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cs.AI2026
E-Bench: Benchmarking Multi-Step Tool-Use Agents in Real-World Product Scenarios
Weihuang Zheng, Tianyuan Zou, Eileen Ye +5
Large Language Models (LLMs) are increasingly deployed as agents that interact with stateful environments over multiple steps: gathering hidden information, composing tool calls, a…
cs.AI2026
ForeSci: Evaluating LLM Agents for Forward-Looking AI Research Judgment
Qiuyu Tian, Haojie Yin, Yingce Xia +5
AI research often requires decisions before future evidence exists: which bottleneck to attack, which direction to pursue, or where a project should be positioned. We introduce For…