Demo Data from EDBT 2026 / reviewers in the wild / expert
Yujia Deng
dblp:167/1908
· DBLP profile ↗
3ranked-venue papers
0as first author
1since 2021 · last 2026
0000-0002-6407-2236ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 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 |
Language models and text generation · 100% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational social science and digital humanities · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Natural language and speech › Language models and text generation
LLM agents |
1.0 | 1 | 2026 | LLM Agents in Law: Taxonomy, Applications, and Challenges · ACL (1) 2026 |
Computational social science and digital humanities › legal informatics
AI and law |
0.3 | 1 | 2026 | LLM Agents in Law: Taxonomy, Applications, and Challenges · ACL (1) 2026 |
Methods — techniques the papers use, named apart from their topics
taxonomy construction · 2.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | LLM Agents in Law: Taxonomy, Applications, and ChallengesabstractShuang Liu, Ruijia Zhang, Ruoyun Ma, Yujia Deng, Lanyi Zhu, Jiayu Li, Zelong Li, Zhibin Shen, Mengnan Du. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026. Ruijia Zhang, Ruoyun Ma, Yujia Deng, Lanyi Zhu, Zhibin Shen, Mengnan Du |
ACL (1) | 4 |
| 2020 | Neural-based time series forecasting of loss of coolant accidents in nuclear power plants
Majdi I. Radaideh, Connor Pigg, Tomasz Kozlowski, Yujia Deng, Annie Qu |
Expert Syst. Appl. | 4 |
| 2016 | Scaled Prioritized Geometric Aggregation Operators and Their Applications to Decision MakingabstractThis paper uses the priority labels to express the detailed prioritized relationship between criteria and develops some scaled prioritized geometric aggregation operators, including the scaled prioritized geometric score (SPGS) operator and the scaled prioritized geometric averaging (SPGA) operator. We also present the uncertain scaled prioritized geometric scoring (USPGS) operator and the uncertain scaled prioritized geometric averaging (USPGA) operator. We investigate the properties of these operators and build the models to derive the weights by maximizing square deviations from a possible range to distinguish the candidate alternatives. The principal advantage of these scaled prioritized geometric aggregation operators is that they are very stable and satisfy monotonicity. Furthermore, we investigate approaches to multi-attribute decision making based on the proposed operators or models and examples are illustrated to show the feasibility and validity of the new approaches. Finally, some further discussions are given. Yingdong He, Zhen He 0001, Panpan Zhou, Yujia Deng |
Int. J. Uncertain. Fuzziness Knowl. Based Syst. | 4 |