cb9-b6c2-ebe8a45eb9db","html_url":"https://github.com/zjukg/KG-LLM-Papers","commit_stats":null,"previous_names":["zjukg/kg-llm-papers"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zjukg%2FKG-LLM-Papers","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zjukg%2FKG-LLM-Papers/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zjukg%2FKG-LLM-Papers/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/zjukg%2FKG-LLM-Papers/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/zjukg","download_url":"https://codeload.github.com/zjukg/KG-LLM-Papers/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240511122,"owners_count":19813224,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["awesome","awesome-kg","awesome-llm","awsome-list","commonsense","gpt","knowledge","knowledge-graph","language-models","large-language-models","llm","nlp","paper-list","prompt","survey"],"created_at":"2024-10-17T10:01:03.680Z","updated_at":"2025-03-01T08:32:39.785Z","avatar_url":"https://github.com/zjukg.png","language":null,"funding_links":[],"categories":["Other Lists","Topics","Tutorials and Notes from Talented People"],"sub_categories":["TeX Lists","LLM \u0026 Knowledge Graph","5. Others"],"readme":"# KG-LLM-Papers\n[![Awesome](https://awesome.re/badge.svg)](https://github.com/zjukg/KG-LLM-Papers) \n[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://github.com/zjukg/KG-LLM-Papers/blob/main/LICENSE)\n![](https://img.shields.io/github/last-commit/zjukg/KG-LLM-Papers?color=green) \n![](https://img.shields.io/badge/PRs-Welcome-red) \n\n\u003eWhat can LLMs do for KGs? Or, in other words, what role can KG play in the era of LLMs?\n\n🙌 This repository collects papers integrating **knowledge graphs (KGs)** and **large language models (LLMs)**.\n\n😎 Welcome to recommend missing papers through **`Pull Requests`**. \n\n\u003c!-- Details of summary and classification of papers are shown in [wiki](https://github.com/zjukg/KG-LLM-Papers/wiki). --\u003e\n\n## 🔔 News\n- **`2025-01` We preprint our Paper [Have We Designed Generalizable Structural Knowledge Promptings? Systematic Evaluation and Rethinking](https://arxiv.org/abs/2501.00244)  [[`Repo`](https://github.com/zjukg/SUBARU)].**\n- **`2024-09` Our paper [MKGL: Mastery of a Three-Word Language](https://openreview.net/forum?id=eqMNwXvOqn) has been accepted by NeurIPS 2024 as a spotlight paper. [[`Repo`](https://github.com/zjukg/MKGL)]**\n- **`2024-07` Our paper [Making Large Language Models Perform Better in Knowledge Graph Completion](https://arxiv.org/abs/2310.06671) has been accepted by ACM MM 2024 as an oral paper. [[`Repo`](https://github.com/zjukg/KoPA)]**\n- **`2024-05` Our paper [Knowledgeable Preference Alignment for LLMs in Domain-specific Question Answering](https://arxiv.org/abs/2311.06503) has been accepted by ACL 2024. [[`Repo`](https://github.com/zjukg/KnowPAT)]**\n- **`2024-02` We preprint our Survey [Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey](http://arxiv.org/abs/2402.05391)  [[`Repo`](https://github.com/zjukg/KG-MM-Survey)].**\n- **`2023-06` We create this repository to maintain a paper list on `Intergrating Knowledge Graphs and Large Language Models`.**\n\n\u003c!--\n*Todo:*\n1. - [ ] `Fine-grained classification of papers`\n2. - [ ] `Update paper project / code`\n3. - [ ] `Wiki page for brief paper introduction`\n--\u003e\n   \n## Content\n\n\n  \n- [📜 Papers](#papers)\n  - [🔖 Surveys](#surveys)\n  - [⚙ Methods](#methods)\n  - [🧰 Resources](#resources-and-benchmarking)\n\n---\n\n##  Papers\n\n### Surveys\n- \\[[arxiv](https://arxiv.org/abs/2402.05391)\\] Knowledge Graphs Meet Multi-Modal Learning: A Comprehensive Survey. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2311.07914)\\] Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2310.07521)\\] Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.04835)\\] On the Evolution of Knowledge Graphs: A Survey and Perspective. `2023.10`\n- \\[[arxiv](https://arxiv.org/pdf/2309.17122)\\] Benchmarking the Abilities of Large Language Models for RDF Knowledge Graph Creation and Comprehension: How Well Do LLMs Speak Turtle? `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2309.01029)\\] Explainability for Large Language Models: A Survey. `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2308.14217)\\] Generations of Knowledge Graphs: The Crazy Ideas and the Business Impact. `2023.08`\n- \\[[arxiv](https://arxiv.org/abs/2308.06374)\\] Large Language Models and Knowledge Graphs: Opportunities and Challenges. `2023.08`\n- \\[[TKDE](https://arxiv.org/pdf/2306.08302)\\] Unifying Large Language Models and Knowledge Graphs: A Roadmap. `2023.06` \\[[Repo](https://github.com/RManLuo/Awesome-LLM-KG)\\]\n- \\[[arxiv](https://arxiv.org/pdf/2306.11489.pdf)\\] ChatGPT is not Enough: Enhancing Large Language Models with Knowledge Graphs for Fact-aware Language Modeling. `2023.06`\n- \\[[arxiv](https://arxiv.org/abs/2211.05994)\\] A Survey of Knowledge-Enhanced Pre-trained Language Models. `2023.05`\n\n\n### Method\n- \\[[EMNLP 2024 findings](https://aclanthology.org/2024.findings-emnlp.524/)\\] Question-guided Knowledge Graph Re-scoring and Injection for Knowledge Graph Question Answering. `2024.11`\n- \\[[EMNLP 2024 findings](https://arxiv.org/abs/2407.11417)\\] SPINACH: SPARQL-Based Information Navigation for Challenging Real-World Questions. `2024.11`\n- \\[[arxiv](https://arxiv.org/pdf/2410.18415)\\] Decoding on Graphs: Faithful and Sound Reasoning on Knowledge Graphs through Generation of Well-Formed Chains. `2024.10`\n- \\[[arxiv](https://arxiv.org/abs/2410.12609)\\] Towards Graph Foundation Models: The Perspective of Zero-shot Reasoning on Knowledge Graphs. `2024.10`\n- \\[[NeurIPS 2024](https://arxiv.org/abs/2410.07526)\\] MKGL: Mastery of a Three-Word Language. `2024.10` \\[[Repo](https://github.com/zjukg/MKGL)\\]\n- \\[[NeurIPS 