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cs.AI2026

Benchmarks for Trajectory Safety Evaluation and Diagnosis in OpenClaw and Codex: ATBench-Claw and ATBench-Codex

Zhonghao Yang, Yu Li, Yanxu Zhu +6

As agent systems move into increasingly diverse execution settings, trajectory-level safety evaluation and diagnosis require benchmarks that evolve with them. ATBench is a diverse…

cs.AI2026

Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions

Yue Xu, Qian Chen, Zizhan Ma +5

Large language models have enabled agentic systems that reason, plan, and interact with tools and environments to accomplish complex tasks. As these agents operate over extended in…

cs.AI2026

Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report v1.5

Dongrui Liu, Yi Yu, Jie Zhang +18

To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, Frontier AI Risk Management Framework in Practice presents a comp…

cs.AI2026

InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discovery

Shiyang Feng, Runmin Ma, Xiangchao Yan +53

We introduce InternAgent-1.5, a unified system designed for end-to-end scientific discovery across computational and empirical domains. The system is built on a structured architec…

cs.AI2026

LPS-Bench: Benchmarking Safety Awareness of Computer-Use Agents in Long-Horizon Planning under Benign and Adversarial Scenarios

Tianyu Chen, Chujia Hu, Ge Gao +3

Computer-use agents (CUAs) execute multi-stage tasks through tools, where an early unsafe decision can propagate to consequential actions. Evaluating only final outcomes can miss s…