25 citations · 55 across the 25 of their papers we have counts for
8 papers · 1 filter
Generate and Instantiate What You Prefer: Text-Guided Diffusion for Sequential Recommendation
Guoqing Hu, Zhengyi Yang, Zhibo Cai +2
Recent advancements in generative recommendation systems, particularly in the realm of sequential recommendation tasks, have shown promise in enhancing generalization to new items.…
Disentangling Masked Autoencoders for Unsupervised Domain Generalization
An Zhang, Han Wang, Xiang Wang +1
Domain Generalization (DG), designed to enhance out-of-distribution (OOD) generalization, is all about learning invariance against domain shifts utilizing sufficient supervision si…
Language Representations Can be What Recommenders Need: Findings and Potentials
Leheng Sheng, An Zhang, Yi Zhang +3
Recent studies empirically indicate that language models (LMs) encode rich world knowledge beyond mere semantics, attracting significant attention across various fields. However, i…
On Softmax Direct Preference Optimization for Recommendation
Yuxin Chen, Junfei Tan, An Zhang +5
Recommender systems aim to predict personalized rankings based on user preference data. With the rise of Language Models (LMs), LM-based recommenders have been widely explored due…
Hello Again! LLM-powered Personalized Agent for Long-term Dialogue
Hao Li, Chenghao Yang, An Zhang +3
Open-domain dialogue systems have seen remarkable advancements with the development of large language models (LLMs). Nonetheless, most existing dialogue systems predominantly focus…
ReactXT: Understanding Molecular "Reaction-ship" via Reaction-Contextualized Molecule-Text Pretraining
Zhiyuan Liu, Yaorui Shi, An Zhang +5
Molecule-text modeling, which aims to facilitate molecule-relevant tasks with a textual interface and textual knowledge, is an emerging research direction. Beyond single molecules,…
ProtT3: Protein-to-Text Generation for Text-based Protein Understanding
Zhiyuan Liu, An Zhang, Hao Fei +4
Language Models (LMs) excel in understanding textual descriptions of proteins, as evident in biomedical question-answering tasks. However, their capability falters with raw protein…
General Debiasing for Graph-based Collaborative Filtering via Adversarial Graph Dropout
An Zhang, Wenchang Ma, Pengbo Wei +2
Graph neural networks (GNNs) have shown impressive performance in recommender systems, particularly in collaborative filtering (CF). The key lies in aggregating neighborhood inform…