{"total":67,"rows":[{"id":"2312.02783","title":"Large Language Models on Graphs: A Comprehensive Survey","created":"2023-12-05","cited_by_count":192,"area":null},{"id":"2111.00064","title":"Node Feature Extraction by Self-Supervised Multi-scale Neighborhood Prediction","created":"2021-10-29","cited_by_count":138,"area":null},{"id":"2306.06283","title":"14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon","created":"2023-06-09","cited_by_count":86,"area":null},{"id":"2206.07579","title":"A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions","created":"2022-06-15","cited_by_count":73,"area":null},{"id":"2308.02565","title":"SimTeG: A Frustratingly Simple Approach Improves Textual Graph Learning","created":"2023-08-03","cited_by_count":73,"area":null},{"id":"2407.07457","title":"GLBench: A Comprehensive Benchmark for Graph with Large Language Models","created":"2024-07-10","cited_by_count":36,"area":null},{"id":"2207.04452","title":"NGAME: Negative Mining-aware Mini-batching for Extreme Classification","created":"2022-07-10","cited_by_count":32,"area":null},{"id":"2302.03341","title":"The Effect of Metadata on Scientific Literature Tagging: A Cross-Field Cross-Model Study","created":"2023-02-07","cited_by_count":17,"area":null},{"id":"2112.08652","title":"Extreme Zero-Shot Learning for Extreme Text Classification","created":"2021-12-16","cited_by_count":15,"area":null},{"id":"2210.08410","title":"ELIAS: End-to-End Learning to Index and Search in Large Output Spaces","created":"2022-10-16","cited_by_count":14,"area":null},{"id":"2402.05894","title":"Large Language Model Meets Graph Neural Network in Knowledge Distillation","created":"2024-02-08","cited_by_count":14,"area":"distill"},{"id":"2204.10716","title":"Hierarchical Label-wise Attention Transformer Model for Explainable ICD Coding","created":"2022-04-22","cited_by_count":13,"area":null},{"id":"2211.00640","title":"CascadeXML: Rethinking Transformers for End-to-end Multi-resolution Training in Extreme Multi-label Classification","created":"2022-10-29","cited_by_count":12,"area":null},{"id":"2502.18771","title":"Exploring Graph Learning Tasks with Pure LLMs: A Comprehensive Benchmark and Investigation","created":"2025-02-26","cited_by_count":12,"area":null},{"id":"2208.04609","title":"E2EG: End-to-End Node Classification Using Graph Topology and Text-based Node Attributes","created":"2022-08-09","cited_by_count":7,"area":null},{"id":"2210.03968","title":"A Survey on Extreme Multi-label Learning","created":"2022-10-08","cited_by_count":7,"area":null},{"id":"2305.12349","title":"PINA: Leveraging Side Information in eXtreme Multi-label Classification via Predicted Instance Neighborhood Aggregation","created":"2023-05-21","cited_by_count":7,"area":null},{"id":"2310.10636","title":"Dual-Encoders for Extreme Multi-Label Classification","created":"2023-10-16","cited_by_count":7,"area":null},{"id":"2402.07309","title":"HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphs","created":"2024-02-11","cited_by_count":7,"area":null},{"id":"2301.11309","title":"SemSup-XC: Semantic Supervision for Zero and Few-shot Extreme Classification","created":"2023-01-26","cited_by_count":6,"area":null},{"id":"2307.08235","title":"Towards Heterogeneous Long-tailed Learning: Benchmarking, Metrics, and Toolbox","created":"2023-07-17","cited_by_count":6,"area":null},{"id":"2307.16265","title":"Recent Advances in Hierarchical Multi-label Text Classification: A Survey","created":"2023-07-30","cited_by_count":6,"area":null},{"id":"2311.05081","title":"Generalized test utilities for long-tail performance in extreme multi-label classification","created":"2023-11-09","cited_by_count":6,"area":null},{"id":"2212.05857","title":"Automated