Key papers

• IV-CoT: Implicit Visual Chain-of-Thought for Structure-Aware Text-to-Image Generation (2026)
  Zixuan Li et al.
  8.74
• Local Synaptic Rules Can Implement a SIGReg Gradient Without Backpropagation (2026)
  Martin Andrews
  4.95
• TextSLIP: Text Self-Supervised CLIP for Medical Report Generation (2026)
  Haoyu Jiang et al.
  4.95
• STST-JEPA: Shallow-Target Spatio-Temporal Joint Embedding Prediction Architecture For EEG Self-Supervised Learning (2026)
  Roy Segal et al.
  4.33
• Self-Supervised Pretraining Improves Cross-Site and Cross-Scale Robustness of Point Cloud Leaf-Wood Segmentation (2026)
  Heeju Mun et al.
  4.33
• FMMVCC: Fuzzy Mamba-based Multi-View Contrastive Clustering for Univariate Time Series (2026)
  Donato Cerciello et al.
  4.33
• Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection (2026)
  Mingyue Zeng et al.
  4.33
• Factorized Spectral Representations for Reinforcement Learning (2026)
  Junyi Wu et al.
  4.33
• Consensus as Privileged Context for Label-Free Self-Distillation (2026)
  John Gkountouras et al.
  4.33
• Groc-PO: Grounded Context Preference Optimization for Truthful Multimodal LLMs (2026)
  Zhixiao Zheng et al.
  4.33
• Anatomically Faithful but Temporally Blind: Auditing Attribution for Left-Ventricular Ejection-Fraction Estimation from Echocardiography (2026)
  Hyunkyung Han et al.
  4.33
• MxGPS: Multiplex Graph Transformers for a Power Grid Foundation Model (2026)
  Charilaos Papaioannou et al.
  4.33
• LLM4EHR: Aligning Clinical Time Series with Medical Event Sequences via Large Language Models (2026)
  Jingteng Li et al.
  4.33
• Encoding Invisible Causation for Bridge Diagnostic Agents: Triple-Guided Retrieval-Augmented Fine-Tuning with QLoRA (2026)
  Takato Yasuno
  4.33
• LunarFM: A Shared Multimodal Representation of the Moon's Surface (2026)
  Marc Girona-Mata et al.
  4.33
• TMR-GGNN: Credit Card Fraud Detection based on Time-Aware Multi-Relational Guided Graph Neural Network (2026)
  Rohit Tewari et al.
  4.27
• Navigating User Behavior toward Personalized Multimodal Generation (2026)
  Hengji Zhou et al.
  4.27
• Learning from Complementary Ultrasound Representations for Liver Disease Classification (2026)
  Sabahattin Mert Daloglu et al.
  3.45
• From Observation to Insight: Mechanistic World Models and the Quest for Autonomous Discovery (2026)
  Ingmar Posner et al.
  3.45
• Teaching Tiny VLA Models Where to Look and How to Move (2026)
  Iok Tong Lei et al.
  1.94
• Learning Joint Embeddings of Function and Process Call Graphs for Malware Detection (2025)
  Kartikeya Aneja and Nagender Aneja and Murat Kantarcioglu
  1.44
• Self-Supervised Graph Representation Learning via Global Context Prediction (2020)
  Zhen Peng et al.
  0.00
• Unsupervised, Efficient and Semantic Expertise Retrieval (2016)
  Christophe Van Gysel et al.
  —
• Scalable Semi-Supervised Learning over Networks using Nonsmooth Convex Optimization (2016)
  Alexander Jung and Alfred O. Hero III and Alexandru Mara and Sabeur Aridhi
  —
• Self-supervised Deep Reinforcement Learning with Generalized Computation Graphs for Robot Navigation (2017)
  Gregory Kahn et al.
  —
• Smooth Neighbors on Teacher Graphs for Semi-supervised Learning (2017)
  Yucen Luo et al.
  —
• Self-Supervised Intrinsic Image Decomposition (2017)
  Michael Janner et al.
  —
• Semi-Supervised and Active Few-Shot Learning with Prototypical Networks (2017)
  Rinu Boney and Alexander Ilin
  —
• Mix-and-Match Tuning for Self-Supervised Semantic Segmentation (2017)
  Xiaohang Zhan et al.
