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Yujia Deng

dblp:167/1908 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Natural language and speech › Language models and text generation
LLM agents
1.012026
LLM Agents in Law: Taxonomy, Applications, and Challenges · ACL (1) 2026
Computational social science and digital humanities › legal informatics
AI and law
0.312026
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
YearPublicationVenuePosition
2026 LLM Agents in Law: Taxonomy, Applications, and Challenges
abstract
Shuang 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 Making
abstract
This 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