26 citations · 40 across the 6 of their papers we have counts for
6 papers
Search-on-Graph: Iterative Informed Navigation for Large Language Model Reasoning on Knowledge Graphs
Jia Ao Sun, Hao Yu, Fabrizio Gotti +6
Large language models (LLMs) augmented with knowledge graphs (KGs) offer a promising approach for knowledge-intensive reasoning. Central to this approach is the selection of approp…
Aligning Query Representation with Rewritten Query and Relevance Judgments in Conversational Search
Fengran Mo, Chen Qu, Kelong Mao +4
Conversational search supports multi-turn user-system interactions to solve complex information needs. Different from the traditional single-turn ad-hoc search, conversational sear…
Unifying Graph Convolution and Contrastive Learning in Collaborative Filtering
Yihong Wu, Le Zhang, Fengran Mo +3
Graph-based models and contrastive learning have emerged as prominent methods in Collaborative Filtering (CF). While many existing models in CF incorporate these methods in their d…
Exploring the Best Practices of Query Expansion with Large Language Models
Le Zhang, Yihong Wu, Qian Yang +1
Large Language Models (LLMs) are foundational in language technologies, particularly in information retrieval (IR). Previous studies have utilized LLMs for query expansion, achievi…
Collaboration and Transition: Distilling Item Transitions into Multi-Query Self-Attention for Sequential Recommendation
Tianyu Zhu, Yansong Shi, Yuan Zhang +3
Modern recommender systems employ various sequential modules such as self-attention to learn dynamic user interests. However, these methods are less effective in capturing collabor…
MoqaGPT : Zero-Shot Multi-modal Open-domain Question Answering with Large Language Model
Le Zhang, Yihong Wu, Fengran Mo +2
Multi-modal open-domain question answering typically requires evidence retrieval from databases across diverse modalities, such as images, tables, passages, etc. Even Large Languag…