arXiv AI July 17, 2026 By Elena Ryumina (St. Petersburg Federal Research Center of the Russian Academy of Sciences), Maxim Markitantov (St. Petersburg Federal Research Center of the Russian Academy of Sciences), Alexandr Axyonov (St. Petersburg Federal Research Center of the Russian Academy of Sciences), Fedor Shchetinin (HSE University, St. Petersburg, Russia), Timur Abdulkadirov (St. Petersburg Federal Research Center of the Russian Academy of Sciences), Dmitry Ryumin (St. Petersburg Federal Research Center of the Russian Academy of Sciences), Alexey Karpov (St. Petersburg Federal Research Center of the Russian Academy of Sciences)

Team RAS in 11th ABAW Competition: Multimodal Ambivalence Recognition Approach

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arXiv:2607. 14702v1 Announce Type: cross Abstract: Automatic recognition of ambivalence and hesitancy is challenging because these states may be expressed through inconsistent linguistic, acoustic, facial, and contextual patterns, while top-performing systems often rely on computationally expensive ensembles.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

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arXiv:2607. 12774v1 Announce Type: cross Abstract: This article presents our results for the 11th Affective Behavior Analysis in-the-Wild (ABAW) competition.

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Knowledge-Guided Multimodal Reasoning over Interacting Streams for Video-Level Ambivalence and Hesitancy Recognition

arXiv:2607. 25961v1 Announce Type: cross Abstract: Ambivalence and hesitancy (A/H) are conflicting affective states that precede the delay or abandonment of health behaviour change.

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llms multimodal

Hugging Face Trending Papers

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Audio-Text Cross-Attention with Psycholinguistic Support Features for Ambivalence/Hesitancy Recognition

We present an audio-text system for the Ambivalence/Hesitancy Video Recognition Challenge of the 11th ABAW Competition. The method excludes visual frames and represents each video as overlapping 5-second windows aligned with transcript timestamps.

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SVF-CR: Synchronized Visual-Facial Cross-Refinement for Multimodal Ambivalence and Hesitancy Recognition

arXiv:2607. 09417v1 Announce Type: cross Abstract: Ambivalence and hesitancy are subtle behavioral states that are expressed through a combination of verbal content, facial behavior, visual context, and acoustic cues.

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Multimodal Ambivalence/Hesitancy Recognition in Videos for Personalized Digital Health Interventions

arXiv:2604. 11730v4 Announce Type: replace-cross Abstract: Using behavioural science, health interventions focus on behaviour change by providing a framework to help patients acquire and maintain healthy habits that improve medical outcomes.

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