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Evo-Harness: Context-to-Harness Skill Compilation for Self-Evolving Agents
Preprint
Tianxin Wei, Zhan Shi, Minhua Lin, Bing He, Zewen Liu, Yisi Sang, Yuanchen Bei, Xuying Ning, Jiaru Zou, Ting-Wei Li, Xiao Lin, Yanjun Zhao, Chi Wang, Benoit Dumoulin, Dakuo Wang, Jingrui He, Hanqing Lu
Key Insight: Compiles contextual experience into reusable harness skills for self-evolving agents.
AgentLLM
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Code as Agent Harness
Preprint
Xuying Ning*, Katherine Tieu*, Dongqi Fu*, Tianxin Wei*, Zihao Li*, Yuanchen Bei*, Jiaru Zou, Mengting Ai, Zhining Liu, Ting-Wei Li, Lingjie Chen, Yanjun Zhao, Ke Yang, Bingxuan Li, Cheng Qian, Gaotang Li, Xiao Lin, Zhichen Zeng, Ruizhong Qiu, Sirui Chen, Yifan Sun, Xiyuan Yang, Ruida Wang, Rui Pan, Chenyuan Yang, Dylan Zhang, Liri Fang, Zikun Cui, Yang Cao, Pan Chen, Dorothy Sun, Ren Chen, Mahesh Srinivasan, Nipun Mathur, Yinglong Xia, Hong Li, Hong Yan, Pan Lu, Lingming Zhang, Tong Zhang, Hanghang Tong, Jingrui He
Key Insight: Treats executable code as a harness for agent deployment, evaluation, and improvement.
AgentLLM
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ReContext: Recursive Evidence Replay as LLM Harness for Long-Context Reasoning
Preprint
Yanjun Zhao*, Ruizhong Qiu*, Tianxin Wei*, Yuanchen Bei, Zhining Liu, Lingjie Chen, Ismini Lourentzou, Hanghang Tong, Jingrui He
Key Insight: Recursively replays evidence to build an LLM harness for long-context reasoning.
AgentLLMRetrieval
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EvoSelect: Data-Efficient LLM Evolution for Targeted Task Adaptation
Preprint
Ting-Wei Li, Sirui Chen, Jiaru Zou, Yingbing Huang, Tianxin Wei, Jingrui He, Hanghang Tong
Key Insight: Data-efficient LLM evolution for adapting models to targeted tasks.
AgentLLMEfficiency
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Adaptive Auto-Harness: Sustained Self-Improvement for Agentic System Deployment on Open-Ended Task Streams
Preprint
Zewen Liu, Zhan Shi, Yisi Sang, Bing He, Minhua Lin, Tianxin Wei, Dakuo Wang, Benoit Dumoulin, Wei Jin, Hanqing Lu
Key Insight: Sustained self-improvement for agentic systems deployed on open-ended task streams.
AgentLLM
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Harness Updating Is Not Harness Benefit: Disentangling Evolution Capabilities in Self-Evolving LLM Agents
Preprint
Minhua Lin, Juncheng Wu, Zijun Wang, Zhan Shi, Yisi Sang, Bing He, Zewen Liu, Tianxin Wei, Zongyu Wu, Zhiwei Zhang, Dakuo Wang, Xiang Zhang, Benoit Dumoulin, Cihang Xie, Yuyin Zhou
Key Insight: Separates harness updates from true harness benefit in self-evolving LLM agents.
AgentLLM
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RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation
Preprint
Shijun Li, Wooseong Yang, Yu Wang, Tianxin Wei, Joydeep Ghosh
Key Insight: Ranking-driven retrieval over collaborative and metadata memories for LLM recommendation.
LLMPersonalizationRetrieval
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Heterogeneous Scientific Foundation Model Collaboration
Preprint
Zihao Li, Jiaru Zou, Feihao Fang, Xuying Ning, Mengting Ai, Tianxin Wei, Sirui Chen, Xiyuan Yang, Jingrui He
Key Insight: Heterogeneous agent collaboration between language models and specialized scientific foundation models.
