{"list":"other","total":194,"rows":[{"id":"1512.03385","title":"Deep Residual Learning for Image Recognition","created":"2015-12-10","cited_by_count":52096},{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"id":"2005.14165","title":"Language Models are Few-Shot Learners","created":"2020-05-28","cited_by_count":32419},{"id":"2303.08774","title":"GPT-4 Technical Report","created":"2023-03-15","cited_by_count":18396},{"id":"1409.1556","title":"Very Deep Convolutional Networks for Large-Scale Image Recognition","created":"2014-09-04","cited_by_count":15364},{"id":"1910.10683","title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","created":"2019-10-23","cited_by_count":14599},{"id":"1907.11692","title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach","created":"2019-07-26","cited_by_count":13372},{"id":"2201.11903","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","created":"2022-01-28","cited_by_count":12459},{"id":"1506.01497","title":"Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks","created":"2015-06-04","cited_by_count":9639},{"id":"2005.11401","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","created":"2020-05-22","cited_by_count":9297},{"id":"1409.0575","title":"ImageNet Large Scale Visual Recognition Challenge","created":"2014-09-01","cited_by_count":8498},{"id":"2304.08485","title":"Visual Instruction Tuning","created":"2023-04-17","cited_by_count":7869},{"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":"1904.09675","title":"BERTScore: Evaluating Text Generation with BERT","created":"2019-04-21","cited_by_count":5512},{"id":"2410.21276","title":"GPT-4o System Card","created":"2024-10-25","cited_by_count":4588},{"id":"1301.3781","title":"Efficient Estimation of Word Representations in Vector Space","created":"2013-01-16","cited_by_count":4375},{"id":"2212.04356","title":"Robust Speech Recognition via Large-Scale Weak Supervision","created":"2022-12-06","cited_by_count":4057},{"id":"2006.11477","title":"wav2vec 2.0: A Framework for Self-Supervised Learning of Speech Representations","created":"2020-06-20","cited_by_count":3905},{"id":"2304.03442","title":"Generative Agents: Interactive Simulacra of Human Behavior","created":"2023-04-07","cited_by_count":3568},{"id":"1705.07750","title":"Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset","created":"2017-05-22","cited_by_count":3270},{"id":"2511.21631","title":"Qwen3-VL Technical Report","created":"2025-11-26","cited_by_count":2793},{"id":"1812.03982","title":"SlowFast Networks for Video Recognition","created":"2018-12-10","cited_by_count":1867},{"id":"2311.05232","title":"A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions","created":"2023-11-09","cited_by_count":1601},{"id":"2004.04696","title":"BLEURT: Learning Robust Metrics for Text Generation","created":"2020-04-09","cited_by_count":1203},{"id":"2106.13230","title":"Video Swin Transformer","created":"2021-06-24","cited_by_count":1091},{"id":"2009.09025","title":"COMET: A Neural Framework for MT Evaluation","created":"2020-09-18","cited_by_count":1033},{"id":"1907.10529","title":"SpanBERT: Improving Pre-training by Representing and Predicting Spans","created":"2019-07-24","cited_by_count":834},{"id":"1512.02595","title":"Deep Speech 2: End-to-End Speech Recognition in English and Mandarin","created":"2015-12-08","cited_by_count":451},{"id":"2408.08921","title":"Graph Retrieval-Augmented Generation: A Survey","created":"2024-08-15","cited_by_count":324},{"id":"1909.03546","title":"Entity, Relation, and Event Extraction with Contextualized Span Representations","created":"2019-09-08","cited_by_count":262},{"id":"2302.10205","title":"ChatIE: Zero-Shot Information Extraction via Chatting with ChatGPT","created":"2023-02-20","cited_by_count":250},{"id":"2203.12277","title":"Unified Structure Generation for Universal Information Extraction","created":"2022-03-23","cited_by_count":221},{"id":"2101.05779","title":"Structured Prediction as Translation between Augmented Natural Languages","created":"2021-01-14","cited_by_count":183},{"id":"2004.13625","title":"Event Extraction by Answering (Almost) Natural Questions","created":"2020-04-28","cited_by_count":177},{"id":"2304.08085","title":"InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction","created":"2023-04-17","cited_by_count":170},{"id":"2104.05919","title":"Document-Level Event Argument Extraction by Conditional Generation","created":"2021-04-13","cited_by_count":155},{"id":"1909.07755","title":"Span-based Joint Entity and Relation Extraction with Transformer