11 papers
Salami Attack: Stealthy Collusive Memory Poisoning against OpenClaw
Zheng Lin, Yuzhe Huang, Zhenxing Niu +2
Long-term memory enables LLM agents to retain useful information across sessions, but also creates an attack surface through which adversaries may poison an agent's persistent memo…
Attention-Guided Reward for Reinforcement Learning-based Jailbreak against Large Reasoning Models
Zheng Lin, Zhenxing Niu, Haoxuan Ji +2
Large Reasoning Models (LRMs) have demonstrated remarkable capabilities in solving complex problems by generating structured, step-by-step reasoning content. However, exposing a mo…
The Tool Decathlon: Benchmarking Language Agents for Diverse, Realistic, and Long-Horizon Task Execution
Junlong Li, Wenshuo Zhao, Jian Zhao +18
Real-world language agents must handle complex, multi-step workflows across diverse Apps. For instance, an agent may manage emails by coordinating with calendars and file systems,…
LOCA-bench: Benchmarking Language Agents Under Controllable and Extreme Context Growth
Weihao Zeng, Yuzhen Huang, Junxian He
Large language models (LLMs) are increasingly capable of carrying out long-running, real-world tasks. However, as the amount of context grows, their reliability often deteriorates,…
SWE-RM: Execution-free Feedback For Software Engineering Agents
KaShun Shum, Binyuan Hui, Jiawei Chen +6
Execution-based feedback like unit testing is widely used in the development of coding agents through test-time scaling (TTS) and reinforcement learning (RL). This paradigm require…
From Accuracy to Robustness: A Study of Rule- and Model-based Verifiers in Mathematical Reasoning
Yuzhen Huang, Weihao Zeng, Xingshan Zeng +2
Trustworthy verifiers are essential for the success of reinforcement learning with verifiable reward (RLVR), which is the core methodology behind various large reasoning models suc…