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Ting Dang

26 papers hereh-index 6134 citations28 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author16
  • last author8

Across the 26 of 26 papers where every author was matched, so the position is known.

fields
  • cs.AI6
  • cs.LG6
  • cs.SD5
  • cs.CL3
  • cs.HC3
  • cs.CV1
same name
  • Ting Dang — 23 papers, h 3
  • Ting Dang — 11 papers, h 2
  • Ting Dang — 6 papers, h 2
  • Ting Dang — 2 papers, h 0
  • Ting Dang — 1 paper
  • Ting Dang — 1 paper, h 7

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
most citedExploring Large-Scale Language Models to Evaluate EEG-Based Multimodal Data for Mental Health

28 citations · 29 across the 23 of their papers we have counts for

collaborators
Showing 2026 · cs.SDShow all

3 papers · 2 filters

cs.SD2026

Listen Then Reason: Perception-Grounded Test-Time Reinforcement Learning for Large Audio-Language Models

Jiaheng Dong, Xiaofeng Yu, Jean Honorio +3

Large audio-language models (LALMs) are increasingly used for a broader range of audio reasoning tasks. These models typically incorporate audio representations into a large langua…

cs.SD2026

Edge-Cloud Collaborative Speech Emotion Captioning via Token-Level Speculative Decoding in Audio-Language Models

Xiangyuan Xue, Jiajun Lu, Yan Gao +3

Speech Emotion Captioning (SEC) leverages large audio-language models to generate rich, context-aware affective descriptions from speech. However, real-world deployment remains cha…

cs.SD2026

Disentangling Reasoning in Large Audio-Language Models for Ambiguous Emotion Prediction

Xiaofeng Yu, Jiaheng Dong, Jean Honorio +3

Speech emotion recognition plays an important role in various applications. However, most existing approaches predict a single emotion label, oversimplifying the inherently ambiguo…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.