7 papers · 2 filters
Recommender System as Slow and Fast Thinkers
Zichen Yuan, Xiaoxuan Dong, Linkun Dai +8
Sequential recommendation models are foundational to modern personalized services, yet their effectiveness varies substantially across heterogeneous user environments. In particula…
Risk-Aware Reranking for Agentic Tool Retrieval
Qinfei Li, Xiaoxuan Dong, Jin Zhang +6
Tool retrieval determines which external tools are exposed to an LLM agent for a user query or task, making retrieval a critical pre-execution safety boundary. Unlike document retr…
Role of Personality in Conversational Information Seeking
Abdisalam Abukar, Junchen Fu, Chengli Zhai +1
Large language models (LLMs) are increasingly used for information seeking, where users find, compare, and evaluate information through dialogue. In this role, the assistant does m…
RecRec: Latent Interests Recursive Reasoning for Sequential Recommendation
Wenhao Deng, Junchen Fu, Hanwen Du +6
Sequential recommender systems rely on a single forward pass to encode user interaction histories and predict the next item. Increasing inference-time computation through latent re…
Stream-aware Side Adaptation for Large Pre-trained Multimodal Embedding Models in Sequential Recommendation
Junchen Fu, Kaiwen Zheng, Ioannis Arapakis +4
Recently, large pretrained multimodal embedding models such as Qwen3-VL Embedding have shown strong promise for sequential recommendation, as they provide reusable semantic item re…
The 2nd EReL@MIR Workshop on Efficient Representation Learning for Multimodal Information Retrieval
Junchen Fu, Xuri Ge, Xin Xin +6
Multimodal representation learning has attracted increasing attention in AI, driven by the strong performance of large, pretrained multimodal foundation models such as Qwen, LLaVA,…