2024](https://arxiv.org/abs/2402.06861)\\] UrbanKGent: A Unified Large Language Model Agent Framework for Urban Knowledge Graph Construction. `2024.10` \\[[Repo](https://github.com/usail-hkust/UrbanKGent)\\]\n- \\[[NeurIPS 2024](https://arxiv.org/abs/2405.16412)\\] KG-FIT: Knowledge Graph Fine-Tuning Upon Open-World Knowledge. `2024.10` \\[[Repo](https://github.com/pat-jj/KG-FIT)\\]\n- \\[[ICML 2024](https://openreview.net/forum?id=JCG0KTPVYy)\\] Coarse-to-Fine Highlighting: Reducing Knowledge Hallucination in Large Language Models. `2024.10` \\[[Repo](https://github.com/shiliu-egg/ICML2024_COFT)\\]\n- \\[[ACL 2024](https://arxiv.org/abs/2410.02811)\\] SAC-KG: Exploiting Large Language Models as Skilled Automatic Constructors for Domain Knowledge Graphs. `2024.09`\n- \\[[NeurIPS 2024](https://arxiv.org/abs/2405.16806)\\] LLM4EA: Entity Alignment with Noisy Annotations from Large Language Models. `2024.09` \\[[Repo](https://github.com/chensyCN/llm4ea_official)\\]\n- \\[[arxiv](https://arxiv.org/abs/2407.00653)\\] Chain-of-Knowledge: Integrating Knowledge Reasoning into Large Language Models by Learning from Knowledge Graphs. `2024.07`\n- \\[[arxiv](https://arxiv.org/abs/2407.10793)\\] GraphEval: A Knowledge-Graph Based LLM Hallucination Evaluation Framework. `2024.07`\n- \\[[arxiv](https://arxiv.org/abs/2407.10805)\\] Think-on-Graph 2.0: Deep and Interpretable Large Language Model Reasoning with Knowledge Graph-guided Retrieval. `2024.07`\n- \\[[ISWC 2024](https://arxiv.org/abs/2407.16127)\\] Finetuning Generative Large Language Models with Discrimination Instructions for Knowledge Graph Completion. `2024.07`\n- \\[[ACL 2024 findings](https://arxiv.org/abs/2402.16568)\\] Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models. `2024.07`\n- \\[[arxiv](https://arxiv.org/abs/2407.21358)\\] Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs. `2024.07`\n- \\[[NAACL 2024 findings](https://arxiv.org/abs/2310.07793)\\] GenTKG: Generative Forecasting on Temporal Knowledge Graph with Large Language Models. `2024.06`\n- \\[[ACL 2024 findings](https://arxiv.org/abs/2402.11199)\\] Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.03746)\\] Efficient Knowledge Infusion via KG-LLM Alignment. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.18114)\\] Knowledge Graph Enhanced Retrieval-Augmented Generation for Failure Mode and Effects Analysis. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.13862)\\] Knowledge Graph-Enhanced Large Language Models via Path Selection. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.14282)\\] Learning to Plan for Retrieval-Augmented Large Language Models from Knowledge Graphs. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.02962)\\] Docs2KG: Unified Knowledge Graph Construction from Heterogeneous Documents Assisted by Large Language Models. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.02110)\\] UniOQA: A Unified Framework for Knowledge Graph Question Answering with Large Language Model. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.02030)\\] Multimodal Reasoning with Multimodal Knowledge Graph. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.01391)\\] Knowledge Graph in Astronomical Research with Large Language Models: Quantifying Driving Forces in Interdisciplinary Scientific Discovery. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.01238)\\] EffiQA: Efficient Question-Answering with Strategic Multi-Model Collaboration on Knowledge Graphs. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.01145)\\] Explore then Determine: A GNN-LLM Synergy Framework for Reasoning over Knowledge Graph. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2406.00036)\\] EMERGE: Integrating RAG for Improved Multimodal EHR Predictive Modeling. `2024.06`\n- \\[[EPJ Data Science](https://epjdatascience.springeropen.com/articles/10.1140/epjds/s13688-024-00481-2)\\] Glitter or Gold? Deriving Structured Insights from Sustainability Reports via Large Language Models. `2024.06`\n- \\[[arxiv](https://arxiv.org/abs/2405.20455)\\] DepsRAG: Towards Managing Software Dependencies using Large Language Models. `2024.06` \\[[Repo](https://github.com/Mohannadcse/DepsRAG)\\]\n- \\[[arxiv](https://arxiv.org/abs/2405.19877)\\] KNOW: A Real-World Ontology for Knowledge Capture with Large Language Models  `2024.05` \\[[Repo](https://github.com/KnowOntology)\\]\n- \\[[arxiv](https://arxiv.org/abs/2405.14831)\\] HippoRAG: Neurobiologically Inspired Long-Term Memory for Large Language Models  `2024.05` \\[[Repo](https://github.com/OSU-NLP-Group/HippoRAG)\\]\n- \\[[arxiv](https://arxiv.org/abs/2405.14012)\\] Prompt-Time Ontology-Driven Symbolic Knowledge Capture with Large Language Models  `2024.05` \\[[Repo](https://github.com/HaltiaAI/paper-PTODSKC)\\]\n- \\[[arxiv](https://arxiv.org/abs/2405.10288)\\] Timeline-based Sentence Decomposition with In-Context Learning for Temporal Fact Extraction. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.09713)\\] SOK-Bench: A Situated Video Reasoning Benchmark with Aligned Open-World Knowledge. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.06545)\\] Mitigating Hallucinations in Large Language Models via Self-Refinement-Enhanced Knowledge Retrieval. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.06524)\\] Prompting Large Language Models with Knowledge Graphs for Question Answering Involving Long-tail Facts. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.04819)\\] DALK: Dynamic Co-Augmentation of LLMs and KG to answer Alzheimer's Disease Questions with Scientific Literature. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.04756)\\] BiasKG: Adversarial Knowledge Graphs to Induce Bias in Large Language Models. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.04753)\\] AttacKG+:Boosting Attack Knowledge Graph Construction with Large Language Models. