Video-LLMs can be trained, via SFT or DPO on a new synthetic dataset UVQA, to refuse questions that cannot be answered from the video content, with modest cost to answerable QA performance.
A.3 ETHICSSTATEMENT In our study, we utilize Large Language Models (LLM) to generate our UVQA dataset and evaluate video-LLMs, which may result in unintended outcomes
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Can Video LLMs Refuse to Answer? Alignment for Answerability in Video Large Language Models
Video-LLMs can be trained, via SFT or DPO on a new synthetic dataset UVQA, to refuse questions that cannot be answered from the video content, with modest cost to answerable QA performance.