arXiv AI
Jun 12
Emotional regulation improves deep learning-based image classification
arXiv:2606. 13081v1 Announce Type: cross Abstract: Emotion significantly influences cognition, enhancing memory and learning under certain conditions.
Personalized Emotional Intelligence in Generative AI through Symbolic Affective Reasoning
arXiv:2607. 10678v1 Announce Type: new Abstract: Emotional intelligence enables humans to recognize emotions, infer their causes, reason about interventions, and modify their environment to achieve desired affective states.
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arXiv AI
Aug 12
Rationale-Guided Learning for Multimodal Emotion Recognition
arXiv:2608. 10448v1 Announce Type: new Abstract: Multimodal emotion recognition in conversation (MERC) requires understanding complex interactions between verbal and non-verbal cues.
arXiv AI
3d ago
LongEmo: Towards Emotion Understanding and Reasoning in Long Videos
arXiv:2609.40079v1 Announce Type: cross Abstract: While recent Multimodal Large Language Models (MLLMs) have shown promise in affective computing, their reasoning capabilities are largely confined to...
Hugging Face Trending Papers
Jul 23
MVEI & EmObserver: Empowering MLLM-Oriented Visual Emotional Intelligence via Emotion Statement Judgement
Affective Image Content Analysis (AICA) aims to recognize and understand emotions elicited by visual content, representing an indispensable step toward Artificial General Intelligence (AGI). However, despite the rapid progress of Multimodal Large Language Models (MLLMs), systematic evaluation of their visual emotional intelligence remains largely absent from recent model releases.
arXiv AI
Jun 18
The Personalization Trap: How User Memory Alters Emotional Reasoning in LLMs
arXiv:2510. 09905v2 Announce Type: replace Abstract: When an AI assistant remembers that Sarah is a single mother working two jobs, does it interpret her stress differently than if she were a wealthy executive?
arXiv AI
Jul 9
EMO-R3: Reflective Reinforcement Learning for Emotional Reasoning in Multimodal Large Language Models
arXiv:2602. 23802v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown remarkable progress in visual reasoning and understanding tasks but still struggle to capture the complexity and subjectivity of human emotions.
arXiv AI
Jul 14
EmoStyle: Affective Conditioning of Style-Specialist Experts for Emotional Image Generation
arXiv:2607. 10165v1 Announce Type: cross Abstract: Emotion-aware artistic image generation requires an image to match the input prompt, follow the specified artistic style, and convey the target emotion.
arXiv AI
Sep 25
Interpreting and Enhancing Emotional Circuits in Large Vision-Language Models via Cross-Modal Information Flow
The paper introduces a steering‑vector‑based causal attribution framework to study how large vision‑language models (LVLMs) translate visual input into emotional narratives. By creating a specialized dataset, the authors uncover a functional decoupling in the LVLM’s three‑stage Adapt‑Aggregate‑Execute mechanism: visual emotional cues are first aggregated in middle layers via sentiment‑specific attention heads, then translated into narrative generation in deeper layers through emotion‑general pathways. Using these insights, they regulate emotional information routing to strengthen attention flow and amplify semantic activation, achieving significant performance gains on the MER‑UniBench and reducing emotional hallucinations through inference‑time intervention.
arXiv Computer Vision
Sep 22
Beyond Emotion Prompts: Fine-Grained Text-to-Image Generation Driven by Valence-Arousal-Dominance
arXiv:2609.24215v1 Announce Type: new Abstract: Although text-to-image models can accurately depict subjects and scenes, creators still struggle to specify the fine-grained emotions an image should c...
arXiv AI
Jun 12
EPIG: Emotion-Based Prompting for Personalised Image Generation
arXiv:2606. 13247v1 Announce Type: new Abstract: Text-to-image diffusion models have achieved impressive results in synthesizing high-quality images from natural language prompts.
arXiv Computer Vision
4d ago
Decoding Affective Nuances: Enhancing MLLMs via Hierarchical Emotion Reasoning and Contrastive Discriminative Pruning
The paper introduces DAN, a training‑free inference‑time framework that improves affective reasoning in multimodal large language models. It combines a Hierarchical Emotional Reasoning Chain (HERC) to better capture fine‑grained visual cues and a Contrastive Discriminative Visual Pruning (CDVP) module to isolate discriminative tokens for semantically similar emotions. Experiments show significant gains, notably a +10.47% improvement on the WebEmo25 benchmark with Qwen3‑VL‑8B‑Instruct.
arXiv Computer Vision
4d ago
DSPO: Diversity-aware Subjective Policy Optimization for Robust Emotional Reasoning
arXiv:2609.36775v1 Announce Type: new Abstract: Reinforcement Learning has significantly advanced the complex reasoning capabilities of MLLMs. However, prevailing RL algorithms suffer a severe failur...