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.04180)\\] Sora Detector: A Unified Hallucination Detection for Large Text-to-Video Models. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.03734)\\] FOKE: A Personalized and Explainable Education Framework Integrating Foundation Models, Knowledge Graphs, and Prompt Engineering. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.02738)\\] Relations Prediction for Knowledge Graph Completion using Large Language Models. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.02105)\\] Evaluating Large Language Models for Structured Science Summarization in the Open Research Knowledge Graph. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.01649)\\] Improving Complex Reasoning over Knowledge Graph with Logic-Aware Curriculum Tuning. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2405.00449)\\] RAG-based Explainable Prediction of Road Users Behaviors for Automated Driving using Knowledge Graphs and Large Language Models. `2024.05`\n- \\[[arxiv](https://arxiv.org/abs/2404.19744)\\] PrivComp-KG : Leveraging Knowledge Graph and Large Language Models for Privacy Policy Compliance Verification. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.19234)\\] Multi-hop Question Answering over Knowledge Graphs using Large Language Models. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.19146)\\] Automated Construction of Theme-specific Knowledge Graphs. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.17723)\\] Retrieval-Augmented Generation with Knowledge Graphs for Customer Service Question Answering. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.17000)\\] Evaluating Class Membership Relations in Knowledge Graphs using Large Language Models. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.15923)\\] KGValidator: A Framework for Automatic Validation of Knowledge Graph Construction. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.13865)\\] Context-Enhanced Language Models for Generating Multi-Paper Citations. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.10384)\\] Reasoning on Efficient Knowledge Paths:Knowledge Graph Guides Large Language Model for Domain Question Answering. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.09763)\\] KG-CTG: Citation Generation through Knowledge Graph-guided Large Language Models. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.09077)\\] CuriousLLM: Elevating Multi-Document QA with Reasoning-Infused Knowledge Graph Prompting. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.07677)\\] ODA: Observation-Driven Agent for integrating LLMs and Knowledge Graphs. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.06571)\\] Building A Knowledge Graph to Enrich ChatGPT Responses in Manufacturing Service Discovery. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.04264)\\] Logic Query of Thoughts: Guiding Large Language Models to Answer Complex Logic Queries with Knowledge Graphs. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.03868)\\] Extract, Define, Canonicalize: An LLM-based Framework for Knowledge Graph Construction. `2024.04`\n- \\[[COLM 2024](https://openreview.net/forum?id=dWYRjT501w)\\] Unveiling LLMs: The Evolution of Latent Representations in a Dynamic Knowledge Graph. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.03080)\\] Construction of Functional Materials Knowledge Graph in Multidisciplinary Materials Science via Large Language Model. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.02389)\\] On Linearizing Structured Data in Encoder-Decoder Language Models: Insights from Text-to-SQL. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.01720)\\] Self-Improvement Programming for Temporal Knowledge Graph Question Answering. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.01425)\\] A Preliminary Roadmap for LLMs as Assistants in Exploring, Analyzing, and Visualizing Knowledge Graphs. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.00942)\\] Evaluating the Factuality of Large Language Models using Large-Scale Knowledge Graphs. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.00589)\\] Harnessing the Power of Large Language Model for Uncertainty Aware Graph Processing. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.00209)\\] EventGround: Narrative Reasoning by Grounding to Eventuality-centric Knowledge Graphs. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.14741)\\] Generate-on-Graph: Treat LLM as both Agent and KG in Incomplete Knowledge Graph Question Answering. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2404.16130)\\] From Local to Global: A Graph RAG Approach to Query-Focused Summarization. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2312.15883)\\] HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responses. `2024.04`\n- \\[[arxiv](https://arxiv.org/abs/2403.14950)\\] KnowLA: Enhancing Parameter-efficient Finetuning with Knowledgeable Adaptation. `2024.03`\n- \\[[LREC-COLING 2024](https://arxiv.org/abs/2403.17532)\\] KC-GenRe: A Knowledge-constrained Generative Re-ranking Method Based on Large Language Models for Knowledge Graph Completion. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.14253)\\] K-Act2Emo: Korean Commonsense Knowledge Graph for Indirect Emotional Expression. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.12151)\\] Fusing Domain-Specific Content from Large Language Models into Knowledge Graphs for Enhanced Zero Shot Object State Classification. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.11786)\\] Construction of Hyper-Relational Knowledge Graphs Using Pre-Trained Large Language Models. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.08593)\\] Call Me When Necessary: LLMs can Efficiently and Faithfully Reason over Structured Environments. