Haitao Mao
14 papers · 2022–2025 · 6 venues · across top CS/AI venues
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Research topics
Machine Learning
(12)
Deep Learning
(8)
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(8)
Artificial Intelligence
(6)
Core AI
(6)
Learning Types · Machine Learning
(5)
Core Methods
(4)
Natural Language Processing
(3)
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Optimization & Theory · Machine Learning
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Resources & Methods
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(1)
Keywords
graph neural network
(7)
node classification
(4)
large language model
(4)
domain adaptation
(2)
graph representation
(2)
link prediction
(2)
ai safety
(2)
multilingual nlp
(1)
weakly supervised learning
(1)
semi-supervised learning
(1)
generalization bound
(1)
harmful content
(1)
network analysis
(1)
learning to rank
(1)
convergence analysis
(1)
stability
(1)
distribution shift
(1)
text generation
(1)
alternating optimization
(1)
multi-view learning
(1)
Papers
A Survey to Recent Progress Towards Understanding In-Context Learning
NAACL 2025
On the Convergence of Moral Self-Correction in Large Language Models
IJCNLP 2025
Intrinsic Self-correction for Enhanced Morality: An Analysis of Internal Mechanisms and the Superficial Hypothesis
EMNLP 2024
Label-free Node Classification on Graphs with Large Language Models (LLMs)
ICLR 2024
PDHG-Unrolled Learning-to-Optimize Method for Large-Scale Linear Programming
ICML 2024
Position: Graph Foundation Models Are Already Here
ICML 2024
Revisiting Link Prediction: a data perspective
ICLR 2024
Text-space Graph Foundation Models: Comprehensive Benchmarks and New Insights
NeurIPS 2024
Alternately Optimized Graph Neural Networks
ICML 2023
Amazon-M2: A Multilingual Multi-locale Shopping Session Dataset for Recommendation and Text Generation
NeurIPS 2023
Demystifying Structural Disparity in Graph Neural Networks: Can One Size Fit All?
NeurIPS 2023
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
NeurIPS 2023
A Large Scale Search Dataset for Unbiased Learning to Rank
NeurIPS 2022
Neuron with Steady Response Leads to Better Generalization
NeurIPS 2022