Teng Xiao

Vasant G. Honavar

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

On a Connection Between Imitation Learning and RLHF.

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[DOI]

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

SimPER: A Minimalist Approach to Preference Alignment without Hyperparameters.

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Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Dialogue-RAG: Enhancing Retrieval for LLMs via Node-Linking Utterance Rewriting.

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Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Revisiting Scaling Laws for Language Models: The Role of Data Quality and Training Strategies.

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Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

Tracing Human Stress From Physiological Signals Using UWB Radar.

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[DOI]

IEEE Internet Things J., October, 2024

MVP-Stereo: A Parallel Multi-View Patchmatch Stereo Method with Dilation Matching for Photogrammetric Application.

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Remote. Sens., March, 2024

Fact-Level Confidence Calibration and Self-Correction.

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CoRR, 2024

MITA: Bridging the Gap between Model and Data for Test-time Adaptation.

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CoRR, 2024

Discovering Invariant Neighborhood Patterns for Heterophilic Graphs.

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CoRR, 2024

MolBind: Multimodal Alignment of Language, Molecules, and Proteins.

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CoRR, 2024

3M-Diffusion: Latent Multi-Modal Diffusion for Text-Guided Generation of Molecular Graphs.

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[DOI]

Huaisheng Zhu

Vasant G. Honavar

CoRR, 2024

Towards Off-Policy Reinforcement Learning for Ranking Policies with Human Feedback.

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[DOI]

CoRR, 2024

Cal-DPO: Calibrated Direct Preference Optimization for Language Model Alignment.

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[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Efficient Contrastive Learning for Fast and Accurate Inference on Graphs.

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Proceedings of the Forty-first International Conference on Machine Learning, 2024

In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation.

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Proceedings of the Forty-first International Conference on Machine Learning, 2024

Pareto Graph Self-Supervised Learning.

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Proceedings of the IEEE International Conference on Acoustics, 2024

How to Leverage Demonstration Data in Alignment for Large Language Model? A Self-Imitation Learning Perspective.

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Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

GeomCLIP: Contrastive Geometry-Text Pre-training for Molecules.

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Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2024

Learning to Reweight for Generalizable Graph Neural Network.

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Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Improving knowledge tracing via a heterogeneous information network enhanced by student interactions.

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Expert Syst. Appl., December, 2023

Learning to Reweight for Graph Neural Network.

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CoRR, 2023

Improving Fairness of Graph Neural Networks: A Graph Counterfactual Perspective.

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[DOI]

CoRR, 2023

Fairness-aware Message Passing for Graph Neural Networks.

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[DOI]

CoRR, 2023

Counterfactual Learning on Graphs: A Survey.

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[DOI]

CoRR, 2023

Simple and Asymmetric Graph Contrastive Learning without Augmentations.

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[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Certifiably Robust Graph Contrastive Learning.

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reconsidering Learning Objectives in Unbiased Recommendation: A Distribution Shift Perspective.

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Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Towards Fair Graph Neural Networks via Graph Counterfactual.

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Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Towards Bridging Algorithm and Theory for Unbiased Recommendation.

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CoRR, 2022

Decoupled Self-supervised Learning for Non-Homophilous Graphs.

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[DOI]

CoRR, 2022

Towards Unbiased and Robust Causal Ranking for Recommender Systems.

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Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Decoupled Self-supervised Learning for Graphs.

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[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

BA-GNN: On Learning Bias-Aware Graph Neural Network.

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[DOI]

Kun Kuang

Proceedings of the 38th IEEE International Conference on Data Engineering, 2022

Representation Matters When Learning From Biased Feedback in Recommendation.

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[DOI]

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022

Towards Off-Policy Learning for Ranking Policies with Logged Feedback.

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Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Progressive Structure from Motion by Iteratively Prioritizing and Refining Match Pairs.

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[DOI]

Remote. Sens., 2021

Learning How to Propagate Messages in Graph Neural Networks.

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[DOI]

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

A General Offline Reinforcement Learning Framework for Interactive Recommendation.

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[DOI]

Donglin Wang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2019

Neural variational matrix factorization for collaborative filtering in recommendation systems.

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[DOI]

Hong Shen

Appl. Intell., 2019

Hierarchical Neural Variational Model for Personalized Sequential Recommendation.

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[DOI]

Shangsong Liang

Zaiqiao Meng

Proceedings of the World Wide Web Conference, 2019

Variational Deep Collaborative Matrix Factorization for Social Recommendation.

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[DOI]

Hui Tian

Hong Shen

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Neural Variational Matrix Factorization with Side Information for Collaborative Filtering.

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[DOI]

Hong Shen

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019

Semi-supervisedly Co-embedding Attributed Networks.

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Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

ISLF: Interest Shift and Latent Factors Combination Model for Session-based Recommendation.

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Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Robustifying Relative Orientations With Respect to Repetitive Structures and Very Short Baselines for Global SfM.

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Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019

Dynamic Bayesian Metric Learning for Personalized Product Search.

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Proceedings of the 28th ACM International Conference on Information and Knowledge Management, 2019

Dynamic Collaborative Recurrent Learning.

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[DOI]