Measure over-refusal in LLMs using OR-Bench
Generate and view leaderboard for LLM evaluations
Explore and manage STM32 ML models with the STM32AI Model Zoo dashboard
GIFT-Eval: A Benchmark for General Time Series Forecasting
View RL Benchmark Reports
Load AI models and prepare your space
Find recent high-liked Hugging Face models
Submit deepfake detection models for evaluation
Create demo spaces for models on Hugging Face
Convert Stable Diffusion checkpoint to Diffusers and open a PR
Pergel: A Unified Benchmark for Evaluating Turkish LLMs
Evaluate reward models for math reasoning
Browse and submit LLM evaluations
OR-Bench Leaderboard is a tool designed to measure and compare over-refusal (OR) behavior in large language models (LLMs). It provides a standardized framework to evaluate how models respond to refusal scenarios, ensuring consistent and fair benchmarking across different models. The leaderboard helps researchers and developers understand the limitations and capabilities of LLMs in handling refusal tasks.
What is over-refusal in LLMs?
Over-refusal refers to when a model refuses to respond to a query, even when it could provide a meaningful answer.
Why is benchmarking over-refusal important?
Benchmarking helps identify models that may excessively refuse to answer, potentially limiting their utility in real-world applications.
How do I interpret the results from OR-Bench Leaderboard?
Results show how often and in what contexts models refuse to respond, enabling comparisons of refusal behavior across different models.