{"list":"other","total":64,"rows":[{"id":"2005.14165","title":"Language Models are Few-Shot Learners","created":"2020-05-28","cited_by_count":32419},{"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":"2004.05150","title":"Longformer: The Long-Document Transformer","created":"2020-04-10","cited_by_count":3413},{"id":"2303.16634","title":"G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment","created":"2023-03-29","cited_by_count":2276},{"id":"2202.03629","title":"Survey of Hallucination in Natural Language Generation","created":"2022-02-08","cited_by_count":2075},{"id":"2007.14062","title":"Big Bird: Transformers for Longer Sequences","created":"2020-07-28","cited_by_count":1684},{"id":"1912.08777","title":"PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization","created":"2019-12-18","cited_by_count":1102},{"id":"2302.04023","title":"A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity","created":"2023-02-08","cited_by_count":894},{"id":"2305.01937","title":"Can Large Language Models Be an Alternative to Human Evaluations?","created":"2023-05-03","cited_by_count":734},{"id":"2003.07082","title":"Stanza: A Python Natural Language Processing Toolkit for Many Human Languages","created":"2020-03-16","cited_by_count":723},{"id":"2106.11520","title":"BARTScore: Evaluating Generated Text as Text Generation","created":"2021-06-22","cited_by_count":722},{"id":"2007.12626","title":"SummEval: Re-evaluating Summarization Evaluation","created":"2020-07-24","cited_by_count":674},{"id":"2004.09813","title":"Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation","created":"2020-04-21","cited_by_count":593},{"id":"2010.11125","title":"Beyond English-Centric Multilingual Machine Translation","created":"2020-10-21","cited_by_count":561},{"id":"1909.02622","title":"MoverScore: Text Generation Evaluating with Contextualized Embeddings and Earth Mover Distance","created":"2019-09-05","cited_by_count":418},{"id":"2111.09525","title":"SummaC: Re-Visiting NLI-based Models for Inconsistency Detection in Summarization","created":"2021-11-18","cited_by_count":407},{"id":"2004.04228","title":"Asking and Answering Questions to Evaluate the Factual Consistency of Summaries","created":"2020-04-08","cited_by_count":378},{"id":"2104.02112","title":"Efficient Attentions for Long Document Summarization","created":"2021-04-05","cited_by_count":345},{"id":"2209.12356","title":"News Summarization and Evaluation in the Era of GPT-3","created":"2022-09-26","cited_by_count":327},{"id":"1804.11283","title":"Newsroom: A Dataset of 1.3 Million Summaries with Diverse Extractive Strategies","created":"2018-04-30","cited_by_count":294},{"id":"2008.00401","title":"Multilingual Translation with Extensible Multilingual Pretraining and Finetuning","created":"2020-08-02","cited_by_count":287},{"id":"1605.09096","title":"Diachronic Word Embeddings Reveal Statistical Laws of Semantic Change","created":"2016-05-30","cited_by_count":221},{"id":"2203.16804","title":"BRIO: Bringing Order to Abstractive Summarization","created":"2022-03-31","cited_by_count":161},{"id":"2010.03093","title":"WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization","created":"2020-10-07","cited_by_count":154},{"id":"2010.07100","title":"Re-evaluating Evaluation in Text Summarization","created":"2020-10-14","cited_by_count":145},{"id":"2305.01625","title":"Unlimiformer: Long-Range Transformers with Unlimited Length Input","created":"2023-05-02","cited_by_count":128},{"id":"2304.02554","title":"Human-like Summarization Evaluation with ChatGPT","created":"2023-04-05","cited_by_count":126},{"id":"2302.08081","title":"Exploring the Limits of ChatGPT for Query or Aspect-based Text Summarization","created":"2023-02-16","cited_by_count":122},{"id":"2004.14900","title":"MLSUM: The Multilingual Summarization Corpus","created":"2020-04-30","cited_by_count":121},{"id":"2004.14118","title":"Analysing Lexical Semantic Change with Contextualised Word Representations","created":"2020-04-29","cited_by_count":92},{"id":"1909.03186","title":"On Extractive and Abstractive Neural Document Summarization with Transformer Language Models","created":"2019-09-07","cited_by_count":83},{"id":"2304.03245","title":"Large language models effectively leverage document-level context for literary translation, but critical errors persist","created":"2023-04-06","cited_by_count":80},{"id":"2207.00939","title":"An Empirical Survey on Long Document Summarization: Datasets, Models and