https://github.com/54zy/CAT4AI
공식 코드Position: AI Evaluation Should Learn from How We Test Humans
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
Position: AI Evaluation Should Learn from How We Test Humans
Algebraic Machine Learning: Learning as computing an algebraic decomposition of a task
Gödel Agent: A Self-Referential Agent Framework for Recursive Self-Improvement
FormalGeo: An Extensible Formalized Framework for Olympiad Geometric Problem Solving
SeaLLMs 3: Open Foundation and Chat Multilingual Large Language Models for Southeast Asian Languages
HARDMath2: A Benchmark for Applied Mathematics Built by Students as Part of a Graduate Class
A Reinforcement Learning Environment for Mathematical Reasoning via Program Synthesis
Absolute Zero: Reinforced Self-play Reasoning with Zero Data
EquivPruner: Boosting Efficiency and Quality in LLM-Based Search via Action Pruning
Semantically-Aligned Equation Generation for Solving and Reasoning Math Word Problems
MathScape: Evaluating MLLMs in multimodal Math Scenarios through a Hierarchical Benchmark
Semantically-Aligned Universal Tree-Structured Solver for Math Word Problems
Challenging the Boundaries of Reasoning: An Olympiad-Level Math Benchmark for Large Language Models
TheoremLlama: Transforming General-Purpose LLMs into Lean4 Experts
Alice: Proactive Learning with Teacher's Demonstrations for Weak-to-Strong Generalization
Enhancing LLM Reasoning with Iterative DPO: A Comprehensive Empirical Investigation
Implicit Reasoning in Transformers is Reasoning through Shortcuts
MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs
URSA: Understanding and Verifying Chain-of-thought Reasoning in Multimodal Mathematics
MAQA: Evaluating Uncertainty Quantification in LLMs Regarding Data Uncertainty
A Diversity-Enhanced Knowledge Distillation Model for Practical Math Word Problem Solving
OmniRouter: Budget and Performance Controllable Multi-LLM Routing
OmniRouter: Budget and Performance Controllable Multi-LLM Routing
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.