ICD Coding using Extreme Multi-label Long Text Transformer-based Models","created":"2022-12-12","cited_by_count":5,"area":null},{"id":"2503.01203","title":"Hypergraph Foundation Model","created":"2025-03-03","cited_by_count":5,"area":null},{"id":"2505.24640","title":"Efficient Text Encoders for Labor Market Analysis","created":"2025-05-30","cited_by_count":5,"area":null},{"id":"2312.02429","title":"PEFA: Parameter-Free Adapters for Large-scale Embedding-based Retrieval Models","created":"2023-12-05","cited_by_count":4,"area":null},{"id":"2401.10337","title":"Noise Contrastive Estimation-based Matching Framework for Low-Resource Security Attack Pattern Recognition","created":"2024-01-18","cited_by_count":4,"area":null},{"id":"2407.08503","title":"DIOR-ViT: Differential Ordinal Learning Vision Transformer for Cancer Classification in Pathology Images","created":"2024-07-10","cited_by_count":4,"area":null},{"id":"2510.13847","title":"DynaSpec: Context-aware Dynamic Speculative Sampling for Large-Vocabulary Language Models","created":"2025-10-11","cited_by_count":4,"area":"inference"},{"id":"2510.17520","title":"Curiosity Meets Cooperation: A Game-Theoretic Approach to Long-Tail Multi-Label Learning","created":"2025-10-20","cited_by_count":4,"area":null},{"id":"2308.13139","title":"MatchXML: An Efficient Text-label Matching Framework for Extreme Multi-label Text Classification","created":"2023-08-25","cited_by_count":3,"area":null},{"id":"2405.04545","title":"Learning label-label correlations in Extreme Multi-label Classification via Label Features","created":"2024-05-03","cited_by_count":3,"area":null},{"id":"2406.11884","title":"Hierarchical Compression of Text-Rich Graphs via Large Language Models","created":"2024-06-13","cited_by_count":3,"area":null},{"id":"2411.03171","title":"Navigating Extremes: Dynamic Sparsity in Large Output Spaces","created":"2024-11-05","cited_by_count":3,"area":null},{"id":"2508.00507","title":"Court of LLMs: Evidence-Augmented Generation via Multi-LLM Collaboration for Text-Attributed Graph Anomaly Detection","created":"2025-08-01","cited_by_count":3,"area":null},{"id":"2306.05553","title":"Equivariant vs. Invariant Layers: A Comparison of Backbone and Pooling for Point Cloud Classification","created":"2023-06-08","cited_by_count":2,"area":null},{"id":"2406.09288","title":"Large Language Model as a Teacher for Zero-shot Tagging at Extreme Scales","created":"2024-06-13","cited_by_count":2,"area":null},{"id":"2411.04276","title":"Labels in Extremes: How Well Calibrated are Extreme Multi-label Classifiers?","created":"2024-11-06","cited_by_count":2,"area":null},{"id":"2411.13687","title":"Your Extreme Multi-label Classifier is Secretly a Hierarchical Text Classifier for Free","created":"2024-11-20","cited_by_count":2,"area":null},{"id":"2505.11538","title":"BrainNetMLP: An Efficient and Effective Baseline for Functional Brain Network Classification","created":"2025-05-14","cited_by_count":2,"area":null},{"id":"2603.10876","title":"An Extreme Multi-label Text Classification (XMTC) Library Dataset: What if we took \"Use of Practical AI in Digital Libraries\" seriously?","created":"2026-03-11","cited_by_count":2,"area":null},{"id":"2204.03954","title":"Are We Really Making Much Progress in Text Classification? A Comparative Review","created":"2022-04-08","cited_by_count":1,"area":null},{"id":"2302.09150","title":"Cluster-Guided Label Generation in Extreme Multi-Label Classification","created":"2023-02-17","cited_by_count":1,"area":null},{"id":"2311.13502","title":"Bitformer: An efficient Transformer with bitwise operation-based attention for Big Data Analytics at low-cost low-precision