https://github.com/yule-BUAA/MergeLLM
공식 코드Extend Model Merging from Fine-Tuned to Pre-Trained Large Language Models via Weight Disentanglement
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Extend Model Merging from Fine-Tuned to Pre-Trained Large Language Models via Weight Disentanglement
Probability-Consistent Preference Optimization for Enhanced LLM Reasoning
Vision Matters: Simple Visual Perturbations Can Boost Multimodal Math Reasoning
Accelerate Parallelizable Reasoning via Parallel Decoding within One Sequence
Unleashing Reasoning Capability of LLMs via Scalable Question Synthesis from Scratch
Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem Solving
CoT-UQ: Improving Response-wise Uncertainty Quantification in LLMs with Chain-of-Thought
R-KV: Redundancy-aware KV Cache Compression for Training-Free Reasoning Models Acceleration
Diagram Formalization Enhanced Multi-Modal Geometry Problem Solver
ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics
Stepwise Self-Consistent Mathematical Reasoning with Large Language Models
Living in the Moment: Can Large Language Models Grasp Co-Temporal Reasoning?
PromptCoT: Synthesizing Olympiad-level Problems for Mathematical Reasoning in Large Language Models
MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn Interactions
MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine
Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks
Multi-View Reasoning: Consistent Contrastive Learning for Math Word Problem
LogicSolver: Towards Interpretable Math Word Problem Solving with Logical Prompt-enhanced Learning
Ape210K: A Large-Scale and Template-Rich Dataset of Math Word Problems
Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process
NeedleBench: Can LLMs Do Retrieval and Reasoning in Information-Dense Context?
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.