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Han-Rong Zhang

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#artificial intelligence Preprint Sep 2026

TraceDance: An Automated System for Building Agent Behavior Benchmarks from Real-World Agent Deployment Traces

An agent can complete a task while exhibiting undesirable behavior during execution. Developers need tests for the specific behaviors encountered in deployment, beyond fixed benchmark suites. We present TraceDance, an agent system that constructs targeted benchmarks from deployment traces for user-specified undesirable...

De-Hai Min, Dao-An Zhang, Yiming Zeng et al. · 0 citations
#machine learning Preprint Sep 2026

EAVer: Long-Form Factuality Verification as an End-to-End Agentic Policy

Long-form factuality verification is commonly implemented as a static decompose-search-verify pipeline, with separately prompted modules processing claims and invoking external search. Treating claims independently makes LLM and search calls scale with claim count and causes repeated searches for overlapping evidence a...

Ke-Ning Zheng, Ao-Ying Zheng, Zhi-Gang Chang et al. · 0 citations
#artificial intelligence Preprint Aug 2026

Dr. Claw: An AI Scientist Workspace for Vibe Research

Dr. Claw is presented, an open-source workspace that wraps existing coding-agent executors in a controllable and auditable human-in-the-loop workflow rather than introducing another autonomous agent.

D. Song, Han-Rong Zhang, Dawei Liu et al. · 0 citations
#artificial intelligence Preprint Aug 2026

AutoCRAT: Within-trajectory Joint Control of Stochasticity and Compute for LLM Reasoning

This work instantiates AutoCRAT, a decoder-side controller for frozen backbones that operates over a discrete action space and updates control decisions only at semantic boundaries, improving stability while remaining responsive to the evolving reasoning process.

Han-Jun Luo, Qiu-Shi Liu, Jing-Yang Zhang et al. · 0 citations
Preprint Aug 2026

Harness the Memory: A Holistic Evaluation of Memory Substrates in Memory Agents

A controlled harness evaluation of memory substrates for memory-augmented agents, covering dense and sparse indices, text records, structural stores, hierarchical stores, refinement-based memories, parametric updates, and activation-compatible context mechanisms, shows that no single substrate consistently dominates.

Wei-Chieh Huang, Wei-Zhi Zhang, Yu-Chen Wu et al. · 2 citations

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