most citedExploring Large-Scale Language Models to Evaluate EEG-Based Multimodal Data for Mental Health

28 citations · 29 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD2025

Token-Level Logits Matter: A Closer Look at Speech Foundation Models for Ambiguous Emotion Recognition

Jule Valendo Halim, Siyi Wang, Hong Jia +1

Emotional intelligence in conversational AI is crucial across domains like human-computer interaction. While numerous models have been developed, they often overlook the complexity…

cs.CV20251 cited

MicarVLMoE: A Modern Gated Cross-Aligned Vision-Language Mixture of Experts Model for Medical Image Captioning and Report Generation

Amaan Izhar, Nurul Japar, Norisma Idris +1

Medical image reporting (MIR) aims to generate structured clinical descriptions from radiological images. Existing methods struggle with fine-grained feature extraction, multimodal…

cs.SD2025

Scaling Auditory Cognition via Test-Time Compute in Audio Language Models

Ting Dang, Yan Gao, Hong Jia

Large language models (LLMs) have shown exceptional versatility in natural language processing, prompting recent efforts to extend their multimodal capabilities to speech processin…

cs.HC202428 cited

Exploring Large-Scale Language Models to Evaluate EEG-Based Multimodal Data for Mental Health

Yongquan Hu, Shuning Zhang, Ting Dang +4

Integrating physiological signals such as electroencephalogram (EEG), with other data such as interview audio, may offer valuable multimodal insights into psychological states or n…

cs.AI2024

Dual-Constrained Dynamical Neural ODEs for Ambiguity-aware Continuous Emotion Prediction

Jingyao Wu, Ting Dang, Vidhyasaharan Sethu +1

There has been a significant focus on modelling emotion ambiguity in recent years, with advancements made in representing emotions as distributions to capture ambiguity. However, t…