Author

Binchi Zhang

University of Virginia

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#machine learning Preprint Sep 2026

It Takes Little to Rewrite Perception: Targeted Semantic Substitution in Vision-Language Models at $\epsilon \leq 4/255$

Vision Language Models (VLMs) are widely deployed in safety-critical scenarios, and understanding to which extent they can be controlled by adversarial perturbation is a prerequisite for evaluating their trustworthiness. Existing representation-alignment attacks, which make a VLM perceive a target image, achieve limite...

Binchi Zhang, Atrisha Sarkar, Apurva Narayan · 0 citations

Preprint Aug 2026

Level-k Distinguishable Mechanisms for Evaluating Bounded Rationality in LLMs

This work formalises a necessary level-K distinguishability condition for strategic depth inference and builds a suite of novel game structures that meet this standard, and finds that model models maintain accurate strategic depth under recursive reasoning, with strong internal consistency between stated reasoning and...

Binchi Zhang, Atrisha Sarkar · 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. · Annual Meeting of the Associ... · 0 citations