130 citations · 526 across the 20 of their papers we have counts for
9 papers · 1 filter
LLM as OS, Agents as Apps: Envisioning AIOS, Agents and the AIOS-Agent Ecosystem
Yingqiang Ge, Yujie Ren, Wenyue Hua +3
This paper envisions a revolutionary AIOS-Agent ecosystem, where Large Language Model (LLM) serves as the (Artificial) Intelligent Operating System (IOS, or AIOS)--an operating sys…
User-Controllable Recommendation via Counterfactual Retrospective and Prospective Explanations
Juntao Tan, Yingqiang Ge, Yan Zhu +4
Modern recommender systems utilize users' historical behaviors to generate personalized recommendations. However, these systems often lack user controllability, leading to diminish…
GenRec: Large Language Model for Generative Recommendation
Jianchao Ji, Zelong Li, Shuyuan Xu +4
In recent years, large language models (LLM) have emerged as powerful tools for diverse natural language processing tasks. However, their potential for recommender systems under th…
Counterfactual Collaborative Reasoning
Jianchao Ji, Zelong Li, Shuyuan Xu +5
Causal reasoning and logical reasoning are two important types of reasoning abilities for human intelligence. However, their relationship has not been extensively explored under ma…
VIP5: Towards Multimodal Foundation Models for Recommendation
Shijie Geng, Juntao Tan, Shuchang Liu +2
Computer Vision (CV), Natural Language Processing (NLP), and Recommender Systems (RecSys) are three prominent AI applications that have traditionally developed independently, resul…
Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training
Juntao Tan, Shelby Heinecke, Zhiwei Liu +3
Sequential recommendation models, models that learn from chronological user-item interactions, outperform traditional recommendation models in many settings. Despite the success of…
OpenAGI: When LLM Meets Domain Experts
Yingqiang Ge, Wenyue Hua, Kai Mei +5
Human Intelligence (HI) excels at combining basic skills to solve complex tasks. This capability is vital for Artificial Intelligence (AI) and should be embedded in comprehensive A…
Causal Inference for Recommendation: Foundations, Methods and Applications
Shuyuan Xu, Jianchao Ji, Yunqi Li +3
Recommender systems are important and powerful tools for various personalized services. Traditionally, these systems use data mining and machine learning techniques to make recomme…
ExplainableFold: Understanding AlphaFold Prediction with Explainable AI
Juntao Tan, Yongfeng Zhang
This paper presents ExplainableFold, an explainable AI framework for protein structure prediction. Despite the success of AI-based methods such as AlphaFold in this field, the unde…