🌟 Overview
ABench is an evolving open-source benchmark suite designed to rigorously evaluate and enhance Large Language Models (LLMs) on complex cross-domain tasks. By targeting current model weaknesses, ABench provides systematic challenges in high-difficulty specialized domains, including physics, actuarial science, logical reasoning, law, and psychology.
🎯 Core Objectives
- Address Evaluation Gaps: Design high-differentiation assessment tasks targeting underperforming question types
- Establish Unified Standards: Create reliable, comparable benchmarks for multi-domain LLM evaluation
- Expand Capability Boundaries: Drive continuous optimization of knowledge systems and reasoning mechanisms through challenging innovative problems
📊 Dataset Release Status
| Domain | Description | Status |
|---|---|---|
| Physics | 500 university/competition-level physics problems (400 static + 100 dynamic parametric variants) covering 10+ fields from classical mechanics to modern physics | ✅ Released |
| Actuary | Curated actuarial exam problems covering core topics: probability statistics, financial mathematics, life/non-life insurance, actuarial models, and risk management | ✅ Released |
| Logic | High-differentiation logical reasoning problems from authoritative tests (LSAT/GMAT/GRE/SBI/Chinese Civil Service Exam) | 🔄 In Preparation |
| Psychology | Psychological case studies and research questions (objective/subjective) evaluating understanding of human behavior and theories | 🔄 In Preparation |
| Law | Authoritative judicial exam materials covering core legal domains: criminal/civil/administrative/procedural/international law | 🔄 In Preparation |