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20112024
most citedGood Semi-supervised Learning that Requires a Bad GAN

228 citations · 2.2k across the 99 of their papers we have counts for

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6 papers · 1 filter

cs.AI2023

Graph Meets LLM: A Novel Approach to Collaborative Filtering for Robust Conversational Understanding

Zheng Chen, Ziyan Jiang, Fan Yang +5

Conversational AI systems such as Alexa need to understand defective queries to ensure robust conversational understanding and reduce user friction. These defective queries often a…

cs.AI2023★ 6 cited

Introspective Tips: Large Language Model for In-Context Decision Making

Liting Chen, Lu Wang, Hang Dong +9

The emergence of large language models (LLMs) has substantially influenced natural language processing, demonstrating exceptional results across various tasks. In this study, we em…

cs.AI2023★ 5 cited

Data-centric AI: Perspectives and Challenges

Daochen Zha, Zaid Pervaiz Bhat, Kwei-Herng Lai +2

The role of data in building AI systems has recently been significantly magnified by the emerging concept of data-centric AI (DCAI), which advocates a fundamental shift from model…

cs.AI2021★ 78 cited

Advancing COVID-19 Diagnosis with Privacy-Preserving Collaboration in Artificial Intelligence

Xiang Bai, Hanchen Wang, Liya Ma +43

Artificial intelligence (AI) provides a promising substitution for streamlining COVID-19 diagnoses. However, concerns surrounding security and trustworthiness impede the collection…

cs.AI2017★ 171 cited

Differentiable Learning of Logical Rules for Knowledge Base Reasoning

Fan Yang, Zhilin Yang, William W. Cohen

We study the problem of learning probabilistic first-order logical rules for knowledge base reasoning. This learning problem is difficult because it requires learning the parameter…

cs.AI2011★ 73 cited

A General Theory of Additive State Space Abstractions

Fan Yang, Joseph Culberson, Robert Holte +2

Informally, a set of abstractions of a state space S is additive if the distance between any two states in S is always greater than or equal to the sum of the corresponding distanc…