LLM agents are moving from single-prompt use to long task streams in which reusable memory becomes a core capability for terminal, software-engineering, and web tasks. Such memory is useful only when stored experience remains reliable across hundreds of interactions, but two failure modes break that assumption in pract...
Hao-Yu Wang, Guang-Yuan Dong, He Liang et al.· 1 citation
This work proposes a dependency-aware code generation framework that explicitly models interactions among code entities through a graph-based representation, and introduces a sparse triplet representation for strong dependencies, significantly improving storage efficiency and computational scalability.
SafeFlow is proposed, a defense framework for multi-agent systems that formalizes malicious cross-agent propagation as a semantic information-flow problem and reduces attack success rates compared to undefended baselines and external defenses while retaining high benign task completion and a high paired safe--harm succ...
Haowen Dai, Zonghao Ying, Wenfeng Li et al.· arXiv.org· 0 citations
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