Pre-training","created":"2019-09-17","cited_by_count":133},{"id":"2304.11633","title":"Evaluating ChatGPT's Information Extraction Capabilities: An Assessment of Performance, Explainability, Calibration, and Faithfulness","created":"2023-04-23","cited_by_count":130},{"id":"2106.09232","title":"Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction","created":"2021-06-17","cited_by_count":129},{"id":"2303.08559","title":"Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!","created":"2023-03-15","cited_by_count":119},{"id":"2310.03668","title":"GoLLIE: Annotation Guidelines improve Zero-Shot Information-Extraction","created":"2023-10-05","cited_by_count":119},{"id":"2004.13590","title":"MAVEN: A Massive General Domain Event Detection Dataset","created":"2020-04-28","cited_by_count":104},{"id":"2108.12724","title":"DEGREE: A Data-Efficient Generation-Based Event Extraction Model","created":"2021-08-29","cited_by_count":83},{"id":"1911.03766","title":"Multi-Sentence Argument Linking","created":"2019-11-09","cited_by_count":81},{"id":"2003.12058","title":"Grounded Situation Recognition","created":"2020-03-26","cited_by_count":78},{"id":"1804.07828","title":"A Multi-Axis Annotation Scheme for Event Temporal Relations","created":"2018-04-20","cited_by_count":75},{"id":"1809.09078","title":"Jointly Multiple Events Extraction via Attention-based Graph Information Aggregation","created":"2018-09-24","cited_by_count":73},{"id":"2210.12810","title":"Code4Struct: Code Generation for Few-Shot Event Structure Prediction","created":"2022-10-23","cited_by_count":70},{"id":"2211.07342","title":"MAVEN-ERE: A Unified Large-scale Dataset for Event Coreference, Temporal, Causal, and Subevent Relation Extraction","created":"2022-11-14","cited_by_count":66},{"id":"2005.02472","title":"Cross-media Structured Common Space for Multimedia Event Extraction","created":"2020-05-05","cited_by_count":61},{"id":"2104.00990","title":"Visual Semantic Role Labeling for Video Understanding","created":"2021-04-02","cited_by_count":60},{"id":"1904.07535","title":"Doc2EDAG: An End-to-End Document-level Framework for Chinese Financial Event Extraction","created":"2019-04-16","cited_by_count":54},{"id":"1910.11621","title":"Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection","created":"2019-10-25","cited_by_count":54},{"id":"2202.12109","title":"Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction","created":"2022-02-24","cited_by_count":54},{"id":"1909.05360","title":"Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction","created":"2019-09-02","cited_by_count":53},{"id":"2010.06727","title":"Joint Constrained Learning for Event-Event Relation Extraction","created":"2020-10-13","cited_by_count":53},{"id":"1609.03632","title":"Joint Extraction of Events and Entities within a Document Context","created":"2016-09-12","cited_by_count":48},{"id":"2205.10475","title":"DeepStruct: Pretraining of Language Models for Structure Prediction","created":"2022-05-21","cited_by_count":45},{"id":"1906.01753","title":"Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution","created":"2019-06-04","cited_by_count":43},{"id":"2010.03009","title":"GATE: Graph Attention Transformer Encoder for Cross-lingual Relation and Event Extraction","created":"2020-10-06","cited_by_count":43},{"id":"2304.06248","title":"LasUIE: Unifying Information Extraction with Latent Adaptive Structure-aware Generative Language Model","created":"2023-04-13","cited_by_count":43},{"id":"2203.08308","title":"Multilingual Generative Language Models for Zero-Shot Cross-Lingual Event Argument Extraction","created":"2022-03-15","cited_by_count":40},{"id":"1812.00195","title":"One for All: Neural Joint Modeling of Entities and Events","created":"2018-12-01","cited_by_count":37},{"id":"2210.12560","title":"PHEE: A Dataset for Pharmacovigilance Event Extraction from Text","created":"2022-10-22","cited_by_count":37},{"id":"2105.14485","title":"CLEVE: Contrastive Pre-training for Event Extraction","created":"2021-05-30","cited_by_count":36},{"id":"2203.08556","title":"LEVEN: A Large-Scale Chinese Legal Event Detection Dataset","created":"2022-03-16","cited_by_count":36},{"id":"2205.06166","title":"Dynamic Prefix-Tuning for Generative Template-based Event Extraction","created":"2022-05-12","cited_by_count":35},{"id":"1708.04320","title":"Situation Recognition with Graph Neural Networks","created":"2017-08-14","cited_by_count":34},{"id":"2403.07969","title":"KnowCoder: Coding Structured Knowledge into LLMs for Universal Information Extraction","created":"2024-03-12","cited_by_count":34},{"id":"2305.13812","title":"Coarse-to-Fine