{"list":"other","total":51,"rows":[{"id":"1810.04805","title":"BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding","created":"2018-10-11","cited_by_count":40399},{"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":"1710.10903","title":"Graph Attention Networks","created":"2017-10-30","cited_by_count":8923},{"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":"1911.02116","title":"Unsupervised Cross-lingual Representation Learning at Scale","created":"2019-11-05","cited_by_count":3935},{"id":"1310.4546","title":"Distributed Representations of Words and Phrases and their Compositionality","created":"2013-10-16","cited_by_count":3474},{"id":"1703.05175","title":"Prototypical Networks for Few-shot Learning","created":"2017-03-15","cited_by_count":3015},{"id":"1611.01144","title":"Categorical Reparameterization with Gumbel-Softmax","created":"2016-11-03","cited_by_count":2739},{"id":"1802.05365","title":"Deep contextualized word representations","created":"2018-02-15","cited_by_count":2290},{"id":"2010.11934","title":"mT5: A massively multilingual pre-trained text-to-text transformer","created":"2020-10-22","cited_by_count":1818},{"id":"1903.10676","title":"SciBERT: A Pretrained Language Model for Scientific Text","created":"2019-03-26","cited_by_count":1414},{"id":"1409.1259","title":"On the Properties of Neural Machine Translation: Encoder-Decoder Approaches","created":"2014-09-03","cited_by_count":1304},{"id":"2001.08210","title":"Multilingual Denoising Pre-training for Neural Machine Translation","created":"2020-01-22","cited_by_count":1035},{"id":"1711.00043","title":"Unsupervised Machine Translation Using Monolingual Corpora Only","created":"2017-10-31","cited_by_count":273},{"id":"1909.03546","title":"Entity, Relation, and Event Extraction with Contextualized Span Representations","created":"2019-09-08","cited_by_count":262},{"id":"1404.2188","title":"A Convolutional Neural Network for Modelling Sentences","created":"2014-04-08","cited_by_count":163},{"id":"1809.10185","title":"Graph Convolution over Pruned Dependency Trees Improves Relation Extraction","created":"2018-09-26","cited_by_count":146},{"id":"1703.04826","title":"Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling","created":"2017-03-14","cited_by_count":137},{"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":"2004.13590","title":"MAVEN: A Massive General Domain Event Detection Dataset","created":"2020-04-28","cited_by_count":104},{"id":"1904.03296","title":"A General Framework for Information Extraction using Dynamic Span Graphs","created":"2019-04-05","cited_by_count":93},{"id":"2201.05078","title":"CLIP-Event: Connecting Text and Images with Event Structures","created":"2022-01-13","cited_by_count":86},{"id":"2108.12724","title":"DEGREE: A Data-Efficient Generation-Based Event Extraction Model","created":"2021-08-29","cited_by_count":83},{"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":"1804.07745","title":"Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion","created":"2018-04-20","cited_by_count":70},{"id":"1707.01066","title":"Zero-Shot Transfer Learning for Event Extraction","created":"2017-07-04","cited_by_count":66},{"id":"1812.06158","title":"Few-shot classification in Named Entity Recognition Task","created":"2018-12-14","cited_by_count":64},{"id":"1912.01140","title":"An Annotated Dataset of Coreference in English Literature","created":"2019-12-03","cited_by_count":58},{"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":"1909.05360","title":"Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction","created":"2019-09-02","cited_by_count":53},{"id":"2104.08692","title":"MT6: Multilingual Pretrained Text-to-Text Transformer with Translation Pairs","created":"2021-04-18","cited_by_count":41},{"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":"2012.15243","title":"Unsupervised Label-aware Event Trigger and Argument Classification","created":"2020-12-30","cited_by_count":27},{"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":"2103.09330","title":"Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks","created":"2021-03-16","cited_by_count":22},{"id":"2012.02353","title":"Few-Shot Event Detection with Prototypical Amortized Conditional Random Field","created":"2020-12-04","cited_by_count":20},{"id":"2006.10093","title":"Extensively Matching for Few-shot Learning Event Detection","created":"2020-06-17","cited_by_count":18},{"id":"2010.12787","title":"Document-level Event Extraction with Efficient End-to-end Learning of Cross-event Dependencies","created":"2020-10-24","cited_by_count":17},{"id":"2105.09509","title":"Adaptive Knowledge-Enhanced Bayesian Meta-Learning for Few-shot Event Detection","created":"2021-05-20","cited_by_count":13},{"id":"1712.03665","title":"Scale Up Event Extraction Learning via Automatic Training Data Generation","created":"2017-12-11","cited_by_count":11},{"id":"1808.08622","title":"Semi-Supervised Event Extraction with Paraphrase Clusters","created":"2018-08-26","cited_by_count":10},{"id":"2109.05747","title":"Honey or Poison? Solving the Trigger Curse in Few-shot Event Detection via Causal Intervention","created":"2021-09-13","cited_by_count":9},{"id":"2203.08552","title":"Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer","created":"2022-03-16","cited_by_count":8},{"id":"1802.05672","title":"Event Nugget Detection with Forward-Backward Recurrent Neural Networks","created":"2018-02-15","cited_by_count":7},{"id":"1910.11368","title":"Extending Event Detection to New Types with Learning from Keywords","created":"2019-10-24","cited_by_count":5},{"id":"2009.09335","title":"Biomedical Event Extraction with Hierarchical Knowledge Graphs","created":"2020-09-20","cited_by_count":5},{"id":"2104.15104","title":"GTN-ED: Event Detection Using Graph Transformer Networks","created":"2021-04-30","cited_by_count":3}],"next_cursor":null}