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Junhao Song 0001

dblp:185/7166-1 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
0009-0009-5178-0258ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Information extraction and text analysis · 87% Generative modeling · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Natural language and speech › Information extraction and text analysis
emotion recognition
0.912025
MERMAID: Multi-perspective Self-reflective Agents with Generative Augmentation for Emotion Recognition · EMNLP 2025
Natural language and speech › Information extraction and text analysis › emotion recognition
multimodal emotion recognition
0.912025
MERMAID: Multi-perspective Self-reflective Agents with Generative Augmentation for Emotion Recognition · EMNLP 2025
Machine learning › Generative modeling › synthetic data generation
generative augmentation
0.312025
MERMAID: Multi-perspective Self-reflective Agents with Generative Augmentation for Emotion Recognition · EMNLP 2025

Methods — techniques the papers use, named apart from their topics

multimodal self-reflection · 0.9cross-modal verification · 0.9
YearPublicationVenuePosition
2026 Exploring efficiency frontiers of thinking budget in medical reasoning: Scaling laws between computational resources and reasoning quality
Ziqian Bi, Hongying Luo, Junhao Song 0001, Enze Ge, Junmin Huang, Keyu Chen 0002, Chia Xin Liang, Chunjie Tian, Jibin Guan, Joe Yeong, Yongzhi Xu, Junfeng Hao
J. Biomed. Informatics4
2025 MERMAID: Multi-perspective Self-reflective Agents with Generative Augmentation for Emotion Recognition
abstract
… "Amusement" "Contentment" "Anger" "Excitement" "Fear" "Amusement" "Sadness" " F e a r " " S a d n e s s " MERMAID Figure 1: Demonstration of MERMAID.Given natural or facial images depicting various emotions, MERMAID produces precise emotion classifications by integrating multimodal self-reflection, generative augmentation to amplify and enrich subtle emotional cues, and cross-modal verification.
Zhongyu Yang, Junhao Song 0001, Siyang Song, Wei Pang 0001, Yingfang Yuan
EMNLP2