most citedLLM-based Privacy Data Augmentation Guided by Knowledge Distillation with a Distribution Tutor for Medical Text Classification

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SE2026

Behavior Specification-Guided Program Synthesis for Binary Deobfuscation

Kangchen Zhu, Shangwen Wang, Zhiliang Tian +5

Deobfuscation is critical to reverse engineering and security analysis because it restores the readability and analyzability of obfuscated code. However, existing research primaril…

cs.CL2026

Think Dense, Not Long: Dynamic Decoupled Conditional Advantage for Efficient Reasoning

Keqin Peng, Yuanxin Ouyang, Xuebo Liu +4

Reinforcement Learning with Verifiable Rewards (RLVR) can elicit strong multi-step reasoning, yet it often encourages overly verbose traces. Moreover, naive length penalties in gro…

cs.SE2026

Atomizer: An LLM-based Collaborative Multi-Agent Framework for Intent-Driven Commit Untangling

Kangchen Zhu, Zhiliang Tian, Shangwen Wang +2

Composite commits, which entangle multiple unrelated concerns, are prevalent in software development and significantly hinder program comprehension and maintenance. Existing automa…

cs.AI2024

Learn to Disguise: Avoid Refusal Responses in LLM's Defense via a Multi-agent Attacker-Disguiser Game

Qianqiao Xu, Zhiliang Tian, Hongyan Wu +4

With the enhanced performance of large models on natural language processing tasks, potential moral and ethical issues of large models arise. There exist malicious attackers who in…

cs.CL2024★ 1 cited

LLM-based Privacy Data Augmentation Guided by Knowledge Distillation with a Distribution Tutor for Medical Text Classification

Yiping Song, Juhua Zhang, Zhiliang Tian +3

As sufficient data are not always publically accessible for model training, researchers exploit limited data with advanced learning algorithms or expand the dataset via data augmen…