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Large language model agents are increasingly deployed to perform complex tasks in real-world environments. However, the knowledge required for correct behavior in these environments is often implicit, undisclosed, and subject to change over time. Recent continual-learning harnesses seek to address this challenge by ena...
CamoDocs is proposed, a poisoning attack that avoids direct query inclusion by camouflaging adversarial documents among benign content, and shows that erasure-heavy clustering defenses such as TrustRAG can reduce ASR, but only with substantial utility drops on retrieval-dependent benchmarks such as NeoQA.
Retrieval-Grounded Voting (RGV), which scores each rollout by the lexical overlap between its final answer and the documents it retrieved, consistently outperforms confidence-based voting and identifies the underlying failure reason as copy inflation.
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