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.08345)\\] From human experts to machines: An LLM supported approach to ontology and knowledge graph construction. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.07398)\\] Complex Reasoning over Logical Queries on Commonsense Knowledge Graphs. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.07311)\\] Knowledge Graph Large Language Model (KG-LLM) for Link Prediction. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.05881)\\] KG-Rank: Enhancing Large Language Models for Medical QA with Knowledge Graphs and Ranking Techniques. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.04261)\\] Advancing Biomedical Text Mining with Community Challenges. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.03008)\\] Knowledge Graphs as Context Sources for LLM-Based Explanations of Learning Recommendations. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.02966)\\] Evidence-Focused Fact Summarization for Knowledge-Augmented Zero-Shot Question Answering. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.02576)\\] AceMap: Knowledge Discovery through Academic Graph. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.02253)\\] KnowPhish: Large Language Models Meet Multimodal Knowledge Graphs for Enhancing Reference-Based Phishing Detection. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.02014)\\] Unveiling Hidden Links Between Unseen Security Entities. `2024.03`\n- \\[[LREC-COLING 2024](https://arxiv.org/abs/2403.01972)\\] Multi-perspective Improvement of Knowledge Graph Completion with Large Language Models. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.01481)\\] Infusing Knowledge into Large Language Models with Contextual Prompts. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.01395)\\] CR-LT-KGQA: A Knowledge Graph Question Answering Dataset Requiring Commonsense Reasoning and Long-Tail Knowledge. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.01390)\\] Right for Right Reasons: Large Language Models for Verifiable Commonsense Knowledge Graph Question Answering. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.01382)\\] Automatic Question-Answer Generation for Long-Tail Knowledge. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2403.00953)\\] AutoRD: An Automatic and End-to-End System for Rare Disease Knowledge Graph Construction Based on Ontologies-enhanced Large Language Models. `2024.03`\n- \\[[arxiv](https://arxiv.org/abs/2402.17786)\\] Stepwise Self-Consistent Mathematical Reasoning with Large Language Models. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.16568)\\] Two-stage Generative Question Answering on Temporal Knowledge Graph Using Large Language Models. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.15048)\\] Unlocking the Power of Large Language Models for Entity Alignment. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.14382)\\] Enhancing Temporal Knowledge Graph Forecasting with Large Language Models via Chain-of-History Reasoning. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.13750)\\] Breaking the Barrier: Utilizing Large Language Models for Industrial Recommendation Systems through an Inferential Knowledge Graph. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.13593)\\] Knowledge Graph Enhanced Large Language Model Editing. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.12728)\\] Modality-Aware Integration with Large Language Models for Knowledge-based Visual Question Answering. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.12352)\\] Graph-Based Retriever Captures the Long Tail of Biomedical Knowledge. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.11804)\\] LLM as Prompter: Low-resource Inductive Reasoning on Arbitrary Knowledge Graphs. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.11541)\\] Counter-intuitive: Large Language Models Can Better Understand Knowledge Graphs Than We Thought. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.11441)\\] InfuserKI: Enhancing Large Language Models with Knowledge Graphs via Infuser-Guided Knowledge Integration. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.11323)\\] Towards Development of Automated Knowledge Maps and Databases for Materials Engineering using Large Language Models. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.11163)\\] KG-Agent: An Efficient Autonomous Agent Framework for Complex Reasoning over Knowledge Graph. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.11034)\\] PAT-Questions: A Self-Updating Benchmark for Present-Anchored Temporal Question-Answering. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.10779)\\] A Condensed Transition Graph Framework for Zero-shot Link Prediction with Large Language Models. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.09911)\\] Enhancing Large Language Models with Pseudo- and Multisource- Knowledge Graphs for Open-ended Question Answering. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.07630)\\] G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.07148)\\] X-LoRA: Mixture of Low-Rank Adapter Experts, a Flexible Framework for Large Language Models with Applications in Protein Mechanics and Design. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.07016)\\] REALM: RAG-Driven Enhancement of Multimodal Electronic Health Records Analysis via Large Language Models. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.06764)\\] GLaM: Fine-Tuning Large Language Models for Domain Knowledge Graph Alignment via Neighborhood Partitioning and Generative Subgraph Encoding. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.05862)\\] Let Your Graph Do the Talking: Encoding Structured Data for LLMs. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.05135)\\] CADReN: Contextual Anchor-Driven Relational Network for Controllable Cross-Graphs Node Importance Estimation. