{"list":"other","total":64,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"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":"2302.13971","title":"LLaMA: Open and Efficient Foundation Language Models","created":"2023-02-27","cited_by_count":14132},{"id":"1907.11692","title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach","created":"2019-07-26","cited_by_count":13372},{"id":"2001.08361","title":"Scaling Laws for Neural Language Models","created":"2020-01-23","cited_by_count":6586},{"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":"2204.02311","title":"PaLM: Scaling Language Modeling with Pathways","created":"2022-04-05","cited_by_count":5326},{"id":"1301.3781","title":"Efficient Estimation of Word Representations in Vector Space","created":"2013-01-16","cited_by_count":4375},{"id":"1910.01108","title":"DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter","created":"2019-10-02","cited_by_count":4307},{"id":"1406.1078","title":"Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation","created":"2014-06-03","cited_by_count":4057},{"id":"2108.07258","title":"On the Opportunities and Risks of Foundation Models","created":"2021-08-16","cited_by_count":4033},{"id":"1409.3215","title":"Sequence to Sequence Learning with Neural Networks","created":"2014-09-10","cited_by_count":2986},{"id":"1906.08237","title":"XLNet: Generalized Autoregressive Pretraining for Language Understanding","created":"2019-06-19","cited_by_count":2811},{"id":"1909.11942","title":"ALBERT: A Lite BERT for Self-supervised Learning of Language Representations","created":"2019-09-26","cited_by_count":2790},{"id":"1908.02265","title":"ViLBERT: Pretraining Task-Agnostic Visiolinguistic Representations for Vision-and-Language Tasks","created":"2019-08-06","cited_by_count":2222},{"id":"2006.03654","title":"DeBERTa: Decoding-enhanced BERT with Disentangled Attention","created":"2020-06-05","cited_by_count":2181},{"id":"1901.08746","title":"BioBERT: a pre-trained biomedical language representation model for biomedical text mining","created":"2019-01-25","cited_by_count":1947},{"id":"2201.08239","title":"LaMDA: Language Models for Dialog Applications","created":"2022-01-20","cited_by_count":1220},{"id":"2004.06165","title":"Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks","created":"2020-04-13","cited_by_count":1214},{"id":"1408.5882","title":"Convolutional Neural Networks for Sentence Classification","created":"2014-08-25","cited_by_count":1127},{"id":"1612.03975","title":"ConceptNet 5.5: An Open Multilingual Graph of General Knowledge","created":"2016-12-12","cited_by_count":1067},{"id":"1604.01696","title":"A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Stories","created":"2016-04-06","cited_by_count":417},{"id":"2305.00050","title":"Causal Reasoning and Large Language Models: Opening a New Frontier for Causality","created":"2023-04-28","cited_by_count":353},{"id":"2005.00333","title":"XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning","created":"2020-05-01","cited_by_count":333},{"id":"1904.09223","title":"ERNIE: Enhanced Representation through Knowledge Integration","created":"2019-04-19","cited_by_count":302},{"id":"2011.00620","title":"Social Chemistry 101: Learning to Reason about Social and Moral Norms","created":"2020-11-01","cited_by_count":255},{"id":"2212.09597","title":"Reasoning with Language Model Prompting: A Survey","created":"2022-12-19","cited_by_count":252},{"id":"2101.00288","title":"Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models","created":"2021-01-01","cited_by_count":222},{"id":"2002.02770","title":"A Survey on Causal Inference","created":"2020-02-05","cited_by_count":202},{"id":"2109.00725","title":"Causal Inference in Natural Language Processing: Estimation, Prediction, Interpretation and Beyond","created":"2021-09-02","cited_by_count":178},{"id":"2212.10465","title":"SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization","created":"2022-12-20","cited_by_count":168},{"id":"2306.05836","title":"Can Large Language Models Infer Causation from Correlation?","created":"2023-06-09","cited_by_count":146},{"id":"2312.04350","title":"CLadder: Assessing Causal Reasoning