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New AI model TellTale recognizes ambivalence from video transcripts

By PulseAugur Editorial · [1 sources] ·

Researchers have developed TellTale, a novel approach for recognizing ambivalence and hesitancy in video interviews using only text transcripts. The system combines three probability streams: two text encoders fine-tuned with LoRA adapters and a zero-shot instruction LLM. TellTale achieved a Macro-F1 score of 0.7364 on a private test set, significantly outperforming the official vision-based baseline. AI

IMPACT This research demonstrates a novel method for analyzing human emotion and intent from text, potentially improving automated content moderation and user behavior analysis.

RANK_REASON The cluster contains an academic paper detailing a new AI model and its performance on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New AI model TellTale recognizes ambivalence from video transcripts

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The cluster contains an academic paper detailing a new AI model and its performance on a specific task. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Abdel-Karim Al-Tamimi, Ali Rodan ·

    TellTale: Blending Multi-Instance LoRA Text Encoders and a Zero-Shot LLM Judge for Ambivalence/Hesitancy Recognition in Videos

    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). Although th…

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