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.04978)\\] An Enhanced Prompt-Based LLM Reasoning Scheme via Knowledge Graph-Integrated Collaboration. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.04627)\\] SPARQL Generation: an analysis on fine-tuning OpenLLaMA for Question Answering over a Life Science Knowledge Graph. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.03339)\\] Interplay of Semantic Communication and Knowledge Learning. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.03299)\\] GUARD: Role-playing to Generate Natural-language Jailbreakings to Test Guideline Adherence of Large Language Models. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.02130)\\] Rendering Graphs for Graph Reasoning in Multimodal Large Language Models. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.01730)\\] Evaluating LLM -- Generated Multimodal Diagnosis from Medical Images and Symptom Analysis. `2024.02`\n- \\[[EACL 2024](https://arxiv.org/abs/2402.01729)\\] Contextualization Distillation from Large Language Model for Knowledge Graph Completion. `2024.02`\n- \\[[EACL 2024](https://arxiv.org/abs/2402.01495)\\] A Comparative Analysis of Conversational Large Language Models in Knowledge-Based Text Generation. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2402.00414)\\] Prompt-Time Symbolic Knowledge Capture with Large Language Models. `2024.02` \\[[Repo](https://github.com/HaltiaAI/paper-PTSKC)\\]\n- \\[[arxiv](https://arxiv.org/abs/2402.00292)\\] Effective Bug Detection in Graph Database Engines: An LLM-based Approach. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2401.16960)\\] Two Heads Are Better Than One: Integrating Knowledge from Knowledge Graphs and Large Language Models for Entity Alignment. `2024.01`\n- \\[[arxiv](https://arxiv.org/abs/2401.14640)\\] Benchmarking Large Language Models in Complex Question Answering Attribution using Knowledge Graphs. `2024.01`\n- \\[[arxiv](https://arxiv.org/abs/2401.13444)\\] Clue-Guided Path Exploration: An Efficient Knowledge Base Question-Answering Framework with Low Computational Resource Consumption. `2024.01`\n- \\[[AAAI 2024](https://arxiv.org/abs/2401.12863)\\] KAM-CoT: Knowledge Augmented Multimodal Chain-of-Thoughts Reasoning. `2024.01`\n- \\[[arxiv](https://arxiv.org/abs/2401.12671)\\] Context Matters: Pushing the Boundaries of Open-Ended Answer Generation with Graph-Structured Knowledge Context. `2024.01`\n- \\[[arxiv](https://arxiv.org/abs/2401.08517)\\] Supporting Student Decisions on Learning Recommendations: An LLM-Based Chatbot with Knowledge Graph Contextualization for Conversational Explainability and Mentoring. `2024.01`\n- \\[[arxiv](https://arxiv.org/abs/2401.07237)\\] Distilling Event Sequence Knowledge From Large Language Models. `2024.01`\n- \\[[ACL 24](https://arxiv.org/abs/2401.06853)\\] Large Language Models Can Learn Temporal Reasoning. `2024.01` \\[[Repo](https://github.com/xiongsiheng/TG-LLM)\\]\n- \\[[arxiv](https://arxiv.org/abs/2401.06072)\\] Chain of History: Learning and Forecasting with LLMs for Temporal Knowledge Graph Completion. `2024.01`\n- \\[[arxiv](https://arxiv.org/abs/2401.04507)\\] TechGPT-2.0: A large language model project to solve the task of knowledge graph construction. `2024.01` \\[[Repo](https://github.com/neukg/TechGPT-2.0)\\]\n- \\[[arxiv](https://arxiv.org/abs/2401.01711)\\] Evaluating Large Language Models in Semantic Parsing for Conversational Question Answering over Knowledge Graphs. `2024.01`\n- \\[[arxiv](https://arxiv.org/abs/2401.00761)\\] The Earth is Flat? Unveiling Factual Errors in Large Language Models. `2024.01`\n- \\[[arxiv](https://arxiv.org/abs/2401.00426)\\] keqing: knowledge-based question answering is a nature chain-of-thought mentor of LLM. `2024.01`\n- \\[[arxiv](https://arxiv.org/abs/2401.03158)\\] Quartet Logic: A Four-Step Reasoning (QLFR) framework for advancing Short Text Classification. `2024.01`\n- \\[[arxiv](https://arxiv.org/abs/2312.17269)\\] Conversational Question Answering with Reformulations over Knowledge Graph. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.15883)\\] Think and Retrieval: A Hypothesis Knowledge Graph Enhanced Medical Large Language Models. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.15880)\\] KnowledgeNavigator: Leveraging Large Language Models for Enhanced Reasoning over Knowledge Graph. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.11813)\\] Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.11785)\\] Zero-Shot Fact-Checking with Semantic Triples and Knowledge Graphs. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.11539)\\] KGLens: A Parameterized Knowledge Graph Solution to Assess What an LLM Does and Doesn't Know. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.11282)\\] LLM-ARK: Knowledge Graph Reasoning Using Large Language Models via Deep Reinforcement Learning. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.09126)\\] Towards Trustworthy AI Software Development Assistance. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.06185)\\] KnowGPT: Black-Box Knowledge Injection for Large Language Models. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.05276)\\] Making Large Language Models Better Knowledge Miners for Online Marketing with Progressive Prompting Augmentation. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.03749)\\] Conceptual Engineering Using Large Language Models. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.03022)\\] Beyond Isolation: Multi-Agent Synergy for Improving Knowledge Graph Construction. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.01954)\\] Zero- and Few-Shots Knowledge Graph Triplet Extraction with Large Language Models. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2312.00353)\\] On Exploring the Reasoning Capability of Large Language Models with Knowledge Graphs. