https://github.com/DIRECT-BIT/SRA-MCTS
공식 코드SRA-MCTS: Self-driven Reasoning Augmentation with Monte Carlo Tree Search for Code Generation
Papers with Code 아카이브
Problem Decomposition
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관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/apple/ml-divide-or-conquer
공식 코드https://github.com/baithebest/adagp
공식 코드SparseLLM: Towards Global Pruning for Pre-trained Language Models
https://github.com/baithebest/sparsellm
공식 코드SparseLLM: Towards Global Pruning for Pre-trained Language Models
https://github.com/john1226966735/adaptive-solver
공식 코드Adaptive-Solver Framework for Dynamic Strategy Selection in Large Language Model Reasoning
https://github.com/khalil-research/matrix-mult-cp
공식 코드Fast Matrix Multiplication Without Tears: A Constraint Programming Approach
https://github.com/kumar-shridhar/distiiling-lm
공식 코드Distilling Reasoning Capabilities into Smaller Language Models
https://github.com/lcs2-iiitd/daslam
공식 코드Small Language Models Fine-tuned to Coordinate Larger Language Models improve Complex Reasoning
https://github.com/mas-research/rollinghorizon
공식 코드https://github.com/mikegu721/agentgroupchat-v2
공식 코드AgentGroupChat-V2: Divide-and-Conquer Is What LLM-Based Multi-Agent System Need
https://github.com/minhaeoh/raise
공식 코드RAISE: Enhancing Scientific Reasoning in LLMs via Step-by-Step Retrieval
https://github.com/prosysscience/job-shop-scheduling
공식 코드Decomposition Strategies and Multi-shot ASP Solving for Job-shop Scheduling
https://github.com/realwangjiahao/tabletime
공식 코드https://github.com/sisl/AutomotivePOMDPs.jl
공식 코드Decomposition Methods with Deep Corrections for Reinforcement Learning
https://github.com/yimengli46/bellman_point_goal
공식 코드Comparison of Model-Free and Model-Based Learning-Informed Planning for PointGoal Navigation
https://github.com/SalesforceAIResearch/MAS-Zero
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.