ST-Bench: A Spatial-Temporal Benchmark for Multi-Agent System Generation on Scientific Research Tasks
cs.AI
Submitted: 2026-10-06
Updated: 2026-10-06
Terminology
Sources
- Program Synthesis with Large Language Models
- Evaluating Large Language Models Trained on Code
- ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery
- Training Verifiers to Solve Math Word Problems
- FlowReasoner: Reinforcing Query-Level Meta-Agents
- Accelerating scientific discovery with Co-Scientist
- Measuring Mathematical Problem Solving With the MATH Dataset
- Automated Design of Agentic Systems
- MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation
- SWE-bench: Can Language Models Resolve Real-World GitHub Issues?
- Knowledge-guided Machine Learning: Current Trends and Future Prospects
- CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society
- GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis
- AgentBench: Evaluating LLMs as Agents
- The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
- Self-Refine: Iterative Refinement with Self-Feedback
- Exploring Physics-Informed Neural Networks for Crop Yield Loss Forecasting
- ClimaX: A foundation model for weather and climate
- Weak-for-Strong: Training Weak Meta-Agent to Harness Strong Executors
- OmniScientist: Toward a Co-evolving Ecosystem of Human and AI Scientists
Related papers
- MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
- Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
- Agents' Last Exam
- The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
- MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
- Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems