This paper presents an overview of the fourteenth edition of the BioASQ challenge, organized in the context of the Conference and Labs of the Evaluation Forum (CLEF) 2026. BioASQ is an international challenge series that supports progress in biomedical language processing tasks ranging from semantic indexing and inform...
Anastasios Nentidis, Georgios Katsimpras, Anastasia Krithara et al.· 0 citations
Hour-scale audio-visual question answering is constrained by a context dilemma: dense whole-recording encoding rapidly exhausts context limits, whereas uniform temporal compression severely dilutes fine-grained acoustic and visual evidence. We introduce LEAP, a framework where the model retrieves its own evidence witho...
Ju-Yi Lin, Zhi-Qiang Lao, Jia-Li Cui et al.· arXiv.org· 0 citations
OPSRD is introduced, which uses a fixed expert role as privileged teaching context for on-policy self-distillation without reference solutions for on-policy self-distillation without reference solutions.
Wei-Jie Ren, Yan-Wen Zhang, Hao Li et al.· arXiv.org· 0 citations
Injection is proposed, an inference-time intervention that combines explicit, role-specific capability guidelines with a guiding prefilled response prefix that improves role-capability alignment across models, reducing above-role accuracy by up to 0.562 while preserving in-role accuracy with a marginal drop of less tha...
Pakhapoom Sarapat, Saksorn Ruangtanusak, Kunat Pipatanakul et al.· 0 citations
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A comprehensive study on PPT spanning five PPT tasks, four PT data mixtures, four parameter scales (500M to 7B), and PT budgets of up to 100B tokens finds that downstream gains arise from PPT tasks that improve long-range retrieval.
Atsuki Yamaguchi, Tatsuro Inaba, Joel Niklaus et al.· 0 citations
Lie detection probes aim to predict from a language model's internal states whether its output is truthful or dishonest. However, role-play complicates what"truth"means for an LLM: language models can adopt a wide range of personas that take very different claims to be true, including personas whose beliefs clearly con...
Maximilian von Klinski, S. Lapuschkin, W. Samek et al.· arXiv.org· 0 citations
Multimodal encoders such as CLIP underlie many downstream systems, but their web-scale training data embed harmful associations that safety alignment must suppress without unnecessarily changing benign representations. Because ethical and practical constraints prevent collecting real unsafe content at scale, existing d...
Tobia Poppi, Silvia Cappelletti, Samuele Poppi et al.· 0 citations
Multi-agent collaboration lets large language models (LLMs) improve question answering through deliberation and feedback. Yet shared discussion couples correction with exposure to the same mistakes, which can erode the diversity needed for voting. Self-consistency offers sampling diversity without feedback, while singl...
Wei-Jie Ren, Yan-Wen Zhang, Hao Li et al.· 0 citations
Cross-lingual transfer describes how knowledge in a source language benefits a target language. Measuring it quantitatively requires broad multilingual pre-training, as prior work has done with cross-lingual transfer matrices. We ask whether transfer is predictable from freely available typological features, and whethe...
Dalton Raphael Harmsen, Swier Garst, Thomas van Osch et al.· 0 citations
As Large Language Model (LLM) agents are increasingly deployed in complex environments, multi-turn interaction attacks have become a significant security challenge. Existing detection methods typically rely on historical context. However, this retrospective logic struggles to identify deep malicious intents that are sp...
Ze-Zhong Wang, Xue-Yang Tang, Rui Lian et al.· 1 citation
Speech emotion recognition (SER) is the task of assigning emotion labels to utterances. Early systems relied on acoustic features, whereas recent approaches combine multiple modalities, most commonly speech and text. Still, performance remains poor on many datasets. Large language models (LLMs) have therefore attracted...
A BERT-BiLSTM-CRF architecture for argument discourse detection and classification, as the system for Daleel 2026, the inaugural Arabic argument mining shared task, is presented.
Bhuvanesh Verma, Ali Abusaleh, Alexander Mehler· Proceedings of The Fourth Ar...· 0 citations
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