in Language Models","created":"2023-12-07","cited_by_count":107},{"id":"1905.00270","title":"ASER: A Large-scale Eventuality Knowledge Graph","created":"2019-05-01","cited_by_count":89},{"id":"1909.04076","title":"Counterfactual Story Reasoning and Generation","created":"2019-09-09","cited_by_count":88},{"id":"2009.07758","title":"GLUCOSE: GeneraLized and COntextualized Story Explanations","created":"2020-09-16","cited_by_count":86},{"id":"1805.06939","title":"Event2Mind: Commonsense Inference on Events, Intents, and Reactions","created":"2018-05-17","cited_by_count":82},{"id":"2012.04698","title":"Generate Your Counterfactuals: Towards Controlled Counterfactual Generation for Text","created":"2020-12-08","cited_by_count":75},{"id":"1911.10422","title":"SemEval-2010 Task 8: Multi-Way Classification of Semantic Relations Between Pairs of Nominals","created":"2019-11-23","cited_by_count":63},{"id":"1906.04941","title":"Joint Reasoning for Temporal and Causal Relations","created":"2019-06-12","cited_by_count":62},{"id":"2002.00269","title":"A Tutorial on Learning With Bayesian Networks","created":"2020-02-01","cited_by_count":57},{"id":"2012.04293","title":"CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions","created":"2020-12-08","cited_by_count":44},{"id":"2302.04752","title":"Benchmarks for Automated Commonsense Reasoning: A Survey","created":"2023-02-09","cited_by_count":40},{"id":"2201.12438","title":"Commonsense Knowledge Reasoning and Generation with Pre-trained Language Models: A Survey","created":"2022-01-28","cited_by_count":38},{"id":"2202.12350","title":"DoCoGen: Domain Counterfactual Generation for Low Resource Domain Adaptation","created":"2022-02-24","cited_by_count":37},{"id":"1412.3773","title":"Distinguishing cause from effect using observational data: methods and benchmarks","created":"2014-12-11","cited_by_count":33},{"id":"2107.09846","title":"Guided Generation of Cause and Effect","created":"2021-07-21","cited_by_count":33},{"id":"2202.07234","title":"Long-term Causal Inference Under Persistent Confounding via Data Combination","created":"2022-02-15","cited_by_count":27},{"id":"2305.16572","title":"Counterfactual reasoning: Testing language models' understanding of hypothetical scenarios","created":"2023-05-26","cited_by_count":27},{"id":"1904.07629","title":"Causality Extraction based on Self-Attentive BiLSTM-CRF with Transferred Embeddings","created":"2019-04-16","cited_by_count":25},{"id":"2305.05191","title":"COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference Perspective","created":"2023-05-09","cited_by_count":22},{"id":"1605.07895","title":"Automatic Extraction of Causal Relations from Natural Language Texts: A Comprehensive Survey","created":"2016-05-25","cited_by_count":16},{"id":"2202.00436","title":"ROCK: Causal Inference Principles for Reasoning about Commonsense Causality","created":"2022-01-31","cited_by_count":16},{"id":"2106.03046","title":"Empowering Language Understanding with Counterfactual Reasoning","created":"2021-06-06","cited_by_count":13},{"id":"2008.00563","title":"SemEval-2020 Task 5: Counterfactual Recognition","created":"2020-08-02","cited_by_count":12},{"id":"2302.10625","title":"Estimating long-term causal effects from short-term experiments and long-term observational data with unobserved confounding","created":"2023-02-21","cited_by_count":12},{"id":"1305.5506","title":"Introduction to Judea Pearl's Do-Calculus","created":"2013-04-26","cited_by_count":5},{"id":"2207.03961","title":"CoSIm: Commonsense Reasoning for Counterfactual Scene Imagination","created":"2022-07-08","cited_by_count":5},{"id":"2209.00869","title":"A Survey of Causal Inference Frameworks","created":"2022-09-02","cited_by_count":5},{"id":"1906.07544","title":"Transfer Learning for Causal Sentence Detection","created":"2019-06-18","cited_by_count":4},{"id":"2205.15016","title":"A Fundamental Probabilistic Fuzzy Logic Framework Suitable for Causal Reasoning","created":"2022-05-30","cited_by_count":3},{"id":"2005.08519","title":"Yseop at SemEval-2020 Task 5: Cascaded BERT Language Model for Counterfactual Statement Analysis","created":"2020-05-18","cited_by_count":1}],"next_cursor":null}