LLMMulti-AgentApplication
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Agentic Reasoning for Large Language Models: A Survey
Survey 2026
Tianxin Wei, Ting-Wei Li, Zhining Liu, Xuying Ning, Ze Yang, Jiaru Zou, Zhichen Zeng, Ruizhong Qiu, Xiao Lin, Dongqi Fu, Zihao Li, Mengting Ai, Duo Zhou, Wenxuan Bao, Yunzhe Li, Gaotang Li, Cheng Qian, Yu Wang, Xiangru Tang, Yin Xiao, Liri Fang, Hui Liu, Xianfeng Tang, Yuji Zhang, Chi Wang, Jiaxuan You, Heng Ji, Hanghang Tong, Jingrui He
Key Insight: Unified taxonomy of how LLM agents plan, use tools, and reflect to reason.
AgentSurvey
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Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory
arXiv 2025
Tianxin Wei, Noveen Sachdeva, Benjamin Coleman, Zhankui He, Yuarchen Bei, Xuying Ning, Mengting Ai, Yunzhe Li, Jingrui He, Ed H. Chi, Chi Wang, Shuo Chen, Fernando Pereira, Wang-Cheng Kang, Derek Zhiyuan Cheng
Key Insight: LLM agents that autonomously build and refine memory from experience at test time.
AgentPersonalization
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CoFiRec: Coarse-to-Fine Tokenization for Generative Recommendation
arXiv 2025
Tianxin Wei*, Xuying Ning*, Xuxing Chen, Ruizhong Qiu, Yupeng Hou, Yan Xie, Shuang Yang, Zhigang Hua, Jingrui He
Key Insight: Hierarchical tokenization bridging semantics and collaboration for generative recommendation.
LLMPersonalization
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Rethinking Memory Mechanisms of Foundation Agents in the Second Half: A Survey
arXiv 2026
Joint work across 27 institutions.
Key Insight: Comprehensive categorization of agent memory mechanisms and key design gaps.
AgentSurveyPersonalization
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AdaFuse: Adaptive Ensemble Decoding with Test-Time Scaling for LLMs
ACL 2026 Main
Chengming Cui*, Tianxin Wei*^, Ziyi Chen, Ruizhong Qiu, Zhichen Zeng, Zhining Liu, Xuying Ning, Duo Zhou, Jingrui He
Key Insight: Fuse multiple LLM outputs adaptively at decode time via test-time scaling.
LLMEfficiencyMulti-Agent
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PaperMind: Benchmarking Agentic Reasoning and Critique over Scientific Papers in Multimodal LLMs
ACL 2026 Findings
Yanjun Zhao*, Tianxin Wei*^, Jiaru Zou, Xuying Ning, Yuanchen Bei, Lingjie Chen, Simmi Rana, Wendy H. Yang, Hanghang Tong, Jingrui He
Key Insight: Benchmark for evaluating multimodal LLM reasoning and critique over scientific papers.
AgentMultimodal
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Mem-Gallery: Benchmarking Multimodal Long-Term Conversational Memory for MLLM Agents
ACL 2026 Main
Yuanchen Bei, Tianxin Wei^, Xuying Ning, Yanjun Zhao, Zhining Liu, Xiao Lin, Yada Zhu, Hendrik Hamann, Jingrui He, Hanghang Tong
Key Insight: Benchmark exposing MLLM agents' failure in long-term multimodal conversational memory.
AgentMultimodalPersonalization
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MC-Search: Evaluating and Enhancing Multimodal Agentic Search with Structured Long Reasoning Chains
ICLR 2026 Oral (Top 1%). Prelim version at NeurIPS 2025 Workshop.
Xuying Ning*, Dongqi Fu*, Tianxin Wei*, Mengting Ai, Jiaru Zou, Ting-Wei Li, Hanghang Tong, Yada Zhu, Hendrik Hamann, Jingrui He
Key Insight: Structured long reasoning chains for multimodal agentic search.
