TianxinWei

Awesome-Agentic-Reasoning. A curated list of papers and resources based on the survey "Agentic Reasoning for Large Language Models"

awesome-distribution-shift. A curated list of papers and resources about the distribution shift in machine learning.

MACR. [KDD 2021] Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System

HyperGCL. [NeurIPS 2022] "Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative" by Tianxin Wei, Yuning You, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang

UniMP. [ICLR 2024] Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond

MLP_Fusion. [ICML 2023] NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning

CLOVER. [KDD 2022] Comprehensive Fair Meta-learned Recommender System

DCCL. [KDD 2025] Connecting Domains and Contrasting Samples: A Ladder for Domain Generalization (DCCL)

Graph_Pool. To build a better graph classification model

weitianxin.github.io. HTML

GraphCL. [NeurIPS 2020] "Graph Contrastive Learning with Augmentations" by Yuning You, Tianlong Chen, Yongduo Sui, Ting Chen, Zhangyang Wang, Yang Shen