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VLDB 2026 Research / reviewers in the wild / expert

Hongsen Huang

dblp:305/6944 · DBLP profile ↗
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2ranked-venue papers
0as first author
2since 2021 · last 2026
—ORCID · none

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

Artificial intelligence and machine learning · 2 · 2 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
2 papers
Trustworthy machine learning · 53% Reinforcement learning · 27% Language models and text generation · 20%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Machine learning › Trustworthy machine learning
interpretability		 1.012026
Learning What Matters: Dynamic Dimension Selection and Aggregation for Interpretable Vision-Language Reward Modeling · ACL (1) 2026
Machine learning › Trustworthy machine learning › interpretability › explainable reinforcement learning
reward model interpretability		 1.012026
Learning What Matters: Dynamic Dimension Selection and Aggregation for Interpretable Vision-Language Reward Modeling · ACL (1) 2026
Natural language and speech › Language models and text generation
alignment		 0.912025
Icon2: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation · EMNLP 2025
Machine learning › Reinforcement learning › reinforcement learning from human feedback
preference-based reinforcement learning		 0.912025
Icon2: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation · EMNLP 2025
Machine learning › Reinforcement learning › reward learning
reward modeling		 0.312026
Learning What Matters: Dynamic Dimension Selection and Aggregation for Interpretable Vision-Language Reward Modeling · ACL (1) 2026

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

vision-language reward modeling · 1.0dynamic dimension selection · 1.0self-synthetic preference data · 0.9
YearPublicationVenuePosition
2026 Learning What Matters: Dynamic Dimension Selection and Aggregation for Interpretable Vision-Language Reward Modeling
abstract
Qiyuan Chen, Hongsen Huang, Jiahe Chen, Qian Shao, Jintai Chen, Hongxia Xu, Renjie Hua, Ren Chuan, Jian Wu. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.
Qiyuan Chen 0003, Hongsen Huang, Qian Shao, Jintai Chen, Renjie Hua, Ren Chuan, Jian Wu 0001
 ACL (1)2
2025 Icon2: Aligning Large Language Models Using Self-Synthetic Preference Data via Inherent Regulation
abstract
Qiyuan Chen, Hongsen Huang, Qian Shao, Jiahe Chen, Jintai Chen, Hongxia Xu, Renjie Hua, Ren Chuan, Jian Wu. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. 2025.
Qiyuan Chen 0003, Hongsen Huang, Qian Shao, Jintai Chen, Renjie Hua, Ren Chuan, Jian Wu 0001
 EMNLP2