Metrics","created":"2022-07-03","cited_by_count":74},{"id":"2305.13091","title":"Large Language Models are Not Yet Human-Level Evaluators for Abstractive Summarization","created":"2023-05-22","cited_by_count":70},{"id":"2005.03724","title":"SUPERT: Towards New Frontiers in Unsupervised Evaluation Metrics for Multi-Document Summarization","created":"2020-05-07","cited_by_count":69},{"id":"1909.00156","title":"NCLS: Neural Cross-Lingual Summarization","created":"2019-08-31","cited_by_count":64},{"id":"2203.06569","title":"SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization","created":"2022-03-13","cited_by_count":61},{"id":"2304.04193","title":"Extractive Summarization via ChatGPT for Faithful Summary Generation","created":"2023-04-09","cited_by_count":59},{"id":"2302.13795","title":"ChatGPT: A Meta-Analysis after 2.5 Months","created":"2023-02-20","cited_by_count":51},{"id":"2210.14250","title":"Exploring Document-Level Literary Machine Translation with Parallel Paragraphs from World Literature","created":"2022-10-25","cited_by_count":45},{"id":"2201.11176","title":"DiscoScore: Evaluating Text Generation with BERT and Discourse Coherence","created":"2022-01-26","cited_by_count":36},{"id":"2208.09770","title":"Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization","created":"2022-08-21","cited_by_count":29},{"id":"2105.13648","title":"Cross-Lingual Abstractive Summarization with Limited Parallel Resources","created":"2021-05-28","cited_by_count":27},{"id":"1904.02036","title":"A Large-Scale Comparison of Historical Text Normalization Systems","created":"2019-04-03","cited_by_count":25},{"id":"2105.03801","title":"Long-Span Summarization via Local Attention and Content Selection","created":"2021-05-08","cited_by_count":24},{"id":"2106.13945","title":"A Training-free and Reference-free Summarization Evaluation Metric via Centrality-weighted Relevance and Self-referenced Redundancy","created":"2021-06-26","cited_by_count":21},{"id":"2305.01633","title":"Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP","created":"2023-05-02","cited_by_count":21},{"id":"2107.08929","title":"MemSum: Extractive Summarization of Long Documents Using Multi-Step Episodic Markov Decision Processes","created":"2021-07-19","cited_by_count":19},{"id":"2205.09641","title":"SNaC: Coherence Error Detection for Narrative Summarization","created":"2022-05-19","cited_by_count":19},{"id":"2108.11696","title":"Rethinking Why Intermediate-Task Fine-Tuning Works","created":"2021-08-26","cited_by_count":18},{"id":"2208.07316","title":"MENLI: Robust Evaluation Metrics from Natural Language Inference","created":"2022-08-15","cited_by_count":18},{"id":"2203.03820","title":"A Variational Hierarchical Model for Neural Cross-Lingual Summarization","created":"2022-03-08","cited_by_count":17},{"id":"2205.08124","title":"When to Use Multi-Task Learning vs Intermediate Fine-Tuning for Pre-Trained Encoder Transfer Learning","created":"2022-05-17","cited_by_count":17},{"id":"2202.10062","title":"USCORE: An Effective Approach to Fully Unsupervised Evaluation Metrics for Machine Translation","created":"2022-02-21","cited_by_count":15},{"id":"2303.17650","title":"Comparing Abstractive Summaries Generated by ChatGPT to Real Summaries Through Blinded Reviewers and Text Classification Algorithms","created":"2023-03-30","cited_by_count":15},{"id":"1704.02497","title":"On the Linearity of Semantic Change: Investigating Meaning Variation via Dynamic Graph Models","created":"2017-04-08","cited_by_count":11},{"id":"1804.02545","title":"Evaluating historical text normalization systems: How well do they generalize?","created":"2018-04-07","cited_by_count":11},{"id":"1803.11112","title":"Identifying Semantic Divergences in Parallel Text without Annotations","created":"2018-03-29","cited_by_count":9},{"id":"2204.00004","title":"Reproducibility Issues for BERT-based Evaluation Metrics","created":"2022-03-30","cited_by_count":9},{"id":"1610.07844","title":"Improving historical spelling normalization with bi-directional LSTMs and multi-task learning","created":"2016-10-25","cited_by_count":8},{"id":"2010.07503","title":"Multi-Task Learning for Cross-Lingual Abstractive Summarization","created":"2020-10-15","cited_by_count":8},{"id":"2101.10759","title":"Summarising Historical Text in Modern Languages","created":"2021-01-26","cited_by_count":6},{"id":"2110.07936","title":"Unifying Cross-lingual Summarization and Machine Translation with Compression Rate","created":"2021-10-15","cited_by_count":5}],"next_cursor":null}