AgentMultimodalRobustness
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Seeing but Not Believing: Probing the Disconnect Between Visual Attention and Answer Correctness in VLMs
ICLR 2026
Zhining Liu, Ziyi Chen, Hui Liu, Chen Luo, Xianfeng Tang, Suhang Wang, Joy Zeng, Zhenwei Dai, Zhan Shi, Tianxin Wei, Benoit Dumoulin, Hanghang Tong
Key Insight: Correct visual attention does not guarantee correct VLM reasoning.
MultimodalRobustness
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Harnessing Consistency for Robust Test-Time LLM Ensemble
EACL 2026 Findings
Zhichen Zeng, Qi Yu, Xiao Lin, Ruizhong Qiu, Xuying Ning, Tianxin Wei, Yuchen Yan, Jingrui He, Hanghang Tong
Key Insight: Consistency-driven test-time LLM ensemble for robust multi-model agreement.
LLMMulti-Agent
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Panda: Test-Time Adaptation with Negative Data Augmentation
AAAI 2026
Ruxi Deng, Wenxuan Bao, Tianxin Wei, Jingrui He
Key Insight: Negative data augmentation at test time for robust domain adaptation.
MultimodalTest-timePersonalizationRobustness
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CLIMB: Class-imbalanced Learning Benchmark on Tabular Data
NeurIPS 2025
Zhining Liu, Zihao Li, Ze Yang, Tianxin Wei, Jian Kang, Yada Zhu, Hendrik Hamann, Jingrui He, Hanghang Tong
Key Insight: Unified benchmark for class-imbalanced tabular learning.
Robustness
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Latte: Collaborative Test-Time Adaptation of Vision-Language Models in Federated Learning
ICCV 2025
Wenxuan Bao, Ruxi Deng, Ruizhong Qiu, Tianxin Wei, Hanghang Tong, Jingrui He
Key Insight: Collaborative test-time VLM adaptation across federated clients without sharing data.
MultimodalTest-timePersonalizationRobustness
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Learning to Instruct: Fine-Tuning a Task-Aware Instruction Optimizer for Black-Box LLMs
EMNLP 2025 Findings
Yunzhe Qi, Jinjin Tian, Tianci Liu, Ruirui Li, Tianxin Wei, Hui Liu, Xianfeng Tang, Monica Xiao Cheng, Jingrui He
Key Insight: Auto-rewrite prompts for black-box LLMs via a learned instruction optimizer.
LLM
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SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence
ACL 2025 Main
Zhining Liu, Rana Ali Amjad, Ravinarayana Adkathimar, Tianxin Wei, Hanghang Tong
Key Insight: LLMs implicitly know where evidence is; self-eliciting beats external retrievers.
LLMRetrieval
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i²VAE: Interest Information Augmentation with Variational Regularizers for Cross-Domain Sequential Recommendation
UAI 2025
Xuying Ning, Wujiang Xu, Tianxin Wei, Xiaolei Liu
Key Insight: Variational interest augmentation for cross-domain sequential recommendation.
PersonalizationRobustness
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Graph4MM: Weaving Multimodal Learning with Structural Information
ICML 2025
Xuying Ning, Dongqi Fu, Tianxin Wei, Wujiang Xu, Jingrui He
Key Insight: Graph structure as inductive bias for richer multimodal representations.
LLMMultimodal
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Breaking Silos: Adaptive Model Fusion Unlocks Better Time Series Forecasting
ICML 2025
Zhining Liu, Ze Yang, Xiao Lin, Ruizhong Qiu, Tianxin Wei, Yada Zhu, Hendrik Hamann, Jingrui He, Hanghang Tong
Key Insight: Adaptive fusion of heterogeneous time series forecasters breaks model silos.
ApplicationEfficiency
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Connecting Domains and Contrasting Samples: A Ladder for Domain Generalization
KDD 2025 (Full Research, AR: 19%)
Tianxin Wei*, Yifan Chen*, Wenxuan Bao, Jingrui He
Key Insight: Progressive domain connection via contrastive alignment for domain generalization.
Robustness
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MLP Fusion: Towards Efficient Fine-tuning of Dense and Mixture-of-Experts Language Models
v1 accepted to ICML 2023. Submitted to IEEE for possible publication.
