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Arithmetic Reasoning

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코드

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

https://github.com/shumkashun/automate-cot

공식 코드

Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data

https://github.com/skytliang/multi-agents-debate

공식 코드

Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate

https://github.com/stanfordnlp/pyreft

공식 코드

ReFT: Representation Finetuning for Language Models

https://github.com/technion-cs-nlp/llm-arithmetic-heuristics

공식 코드

Arithmetic Without Algorithms: Language Models Solve Math With a Bag of Heuristics

https://github.com/tianhongzxy/core

공식 코드

Solving Math Word Problems via Cooperative Reasoning induced Language Models

https://github.com/vanderschaarlab/prompt-oirl

공식 코드

Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL

https://github.com/vis-nlp/opencqa

공식 코드

OpenCQA: Open-ended Question Answering with Charts

https://github.com/vita-group/tape

공식 코드

Rethinking Addressing in Language Models via Contexualized Equivariant Positional Encoding

https://github.com/wellecks/llmstep

공식 코드

Llemma: An Open Language Model For Mathematics

https://github.com/wengsyx/neural-comprehension

공식 코드

Mastering Symbolic Operations: Augmenting Language Models with Compiled Neural Networks

https://github.com/whu-zqh/dup

공식 코드

Achieving >97% on GSM8K: Deeply Understanding the Problems Makes LLMs Better Solvers for Math Word Problems

https://github.com/wjn1996/chain-of-knowledge

공식 코드

Boosting Language Models Reasoning with Chain-of-Knowledge Prompting

https://github.com/wuhy68/parameter-efficient-moe

공식 코드

Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks

https://github.com/xiwenchao/omac-demo

공식 코드

OMAC: A Broad Optimization Framework for LLM-Based Multi-Agent Collaboration

https://github.com/xiye17/sat-lm

공식 코드

SatLM: Satisfiability-Aided Language Models Using Declarative Prompting

https://github.com/xlang-ai/batch-prompting

공식 코드

Batch Prompting: Efficient Inference with Large Language Model APIs

https://github.com/xuekai-zhu/pad

공식 코드

PaD: Program-aided Distillation Can Teach Small Models Reasoning Better than Chain-of-thought Fine-tuning

https://github.com/xuzhao0/model-selection-reasoning

공식 코드

Automatic Model Selection with Large Language Models for Reasoning

https://github.com/xydaytoy/eva

공식 코드

Bridging the Gap between Different Vocabularies for LLM Ensemble

https://github.com/yangling0818/buffer-of-thought-llm

공식 코드

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

https://github.com/yaoching0/gac

공식 코드

Breaking the Ceiling of the LLM Community by Treating Token Generation as a Classification for Ensembling

https://github.com/yetianjhu/alphallm

공식 코드

Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing

https://github.com/youblei/prompt-space

공식 코드

Prompt Space Optimizing Few-shot Reasoning Success with Large Language Models

https://github.com/ysymyth/tree-of-thought-llm

공식 코드

Tree of Thoughts: Deliberate Problem Solving with Large Language Models

https://github.com/zhaoyiran924/adv-in-context-learning

공식 코드

Prompt Optimization via Adversarial In-Context Learning

https://github.com/ziyangjoy/diablo

공식 코드

DiaBlo: Diagonal Blocks Are Sufficient For Finetuning

https://github.com/zjunlp/Prompt4ReasoningPapers

공식 코드

Reasoning with Language Model Prompting: A Survey

https://github.com/znlp/language-imbalance-driven-rewarding

공식 코드

Language Imbalance Driven Rewarding for Multilingual Self-improving

https://github.com/2023-MindSpore-4/Code12/tree/main/MindFormers/llama

LLaMA: Open and Efficient Foundation Language Models

https://github.com/AUCOHL/RTL-Repo

GPT-4 Technical Report

https://github.com/IBM/Dromedary

Llama 2: Open Foundation and Fine-Tuned Chat Models

https://github.com/Leeroo-AI/mergoo

Branch-Train-MiX: Mixing Expert LLMs into a Mixture-of-Experts LLM

https://github.com/Lightning-AI/lit-gpt

Llama 2: Open Foundation and Fine-Tuned Chat Models

https://github.com/Lightning-AI/lit-llama

LLaMA: Open and Efficient Foundation Language Models

https://github.com/MS-P3/code5/tree/main/llama

LLaMA: Open and Efficient Foundation Language Models

https://github.com/MS-P3/code5/tree/main/llama2

LLaMA: Open and Efficient Foundation Language Models

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