collaborators

6 papers

cs.CR2026

FreoStream:Enhancing Stream Guardrails via Future-Aware Reasoning and Safety-Aligned Optimization

Jianwei Wang, Guoyang Shen, Yanhong Wu +5

Stream guardrails enable token-level safety detection before full responses are generated. However, they often make overly conservative judgements and block those sensitive but saf…

cs.CR2026

Evolving Skill-Structured Attack Memory Enhances LLM Jailbreaking

Junke Zhang, Jianwei Wang, Sishuo Chen +3

Jailbreak attacks on large language models (LLMs) aim to induce LLMs to produce content that they are expected to refuse. Automated black-box jailbreak generation is important for…

cs.CL2026

RCP-Merging: Merging Long Chain-of-Thought Models with Domain-Specific Models by Considering Reasoning Capability as Prior

Junyao Yang, Jianwei Wang, Huiping Zhuang +2

Large Language Models (LLMs) with long chain-of-thought (CoT) capability, termed Reasoning Models, demonstrate superior intricate problem-solving abilities through multi-step long…

cs.CR2025

RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis

Jianwei Wang, Chengming Shi, Junyao Yang +5

The success of large language models (LLMs) has attracted many individuals to fine-tune them for domain-specific tasks by uploading their data. However, in sensitive areas like hea…

cs.CL2025

SynAdapt: Learning Adaptive Reasoning in Large Language Models via Synthetic Continuous Chain-of-Thought

Jianwei Wang, Ziming Wu, Fuming Lai +2

While Chain-of-Thought (CoT) reasoning improves model performance, it incurs significant time costs due to the generation of discrete CoT tokens (DCoT). Continuous CoT (CCoT) offer…

cs.CR2025

PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration

Ziqian Zeng, Jianwei Wang, Junyao Yang +4

The widespread usage of online Large Language Models (LLMs) inference services has raised significant privacy concerns about the potential exposure of private information in user i…