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From the 1 of 11 linked papers with an AI index.

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11 papers

cs.AI2026

Explicit State Elicitation Is Not Enough: A Controlled Audit of Memory-Policy Classification

Yihang Chen, Pin Qian, Su Wang +4

Personalized agents must decide whether retrieved user memory should be used, ignored, updated, or queried before it affects a current task. We use this setting to develop an empir…

cs.AI2026

BAP-SQL: Budget-Aware Observation Planning for Agentic Text-to-SQL

Chong Peng, Pin Qian, Su Wang +2

Tool-using agents do not merely consume observations: their actions determine what arrives next. In agentic text-to-SQL, a broad query can spend context and database work before us…

cs.LG2026

When Should Active RAG Retrieve? A Budget-Aware Evaluation of Utility, Calibration, and Cost

Pin Qian, Su Wang, Chong Peng +5

Active RAG systems decide when to retrieve external knowledge during generation, making them a budget-sensitive case of agentic RAG and self-adaptive retrieval. Yet evaluations oft…

cs.LG2026

Toward User-Conditioned Evaluation of Personal LLM Agents under Temporal Interventions

Pin Qian, Su Wang, Yihang Chen +5

Personal agents maintain memories, learned skills, tool configurations, and policy state that evolve with each user. Existing agent benchmarks often evaluate these capabilities in…

cs.CR2026

Phantom Guardrails: When Self-Improving Agent Harnesses Fix Failures That Never Happened

Su Wang, Pin Qian, Yifan Lin +5

The paper investigates how self‑improving AI agents can hallucinate non‑existent failures and create unnecessary guardrails, introducing a deterministic Counterfactual Fabrication…

cs.AI2026

Operational Reframing and Approval-Framed Delegation in Multi-Agent LLM Safety

Lifei Liu, Haoran Yu, Xiaochong Jiang +3

Safety evaluations of multi-agent LLM systems often compare a direct prompt with a planner-executor pipeline and report the difference as a single "pipeline effect." We argue that…