https://github.com/zyzhangustc/mellm
공식 코드MELLM: Exploring LLM-Powered Micro-Expression Understanding Enhanced by Subtle Motion Perception
Papers with Code 아카이브
Large Language Model
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zyzisastudyreallyhardguy/llm4sd
공식 코드Large Language Models for Scientific Synthesis, Inference and Explanation
https://github.com/zz1358m/mcts-ahd-master
공식 코드Monte Carlo Tree Search for Comprehensive Exploration in LLM-Based Automatic Heuristic Design
https://github.com/zzoliman/covid-vaccine-misinfo-mic
공식 코드https://gitlab.com/sphelps/llm-cooperation
공식 코드https://gitlab.irlab.org/irlab/cabuxa
공식 코드Conversations in Galician: a Large Language Model for an Underrepresented Language
https://huggingface.co/aminhaeri/risk-embed
공식 코드Generative AI Enhanced Financial Risk Management Information Retrieval
https://huggingface.co/emilgoh/mistral-verilog
공식 코드From English to ASIC: Hardware Implementation with Large Language Model
https://huggingface.co/jslin09/bloom-560m-finetuned-fraud
공식 코드Legal Documents Drafting with Fine-Tuned Pre-Trained Large Language Model
https://huggingface.co/mims-harvard/ToolRAG-T1-GTE-Qwen2-1.5B
공식 코드TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools
https://huggingface.co/mims-harvard/TxAgent-T1-Llama-3.1-8B
공식 코드TxAgent: An AI Agent for Therapeutic Reasoning Across a Universe of Tools
https://zenodo.org/record/10500594
공식 코드https://github.com/1171-jpg/brainteaser
BRAINTEASER: Lateral Thinking Puzzles for Large Language Models
https://github.com/2023-MindSpore-1/ms-code-16/tree/main/advanced_east
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
https://github.com/2023-MindSpore-1/ms-code-224/tree/main/advanced_east
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
https://github.com/2023-MindSpore-4/Code10/tree/main/DeepText
https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/glm2
WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/codegen
CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
https://github.com/2024-MindSpore-1/Code2/tree/main/model-1/dpr
Fine-tune the Entire RAG Architecture (including DPR retriever) for Question-Answering
https://github.com/2024-MindSpore-1/Code4/tree/main/DeepText
https://github.com/2024-MindSpore-1/Code5/tree/main/advanced_east
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
https://github.com/2024-MindSpore-1/Code6/tree/main/advanced_east
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
https://github.com/42Shawn/LLaVA-PruMerge
LLaVA-PruMerge: Adaptive Token Reduction for Efficient Large Multimodal Models
https://github.com/AIM-Intelligence/Automated-Multi-Turn-Jailbreaks
LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet
https://github.com/AMAP-ML/RealQA
https://github.com/Anna-Bele/LLM_MCTS_Search
Compiler Optimization via LLM Reasoning for Efficient Model Serving
https://github.com/ArionDas/Generative_AI_Research
Retrieval-Augmented Generation for AI-Generated Content: A Survey
https://github.com/AyeshaAmjad0828/Unstructured-Data-Extraction
An agentic system with reinforcement-learned subsystem improvements for parsing form-like documents
https://github.com/BYU-PCCL/z-machine-games
https://github.com/CRIPAC-DIG/RecTextAttack
Stealthy Attack on Large Language Model based Recommendation
https://github.com/Cloud-CV/visual-chatbot
https://github.com/DIRECT-BIT/SRA-MCTS
CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
https://github.com/DYEvaLab/EvalMuse
Seedream 2.0: A Native Chinese-English Bilingual Image Generation Foundation Model
https://github.com/DevSinghSachan/unsupervised-passage-reranking
End-to-End Training of Neural Retrievers for Open-Domain Question Answering
https://github.com/EkaterinaXie/LiteVAR
Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction
https://github.com/ElectricAlexis/NotaGen
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.