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Le Chen

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#artificial intelligence Preprint Sep 2026

LAM: Efficient Lossy Agent Memory Framework With A Retrieval-Score Error Bound

Agent memory grows as agents read inputs, reason, and call tools. Longer histories increase inference cost and eventually exceed the context window. LLM-based summarization reduces this history but adds latency and provides no explicit bound on information loss. We propose LAM, a Lossy Agent Memory system with three co...

Bai-Xi Sun, Le Chen, Anjir Ahmed Chowdhury et al. · 0 citations
#artificial intelligence Preprint Aug 2026

CEDAR: Automata as Verifiable Interfaces for Language-Guided Embodied Action

CEDAR is presented, a counterexample-guided framework that grounds instructions as regular languages over environment event traces and represents both skills and specifications as deterministic finite automata, suggesting that regular languages offer a practical verification layer between natural-language instructions...

Le Chen, Alvaro Velasquez, Ashutosh Trivedi · 0 citations

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