A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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MemGuard proposes persisting verifier signals to govern what LLM-agent memory systems store and when stored information may influence later decisions.
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This paper proposes a multi-agent evaluation framework that aligns LLM-agent-based automated evaluation with multi-dimensional human evaluation for real-world text generation.
M. Ferrag, N. Tihanyi, Djallel Hamouda, et al.
A unified threat model for LLM-agent ecosystems covering host-to-tool and agent-to-agent attacks, with over 30 techniques and mitigation strategies.