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2311.17330)\\] Biomedical knowledge graph-optimized prompt generation for large language models. `2023.11` \\[[Repo](https://github.com/BaranziniLab/KG_RAG)\\]\n- \\[[arxiv](https://arxiv.org/abs/2311.16137)\\] A Graph-to-Text Approach to Knowledge-Grounded Response Generation in Human-Robot Interaction. `2023.11`\n- \\[[EMNLP 2023](http://arxiv.org/abs/2311.01150)\\]Revisiting the Knowledge Injection Frameworks. `2023.12`\n- \\[[EMNLP 2023](https://aclanthology.org/2023.emnlp-main.143)\\]Does the Correctness of Factual Knowledge Matter for Factual Knowledge-Enhanced Pre-trained Language Models? `2023.12`\n- \\[[EMNLP 2023](https://aclanthology.org/2023.emnlp-main.228/)\\]ReasoningLM: Enabling Structural Subgraph Reasoning in Pre-trained Language Models for Question Answering over Knowledge Graph. `2023.12`\n- \\[[EMNLP 2023 Findings](https://aclanthology.org/2023.findings-emnlp.580/)\\]KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completion. `2023.12`\n- \\[[arxiv](https://arxiv.org/abs/2311.01862)\\] $R^3$-NL2GQL: A Hybrid Models Approach for for Accuracy Enhancing and Hallucinations Mitigation. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2311.13314)\\] Mitigating Large Language Model Hallucinations via Autonomous Knowledge Graph-based Retrofitting. `2023.11`\n- \\[[EMNLP 2023](https://arxiv.org/abs/2305.14202)\\] Fine-tuned LLMs Know More, Hallucinate Less with Few-Shot Sequence-to-Sequence Semantic Parsing over Wikidata. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2311.09841)\\] Leveraging LLMs in Scholarly Knowledge Graph Question Answering. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2311.06503)\\] Knowledgeable Preference Alignment for LLMs in Domain-specific Question Answering. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2311.03837)\\] OLaLa: Ontology Matching with Large Language Models. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2311.02956)\\] In-Context Learning for Knowledge Base Question Answering for Unmanned Systems based on Large Language Models. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2311.01266)\\] Let's Discover More API Relations: A Large Language Model-based AI Chain for Unsupervised API Relation Inference. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2311.00444)\\] Form follows Function: Text-to-Text Conditional Graph Generation based on Functional Requirements. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2310.02166)\\] Large Language Models Meet Knowledge Graphs to Answer Factoid Questions. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.07008)\\] Answer Candidate Type Selection: Text-to-Text Language Model for Closed Book Question Answering Meets Knowledge Graphs. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2311.00287)\\] Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.20170)\\] DIVKNOWQA: Assessing the Reasoning Ability of LLMs via Open-Domain Question Answering over Knowledge Base and Text. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.19998)\\] Generative retrieval-augmented ontologic graph and multi-agent strategies for interpretive large language model-based materials design. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.18951)\\] A Multimodal Ecological Civilization Pattern Recommendation Method Based on Large Language Models and Knowledge Graph. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.18356)\\] LoRAShear: Efficient Large Language Model Structured Pruning and Knowledge Recovery. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.16421)\\] Graph Agent: Explicit Reasoning Agent for Graphs. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.14174)\\] An In-Context Schema Understanding Method for Knowledge Base Question Answering. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.13023)\\] GraphGPT: Graph Instruction Tuning for Large Language Models. `2023.10`\n- \\[[EMNLP 2023 Findings](https://arxiv.org/abs/2310.11638)\\] Systematic Assessment of Factual Knowledge in Large Language Models. `2023.10`\n- \\[[EMNLP 2023 Findings](https://arxiv.org/abs/2310.11220)\\] KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.10445)\\] MechGPT, a language-based strategy for mechanics and materials modeling that connects knowledge across scales, disciplines and modalities. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.09089)\\] Qilin-Med: Multi-stage Knowledge Injection Advanced Medical Large Language Model. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.08975)\\] ChatKBQA: A Generate-then-Retrieve Framework for Knowledge Base Question Answering with Fine-tuned Large Language Models. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.08365)\\] From Large Language Models to Knowledge Graphs for Biomarker Discovery in Cancer. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.06671)\\] Making Large Language Models Perform Better in Knowledge Graph Completion. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.08279)\\] CP-KGC: Constrained-Prompt Knowledge Graph Completion with Large Language Models. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.07170)\\] PHALM: Building a Knowledge Graph from Scratch by Prompting Humans and a Language Model. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.03269)\\] InstructProtein: Aligning Human and Protein Language via Knowledge Instruction. