EDBT 2026 Demo / reviewers in the wild / expert
Chenkun Tan
dblp:367/4199
· DBLP profile ↗
2ranked-venue papers
0as first author
2since 2021 · last 2025
—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 |
Language models and text generation · 42% Vision and language · 20% Information extraction and text analysis · 20% |
Topics — the 6 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Information extraction and text analysis
dataset construction |
0.9 | 1 | 2025 | UnifiedVisual: A Framework for Constructing Unified Vision-Language Datasets · EMNLP 2025 |
Computer vision › Vision and language
vision-language dataset |
0.9 | 1 | 2025 | UnifiedVisual: A Framework for Constructing Unified Vision-Language Datasets · EMNLP 2025 |
Natural language and speech › Language models and text generation
alignment |
0.8 | 1 | 2024 | InferAligner: Inference-Time Alignment for Harmlessness through Cross-Model Guidance · EMNLP 2024 |
Machine learning › Trustworthy machine learning › AI safety
harmlessness |
0.8 | 1 | 2024 | InferAligner: Inference-Time Alignment for Harmlessness through Cross-Model Guidance · EMNLP 2024 |
Natural language and speech › Language models and text generation › alignment
inference-time alignment |
0.8 | 1 | 2024 | InferAligner: Inference-Time Alignment for Harmlessness through Cross-Model Guidance · EMNLP 2024 |
Natural language and speech › Language models and text generation
multimodal language model |
0.3 | 1 | 2025 | UnifiedVisual: A Framework for Constructing Unified Vision-Language Datasets · EMNLP 2025 |
Methods — techniques the papers use, named apart from their topics
cross-model guidance · 0.8
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | UnifiedVisual: A Framework for Constructing Unified Vision-Language DatasetsabstractPengyu Wang, Shaojun Zhou, Chenkun Tan, Xinghao Wang, Wei Huang, Zhen Ye, Zhaowei Li, Botian Jiang, Dong Zhang, Xipeng Qiu. Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing. 2025. Pengyu Wang 0006, Shaojun Zhou, Chenkun Tan, Zhen Ye 0006, Botian Jiang, Xipeng Qiu |
EMNLP | 3 |
| 2024 | InferAligner: Inference-Time Alignment for Harmlessness through Cross-Model GuidanceabstractPengyu Wang, Dong Zhang, Linyang Li, Chenkun Tan, Xinghao Wang, Mozhi Zhang, Ke Ren, Botian Jiang, Xipeng Qiu. Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing. 2024. Pengyu Wang 0006, Linyang Li, Chenkun Tan, Mozhi Zhang, Botian Jiang, Xipeng Qiu |
EMNLP | 4 |