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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/qiuhaolu/tner

공식 코드

Large Language Models Struggle in Token-Level Clinical Named Entity Recognition

https://github.com/qizekun/ShapeLLM

공식 코드

ShapeLLM: Universal 3D Object Understanding for Embodied Interaction

https://github.com/qizhou000/visedit

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Attribution Analysis Meets Model Editing: Advancing Knowledge Correction in Vision Language Models with VisEdit

https://github.com/qlm-project/qlm

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Queue management for slo-oriented large language model serving

https://github.com/qlu-nlp/biancang

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BianCang: A Traditional Chinese Medicine Large Language Model

https://github.com/qmme/t2vqa

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Subjective-Aligned Dataset and Metric for Text-to-Video Quality Assessment

https://github.com/qq-mm/video-ccam

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Video-CCAM: Enhancing Video-Language Understanding with Causal Cross-Attention Masks for Short and Long Videos

https://github.com/qqqube/emulate

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EMULATE: A Multi-Agent Framework for Determining the Veracity of Atomic Claims by Emulating Human Actions

https://github.com/qqw-ing/rag-reasonalignment

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AlignRAG: Leveraging Critique Learning for Evidence-Sensitive Retrieval-Augmented Reasoning

https://github.com/quanshr/dmoerm

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DMoERM: Recipes of Mixture-of-Experts for Effective Reward Modeling

https://github.com/qurrent-ai/res-q

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RES-Q: Evaluating Code-Editing Large Language Model Systems at the Repository Scale

https://github.com/qwenlm/qwen

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Qwen Technical Report

https://github.com/qzqdz/CoVer

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Collaborative Stance Detection via Small-Large Language Model Consistency Verification

https://github.com/radssk/mp-rred

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A Multi-Pass Large Language Model Framework for Precise and Efficient Radiology Report Error Detection

https://github.com/rafaelamartelo/floodgpt-4_prototype

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Towards Democratized Flood Risk Management: An Advanced AI Assistant Enabled by GPT-4 for Enhanced Interpretability and Public Engagement

https://github.com/rafiibnsultan/geosam

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GeoSAM: Fine-tuning SAM with Multi-Modal Prompts for Mobility Infrastructure Segmentation

https://github.com/rahvis/cognitive-weave

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Cognitive Weave: Synthesizing Abstracted Knowledge with a Spatio-Temporal Resonance Graph

https://github.com/raibows/learn-to-reason

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Democratizing Reasoning Ability: Tailored Learning from Large Language Model

https://github.com/rainbowluocs/openomni

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OpenOmni: Large Language Models Pivot Zero-shot Omnimodal Alignment across Language with Real-time Self-Aware Emotional Speech Synthesis

https://github.com/randallbalestriero/splinellm

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Characterizing Large Language Model Geometry Helps Solve Toxicity Detection and Generation

https://github.com/raphaelmerx/tulun

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TULUN: Transparent and Adaptable Low-resource Machine Translation

https://github.com/rattlesnakey/cofitune

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Balancing Speciality and Versatility: a Coarse to Fine Framework for Supervised Fine-tuning Large Language Model

https://github.com/rayleizhu/vllm-ra

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RelayAttention for Efficient Large Language Model Serving with Long System Prompts

https://github.com/razvandu/conciserl

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ConciseRL: Conciseness-Guided Reinforcement Learning for Efficient Reasoning Models

https://github.com/razvandu/layerwisequant

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Layer-Wise Quantization: A Pragmatic and Effective Method for Quantizing LLMs Beyond Integer Bit-Levels

https://github.com/razvanip13/towards_lighter_and_robust_evaluation

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Towards Lighter and Robust Evaluation for Retrieval Augmented Generation

https://github.com/rbturnbull/hespi

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Hespi: A pipeline for automatically detecting information from hebarium specimen sheets

https://github.com/rcgai/simplyretrieve

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SimplyRetrieve: A Private and Lightweight Retrieval-Centric Generative AI Tool

https://github.com/rdnfn/icai

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Inverse Constitutional AI: Compressing Preferences into Principles

https://github.com/real-stanford/reflect

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REFLECT: Summarizing Robot Experiences for Failure Explanation and Correction

https://github.com/reallmasic/consmax

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ConSmax: Hardware-Friendly Alternative Softmax with Learnable Parameters

https://github.com/reason-wang/instructllm

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Demystifying Instruction Mixing for Fine-tuning Large Language Models

https://github.com/rebelsnlu-jaist/llmu-robustness

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Improving LLM Unlearning Robustness via Random Perturbations

https://github.com/recsys-lab/rag-visualrec

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RAG-VisualRec: An Open Resource for Vision- and Text-Enhanced Retrieval-Augmented Generation in Recommendation

https://github.com/redwoodresearch/alignment_faking_public

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Alignment faking in large language models

https://github.com/regionch/sprec

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SPRec: Leveraging Self-Play to Debias Preference Alignment for Large Language Model-based Recommendations

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