128 citations · 927 across the 99 of their papers we have counts for
8 papers · 1 filter
Optimizing VLP-aligned Multimodal Intent Representation with Correct Visual Instantiation for Zero-Shot Composed Image Retrieval
Xuri Ge, Chunhao Wang, Junchen Fu +7
ZS-CIR aims to retrieve a target image from a reference image and a modification text without paired supervision, typically by encoding composed queries as text-dominant representa…
Token-Level Credit Assignment Optimization for Generative Document Retrieval
Xinpeng Zhao, Yang Liu, Ran Chen +6
Generative retrieval models perform document retrieval by autoregressively generating document identifiers (DocIDs). This process naturally forms a sequential decision problem, i.e…
Do Generative Recommenders Deepen the Information Cocoon? A Closed-Loop Simulation with LLM-powered User Simulators
Jiyuan Yang, Gengxin Sun, Mengqi Zhang +5
Recommender systems alleviate information overload, yet repeated feedback between recommendations and user interactions can reinforce existing preferences and narrow users' exposur…
MADS: Model-Aware Diverse Core Set Selection for Instruction Tuning
Yi Bai, Wenhao Zhang, Yao Chen +3
Instruction fine-tuning is employed to enhance the instruction-following ability of large language models (LLMs). As the amount of instruction fine-tuning data increases, selecting…
Integrating Chain-of-Thought into Generative Retrieval: A Preliminary Study
Wenhao Zhang, Ruihao Yu, Yi Bai +2
While generative retrieval (GR) demonstrates competitive performance on standard retrieval benchmarks, existing approaches directly map queries to document identifiers (docids) wit…
Federated User Behavior Modeling for Privacy-Preserving LLM Recommendation
Lei Guo, Hongyun Yang, Pengjie Ren +3
Large Language Models have shown great success in recommender systems. However, the limited and sparse nature of user data often restricts the LLM's ability to effectively model be…