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.
By Podakanti Satyajith Chary, Barath Parthiban, Pranesh Velmurugan, Adeeba Khan, Nagarajan Ganapathy
arXiv:2607. 12774v1 Announce Type: cross Abstract: This article presents our results for the 11th Affective Behavior Analysis in-the-Wild (ABAW) competition.
By Aleksei Bakin, Andrey V. Savchenko
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.
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)
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.
arXiv:2608. 06409v1 Announce Type: cross Abstract: Speech language models are increasingly evaluated on paralinguistic tasks by the accuracy of prompted answers, but answer accuracy combines failures at different stages of the audio-to-answer computation.
By Linkai Peng, Baorian Nuchged
arXiv:2607. 16635v1 Announce Type: cross Abstract: We present TellTale, a text-only approach to ambivalence/hesitancy (A/H) recognition in interview videos, evaluated on the BAH dataset as part of the 3rd A/H Video Recognition Challenge (11th ABAW Workshop, ECCV 2026).
By Abdel-Karim Al-Tamimi, Ali Rodan