{"list":"other","total":94,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"2005.14165","title":"Language Models are Few-Shot Learners","created":"2020-05-28","cited_by_count":32419},{"id":"2307.09288","title":"Llama 2: Open Foundation and Fine-Tuned Chat Models","created":"2023-07-18","cited_by_count":13028},{"id":"2201.11903","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","created":"2022-01-28","cited_by_count":12459},{"id":"1609.02907","title":"Semi-Supervised Classification with Graph Convolutional Networks","created":"2016-09-09","cited_by_count":11361},{"id":"1710.10903","title":"Graph Attention Networks","created":"2017-10-30","cited_by_count":8923},{"id":"1706.02216","title":"Inductive Representation Learning on Large Graphs","created":"2017-06-07","cited_by_count":6320},{"id":"1910.13461","title":"BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension","created":"2019-10-29","cited_by_count":5893},{"id":"1810.00826","title":"How Powerful are Graph Neural Networks?","created":"2018-10-01","cited_by_count":4393},{"id":"1704.01212","title":"Neural Message Passing for Quantum Chemistry","created":"2017-04-04","cited_by_count":3487},{"id":"1812.08434","title":"Graph Neural Networks: A Review of Methods and Applications","created":"2018-12-20","cited_by_count":1576},{"id":"1403.6652","title":"DeepWalk: Online Learning of Social Representations","created":"2014-03-26","cited_by_count":1547},{"id":"1806.01973","title":"Graph Convolutional Neural Networks for Web-Scale Recommender Systems","created":"2018-06-06","cited_by_count":1138},{"id":"1703.00564","title":"MoleculeNet: A Benchmark for Molecular Machine Learning","created":"2017-03-02","cited_by_count":1051},{"id":"1412.2306","title":"Deep Visual-Semantic Alignments for Generating Image Descriptions","created":"2014-12-07","cited_by_count":968},{"id":"2102.09844","title":"E(n) Equivariant Graph Neural Networks","created":"2021-02-19","cited_by_count":965},{"id":"1810.02244","title":"Weisfeiler and Leman Go Neural: Higher-order Graph Neural Networks","created":"2018-10-04","cited_by_count":881},{"id":"2006.05205","title":"On the Bottleneck of Graph Neural Networks and its Practical Implications","created":"2020-06-09","cited_by_count":631},{"id":"2003.02320","title":"Knowledge Graphs","created":"2020-03-04","cited_by_count":621},{"id":"1911.06455","title":"Graph Transformer Networks","created":"2019-11-06","cited_by_count":523},{"id":"2111.01243","title":"Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey","created":"2021-11-01","cited_by_count":463},{"id":"1911.04942","title":"RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parsers","created":"2019-11-10","cited_by_count":424},{"id":"2010.09885","title":"ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction","created":"2020-10-19","cited_by_count":337},{"id":"2307.03393","title":"Exploring the Potential of Large Language Models (LLMs) in Learning on Graphs","created":"2023-07-07","cited_by_count":274},{"id":"2305.10037","title":"Can Language Models Solve Graph Problems in Natural Language?","created":"2023-05-17","cited_by_count":252},{"id":"1701.05923","title":"Gate-Variants of Gated Recurrent Unit (GRU) Neural Networks","created":"2017-01-20","cited_by_count":242},{"id":"2305.15066","title":"GPT4Graph: Can Large Language Models Understand Graph Structured Data ? An Empirical Evaluation and Benchmarking","created":"2023-05-24","cited_by_count":210},{"id":"2312.02783","title":"Large Language Models on Graphs: A Comprehensive Survey","created":"2023-12-05","cited_by_count":192},{"id":"2207.02505","title":"Pure Transformers are Powerful Graph Learners","created":"2022-07-06","cited_by_count":188},{"id":"1905.04943","title":"Universal Invariant and Equivariant Graph Neural Networks","created":"2019-05-13","cited_by_count":183},{"id":"2402.08170","title":"LLaGA: Large Language and Graph Assistant","created":"2024-02-13","cited_by_count":181},{"id":"2001.05140","title":"Graph-Bert: Only Attention is Needed for Learning Graph Representations","created":"2020-01-15","cited_by_count":177},{"id":"2311.00423","title":"LLMRec: Large Language Models with Graph Augmentation for