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awesome-knowledge-injection-in-LLMs
https://github.com/lyyang01/awesome-knowledge-injection-in-LLMs
Last synced: 1 day ago
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knowlege injection with external knowledge (document corpus or other types of knowledge that is different from KB)
- LLaMAIndex
- LangChain
- Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework
- Unified Demonstration Retriever for In-Context Learning
- ChatDB: Augmenting LLMs with Databases as Their Symbolic Memory
- The CALLA Dataset: Probing LLMs' Interactive Knowledge Acquisition from Chinese Medical Literature
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knowledge injection in the pre-training or fine-tuning process
- BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining
- DoctorGLM: Fine-tuning your Chinese Doctor is not a Herculean Task
- ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge
- PMC-LLaMA: Towards Building Open-source Language Models for Medicine
- HuatuoGPT, Towards Taming Language Models To Be a Doctor
- HuatuoGPT, Towards Taming Language Models To Be a Doctor
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knowledge injection with KB
- DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases
- Knowledge Solver: Teaching LLMs to Search for Domain Knowledge from Knowledge Graphs
- KnowledGPT: Enhancing Large Language Models with Retrieval and Storage Access on Knowledge Bases
- MindMap: Knowledge Graph Prompting Sparks Graph of Thoughts in Large Language Models
- Augmenting Black-box LLMs with Medical Textbooks for Clinical Question Answering
- Chain of Knowledge: A Framework for Grounding Large Language Models with Structured Knowledge Bases
- KITLM: Domain-Specific Knowledge InTegration into Language Models for Question Answering
- RET-LLM: Towards a General Read-Write Memory for Large Language Models
- ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings
- Leveraging A Medical Knowledge Graph into Large Language Models for Diagnosis Prediction
- Knowledge-tuning Large Language Models with Structured Medical Knowledge Bases for Reliable Response Generation in Chinese
- Two is Better Than One: Answering Complex Questions by Multiple Knowledge Sources with Generalized Links
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knowledge injection with model self-driving
- Generate rather than Retrieve: Large Language Models are Strong Context Generators
- Least-to-Most Prompting Enables Complex Reasoning in Large Language Models
- Large Language Models Are Reasoning Teachers
- Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-Step
- Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
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knowledge probing benchmarks
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