activity
20212024
most citedOpenAGI: When LLM Meets Domain Experts

76 citations · 282 across the 19 of their papers we have counts for

collaborators
Showing 2023Show all

8 papers · 1 filter

cs.OS2023★ 2 cited

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…

cs.IR2023

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…

cs.IR2023★ 6 cited

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…

cs.IR2023★ 20 cited

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…

cs.IR2023★ 7 cited

UP5: Unbiased Foundation Model for Fairness-aware Recommendation

Wenyue Hua, Yingqiang Ge, Shuyuan Xu +2

Recent advances in Foundation Models such as Large Language Models (LLMs) have propelled them to the forefront of Recommender Systems (RS). Despite their utility, there is a growin…

cs.AI2023★ 76 cited

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…

cs.IR2023★ 10 cited

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…

cs.AI2023★ 1 cited

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…