  —
• Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning (2018)
  Qimai Li et al.
  —
• Semi-Supervised Online Structure Learning for Composite Event Recognition (2018)
  Evangelos Michelioudakis and Alexander Artikis and Georgios Paliouras
  —
• Self-weighted Multiple Kernel Learning for Graph-based Clustering and Semi-supervised Classification (2018)
  Zhao Kang et al.
  —
• Every Node Counts: Self-Ensembling Graph Convolutional Networks for Semi-Supervised Learning (2018)
  Yawei Luo et al.
  —
• Deep Graph Infomax (2018)
  Petar Veli\v{c}kovi\'c et al.
  —
• Semi-Supervised Overlapping Community Finding based on Label Propagation with Pairwise Constraints (2018)
  Elham Alghamdi and Derek Greene
  —
• Multi-Task Graph Autoencoders (2018)
  Phi Vu Tran
  —
• SGR: Self-Supervised Spectral Graph Representation Learning (2018)
  Anton Tsitsulin et al.
  —
• Contrastive Training for Models of Information Cascades (2018)
  Shaobin Xu and David A. Smith
  —
• Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels (2019)
  Ke Sun et al.
  —
• DSL: Discriminative Subgraph Learning via Sparse Self-Representation (2019)
  Lin Zhang et al.
  —
• Semi-Supervised Few-Shot Learning for Dual Question-Answer Extraction (2019)
  Jue Wang et al.
  —
• Semi-Supervised Graph Classification: A Hierarchical Graph Perspective (2019)
  Jia Li et al.
  —
• Energy Models for Better Pseudo-Labels: Improving Semi-Supervised Classification with the 1-Laplacian Graph Energy (2019)
  Angelica I. Aviles-Rivero et al.
  —
• Cascade-BGNN: Toward Efficient Self-supervised Representation Learning on Large-scale Bipartite Graphs (2019)
  Chaoyang He et al.
  —
• Semi-Supervised Tensor Factorization for Node Classification in Complex Social Networks (2019)
  Georgios Katsimpras et al.
  —
• Contrastive Reasons Detection and Clustering from Online Polarized Debate (2019)
  Amine Trabelsi and Osmar R. Zaiane
  —
• Graph Few-shot Learning via Knowledge Transfer (2019)
  Huaxiu Yao et al.
  —
• Self-supervised Learning for ECG-based Emotion Recognition (2019)
  Pritam Sarkar et al.
  —
• Unsupervised Multi-Task Feature Learning on Point Clouds (2019)
  Kaveh Hassani and Mike Haley
  —
• Pre-train and Learn: Preserve Global Information for Graph Neural Networks (2019)
  Danhao Zhu et al.
  —
• Weakly Supervised Prostate TMA Classification via Graph Convolutional Networks (2019)
  Jingwen Wang et al.
  —
• Unsupervised Domain Adaptation of Contextual Embeddings for Low-Resource Duplicate Question Detection (2019)
  Alexandre Rochette et al.
  —
• Self-Assignment Flows for Unsupervised Data Labeling on Graphs (2019)
  Matthias Zisler et al.
  —
• HighwayGraph: Modelling Long-distance Node Relations for Improving General Graph Neural Network (2019)
  Deli Chen et al.
  —
• Higher-order Weighted Graph Convolutional Networks (2019)
  Songtao Liu et al.
  —
• GraphTER: Unsupervised Learning of Graph Transformation Equivariant Representations via Auto-Encoding Node-wise Transformations (2019)
  Xiang Gao et al.
  —
• Heterogeneous Deep Graph Infomax (2019)
  Yuxiang Ren et al.
  —
• SSAH: Semi-supervised Adversarial Deep Hashing with Self-paced Hard Sample Generation (2019)
  Sheng Jin et al.
  —
• SAG-VAE: End-to-end Joint Inference of Data Representations and Feature Relations (2019)
  Chen Wang et al.
  —
• Graph Inference Learning for Semi-supervised Classification (2020)
  Chunyan Xu et al.
  —