collaborators

7 papers

cs.AI2026

FIDES: Faithful Inference via Deep Evidence Signals for Retrieval-Memory Conflict in RAG

Zhe Yu, Wenpeng Xing, Tiancheng Zhao +3

When retrieved evidence contradicts parametric memory, language models frequently ignore context and default to memorized priors -- a failure that undermines the core purpose of re…

cs.LG2026

Spectral Logit Sculpting: Adaptive Low-Rank Logit Transformation for Controlled Text Generation

Jin Li, Zhebo Wang, Tianliang Lu +3

Entropy-based inference methods have gained traction for improving the reliability of Large Language Models (LLMs). However, many existing approaches, such as entropy minimization…

cs.CL2026

ICPO: Illocution-Calibrated Policy Optimization for Multi-Turn Conversation

Zhebo Wang, Xiaohu Mu, Zijie Zhou +4

Large Language Models (LLMs) in multi-turn conversations often suffer from a ``lost-in-conversation'' phenomenon, where they struggle to recover from early incorrect assumptions, p…

cs.CL2026

Latent Fusion Jailbreak: Blending Harmful and Harmless Representations to Elicit Unsafe LLM Outputs

Wenpeng Xing, Mohan Li, Bohan Yang +5

Safety-aligned large language models can still be manipulated through white-box interventions that modify their internal representations. We introduce Latent Fusion Jailbreak (LFJ)…

cs.CL2025

SproutBench: A Benchmark for Safe and Ethical Large Language Models for Youth

Wenpeng Xing, Lanyi Wei, Haixiao Hu +5

The rapid proliferation of large language models (LLMs) in applications targeting children and adolescents necessitates a fundamental reassessment of prevailing AI safety framework…

cs.CR2025

PREE: Towards Harmless and Adaptive Fingerprint Editing in Large Language Models via Knowledge Prefix Enhancement

Xubin Yue, Zhenhua Xu, Wenpeng Xing +3

Addressing the intellectual property protection challenges in commercial deployment of large language models (LLMs), existing black-box fingerprinting techniques face dual challeng…