Author

Barbara Plank

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#artificial intelligence May 2026

Clarify, Abstain or Answer? Strategising in Conversation with Belief-Augmented Generation

Belief-Augmented Generation (BAG) is proposed: grounding LLMs in their own belief state via the prompt and letting them reason over these K samples to decide on and execute a conversational strategy: clarify, abstain, or answer.

Joris Baan, Wilker Aziz, Barbara Plank et al. · arXiv.org · 0 citations

#natural language process... Jun 2026

Uncertainty Is Not a Safety Net for Clinical VQA, but Can It Anticipate Model Failure?

It is found that uncertainty on the unperturbed input reliably anticipates which predictions will collapse under NOTA, indicating that UE in current VLMs carries diagnostic information about model fragility.

Arnisa Fazla, A. Testoni, A. Abu-Hanna et al. · arXiv.org · 0 citations

#natural language process... May 2026

Human Label Variation as Stable Signal: Learning Annotator-Specific Explanation Behavior via Cross-Annotator Preference Optimization

Overall, the results show that HLV can be learned as annotator-specific label-explanation behavior, suggesting a path toward scalable explanation-based annotation grounded in annotator histories rather than labels alone.

Beiduo Chen, Pingjun Hong, Ziyun Zhang et al. · arXiv.org · 0 citations