NanshineLoong / Self-Evolving-BenchmarkLinks
A framework for evolving and testing question-answering datasets with various models.
☆17Updated last year
Alternatives and similar repositories for Self-Evolving-Benchmark
Users that are interested in Self-Evolving-Benchmark are comparing it to the libraries listed below
Sorting:
- [ICLR'24 spotlight] Tool-Augmented Reward Modeling☆51Updated 3 months ago
- [NeurIPS'24] Weak-to-Strong Search: Align Large Language Models via Searching over Small Language Models☆62Updated 9 months ago
- A Dynamic Visual Benchmark for Evaluating Mathematical Reasoning Robustness of Vision Language Models☆26Updated 10 months ago
- [COLING 2025] ToolEyes: Fine-Grained Evaluation for Tool Learning Capabilities of Large Language Models in Real-world Scenarios☆69Updated 4 months ago
- Source code of "Reasons to Reject? Aligning Language Models with Judgments"☆58Updated last year
- Scalable Meta-Evaluation of LLMs as Evaluators☆42Updated last year
- A simple GPT-based evaluation tool for multi-aspect, interpretable assessment of LLMs.☆87Updated last year
- Watch Every Step! LLM Agent Learning via Iterative Step-level Process Refinement (EMNLP 2024 Main Conference)☆61Updated 11 months ago
- DuoGuard: A Two-Player RL-Driven Framework for Multilingual LLM Guardrails☆27Updated 6 months ago
- Code for ICLR 2024 paper "CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets"☆58Updated last year
- [NAACL 2025] The official implementation of paper "Learning From Failure: Integrating Negative Examples when Fine-tuning Large Language M…☆29Updated last year
- official implementation of paper "Process Reward Model with Q-value Rankings"☆61Updated 7 months ago
- [ICML'2024] Can AI Assistants Know What They Don't Know?☆83Updated last year
- [NAACL 2024] A Synthetic, Scalable and Systematic Evaluation Suite for Large Language Models☆33Updated last year
- Interpretable Contrastive Monte Carlo Tree Search Reasoning☆48Updated 10 months ago
- Code for the 2025 ACL publication "Fine-Tuning on Diverse Reasoning Chains Drives Within-Inference CoT Refinement in LLMs"☆33Updated 3 months ago
- Code for ACL2024 paper - Adversarial Preference Optimization (APO).☆56Updated last year
- [ACL-25] We introduce ScaleQuest, a scalable, novel and cost-effective data synthesis method to unleash the reasoning capability of LLMs.☆68Updated 10 months ago
- This the implementation of LeCo☆31Updated 8 months ago
- Official code implementation for the ACL 2025 paper: 'CoT-based Synthesizer: Enhancing LLM Performance through Answer Synthesis'☆30Updated 4 months ago
- [EMNLP 2024] Source code for the paper "Learning Planning-based Reasoning with Trajectory Collection and Process Rewards Synthesizing".☆82Updated 8 months ago
- ☆49Updated 10 months ago
- [NeurIPS 2024] The official implementation of paper: Chain of Preference Optimization: Improving Chain-of-Thought Reasoning in LLMs.☆127Updated 6 months ago
- ☆53Updated 7 months ago
- ☆101Updated last year
- The official repository of "Improving Large Language Models via Fine-grained Reinforcement Learning with Minimum Editing Constraint"☆38Updated last year
- Extensive Self-Contrast Enables Feedback-Free Language Model Alignment☆20Updated last year
- [ACL 2023] Solving Math Word Problems via Cooperative Reasoning induced Language Models (LLMs + MCTS + Self-Improvement)☆50Updated last year
- [NeurIPS 2024 Oral] Aligner: Efficient Alignment by Learning to Correct☆185Updated 8 months ago
- This is an official implementation of the Reward rAnked Fine-Tuning Algorithm (RAFT), also known as iterative best-of-n fine-tuning or re…☆37Updated last year