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2310.01290)\\] Knowledge Crosswords: Geometric Reasoning over Structured Knowledge with Large Language Models. `2023.10`\n- \\[[ICLR 2024](https://arxiv.org/abs/2310.01061)\\] Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning. `2023.10` \\[[Repo](https://github.com/RManLuo/reasoning-on-graphs)\\]\n- \\[[arxiv](https://arxiv.org/abs/2310.00299)\\] RelBERT: Embedding Relations with Language Models. `2023.10`\n- \\[[arxiv](https://arxiv.org/abs/2309.17122)\\] Benchmarking the Abilities of Large Language Models for RDF Knowledge Graph Creation and Comprehension: How Well Do LLMs Speak Turtle?. `2023.09`\n- \\[[arxiv](https://arxiv.org/pdf/2309.16134)\\] Let's Chat to Find the APIs: Connecting Human, LLM and Knowledge Graph through AI Chain. `2023.09`\n- \\[[arxiv](https://arxiv.org/pdf/2309.15427)\\] Graph Neural Prompting with Large Language Models. `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2309.12132)\\] A knowledge representation approach for construction contract knowledge modeling. `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2309.11206)\\] Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering. `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2309.08594)\\] \"Merge Conflicts!\" Exploring the Impacts of External Distractors to Parametric Knowledge Graphs. `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2309.00240)\\] FactLLaMA: Optimizing Instruction-Following Language Models with External Knowledge for Automated Fact-Checking. `2023.09`\n- \\[[arxiv](https://arxiv.org/pdf/2309.01538)\\] ChatRule: Mining Logical Rules with Large Language Models for Knowledge Graph Reasoning. `2023.09`\n- \\[[AAAI 2024](https://arxiv.org/abs/2309.04695)\\] Code-Style In-Context Learning for Knowledge-Based Question Answering. `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2309.04565)\\] Unleashing the Power of Graph Learning through LLM-based Autonomous Agents. `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2309.04175)\\] Knowledge-tuning Large Language Models with Structured Medical Knowledge Bases for Reliable Response Generation in Chinese. `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2309.03118)\\] Knowledge Solver: Teaching LLMs to Search for Domain Knowledge from Knowledge Graphs. `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2308.14429)\\] Biomedical Entity Linking with Triple-aware Pre-Training. `2023.08`\n- \\[[arxiv](https://arxiv.org/abs/2308.13916)\\] Exploring Large Language Models for Knowledge Graph Completion. `2023.08` \\[[Repo](https://github.com/yao8839836/kg-llm)\\]\n- \\[[arxiv](https://arxiv.org/abs/2308.16622)\\] Developing a Scalable Benchmark for Assessing Large Language Models in Knowledge Graph Engineering. `2023.08`\n- \\[[arxiv](https://arxiv.org/abs/2308.14321)\\] Leveraging A Medical Knowledge Graph into Large Language Models for Diagnosis Prediction. `2023.08`\n- \\[[arxiv](https://arxiv.org/abs/2308.12028)\\] LKPNR: LLM and KG for Personalized News Recommendation Framework. `2023.08`\n- \\[[arxiv](https://arxiv.org/abs/2308.11730)\\] Knowledge Graph Prompting for Multi-Document Question Answering. `2023.08`\n- \\[[arxiv](https://arxiv.org/abs/2308.10168)\\] Head-to-Tail: How Knowledgeable are Large Language Models (LLM)? A.K.A. Will LLMs Replace Knowledge Graphs?. `2023.08`\n- \\[[arxiv](https://arxiv.org/abs/2308.09729)\\] MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models. `2023.08`\n- \\[[arxiv](https://arxiv.org/abs/2308.00081)\\] Towards Semantically Enriched Embeddings for Knowledge Graph Completion. `2023.07`\n- \\[[TKDE 2024](https://arxiv.org/abs/2307.11772)\\] AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Models. `2023.07`\n- \\[[arxiv](https://arxiv.org/abs/2307.07312)\\] Using Large Language Models for Zero-Shot Natural Language Generation from Knowledge Graphs. `2023.07`\n- \\[[ICLR 2024](https://arxiv.org/abs/2307.07697)\\] Think-on-Graph: Deep and Responsible Reasoning of Large Language Model with Knowledge Graph. `2023.07`\n- \\[[SIGKDD 2024 Explorations](https://arxiv.org/abs/2307.03393)\\] Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs. `2023.07`\n- \\[[arxiv](https://arxiv.org/abs/2307.05722)\\] Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations. `2023.07`\n- \\[[arxiv](https://arxiv.org/abs/2307.02738)\\] RecallM: An Architecture for Temporal Context Understanding and Question Answering. `2023.07`\n- \\[[arxiv](https://arxiv.org/abs/2307.06917)\\] LLM-assisted Knowledge Graph Engineering: Experiments with ChatGPT. `2023.07`\n- \\[[arxiv](https://arxiv.org/abs/2307.01128)\\] Iterative Zero-Shot LLM Prompting for Knowledge Graph Construction. `2023.07`\n- \\[[arxiv](https://arxiv.org/abs/2306.10241)\\] Snowman: A Million-scale Chinese Commonsense Knowledge Graph Distilled from Foundation Model\n. `2023.06`\n- \\[[arxiv](https://arxiv.org/pdf/2306.04136.pdf)\\] Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering. `2023.06`\n- \\[[arxiv](https://arxiv.org/abs/2306.10723)\\] Fine-tuning Large Enterprise Language Models via Ontological Reasoning. `2023.06`\n- \\[[NeurIPS 2023](https://arxiv.org/abs/2305.18395)\\] Knowledge-Augmented Reasoning Distillation for Small Language Models in Knowledge-Intensive Tasks. `2023.05`\n- \\[[arxiv](https://arxiv.org/pdf/2305.04676)\\] Enhancing Knowledge Graph Construction Using Large Language Models. `2023.05`\n- \\[[arxiv](https://arxiv.org/abs/2305.03513)\\] ChatGraph: Interpretable Text Classification by Converting ChatGPT Knowledge to Graphs. `2023.05`\n- \\[[ACL 2023](https://arxiv.org/abs/2305.06590)\\] FactKG: Fact Verification via Reasoning on Knowledge Graphs. `2023.05`\n- \\[[arxiv](https://arxiv.org/abs/2304.05973)\\] HiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented Prompting. `2023.04`\n- \\[[EMNLP 2023](https://arxiv.org/abs/2305.09645)\\] StructGPT: A General Framework for Large Language Model to Reason over Structured Data. `2023.05`\n- \\[[ICLR 2024](https://arxiv.org/abs/2305.19523)\\] Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning. `2023.05`\n- \\[[arxiv](https://arxiv.org/abs/2305.13168)\\] LLMs for Knowledge Graph Construction and Reasoning: Recent Capabilities and Future Opportunities. `2023.05` \\[[Repo](https://github.com/zjunlp/AutoKG)\\]\n- \\[[NeurIPS 