194 citations · 1.2k across the 81 of their papers we have counts for
96 papers
Event Extraction in Large Language Model
Bobo Li, Xudong Han, Jiang Liu +11
Large language models (LLMs) and multimodal LLMs are changing event extraction (EE): prompting and generation can often produce structured outputs in zero shot or few shot settings…
OneTrans: Unified Feature Interaction and Sequence Modeling with One Transformer in Industrial Recommender
Zhaoqi Zhang, Haolei Pei, Jun Guo +5
In recommendation systems, scaling up feature-interaction modules (e.g., Wukong, RankMixer) or user-behavior sequence modules (e.g., LONGER) has achieved notable success. However,…
A Survey of Real-World Recommender Systems: Challenges, Constraints, and Industrial Perspectives
Kuan Zou, Aixin Sun
Recommender systems have generated tremendous value for both users and businesses, drawing significant attention from academia and industry alike. However, due to practical constra…
Does Multimodality Improve Recommender Systems as Expected? A Critical Analysis and Future Directions
Hongyu Zhou, Yinan Zhang, Aixin Sun +1
Multimodal recommendation systems are increasingly popular for their potential to improve performance by integrating diverse data types. However, the actual benefits of this integr…
Towards Storage-Efficient Visual Document Retrieval: An Empirical Study on Reducing Patch-Level Embeddings
Yubo Ma, Jinsong Li, Yuhang Zang +8
Despite the strong performance of ColPali/ColQwen2 in Visualized Document Retrieval (VDR), it encodes each page into multiple patch-level embeddings and leads to excessive memory u…
RoboEgo System Card: An Omnimodal Model with Native Full Duplexity
Yiqun Yao, Xiang Li, Xin Jiang +4
Humans naturally process real-world multimodal information in a full-duplex manner. In artificial intelligence, replicating this capability is essential for advancing model develop…