8 citations · 89 across the 68 of their papers we have counts for
11 papers · 1 filter
Reasoning over Semantic IDs Enhances Generative Recommendation
Yingzhi He, Yan Sun, Junfei Tan +6
Recent advances in generative recommendation have leveraged pretrained LLMs by formulating sequential recommendation as autoregressive generation over a unified token space compris…
Preference Diffusion for Recommendation
Shuo Liu, An Zhang, Guoqing Hu +2
Recommender systems predict personalized item rankings based on user preference distributions derived from historical behavior data. Recently, diffusion models (DMs) have gained at…
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…
Towards Human-centered Proactive Conversational Agents
Yang Deng, Lizi Liao, Zhonghua Zheng +2
Recent research on proactive conversational agents (PCAs) mainly focuses on improving the system's capabilities in anticipating and planning action sequences to accomplish tasks an…
SCTc-TE: A Comprehensive Formulation and Benchmark for Temporal Event Forecasting
Yunshan Ma, Chenchen Ye, Zijian Wu +4
Temporal complex event forecasting aims to predict the future events given the observed events from history. Most formulations of temporal complex event are unstructured or without…
MultiCBR: Multi-view Contrastive Learning for Bundle Recommendation
Yunshan Ma, Yingzhi He, Xiang Wang +4
Bundle recommendation seeks to recommend a bundle of related items to users to improve both user experience and the profits of platform. Existing bundle recommendation models have…
A Study of Implicit Ranking Unfairness in Large Language Models
Chen Xu, Wenjie Wang, Yuxin Li +3
Recently, Large Language Models (LLMs) have demonstrated a superior ability to serve as ranking models. However, concerns have arisen as LLMs will exhibit discriminatory ranking be…
Leveraging Multimodal Features and Item-level User Feedback for Bundle Construction
Yunshan Ma, Xiaohao Liu, Yinwei Wei +3
Automatic bundle construction is a crucial prerequisite step in various bundle-aware online services. Previous approaches are mostly designed to model the bundling strategy of exis…
Empowering Collaborative Filtering with Principled Adversarial Contrastive Loss
An Zhang, Leheng Sheng, Zhibo Cai +2
Contrastive Learning (CL) has achieved impressive performance in self-supervised learning tasks, showing superior generalization ability. Inspired by the success, adopting CL into…
On Generative Agents in Recommendation
An Zhang, Yuxin Chen, Leheng Sheng +2
Recommender systems are the cornerstone of today's information dissemination, yet a disconnect between offline metrics and online performance greatly hinders their development. Add…