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20242026
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cs.CL2026

SCOPE: Sequential Conformal Probing for Reliable OOD Rejection in LLM Services

Zhuoyun Li, Boxuan Wang, Changshun Wu +2

Rejecting inputs outside the defined in-distribution (IND) service scope is critical for large language model (LLM) services, where unsupported requests should be filtered before f…

cs.CL2026

Lying with Truths: Open-Channel Multi-Agent Collusion for Belief Manipulation via Generative Montage

Jinwei Hu, Xinmiao Huang, Youcheng Sun +2

As large language models (LLMs) transition to autonomous agents synthesizing real-time information, their reasoning capabilities introduce an unexpected attack surface. This paper…

cs.CL2026

FragileFlow: Spectral Control of Correct-but-Fragile Predictions for Foundation Model Robustness

Zhuoyun Li, Boxuan Wang, Jinwei Hu +2

Robust adaptation of LLMs and VLMs is often evaluated by average accuracy or average consistency under perturbations. However, these averages can hide a structured failure mode: a…

cs.CL2026

Where Do Prompt Perturbations Break Generation? A Segment-Level View of Robustness in LoRA-Tuned Language Models

Zhuoyun Li, Boxuan Wang, Jinwei Hu +6

Large language models are sensitive to minor prompt perturbations, yet existing robustness methods usually enforce consistency at the whole-sequence level. This holistic view can h…

cs.CL2025

FALCON: Fine-grained Activation Manipulation by Contrastive Orthogonal Unalignment for Large Language Model

Jinwei Hu, Zhenglin Huang, Xiangyu Yin +4

Large language models have been widely applied, but can inadvertently encode sensitive or harmful information, raising significant safety concerns. Machine unlearning has emerged t…