Papers with Code 아카이브

Mathematical Reasoning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

전체 기법전체 데이터셋

하위 태스크

7

평가표

11

보존된 평가 기록

41

코드

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

https://github.com/ymcui/chinese-mixtral

Mixtral of Experts

https://github.com/young-geng/easylm

LLaMA: Open and Efficient Foundation Language Models

https://github.com/yuanmu97/secure-transformer-inference

LLaMA: Open and Efficient Foundation Language Models

https://github.com/yuxiaw/openfactcheck

FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios

https://github.com/yynil/rwkvinside

DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

https://github.com/zhanglab-aim/lingo

LoRA: Low-Rank Adaptation of Large Language Models

https://github.com/zhaolingao/langptune

LoRA: Low-Rank Adaptation of Large Language Models

https://github.com/zhaoolee/garss

GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models

https://github.com/zihanzhaosjtu/librisqa

LLaMA: Open and Efficient Foundation Language Models

https://github.com/ziyuguo99/image-generation-cot

MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine

https://github.com/zjunlp/deepke

Reasoning with Language Model Prompting: A Survey

https://github.com/zjunlp/trice

LoRA: Low-Rank Adaptation of Large Language Models

https://github.com/zongqianwu/st-cot

Large Language Models are Zero-Shot Reasoners

https://github.com/zurichnlp/contradecode

Llama 2: Open Foundation and Fine-Tuned Chat Models

https://huggingface.co/datasets/peiyi9979/Math-Shepherd

Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations

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