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cs.AI2026
Position: A Three-Layer Probabilistic Assume-Guarantee Architecture Is Structurally Required for Safe LLM Agent Deployment
S. Bensalem, Y. Dong, M. Franzle +6
This position paper argues that enforcing LLM agent safety within a single abstraction layer is not merely suboptimal but categorically insufficient for deployed LLM agents -- a st…
cs.AI2026
PrefixGuard: Online Failure Warning and Trace-Grounded Diagnosis for LLM Agents
Xinmiao Huang, Jinwei Hu, Rajarshi Roy +4
Large language model (LLM) agents execute multi-step tasks, but terminal verdicts arrive too late for intervention. Agent traces mix messages, tool calls, and feedback, making it d…
cs.AI2025
About Time: Model-free Reinforcement Learning with Timed Reward Machines
Rajarshi Roy, Anirban Majumdar, Ritam Raha +2
Reward specification plays a central role in reinforcement learning (RL), guiding the agent's behavior. To express non-Markovian rewards, formalisms such as reward machines have be…