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Zheng-Zhang Chen

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Preprint Aug 2026

HARP: Hierarchical Adaptive Ranking with Preference-Adaptive Fusion for Query-Based CVE Prioritization

Vulnerability prioritization is inherently preference dependent, since the same CVE can receive different remediation priority under different operational preference scenarios. Existing scoring systems and ranking methods typically assume a fixed criterion. In practice, organizations already operate under a preference...

Hao-Chen Liu, Zheng-Zhang Chen, Hao-Yu Wang et al. · 0 citations
#artificial intelligence Preprint Oct 2026

WorkflowOps: Learning Agent Collaboration Priors for Multi-Agent Workflow Orchestration

Multi-agent systems are increasingly deployed for complex knowledge work, yet their orchestration layers remain largely memoryless: each new task is decomposed, assigned, and executed from scratch with no benefit from prior successful executions. We present WorkflowOps, a multi-agent workflow orchestration framework th...

Qi-Lai Cheng, Sheng-Yu Chen, Wei Cheng et al. · 0 citations
#artificial intelligence Preprint Oct 2026

Which and When to Admit: Gradient Admission for Data-Centric Small Language Model Finetuning

LoRA fine-tuning adapts small language models (SLMs) to heterogeneous instruction data within a low-rank update subspace, making it vulnerable to three structural problems: conflicting gradients that cancel, static data selection that cannot track evolving learning dynamics, and subspace saturation that causes later up...

Hong-Yu Cao, Yan-Chi Liu, Kun-Peng Liu et al. · 0 citations
#artificial intelligence Preprint Sep 2026

PolicyMem: Geometric Policy Memory for LLM Governance

PolicyMem is introduced, a geometric policy memory that externalizes natural-language policies as reusable geometric memory objects represented by low-rank subspaces in a shared representation space that achieves state-of-the-art unsafe behavior detection while enabling effective policy attribution, rewriting, and post...

Yuan-Chen Bei, Zheng-Zhang Chen, Yan-Jun Zhao et al. · 0 citations
Conference Open access 2026

LOKA: Conflict-Aware LLM Knowledge Update with Adaptive Knowledge Memory

This work investigates the problem of LLM knowledge updates, which requires simultaneously unlearning unwanted information and learning new knowledge, and proposes LOKA, a conflict-aware framework for Large language mOdel Knowledge updAtes.

Binchi Zhang, Zhengzhang Chen, Zaiyi Zheng et al. · 0 citations
Conference Open access 2026

Uncertainty-Aware Test-Time Search for Optimization Problem Solving

UMCTS is an Uncertainty-aware Monte Carlo Tree Search framework that combines the language understanding capability of large language models with the reliability of well-established solvers and achieves state-of-the-art solution accuracy and improves efficiency by reducing token usage.

Linlin Yu, Xujiang Zhao, Dong Li et al. · 0 citations

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