Mengting Ai*, Tianxin Wei*, Yifan Chen*, Zeming Guo, Jingrui He
Key Insight: Lightweight MLP fusion for parameter-efficient fine-tuning of dense and MoE LLMs.
LLMEfficiency
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ResMoE: Space-efficient Compression of Mixture of Experts LLMs via Residual Restoration
KDD 2025 (Full Research, AR: 19%)
Mengting Ai*, Tianxin Wei*^, Yifan Chen*, Zhichen Zeng, Ritchie Zhao, Girish Varatkar, Bita Darvish Rouhani, Xianfeng Tang, Hanghang Tong, Jingrui He
Key Insight: Residual restoration compresses MoE LLMs while preserving expert specialization.
LLMEfficiency
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Meta Clustering of Neural Bandits
KDD 2024 (Full Research, AR: 20%)
Yikun Ban, Yunzhe Qi, Tianxin Wei, Lihui Liu, Jingrui He
Key Insight: Meta-learning discovers bandit arm clusters for efficient shared exploration.
Efficiency
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Graph Mixup on Approximate Gromov-Wasserstein Geodesics
ICML 2024 (Full Research, AR: 27.5%)
Zhichen Zeng, Ruizhong Qiu, Zhe Xu, Zhining Liu, Yuchen Yan, Tianxin Wei, Lei Ying, Jingrui He, Hanghang Tong
Key Insight: Graph mixup along Gromov-Wasserstein geodesics for topology-aware augmentation.
Robustness
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Language Models as Semantic Indexers
ICML 2024 (Full Research, AR: 27.5%)
Bowen Jin, Hansi Zeng, Guoyin Wang, Xiusi Chen, Tianxin Wei, Ruirui Li, Zhengyang Wang, Zheng Li, Yang Li, Hanqing Lu, Suhang Wang, Jiawei Han, Xianfeng Tang
Key Insight: Language models as end-to-end semantic indexers replacing traditional retrieval.
LLMRetrieval
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Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond
ICLR 2024 (Full Research, AR: 31%)
Tianxin Wei, Bowen Jin, Ruirui Li, Hansi Zeng, Zhengyang Wang, Jianhui Sun, Qingyu Yin, Hanqing Lu, Suhang Wang, Jingrui He, Xianfeng Tang
Key Insight: One vision-language model for unified multi-modal generative recommendation.
LLMMultimodalPersonalization
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Scalable and Effective Generative Information Retrieval
WWW 2024 (Oral) (Full Research, AR: 20.2%)
Hansi Zeng, Chen Luo, Bowen Jin, Sheikh Muhammad Sarwar, Tianxin Wei, Hamed Zamani
Key Insight: Scalable generative retrieval via residual-quantized prefix language modeling.
LLMRetrieval
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TAU: Trajectory Data Augmentation with Uncertainty for Next POI Recommendation
AAAI 2024 (Full Research, AR: 24%)
Zhuang Zhuang, Tianxin Wei^, Lingbo Liu, Heng Qi, Yanming Shen, Baocai Yin
Key Insight: Uncertainty-aware trajectory augmentation for next POI recommendation.
RobustnessPersonalization
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Meta-Learning with Neural Bandit Scheduler
NeurIPS 2023 (Full Research, AR: 26.1%)
Yunzhe Qi, Yikun Ban, Tianxin Wei, Jiaru Zou, Huaxiu Yao, Jingrui He
Key Insight: Neural bandit scheduling for adaptive task allocation in meta-learning.
Efficiency
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Adaptive Test-Time Personalization for Federated Learning
NeurIPS 2023 (Full Research, AR: 26.1%)
Wenxuan Bao*, Tianxin Wei*, Haohan Wang, Jingrui He
Key Insight: Test-time personalization bridging global federated models to local distributions.
RobustnessTest-timePersonalization
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NTK-approximating MLP Fusion for Efficient Language Model Fine-tuning
ICML 2023 (Full Research, AR: 27.9%)
Tianxin Wei*^, Zeming Guo*, Yifan Chen*, Jingrui He
Key Insight: NTK-principled MLP fusion for theoretically grounded efficient LLM fine-tuning.