Recommendation","created":"2023-11-01","cited_by_count":172},{"id":"2308.10168","title":"Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?","created":"2023-08-20","cited_by_count":168},{"id":"2302.02941","title":"On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology","created":"2023-02-06","cited_by_count":166},{"id":"2206.04910","title":"NAGphormer: A Tokenized Graph Transformer for Node Classification in Large Graphs","created":"2022-06-10","cited_by_count":137},{"id":"2209.05481","title":"A Molecular Multimodal Foundation Model Associating Molecule Graphs with Natural Language","created":"2022-09-12","cited_by_count":131},{"id":"2310.12798","title":"MolCA: Molecular Graph-Language Modeling with Cross-Modal Projector and Uni-Modal Adapter","created":"2023-10-19","cited_by_count":128},{"id":"1904.02342","title":"Text Generation from Knowledge Graphs with Graph Transformers","created":"2019-04-04","cited_by_count":122},{"id":"2402.05862","title":"Let Your Graph Do the Talking: Encoding Structured Data for LLMs","created":"2024-02-08","cited_by_count":118},{"id":"2401.17197","title":"Data-efficient Fine-tuning for LLM-based Recommendation","created":"2024-01-30","cited_by_count":104},{"id":"2311.07914","title":"Can Knowledge Graphs Reduce Hallucinations in LLMs? : A Survey","created":"2023-11-14","cited_by_count":92},{"id":"2311.16208","title":"InstructMol: Multi-Modal Integration for Building a Versatile and Reliable Molecular Assistant in Drug Discovery","created":"2023-11-27","cited_by_count":86},{"id":"1911.07470","title":"Graph Transformer for Graph-to-Sequence Learning","created":"2019-11-18","cited_by_count":82},{"id":"2308.06911","title":"GIT-Mol: A Multi-modal Large Language Model for Molecular Science with Graph, Image, and Text","created":"2023-08-14","cited_by_count":82},{"id":"2304.11116","title":"Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT","created":"2023-04-10","cited_by_count":80},{"id":"2403.01121","title":"OpenGraph: Towards Open Graph Foundation Models","created":"2024-03-02","cited_by_count":78},{"id":"2204.09888","title":"Fairness in Graph Mining: A Survey","created":"2022-04-21","cited_by_count":76},{"id":"1904.03396","title":"Step-by-Step: Separating Planning from Realization in Neural Data-to-Text Generation","created":"2019-04-06","cited_by_count":75},{"id":"2102.07988","title":"TeraPipe: Token-Level Pipeline Parallelism for Training Large-Scale Language Models","created":"2021-02-16","cited_by_count":75},{"id":"2405.08011","title":"A Survey of Large Language Models for Graphs","created":"2024-05-10","cited_by_count":72},{"id":"2306.13089","title":"GIMLET: A Unified Graph-Text Model for Instruction-Based Molecule Zero-Shot Learning","created":"2023-05-28","cited_by_count":70},{"id":"2402.13630","title":"UniGraph: Learning a Unified Cross-Domain Foundation Model for Text-Attributed Graphs","created":"2024-02-21","cited_by_count":66},{"id":"2309.11206","title":"Retrieve-Rewrite-Answer: A KG-to-Text Enhanced LLMs Framework for Knowledge Graph Question Answering","created":"2023-09-20","cited_by_count":65},{"id":"2402.07197","title":"GraphTranslator: Aligning Graph Model to Large Language Model for Open-ended Tasks","created":"2024-02-11","cited_by_count":63},{"id":"1806.09835","title":"Graph-to-Sequence Learning using Gated Graph Neural Networks","created":"2018-06-26","cited_by_count":61},{"id":"2404.14741","title":"Generate-on-Graph: Treat LLM as both Agent and KG in Incomplete Knowledge Graph Question Answering","created":"2024-04-23","cited_by_count":60},{"id":"2106.10502","title":"JointGT: Graph-Text Joint Representation Learning for Text Generation from Knowledge Graphs","created":"2021-06-19","cited_by_count":58},{"id":"1704.08381","title":"Neural AMR: Sequence-to-Sequence Models for Parsing and Generation","created":"2017-04-26","cited_by_count":56},{"id":"1802.08888","title":"N-GCN: Multi-scale Graph Convolution for Semi-supervised Node Classification","created":"2018-02-24","cited_by_count":54},{"id":"2402.10359","title":"Can we Soft Prompt LLMs for Graph Learning Tasks?","created":"2024-02-15","cited_by_count":52},{"id":"2310.14753","title":"Rethinking Tokenizer and Decoder in Masked Graph Modeling for Molecules","created":"2023-10-23","cited_by_count":49},{"id":"2310.17110","title":"LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs?","created":"2023-10-26","cited_by_count":40},{"id":"2210.05801","title":"Linkless