Contrastive Learning in Image-Text-Graph Space for Improved Vision-Language Compositionality","created":"2023-05-23","cited_by_count":32},{"id":"2012.02505","title":"Financial Document Causality Detection Shared Task (FinCausal 2020)","created":"2020-12-04","cited_by_count":31},{"id":"2105.14924","title":"Document-level Event Extraction via Heterogeneous Graph-based Interaction Model with a Tracker","created":"2021-05-31","cited_by_count":29},{"id":"2005.06579","title":"Document-Level Event Role Filler Extraction using Multi-Granularity Contextualized Encoding","created":"2020-05-13","cited_by_count":28},{"id":"2311.04284","title":"CRAB: Assessing the Strength of Causal Relationships Between Real-world Events","created":"2023-11-07","cited_by_count":28},{"id":"2311.09562","title":"TextEE: Benchmark, Reevaluation, Reflections, and Future Challenges in Event Extraction","created":"2023-11-16","cited_by_count":28},{"id":"2110.07476","title":"Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding","created":"2021-10-14","cited_by_count":26},{"id":"2205.12505","title":"GENEVA: Benchmarking Generalizability for Event Argument Extraction with Hundreds of Event Types and Argument Roles","created":"2022-05-25","cited_by_count":26},{"id":"2310.05066","title":"Guideline Learning for In-context Information Extraction","created":"2023-10-08","cited_by_count":24},{"id":"2405.05008","title":"ADELIE: Aligning Large Language Models on Information Extraction","created":"2024-05-08","cited_by_count":24},{"id":"2010.14123","title":"Event Detection: Gate Diversity and Syntactic Importance Scoresfor Graph Convolution Neural Networks","created":"2020-10-27","cited_by_count":23},{"id":"2104.05022","title":"WEC: Deriving a Large-scale Cross-document Event Coreference dataset from Wikipedia","created":"2021-04-11","cited_by_count":23},{"id":"2105.10922","title":"OntoED: Low-resource Event Detection with Ontology Embedding","created":"2021-05-23","cited_by_count":23},{"id":"2212.04542","title":"VASR: Visual Analogies of Situation Recognition","created":"2022-12-08","cited_by_count":22},{"id":"2208.07989","title":"DICE: Data-Efficient Clinical Event Extraction with Generative Models","created":"2022-08-16","cited_by_count":20},{"id":"2109.12776","title":"Joint Multimedia Event Extraction from Video and Article","created":"2021-09-27","cited_by_count":19},{"id":"2203.16518","title":"Collaborative Transformers for Grounded Situation Recognition","created":"2022-03-30","cited_by_count":19},{"id":"2305.16734","title":"AMPERE: AMR-Aware Prefix for Generation-Based Event Argument Extraction Model","created":"2023-05-26","cited_by_count":19},{"id":"2011.12249","title":"Generalizing Cross-Document Event Coreference Resolution Across Multiple Corpora","created":"2020-11-24","cited_by_count":18},{"id":"2209.02693","title":"OneEE: A One-Stage Framework for Fast Overlapping and Nested Event Extraction","created":"2022-09-06","cited_by_count":18},{"id":"2211.07067","title":"Retrieval-Augmented Generative Question Answering for Event Argument Extraction","created":"2022-11-14","cited_by_count":18},{"id":"2502.16377","title":"Instruction-Tuning LLMs for Event Extraction with Annotation Guidelines","created":"2025-02-22","cited_by_count":18},{"id":"1906.06947","title":"Open Domain Event Extraction Using Neural Latent Variable Models","created":"2019-06-17","cited_by_count":17},{"id":"2108.08669","title":"Video Relation Detection via Tracklet based Visual Transformer","created":"2021-08-19","cited_by_count":17},{"id":"2201.03335","title":"DeepKE: A Deep Learning Based Knowledge Extraction Toolkit for Knowledge Base Population","created":"2022-01-10","cited_by_count":17},{"id":"2211.05955","title":"MEE: A Novel Multilingual Event Extraction Dataset","created":"2022-11-11","cited_by_count":17},{"id":"2310.09158","title":"Improving Large Language Models in Event Relation Logical Prediction","created":"2023-10-13","cited_by_count":17},{"id":"2401.03082","title":"UMIE: Unified Multimodal Information Extraction with Instruction Tuning","created":"2024-01-05","cited_by_count":17},{"id":"1604.08120","title":"Extracting Temporal and Causal Relations between Events","created":"2016-04-27","cited_by_count":16},{"id":"2205.00241","title":"A Two-Stream AMR-enhanced Model for Document-level Event Argument Extraction","created":"2022-04-30","cited_by_count":16},{"id":"2307.05567","title":"Event Extraction as Question Generation and Answering","created":"2023-07-10","cited_by_count":16}],"next_cursor":"100"}