LLMEfficiency
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Augmentations in Hypergraph Contrastive Learning: Fabricated and Generative
NeurIPS 2022 (Full Research, AR: 25.6%)
Tianxin Wei*, Yuning You*, Tianlong Chen, Yang Shen, Jingrui He, Zhangyang Wang
Key Insight: Fabricated and generative augmentations for hypergraph contrastive learning.
Robustness
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Comprehensive Fair Meta-learned Recommender System
KDD 2022 (Full Research, AR: 15.0%)
Tianxin Wei, Jingrui He
Key Insight: Meta-learned recommendation with built-in fairness across user demographics.
FairnessPersonalization
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Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System
KDD 2021 (Full Research, AR: 15.4%)
Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi, Xiangnan He
Key Insight: Counterfactual reasoning removes popularity bias from any recommender.
BiasPersonalization
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Causal Intervention for Leveraging Popularity Bias in Recommendation
SIGIR 2021 Best Paper Honorable Mention (1 out of All) (Full Research, AR: 21%)
Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling, Yongdong Zhang
Key Insight: Causal intervention that leverages popularity signals while suppressing recommendation bias.
BiasPersonalization
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Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning
ICDM 2020 (Full Research, AR: 9.8%)
Tianxin Wei, Ziwei Wu, Ruirui Li, Ziniu Hu, Fuli Feng, Xiangnan He, Yizhou Sun, Wei Wang
Key Insight: Meta-learning for rapid cold-start adaptation from few user interactions.
TransferabilityPersonalization
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Unpaired Multimodal Neural Machine Translation via Reinforcement Learning
DASFAA 2021 (Full Research, AR: 20%)
Yijun Wang*, Tianxin Wei*, Qi Liu, Enhong Chen
Key Insight: RL-based alignment of unpaired images and text for multimodal translation.
Multimodal
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AR-Stock: Deep Augmented Relational Stock Prediction
AAAI 2021 Workshop on Knowledge Discovery from Unstructured Data (Oral)
Tianxin Wei, Yuning You, Tianlong Chen
Key Insight: Augmented relational graph learning capturing inter-stock market dynamics.
Application
-
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DiffKGW: Stealthy and Robust Diffusion Model Watermarking
TMLR
Tianxin Wei, Ruizhong Qiu, Yifan Chen, Yunzhe Qi, Jiacheng Lin, Wenxuan Bao, Wenju Xu, Sreyashi Nag, Ruirui Li, Hanqing Lu, Zhengyang Wang, Chen Luo, Hui Liu, Suhang Wang, Jingrui He, Qi He, Xianfeng Tang
Key Insight: Stealthy robust watermarking for diffusion models via generation time intervention analogous to LLMs.
DiffusionRobustness
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Pave Your Own Path: Graph Gradual Domain Adaptation on Fused Gromov-Wasserstein Geodesics
TMLR
Zhichen Zeng, Ruizhong Qiu, Wenxuan Bao, Tianxin Wei, Xiao Lin, Yuchen Yan, Tarek F. Abdelzaher, Jiawei Han, Hanghang Tong
Key Insight: Gradual graph domain adaptation along fused Gromov-Wasserstein geodesics.
Robustness
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Flow Matching Meets Biology and Life Science: A Survey
npj Artificial Intelligence
Zihao Li, Zhichen Zeng, Xiao Lin, Feihao Fang, Yanru Qu, Zhe Xu, Zhining Liu, Xuying Ning, Tianxin Wei, Ge Liu, Hanghang Tong, Jingrui He
Key Insight: Survey connecting flow matching to molecular and biological modeling.
SurveyApplication
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Graph Contrastive Learning: An Odyssey towards Generalizable, Scalable and Principled Representation Learning on Graphs
IEEE Data Engineering Bulletin
Yan Han, Yuning You, Wenqing Zheng, Scott Hoang, Tianxin Wei, Majdi Hassan, Tianlong Chen, Ying Ding, Yang Shen, Zhangyang Wang
Key Insight: Roadmap from augmentation design to principled graph contrastive learning.
Survey