Link Prediction via Relational Distillation","created":"2022-10-11","cited_by_count":39},{"id":"2006.04702","title":"CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training","created":"2020-06-08","cited_by_count":38},{"id":"2308.02117","title":"VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs","created":"2023-08-04","cited_by_count":35},{"id":"2402.15183","title":"GraphEdit: Large Language Models for Graph Structure Learning","created":"2024-02-23","cited_by_count":33},{"id":"2001.11003","title":"Modeling Global and Local Node Contexts for Text Generation from Knowledge Graphs","created":"2020-01-29","cited_by_count":30},{"id":"2202.10688","title":"Graph Lifelong Learning: A Survey","created":"2022-02-22","cited_by_count":30},{"id":"1908.05957","title":"Densely Connected Graph Convolutional Networks for Graph-to-Sequence Learning","created":"2019-08-16","cited_by_count":29},{"id":"1810.09995","title":"Deep Graph Convolutional Encoders for Structured Data to Text Generation","created":"2018-10-23","cited_by_count":27},{"id":"2210.12130","title":"Graph Few-shot Learning with Task-specific Structures","created":"2022-10-21","cited_by_count":26},{"id":"2402.00858","title":"Can Large Language Models Understand Context?","created":"2024-02-01","cited_by_count":26},{"id":"2112.02936","title":"Pairwise Learning for Neural Link Prediction","created":"2021-12-06","cited_by_count":23},{"id":"2308.14522","title":"Graph Meets LLMs: Towards Large Graph Models","created":"2023-08-28","cited_by_count":20},{"id":"2402.12022","title":"Distilling Large Language Models for Text-Attributed Graph Learning","created":"2024-02-19","cited_by_count":20},{"id":"2204.06674","title":"GAP: A Graph-aware Language Model Framework for Knowledge Graph-to-Text Generation","created":"2022-04-13","cited_by_count":16},{"id":"2202.07826","title":"CenGCN: Centralized Convolutional Networks with Vertex Imbalance for Scale-Free Graphs","created":"2022-02-16","cited_by_count":14},{"id":"2402.16567","title":"Aligning Large Language Models to a Domain-specific Graph Database for NL2GQL","created":"2024-02-26","cited_by_count":14},{"id":"2406.12052","title":"UniGLM: Training One Unified Language Model for Text-Attributed Graph Embedding","created":"2024-06-17","cited_by_count":14},{"id":"2403.17780","title":"CaseLink: Inductive Graph Learning for Legal Case Retrieval","created":"2024-03-26","cited_by_count":11},{"id":"2407.12068","title":"Learning on Graphs with Large Language Models(LLMs): A Deep Dive into Model Robustness","created":"2024-07-16","cited_by_count":11},{"id":"1508.03843","title":"The Gremlin Graph Traversal Machine and Language","created":"2015-08-16","cited_by_count":10},{"id":"2401.16784","title":"Graph Fairness Learning under Distribution Shifts","created":"2024-01-30","cited_by_count":10},{"id":"2210.04105","title":"KALM: Knowledge-Aware Integration of Local, Document, and Global Contexts for Long Document Understanding","created":"2022-10-08","cited_by_count":9},{"id":"2406.06729","title":"Synthetic Query Generation using Large Language Models for Virtual Assistants","created":"2024-06-10","cited_by_count":9},{"id":"2405.13902","title":"LOGIN: A Large Language Model Consulted Graph Neural Network Training Framework","created":"2024-05-22","cited_by_count":8},{"id":"2402.19414","title":"Higher-Order Networks Representation and Learning: A Survey","created":"2024-02-29","cited_by_count":7},{"id":"2402.03732","title":"Deep Outdated Fact Detection in Knowledge Graphs","created":"2024-02-06","cited_by_count":6},{"id":"1312.6565","title":"Mobile Multimedia Recommendation in Smart Communities: A Survey","created":"2013-12-23","cited_by_count":5},{"id":"2305.07521","title":"AGFormer: Efficient Graph Representation with Anchor-Graph Transformer","created":"2023-05-12","cited_by_count":5},{"id":"2406.19249","title":"NTFormer: A Composite Node Tokenized Graph Transformer for Node Classification","created":"2024-06-27","cited_by_count":5},{"id":"2412.20040","title":"A Contrastive Pretrain Model with Prompt Tuning for Multi-center Medication Recommendation","created":"2024-12-28","cited_by_count":3},{"id":"2405.20684","title":"Joint Embeddings for Graph Instruction Tuning","created":"2024-05-31","cited_by_count":2}],"next_cursor":null}