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Large Language Model

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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/openbmb/ultrarag

공식 코드

UltraRAG: A Modular and Automated Toolkit for Adaptive Retrieval-Augmented Generation

https://github.com/openbmb/viscpm

공식 코드

Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages

https://github.com/openbmb/visrag

공식 코드

VisRAG: Vision-based Retrieval-augmented Generation on Multi-modality Documents

https://github.com/opendatalab/OHR-Bench

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OCR Hinders RAG: Evaluating the Cascading Impact of OCR on Retrieval-Augmented Generation

https://github.com/opendatalab/OmniDocBench

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OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations

https://github.com/opendatalab/openhueval

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OpenHuEval: Evaluating Large Language Model on Hungarian Specifics

https://github.com/opendfm/bai-scieval

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SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific Research

https://github.com/opendfm/rememberer

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Large Language Models Are Semi-Parametric Reinforcement Learning Agents

https://github.com/opendfm/scieval

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SciEval: A Multi-Level Large Language Model Evaluation Benchmark for Scientific Research

https://github.com/opengvlab/diffagent

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DiffAgent: Fast and Accurate Text-to-Image API Selection with Large Language Model

https://github.com/opengvlab/instruct2act

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Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model

https://github.com/opengvlab/interngpt

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VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks

https://github.com/opengvlab/internvl

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InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks

https://github.com/opengvlab/omniquant

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OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models

https://github.com/opengvlab/piip

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Parameter-Inverted Image Pyramid Networks for Visual Perception and Multimodal Understanding

https://github.com/opengvlab/vinci

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An Egocentric Vision-Language Model based Portable Real-time Smart Assistant

https://github.com/opengvlab/visionllm

공식 코드

VisionLLM: Large Language Model is also an Open-Ended Decoder for Vision-Centric Tasks

https://github.com/opening-up-chatgpt/opening-up-chatgpt.github.io

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Opening up ChatGPT: Tracking openness, transparency, and accountability in instruction-tuned text generators

https://github.com/openmatch/activerag

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ActiveRAG: Autonomously Knowledge Assimilation and Accommodation through Retrieval-Augmented Agents

https://github.com/openmatch/rag-ddr

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RAG-DDR: Optimizing Retrieval-Augmented Generation Using Differentiable Data Rewards

https://github.com/openmeshlab/meshxl

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MeshXL: Neural Coordinate Field for Generative 3D Foundation Models

https://github.com/opennlplab/transnormerllm

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TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer

https://github.com/openpsi-project/realhf

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ReaL: Efficient RLHF Training of Large Language Models with Parameter Reallocation

https://github.com/openroad-assistant/eda-corpus

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EDA Corpus: A Large Language Model Dataset for Enhanced Interaction with OpenROAD

https://github.com/openrobotlab/egohod

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Modeling Fine-Grained Hand-Object Dynamics for Egocentric Video Representation Learning

https://github.com/openrobotlab/grutopia

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GRUtopia: Dream General Robots in a City at Scale

https://github.com/openrobotlab/unihsi

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Unified Human-Scene Interaction via Prompted Chain-of-Contacts

https://github.com/openspg/kag

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KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation

https://github.com/optima-cityu/llm4ad

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LLM4AD: A Platform for Algorithm Design with Large Language Model

https://github.com/optima-cti/intellbot

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IntellBot: Retrieval Augmented LLM Chatbot for Cyber Threat Knowledge Delivery

https://github.com/optimalscale/lmflow

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LISA: Layerwise Importance Sampling for Memory-Efficient Large Language Model Fine-Tuning

https://github.com/optml-group/mu-coreset

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LLM Unlearning Reveals a Stronger-Than-Expected Coreset Effect in Current Benchmarks

https://github.com/orange-city/ll_gen_dd

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Boosting Disfluency Detection with Large Language Model as Disfluency Generator

https://github.com/orange-opensource/wikifactdiff

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WikiFactDiff: A Large, Realistic, and Temporally Adaptable Dataset for Atomic Factual Knowledge Update in Causal Language Models

https://github.com/orange0629/prompting

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SPRIG: Improving Large Language Model Performance by System Prompt Optimization

https://github.com/orcax/CAFE

공식 코드

CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.