devices","created":"2023-11-22","cited_by_count":1,"area":null},{"id":"2402.18434","title":"Graph Regularized Encoder Training for Extreme Classification","created":"2024-02-28","cited_by_count":1,"area":null},{"id":"2405.03714","title":"UniDEC : Unified Dual Encoder and Classifier Training for Extreme Multi-Label Classification","created":"2024-05-04","cited_by_count":1,"area":null},{"id":"2407.05656","title":"Multi-label Learning with Random Circular Vectors","created":"2024-07-08","cited_by_count":1,"area":null},{"id":"2505.12964","title":"MA-COIR: Leveraging Semantic Search Index and Generative Models for Ontology-Driven Biomedical Concept Recognition","created":"2025-05-19","cited_by_count":1,"area":null},{"id":"2606.01117","title":"HASTE: Hardware-Aware Dynamic Sparse Training for Large Output Spaces","created":"2026-05-31","cited_by_count":1,"area":null},{"id":"2210.10160","title":"Uncertainty in Extreme Multi-label Classification","created":"2022-10-18","cited_by_count":0,"area":null},{"id":"2302.14695","title":"Pushing One Pair of Labels Apart Each Time in Multi-Label Learning: From Single Positive to Full Labels","created":"2023-02-28","cited_by_count":0,"area":null},{"id":"2305.19470","title":"Label Embedding via Low-Coherence Matrices","created":"2023-05-31","cited_by_count":0,"area":null},{"id":"2408.09585","title":"On the Necessity of World Knowledge for Mitigating Missing Labels in Extreme Classification","created":"2024-08-18","cited_by_count":0,"area":null},{"id":"2410.23066","title":"Don't Pay Attention, PLANT It: Pretraining Attention via Learning-to-Rank","created":"2024-10-30","cited_by_count":0,"area":null},{"id":"2412.13809","title":"Extreme Multi-label Completion for Semantic Document Labelling with Taxonomy-Aware Parallel Learning","created":"2024-12-18","cited_by_count":0,"area":null},{"id":"2505.03775","title":"Hierarchical Multi-Label Generation with Probabilistic Level-Constraint","created":"2025-04-30","cited_by_count":0,"area":null},{"id":"2506.07168","title":"Efficient Text-Attributed Graph Learning through Selective Annotation and Graph Alignment","created":"2025-06-08","cited_by_count":0,"area":null},{"id":"2510.04551","title":"Fine-grained auxiliary learning for real-world product recommendation","created":"2025-10-06","cited_by_count":0,"area":null},{"id":"2602.15330","title":"A Scalable Curiosity-Driven Game-Theoretic Framework for Long-Tail Multi-Label Learning in Data Mining","created":"2026-02-17","cited_by_count":0,"area":null},{"id":"2603.03176","title":"FEAST: Retrieval-Augmented Multi-Hierarchical Food Classification for the FoodEx2 System","created":"2026-03-03","cited_by_count":0,"area":"rag"},{"id":"2603.21056","title":"Semi-Supervised Learning with Balanced Deep Representation Distributions","created":"2026-03-22","cited_by_count":0,"area":null},{"id":"2605.21154","title":"Automated ICD Classification of Psychiatric Diagnoses: From Classical NLP to Large Language Models","created":"2026-05-20","cited_by_count":0,"area":null},{"id":"2606.25237","title":"Extreme Meta-Classification for Large-Scale Zero-Shot Retrieval","created":"2026-06-23","cited_by_count":0,"area":null},{"id":"2607.14882","title":"Does generative AI supersede supervised XMLC? A Benchmark Study on Automated Subject Indexing with German Scientific Literature","created":"2026-07-16","cited_by_count":0,"area":null},{"id":"2609.12915","title":"LLM-Enhanced Dual-Branch Learning for Large-Scale Multi-Label Text Classification","created":"2026-09-11","cited_by_count":0,"area":null},{"id":"2610.02516","title":"Student-Guided Teacher Distillation for Efficient LLM Task Routing: Positioning Against Jev-Style System-1 Classifiers","created":"2026-10-01","cited_by_count":0,"area":null}],"next_cursor":null}