The paper proposes a Bayesian Spectral Emotion Transition Discovery (BSETD) framework to model emotion transitions using multi-annotator soft labels, successfully recovering distinct affective transit…

This paper proposes a framework for summarizing dialogues, modeling semantic and emotion dynamics using multimodal inputs and an adapted hierarchical Chain-of-Agents approach.

This paper proposes CPM-MultiAgent, a framework for modeling dynamic emotional evolution in persona-based dialogue systems using the Component Process Model.

An autonomous system reliably evoked strong, differentiated emotions in users through affective patterns, but the channel the machine would read for bodily responses remained largely silent.

The paper uses sparse autoencoders to identify specific latent features within LLM-based TTS models, enabling interpretable and fine-grained control over emotional expression by intervening in small s…

This paper introduces DyadEE, a dataset for emotional entrainment detection in conversational interactions, and TRACE, a window-level framework for modeling dyadic interaction using emotion fine-tuned…

Sympatheia is a speech-to-speech dialogue framework that generates emotionally adaptive responses by conditioning its output on continuous affect signals derived from user speech or external multimoda…

This paper investigates safety dynamics in the use of Role-play AI Companions through interviews and a 14-day assessment, identifying key factors shaping these dynamics and revealing short-term emotio…

This paper proposes PeakFlow, a framework for dynamic affective trajectory prediction in EEG data using a peak-guided coarse-to-refined approach.

This paper argues that affect is constitutive of cognition and identifies two core barriers for Affective Tools for Thought (TfTs). It proposes three design strategies to address these barriers: Chain…

This paper explores the effect of different narrative strategies in data visualizations on eliciting prosocial feelings and behaviors during humanitarian crises.

The paper proposes ESC-Skills, a skill-centric framework that discovers and self-evolves executable emotional support skills to improve the interpretability and emotional quality of conversational AI.

This paper presents a vision-language pipeline, named Keep Yelling Assistant (KYA), that detects risky driving behaviors and generates emotionally expressive responses in real-time.

The paper introduces InsightVQA, a large-scale benchmark dataset designed for hierarchical visual question answering that assesses complex emotion understanding and cognitive reasoning beyond simple e…

This paper proposes a mood-conditioned ranking framework for music recommendation systems using user affective signals in the energy-valence space.

This paper introduces FreakOut-LLM, demonstrating that emotional context, specifically stress, significantly compromises the safety alignment of large language models, increasing jailbreak susceptibil…

This paper proposes DCC, a Dynamic Commonsense Coordination Framework for Empathetic Response Generation, consisting of three modules: SCE-AttnRes, AGCF, and ICAD.

This paper investigates entrainment effects in multi-party human-agent conversations and finds limited global entrainment and cohort-dependent entrainment with the agent.

This paper conducted a randomized controlled trial on Reddit to test the effectiveness of various deescalation strategies in reducing personal insults using automated replies.