activity
20232026
most citedTool Learning in the Wild: Empowering Language Models as Automatic Tool Agents

6 citations · 14 across the 21 of their papers we have counts for

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5 papers · 1 filter

cs.IR2025

The 2nd Workshop on Human-Centered Recommender Systems

Kaike Zhang, Jiakai Tang, Du Su +6

Recommender systems shape how people discover information, form opinions, and connect with society. Yet, as their influence grows, traditional metrics, e.g., accuracy, clicks, and…

cs.IR2025

Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models

Zhengliang Shi, Lingyong Yan, Weiwei Sun +7

Retrieval-augmented generation (RAG) integrates large language models ( LLM s) with retrievers to access external knowledge, improving the factuality of LLM generation in knowledge…

cs.IR2025

The 1st EReL@MIR Workshop on Efficient Representation Learning for Multimodal Information Retrieval

Junchen Fu, Xuri Ge, Xin Xin +5

Multimodal representation learning has garnered significant attention in the AI community, largely due to the success of large pre-trained multimodal foundation models like LLaMA,…

cs.IR2025★ 1 cited

Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation

Shijie Wang, Wenqi Fan, Yue Feng +4

Recommender systems have become increasingly vital in our daily lives, helping to alleviate the problem of information overload across various user-oriented online services. The em…

cs.IR2023★ 3 cited

Lending Interaction Wings to Recommender Systems with Conversational Agents

Jiarui Jin, Xianyu Chen, Fanghua Ye +5

Recommender systems trained on offline historical user behaviors are embracing conversational techniques to online query user preference. Unlike prior conversational recommendation…