{"id":19571204,"url":"https://github.com/skywardai/paper_gallery","last_synced_at":"2026-03-19T10:33:16.506Z","repository":{"id":255643695,"uuid":"850845211","full_name":"SkywardAI/paper_gallery","owner":"SkywardAI","description":"Papers gallery for using LLMs ability over 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The papers gallery\n\nThis directory contains the papers that as reference for the project.\n\n|No|Title|Studio Lab|Kaggle|Colab|Description|Researcher|\n|---|---|---|---|---|---|---|\n|1|[Text2SQL is Not Enough: Unifying AI and Databases with TAG](text2SQL/2408.14717v1.pdf)||||Answering natural language questions over databases|[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n|2|[LOTUS: Enabling Semantic Queries with LLMs Over Tables of Unstructured and Structured Data](mimic_paper/LOTUS.pdf)||||Answering natural language questions over databases|[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n\n# Medical\n\n![](img/MIMIC_Mind%20Map.svg)\n\n## mimic-iv paper\n\n|No|Title|Studio Lab|Kaggle|Colab|Description|Researcher|\n|---|---|---|---|---|---|---|\n|1|[MIMIC-Extract: A Data Extraction, Preprocessing, and Representation Pipeline for MIMIC-III](mimic_paper/MIMIC-Extract.pdf)|||||[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n|2|[Democratizing EHR analyses with FIDDLE: a flexible data- driven preprocessing pipeline for structured clinical data](mimic_paper/FIDDLE.pdf)|||||[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n|3|[An Extensive Data Processing Pipeline for MIMIC-IV](mimic_paper/MIMICIV%20Pipeline.pdf)||||Basic structure of data extract pipeline|[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n|4|[Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events](mimic_paper/Event%20Stream%20GPT.pdf)|||||[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n|5|[INTERPOLATION-PREDICTION NETWORKS FOR IRREGULARLY SAMPLED TIME SERIES](mimic_paper/IP-Net.pdf)|||||[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n|6|[MULTI-TIME ATTENTION NETWORKS FOR IRREGULARLY SAMPLED TIME SERIES](mimic_paper/mTAN.pdf)|||||[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n|7|[Heteroscedastic Temporal Variational Autoencoder For Irregularly Sampled Time Series](mimic_paper/HeTVAE.pdf)|||||[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n|8|[Multitask learning and benchmarking with clinical time series data](mimic_paper/MIMIC-III%20Benchmarking.pdf)|||||[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n|9|[Using Clinical Notes with Time Series Data for ICU Management](mimic_paper/Fusion.pdf)|||||[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n|10|[Predicting in-hospital mortality by combining clinical notes with time-series data](mimic_paper/BERT.pdf)|||||[Bowen](https://github.com/Aisuko), [Yuwei](https://github.com/wangyuweikiwi)|\n\n\n## mimic-iv datasets\n\n|No|Title|List on Kaggle|Huggingface|Description|Researcher|\n|---|---|---|---|---|---|\n|1|Raw MIMIC-IV v1.0|[![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/code/aisuko/pre-download-mimic-iv-v1-0-dataset)||Private|[Yuwei](https://github.com/wangyuweikiwi)|\n|2|Raw MIMIC-IV v2.0|[![Kaggle](https://kaggle.com/static/images/open-in-kaggle.svg)](https://www.kaggle.com/datasets/skywardai/mimic-iv-classification-regression-tasks/data)||Public|[Yuwei](https://github.com/wangyuweikiwi)|\n|3|Raw MIMIC-IV v2.0||[![Huggingface](https://huggingface.co/datasets/huggingface/badges/resolve/main/dataset-on-hf-sm-dark.svg)](https://huggingface.co/datasets/aisuko/mimic_iv_classification_regression_tasks)|Public|[Yuwei](https://github.com/wangyuweikiwi)|\n\n\n\n\n# Security\n\n## Machine unlearning\n\n|No|Title|Studio Lab|Kaggle|Colab|Description|Researcher|\n|---|---|---|---|---|---|---|\n|1|[Machine Unlearning](security/1912.03817v3.pdf)||||A mechanism that user can remove harmful data from llm in real time|Arjuna|\n|2|[Does Refusal Training in LLMs Generalize to the Past Tense?](security/2407.11969v2.pdf)||||LLM attack|[Tyson](https://github.com/Murkeee)|\n\n\n# References\n\n* https://huggingface.co/datasets/huggingface/badges/blob/main/README.md?code=true\n* https://github.com/Aisuko/generative-ai\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fskywardai%2Fpaper_gallery","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fskywardai%2Fpaper_gallery","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fskywardai%2Fpaper_gallery/lists"}