Tianxin Wei

Orcid: 0000-0003-4450-2005

According to our database1, Tianxin Wei authored at least 40 papers between 2020 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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Bibliography

2025
Seeing but Not Believing: Probing the Disconnect Between Visual Attention and Answer Correctness in VLMs.
CoRR, October, 2025

Graph4MM: Weaving Multimodal Learning with Structural Information.
CoRR, October, 2025

Harnessing Consistency for Robust Test-Time LLM Ensemble.
CoRR, October, 2025

Hierarchical LoRA MoE for Efficient CTR Model Scaling.
CoRR, October, 2025

NIRVANA: Structured pruning reimagined for large language models compression.
CoRR, September, 2025

Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning.
CoRR, July, 2025

Flow Matching Meets Biology and Life Science: A Survey.
CoRR, July, 2025

Saffron-1: Towards an Inference Scaling Paradigm for LLM Safety Assurance.
CoRR, June, 2025

Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting.
CoRR, May, 2025

CLIMB: Class-imbalanced Learning Benchmark on Tabular Data.
CoRR, May, 2025

Pave Your Own Path: Graph Gradual Domain Adaptation on Fused Gromov-Wasserstein Geodesics.
CoRR, May, 2025

CATS: Mitigating Correlation Shift for Multivariate Time Series Classification.
CoRR, April, 2025

i<sup>2</sup>VAE: Interest Information Augmentation with Variational Regularizers for Cross-Domain Sequential Recommendation.
Proceedings of the Conference on Uncertainty in Artificial Intelligence, 2025

Connecting Domains and Contrasting Samples: A Ladder for Domain Generalization.
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

ResMoE: Space-efficient Compression of Mixture of Experts LLMs via Residual Restoration.
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, 2025

LLM-Forest: Ensemble Learning of LLMs with Graph-Augmented Prompts for Data Imputation.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024
PyG-SSL: A Graph Self-Supervised Learning Toolkit.
CoRR, 2024

LLM-Forest for Health Tabular Data Imputation.
CoRR, 2024

Unleashing the Power of LLMs as Multi-Modal Encoders for Text and Graph-Structured Data.
CoRR, 2024

WAPITI: A Watermark for Finetuned Open-Source LLMs.
CoRR, 2024

Scalable and Effective Generative Information Retrieval.
Proceedings of the ACM on Web Conference 2024, 2024

Meta Clustering of Neural Bandits.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Graph Mixup on Approximate Gromov-Wasserstein Geodesics.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Language Models as Semantic Indexers.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

TAU: Trajectory Data Augmentation with Uncertainty for Next POI Recommendation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Graph Contrastive Learning: An Odyssey towards Generalizable, Scalable and Principled Representation Learning on Graphs.
IEEE Data Eng. Bull., 2023

Meta-Learning with Neural Bandit Scheduler.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Adaptive Test-Time Personalization for Federated Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning.
Proceedings of the International Conference on Machine Learning, 2023

Robust Basket Recommendation via Noise-tolerated Graph Contrastive Learning.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Neural Collaborative Filtering Bandits via Meta Learning.
CoRR, 2022

Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Comprehensive Fair Meta-learned Recommender System.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
Causal Intervention for Leveraging Popularity Bias in Recommendation.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Unpaired Multimodal Neural Machine Translation via Reinforcement Learning.
Proceedings of the Database Systems for Advanced Applications, 2021

2020
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System.
CoRR, 2020

Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020


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