collaborators

10 papers

cs.AI2026

VERA: Authority-Preserving Edge Revocation for Federated AI-Agent Workflows

Lifei Liu, Haoran Yu, Xiaochong Jiang

Modern agent frameworks compose planners, tool agents, remote services, and shared specialists into runtime delegation graphs, but their revocation APIs still resemble token or sub…

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.CR2026

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

Su Wang, Pin Qian, Yifan Lin +5

Self-improving AI agents are designed to learn from their mistakes. We show they can also hallucinate mistakes that never happened. We study this failure mode in automated harness…

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…

cs.CR2026

ChainCaps: Composition-Safe Tool-Using Agents via Monotonic Capability Attenuation

Xiaochong Jiang, Shiqi Yang, Ziwei Li +3

Tool-using agents increasingly operate in open-ended deployment environments, where they compose file systems, web APIs, code interpreters, and enterprise services at runtime. This…

cs.SE2026

Habituation at the Gate: Rising Approval and Declining Scrutiny in Human Review of AI Agent Code

Haoran Yu, Lifei Liu, Xiaochong Jiang +4

As AI coding agents (e.g., GitHub Copilot, Devin, OpenAI Codex, Cursor) submit pull requests to open-source repositories at scale, a key question arises: do human reviewers gradual…