{"list":"other","total":56,"rows":[{"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":"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":"2005.11401","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","created":"2020-05-22","cited_by_count":9297},{"id":"1703.03400","title":"Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks","created":"2017-03-09","cited_by_count":4897},{"id":"1703.05175","title":"Prototypical Networks for Few-shot Learning","created":"2017-03-15","cited_by_count":3015},{"id":"1702.08734","title":"Billion-scale similarity search with GPUs","created":"2017-02-28","cited_by_count":2497},{"id":"1606.04080","title":"Matching Networks for One Shot Learning","created":"2016-06-13","cited_by_count":2255},{"id":"2102.09690","title":"Calibrate Before Use: Improving Few-Shot Performance of Language Models","created":"2021-02-19","cited_by_count":1392},{"id":"2101.06804","title":"What Makes Good In-Context Examples for GPT-$3$?","created":"2021-01-17","cited_by_count":1195},{"id":"1911.00172","title":"Generalization through Memorization: Nearest Neighbor Language Models","created":"2019-11-01","cited_by_count":800},{"id":"1912.02164","title":"Plug and Play Language Models: A Simple Approach to Controlled Text Generation","created":"2019-12-04","cited_by_count":799},{"id":"1909.05858","title":"CTRL: A Conditional Transformer Language Model for Controllable Generation","created":"2019-09-11","cited_by_count":762},{"id":"1312.6211","title":"An Empirical Investigation of Catastrophic Forgetting in Gradient-Based Neural Networks","created":"2013-12-21","cited_by_count":722},{"id":"1803.11175","title":"Universal Sentence Encoder","created":"2018-03-29","cited_by_count":489},{"id":"1707.09835","title":"Meta-SGD: Learning to Learn Quickly for Few-Shot Learning","created":"2017-07-31","cited_by_count":379},{"id":"2009.06367","title":"GeDi: Generative Discriminator Guided Sequence Generation","created":"2020-09-14","cited_by_count":378},{"id":"1703.00955","title":"Toward Controlled Generation of Text","created":"2017-03-02","cited_by_count":272},{"id":"2010.00710","title":"Nearest Neighbor Machine Translation","created":"2020-10-01","cited_by_count":209},{"id":"1904.09545","title":"Good-Enough Compositional Data Augmentation","created":"2019-04-21","cited_by_count":158},{"id":"2008.09335","title":"MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark","created":"2020-08-21","cited_by_count":158},{"id":"1606.03622","title":"Data Recombination for Neural Semantic Parsing","created":"2016-06-11","cited_by_count":111},{"id":"1705.04228","title":"Incremental Learning Through Deep Adaptation","created":"2017-05-11","cited_by_count":108},{"id":"1808.08437","title":"Meta-Learning for Low-Resource Neural Machine Translation","created":"2018-08-25","cited_by_count":105},{"id":"1810.07942","title":"Semantic Parsing for Task Oriented Dialog using Hierarchical Representations","created":"2018-10-18","cited_by_count":101},{"id":"1709.08878","title":"Generating Sentences by Editing Prototypes","created":"2017-09-26","cited_by_count":88},{"id":"2006.05702","title":"Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network","created":"2020-06-10","cited_by_count":83},{"id":"1808.04776","title":"Retrieve and Refine: Improved Sequence Generation Models For Dialogue","created":"2018-08-14","cited_by_count":82},{"id":"1812.01194","title":"A Retrieve-and-Edit Framework for Predicting Structured Outputs","created":"2018-12-04","cited_by_count":73},{"id":"2010.03546","title":"Low-Resource Domain Adaptation for Compositional Task-Oriented Semantic Parsing","created":"2020-10-07","cited_by_count":72},{"id":"1812.06158","title":"Few-shot classification in Named Entity Recognition Task","created":"2018-12-14","cited_by_count":64},{"id":"1804.02559","title":"Guiding Neural Machine Translation with Retrieved Translation Pieces","created":"2018-04-07","cited_by_count":63},{"id":"1905.12188","title":"Exploiting Persona Information for Diverse Generation of Conversational Responses","created":"2019-05-29","cited_by_count":58},{"id":"1911.03863","title":"Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks","created":"2019-11-10","cited_by_count":57},{"id":"2102.01335","title":"Neural Data Augmentation via Example Extrapolation","created":"2021-02-02","cited_by_count":54},{"id":"1908.10423","title":"Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks","created":"2019-08-27","cited_by_count":48},{"id":"1910.04176","title":"A Closer Look At Feature Space Data Augmentation For Few-Shot Intent Classification","created":"2019-10-09","cited_by_count":45},{"id":"1808.10025","title":"Retrieval-Based Neural Code Generation","created":"2018-08-29","cited_by_count":41},{"id":"2010.11988","title":"Meta-Learning for Domain Generalization in Semantic Parsing","created":"2020-10-22","cited_by_count":41},{"id":"2104.05763","title":"Few-shot Intent Classification and Slot Filling with Retrieved Examples","created":"2021-04-12","cited_by_count":35},{"id":"2004.10793","title":"Learning to Classify Intents and Slot Labels Given a Handful of Examples","created":"2020-04-22","cited_by_count":31},{"id":"2009.13272","title":"Augmented Natural Language for Generative Sequence Labeling","created":"2020-09-15","cited_by_count":29},{"id":"1904.04428","title":"Text Generation with Exemplar-based Adaptive Decoding","created":"2019-04-09","cited_by_count":28},{"id":"1712.02719","title":"Incremental Learning in Deep Convolutional Neural Networks Using Partial Network Sharing","created":"2017-12-07","cited_by_count":22},{"id":"2010.11791","title":"ConVEx: Data-Efficient and Few-Shot Slot Labeling","created":"2020-10-22","cited_by_count":22},{"id":"1704.05974","title":"Cross-domain Semantic Parsing via Paraphrasing","created":"2017-04-20","cited_by_count":19},{"id":"2006.16336","title":"Learning Sparse Prototypes for Text Generation","created":"2020-06-29","cited_by_count":15},{"id":"2109.10410","title":"RETRONLU: Retrieval Augmented Task-Oriented Semantic Parsing","created":"2021-09-21","cited_by_count":15},{"id":"1802.02032","title":"Improving Variational Encoder-Decoders in Dialogue Generation","created":"2018-02-06","cited_by_count":13},{"id":"2004.01267","title":"MZET: Memory Augmented Zero-Shot Fine-grained Named Entity Typing","created":"2020-04-02","cited_by_count":12},{"id":"2009.08138","title":"FewJoint: A Few-shot Learning Benchmark for Joint Language Understanding","created":"2020-09-17","cited_by_count":10},{"id":"2009.12046","title":"Controllable Text Generation with Focused Variation","created":"2020-09-25","cited_by_count":7},{"id":"2101.10708","title":"Few-Shot Semantic Parsing for New Predicates","created":"2021-01-26","cited_by_count":7},{"id":"1903.10842","title":"Improve Diverse Text Generation by Self Labeling Conditional Variational Auto Encoder","created":"2019-03-26","cited_by_count":6},{"id":"2009.09568","title":"Vector Projection Network for Few-shot Slot Tagging in Natural Language Understanding","created":"2020-09-21","cited_by_count":4},{"id":"1910.12197","title":"Look-up and Adapt: A One-shot Semantic Parser","created":"2019-10-27","cited_by_count":3}],"next_cursor":null}