Author

Minji Kim

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#artificial intelligence Preprint Sep 2026

Knowing What Not to Answer: Selective Non-Compliance in Vision-Language Models

Vision-language models (VLMs) are expected to respond helpfully to appropriate requests while withholding compliance with requests that are incorrect, unsafe, infeasible, or unanswerable. However, existing benchmarks predominantly evaluate non-compliance at the level of the query as a whole, assuming that each request...

Minji Kim, Jihyoung Jang, Hyounghun Kim · 0 citations

#artificial intelligence Preprint Sep 2026

Refuse without Refusal: A Structural Analysis of Safety-Tuning Responses for Reducing False Refusals in Language Models

This paper decomposes a response in the safety-tuning dataset into two distinct components: a boilerplate refusal statement and a rationale explaining the refusal, and shows that refusal statements impede accurate discrimination between harmful and benign queries by inducing reliance on superficial cues.

Minji Kim, Hyounghun Kim · 2 citations