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MMLU

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

https://github.com/eggachecat/chair

공식 코드

CHAIR -- Classifier of Hallucination as Improver

https://github.com/enyac-group/quamba

공식 코드

Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models

https://github.com/eq-bench/eq-bench

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EQ-Bench: An Emotional Intelligence Benchmark for Large Language Models

https://github.com/espere-1119-song/video-mmlu

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Video-MMLU: A Massive Multi-Discipline Lecture Understanding Benchmark

https://github.com/facebookresearch/advprompter

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AdvPrompter: Fast Adaptive Adversarial Prompting for LLMs

https://github.com/facebookresearch/any4

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any4: Learned 4-bit Numeric Representation for LLMs

https://github.com/facebookresearch/atlas

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Atlas: Few-shot Learning with Retrieval Augmented Language Models

https://github.com/facebookresearch/layerskip

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LayerSkip: Enabling Early Exit Inference and Self-Speculative Decoding

https://github.com/facebookresearch/reasonir

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ReasonIR: Training Retrievers for Reasoning Tasks

https://github.com/felipemaiapolo/efficbench

공식 코드

tinyBenchmarks: evaluating LLMs with fewer examples

https://github.com/felipemaiapolo/prompteval

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Efficient multi-prompt evaluation of LLMs

https://github.com/felipemaiapolo/tinybenchmarks

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tinyBenchmarks: evaluating LLMs with fewer examples

https://github.com/flagopen/flagembedding

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LM-Cocktail: Resilient Tuning of Language Models via Model Merging

https://github.com/gabrielkmbo/explore-rl

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Step-wise Policy for Rare-tool Knowledge (SPaRK): Offline RL that Drives Diverse Tool Use in LLMs

https://github.com/gersteinlab/medagents

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MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning

https://github.com/git-disl/llm-topla

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LLM-TOPLA: Efficient LLM Ensemble by Maximising Diversity

https://github.com/gonglinyuan/metro_t0

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Model-Generated Pretraining Signals Improves Zero-Shot Generalization of Text-to-Text Transformers

https://github.com/google-research/crosslingual-knowledge-barriers

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Crosslingual Capabilities and Knowledge Barriers in Multilingual Large Language Models

https://github.com/google-research/google-research

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UL2: Unifying Language Learning Paradigms

https://github.com/graph-and-geometric-learning/helm

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HELM: Hyperbolic Large Language Models via Mixture-of-Curvature Experts

https://github.com/hazyresearch/lolcats

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LoLCATs: On Low-Rank Linearizing of Large Language Models

https://github.com/hf-lin/ChatMusician

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ChatMusician: Understanding and Generating Music Intrinsically with LLM

https://github.com/htqin/ir-qlora

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Accurate LoRA-Finetuning Quantization of LLMs via Information Retention

https://github.com/huggingface/yourbench

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YourBench: Easy Custom Evaluation Sets for Everyone

https://github.com/imoneoi/openchat

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Instruction Tuning with Human Curriculum

https://github.com/jeffwillette/cascading_kv_cache

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Training-Free Exponential Context Extension via Cascading KV Cache

https://github.com/joelniklaus/lawinstruct

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LawInstruct: A Resource for Studying Language Model Adaptation to the Legal Domain

https://github.com/johnheo/adadim-llm

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Rethinking Channel Dimensions to Isolate Outliers for Low-bit Weight Quantization of Large Language Models

https://github.com/joshuaongg21/comat

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CoMAT: Chain of Mathematically Annotated Thought Improves Mathematical Reasoning

https://github.com/justtherightsize/empo

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EmPO: Emotion Grounding for Empathetic Response Generation through Preference Optimization

https://github.com/katiekang1998/llm_hallucinations

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Unfamiliar Finetuning Examples Control How Language Models Hallucinate

https://github.com/kevinwu23/stanford-medcasereasoning

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MedCaseReasoning: Evaluating and learning diagnostic reasoning from clinical case reports

https://github.com/keyonvafa/human-generalization-llms

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Do Large Language Models Perform the Way People Expect? Measuring the Human Generalization Function

https://github.com/kingdalfgoodman/lota-qaf

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LoTA-QAF: Lossless Ternary Adaptation for Quantization-Aware Fine-Tuning

https://github.com/kl4805/shoppingmmlu

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Shopping MMLU: A Massive Multi-Task Online Shopping Benchmark for Large Language Models

https://github.com/kotekjedi/capability-based-scaling

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Capability-Based Scaling Laws for LLM Red-Teaming

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