2023](https://arxiv.org/abs/2305.10037)\\] Can Language Models Solve Graph Problems in Natural Language? `2023.05`\n- \\[[arxiv](https://arxiv.org/abs/2305.09858)\\] Knowledge Graph Completion Models are Few-shot Learners: An Empirical Study of Relation Labeling in E-commerce with LLMs. `2023.05`\n- \\[[arxiv](https://arxiv.org/abs/2305.16755)\\] Can large language models generate salient negative statements? `2023.05`\n- \\[[arxiv](https://arxiv.org/abs/2305.15066)\\] GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking. `2023.05`\n- \\[[arxiv](https://arxiv.org/abs/2305.01157)\\] Complex Logical Reasoning over Knowledge Graphs using Large Language Models. `2023.05`  \\[[Repo](https://github.com/Akirato/LLM-KG-Reasoning/tree/main)\\]\n- \\[[arxiv](https://arxiv.org/abs/2305.00050)\\] Causal Reasoning and Large Language Models: Opening a New Frontier for Causality. `2023.04`\n- \\[[arxiv](https://arxiv.org/abs/2303.05279)\\] Can large language models build causal graphs? `2023.04`\n- \\[[arxiv](https://arxiv.org/abs/2304.05774)\\] Using Multiple RDF Knowledge Graphs for Enriching ChatGPT Responses. `2023.04`\n- \\[[arxiv](https://arxiv.org/abs/2304.11116)\\] Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT. `2023.04`\n- \\[[arxiv](https://arxiv.org/abs/2304.02711)\\] Structured prompt interrogation and recursive extraction of semantics (SPIRES): A method for populating knowledge bases using zero-shot learning. `2023.04` \\[[Repo](https://github.com/monarch-initiative/ontogpt)\\]\n\n\n### Resources and Benchmarking\n- \\[[arxiv](https://arxiv.org/abs/2404.13207)\\] STaRK: Benchmarking LLM Retrieval on Textual and Relational Knowledge Bases. `2024.04` \\[[Repo](https://github.com/snap-stanford/stark)\\]\n- \\[[arxiv](https://arxiv.org/abs/2402.06341)\\] RareBench: Can LLMs Serve as Rare Diseases Specialists?. `2024.02`\n- \\[[arxiv](https://arxiv.org/abs/2401.14640)\\] Benchmarking Large Language Models in Complex Question Answering Attribution using Knowledge Graphs. `2024.01`\n- \\[[ACL 24](https://arxiv.org/abs/2401.06853)\\] Large Language Models Can Learn Temporal Reasoning. `2024.01` \\[[Repo](https://github.com/xiongsiheng/TG-LLM)\\]\n- \\[[arxiv](https://arxiv.org/abs/2311.09174)\\] AbsPyramid: Benchmarking the Abstraction Ability of Language Models with a Unified Entailment Graph. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2311.07509)\\] A Benchmark to Understand the Role of Knowledge Graphs on Large Language Model's Accuracy for Question Answering on Enterprise SQL Databases. `2023.11`\n- \\[[arxiv](https://arxiv.org/abs/2310.05634)\\] Towards Verifiable Generation: A Benchmark for Knowledge-aware Language Model Attribution. `2023.10`\n- \\[[EMNLP 2023](https://arxiv.org/abs/2310.15517)\\] MarkQA: A large scale KBQA dataset with numerical reasoning. `2023.10`\n- \\[[CIKM 2023](https://arxiv.org/abs/2306.14704)\\] Ontology Enrichment from Texts: A Biomedical Dataset for Concept Discovery and Placement. `2023.06`\n- \\[[arxiv](https://arxiv.org/abs/2306.05783)\\] Xiezhi: An Ever-Updating Benchmark for Holistic Domain Knowledge Evaluation. `2023.06`\n- \\[[AACL 2023 System Demonstrations](https://arxiv.org/abs/2210.00305)\\] LambdaKG: A Library for Pre-trained Language Model-Based Knowledge Graph Embeddings `2023.03` \\[[Repo](http://47.92.96.190:9001/)\\]\n- \\[[arxiv](https://arxiv.org/abs/2309.11669)\\] Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation. `2023.09`\n- \\[[arxiv](https://arxiv.org/abs/2310.08365)\\] From Large Language Models to Knowledge Graphs for Biomarker Discovery in Cancer. `2023.10`\n- \\[[ISWC 2023](https://arxiv.org/abs/2308.02357)\\] Text2KGBench: A Benchmark for Ontology-Driven Knowledge Graph Generation from Text. `2023.08`\n\n\n\n## Contribution\n### 👥 Contributors\n\n\u003ca href=\"https://github.com/zjukg/KG-LLM-Papers/graphs/contributors\"\u003e\n  \u003cimg src=\"https://contrib.rocks/image?repo=zjukg/KG-LLM-Papers\" /\u003e\n\u003c/a\u003e\n\n### 🎉 Contributing ( welcome ! )\n\n- ✨ Add a new paper or update an existing KG-related LLM paper.\n- 🧐 Use the same format as existing entries to describe the work.\n- 😄 A very brief explanation why you think a paper should be added or updated is recommended (Not Neccessary) via **`Adding Issues`** or **`Pull Requests`**.\n\n**Don't worry if you put something wrong, they will be fixed for you. Just feel free to contribute and promote your awesome work here! 🤩 We'll get back to you in time ~ 😉**\n\n![Star History Chart](https://api.star-history.com/svg?repos=zjukg/KG-LLM-Papers\u0026type=Date)\n\n## 🤝 Cite:\nIf this Repo is helpful to you, please consider citing our paper. We would greatly appreciate it :)\n```bigquery\n@article{DBLP:journals/corr/abs-2311-06503,\n  author       = {Yichi Zhang and\n                  Zhuo Chen and\n                  Yin Fang and\n                  Lei Cheng and\n                  Yanxi Lu and\n                  Fangming Li and\n                  Wen Zhang and\n                  Huajun Chen},\n  title        = {Knowledgeable Preference Alignment for LLMs in Domain-specific Question\n                  Answering},\n  journal      = {CoRR},\n  volume       = {abs/2311.06503},\n  year         = {2023}\n}\n```\n```bigquery\n@article{DBLP:journals/corr/abs-2310-06671,\n  author       = {Yichi Zhang and\n                  Zhuo Chen and\n                  Wen Zhang and\n                  Huajun Chen},\n  title        = {Making Large Language Models Perform Better in Knowledge Graph Completion},\n  journal      = {CoRR},\n  volume       = {abs/2310.06671},\n  year         = {2023}\n}\n```\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzjukg%2FKG-LLM-Papers","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzjukg%2FKG-LLM-Papers","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzjukg%2FKG-LLM-Papers/lists"}