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Arithmetic Reasoning

태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.

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하위 태스크

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평가표

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보존된 평가 기록

169

코드

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

https://github.com/gair-nlp/abel

Solving Quantitative Reasoning Problems with Language Models

https://github.com/gammatauai/leetcode-hard-gym

Sparks of Artificial General Intelligence: Early experiments with GPT-4

https://github.com/ganjinzero/rrhf

LLaMA: Open and Efficient Foundation Language Models

https://github.com/gen-verse/reasonflux

Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models

https://github.com/ggerganov/llama.cpp

LLaMA: Open and Efficient Foundation Language Models

https://github.com/ggml-org/llama.cpp

LLaMA: Open and Efficient Foundation Language Models

https://github.com/glb400/Toy-RecLM

Llama 2: Open Foundation and Fine-Tuned Chat Models

https://github.com/gpt4life/alpagasus

GPT-4 Technical Report

https://github.com/grantslatton/llama.cpp

LLaMA: Open and Efficient Foundation Language Models

https://github.com/greenbitai/low_bit_llama

LLaMA: Open and Efficient Foundation Language Models

https://github.com/guinmoon/llmfarm

LLaMA: Open and Efficient Foundation Language Models

https://github.com/hamishivi/easylm

LLaMA: Open and Efficient Foundation Language Models

https://github.com/hkust-nlp/b-star

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

https://github.com/huggingface/transformers

LLaMA: Open and Efficient Foundation Language Models

https://github.com/hughbzhang/o1_inference_scaling_laws

Self-Consistency Improves Chain of Thought Reasoning in Language Models

https://github.com/huiwy/reflection-on-trees

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

https://github.com/icalk-nlp/educhat

LLaMA: Open and Efficient Foundation Language Models

https://github.com/idiap/abroad-re

Llama 2: Open Foundation and Fine-Tuned Chat Models

https://github.com/jackaduma/Alpaca-LoRA-RLHF-PyTorch

LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

https://github.com/katamb/tree-of-thought-llm-ca

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

https://github.com/kayvr/token-hawk

LLaMA: Open and Efficient Foundation Language Models

https://github.com/kbressem/medalpaca

LLaMA: Open and Efficient Foundation Language Models

https://github.com/knowlab/bi-weekly-paper-presentation

Mistral 7B

https://github.com/krafton-ai/korani

LLaMA: Open and Efficient Foundation Language Models

https://github.com/lastmile-ai/aiconfig/tree/main/cookbooks/Multi-LLM-Consistency

Self-Consistency Improves Chain of Thought Reasoning in Language Models

https://github.com/leiluk1/codesearcher

CodeT5+: Open Code Large Language Models for Code Understanding and Generation

https://github.com/lflage/openfactscore

GPT-4 Technical Report

https://github.com/llamafamily/llama-chinese

LLaMA: Open and Efficient Foundation Language Models

https://github.com/longhao-chen/aicas2024

LLaMA: Open and Efficient Foundation Language Models

https://github.com/lqtrung1998/mwp_reft

ReFT: Representation Finetuning for Language Models

https://github.com/lucidrains/CALM-pytorch

LLM Augmented LLMs: Expanding Capabilities through Composition

https://github.com/meetyou-ai-lab/can-mc-evaluate-llms

Llama 2: Open Foundation and Fine-Tuned Chat Models

https://github.com/meta-llama/llama

LLaMA: Open and Efficient Foundation Language Models

https://github.com/mgmalek/efficient_cross_entropy

Mistral 7B

https://github.com/microsoft/guidance

Sparks of Artificial General Intelligence: Early experiments with GPT-4

https://github.com/nebuly-ai/nebullvm/tree/main/apps/accelerate/chatllama

LLaMA: Open and Efficient Foundation Language Models

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