{"list":"other","total":57,"rows":[{"id":"1706.03762","title":"Attention Is All You Need","created":"2017-06-12","cited_by_count":60361},{"id":"1912.01703","title":"PyTorch: An Imperative Style, High-Performance Deep Learning Library","created":"2019-12-03","cited_by_count":20305},{"id":"1907.11692","title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach","created":"2019-07-26","cited_by_count":13372},{"id":"2111.06377","title":"Masked Autoencoders Are Scalable Vision Learners","created":"2021-11-11","cited_by_count":7403},{"id":"1804.07461","title":"GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding","created":"2018-04-20","cited_by_count":4899},{"id":"2104.09864","title":"RoFormer: Enhanced Transformer with Rotary Position Embedding","created":"2021-04-20","cited_by_count":4703},{"id":"1909.11942","title":"ALBERT: A Lite BERT for Self-supervised Learning of Language Representations","created":"2019-09-26","cited_by_count":2790},{"id":"1704.05426","title":"A Broad-Coverage Challenge Corpus for Sentence Understanding through Inference","created":"2017-04-18","cited_by_count":2682},{"id":"2106.08254","title":"BEiT: BERT Pre-Training of Image Transformers","created":"2021-06-15","cited_by_count":2375},{"id":"2006.03654","title":"DeBERTa: Decoding-enhanced BERT with Disentangled Attention","created":"2020-06-05","cited_by_count":2181},{"id":"1806.03822","title":"Know What You Don't Know: Unanswerable Questions for SQuAD","created":"2018-06-11","cited_by_count":1554},{"id":"2203.12602","title":"VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training","created":"2022-03-23","cited_by_count":1322},{"id":"2002.08155","title":"CodeBERT: A Pre-Trained Model for Programming and Natural Languages","created":"2020-02-19","cited_by_count":1310},{"id":"2111.09543","title":"DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing","created":"2021-11-18","cited_by_count":1254},{"id":"2111.09886","title":"SimMIM: A Simple Framework for Masked Image Modeling","created":"2021-11-18","cited_by_count":1153},{"id":"1703.00564","title":"MoleculeNet: A Benchmark for Molecular Machine Learning","created":"2017-03-02","cited_by_count":1051},{"id":"2103.10360","title":"GLM: General Language Model Pretraining with Autoregressive Blank Infilling","created":"2021-03-18","cited_by_count":1031},{"id":"1708.00055","title":"SemEval-2017 Task 1: Semantic Textual Similarity - Multilingual and Cross-lingual Focused Evaluation","created":"2017-07-31","cited_by_count":1001},{"id":"1805.12471","title":"Neural Network Acceptability Judgments","created":"2018-05-31","cited_by_count":958},{"id":"1907.10529","title":"SpanBERT: Improving Pre-training by Representing and Predicting Spans","created":"2019-07-24","cited_by_count":834},{"id":"1905.03197","title":"Unified Language Model Pre-training for Natural Language Understanding and Generation","created":"2019-05-08","cited_by_count":670},{"id":"2009.08366","title":"GraphCodeBERT: Pre-training Code Representations with Data Flow","created":"2020-09-17","cited_by_count":609},{"id":"1711.02281","title":"Non-Autoregressive Neural Machine Translation","created":"2017-11-07","cited_by_count":463},{"id":"1904.01561","title":"Analyzing Learned Molecular Representations for Property Prediction","created":"2019-04-02","cited_by_count":375},{"id":"2010.09885","title":"ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction","created":"2020-10-19","cited_by_count":337},{"id":"2401.00368","title":"Improving Text Embeddings with Large Language Models","created":"2023-12-31","cited_by_count":303},{"id":"2110.07728","title":"Pre-training Molecular Graph Representation with 3D Geometry","created":"2021-10-07","cited_by_count":248},{"id":"2211.15029","title":"DiffusionBERT: Improving Generative Masked Language Models with Diffusion Models","created":"2022-11-28","cited_by_count":214},{"id":"2106.09553","title":"Large-Scale Chemical Language Representations Capture Molecular Structure and Properties","created":"2021-06-17","cited_by_count":206},{"id":"2002.12804","title":"UniLMv2: Pseudo-Masked Language Models for Unified Language Model Pre-Training","created":"2020-02-28","cited_by_count":204},{"id":"2006.15595","title":"Rethinking Positional Encoding in Language Pre-training","created":"2020-06-28","cited_by_count":197},{"id":"2302.10198","title":"Can ChatGPT Understand Too? A Comparative Study on ChatGPT and Fine-tuned BERT","created":"2023-02-19","cited_by_count":155},{"id":"2310.15950","title":"Representation Learning with Large Language Models for Recommendation","created":"2023-10-24","cited_by_count":155},{"id":"2110.04126","title":"3D Infomax improves GNNs for Molecular Property Prediction","created":"2021-10-08","cited_by_count":146},{"id":"2202.08005","title":"Should You Mask 15% in Masked Language Modeling?","created":"2022-02-16","cited_by_count":118},{"id":"2402.18567","title":"Diffusion Language Models Are Versatile Protein Learners","created":"2024-02-28","cited_by_count":98},{"id":"2004.07437","title":"Non-Autoregressive Machine Translation with Latent Alignments","created":"2020-04-16","cited_by_count":96},{"id":"1806.09206","title":"N-Gram Graph: Simple Unsupervised Representation for Graphs, with Applications to Molecules","created":"2018-06-24","cited_by_count":93},{"id":"2005.07421","title":"Spelling Error Correction with Soft-Masked BERT","created":"2020-05-15","cited_by_count":90},{"id":"2307.16645","title":"Scaling Sentence Embeddings with Large Language Models","created":"2023-07-31","cited_by_count":85},{"id":"2402.15449","title":"Repetition Improves Language Model Embeddings","created":"2024-02-23","cited_by_count":72},{"id":"2410.13782","title":"DPLM-2: A Multimodal Diffusion Protein Language Model","created":"2024-10-17","cited_by_count":64},{"id":"1711.04810","title":"\"Found in Translation\": Predicting Outcomes of Complex Organic Chemistry Reactions using Neural Sequence-to-Sequence Models","created":"2017-11-13","cited_by_count":55},{"id":"2205.07459","title":"Directed Acyclic Transformer for Non-Autoregressive Machine Translation","created":"2022-05-16","cited_by_count":44},{"id":"2311.05296","title":"BeLLM: Backward Dependency Enhanced Large Language Model for Sentence Embeddings","created":"2023-11-09","cited_by_count":32},{"id":"2204.04163","title":"Contextual Representation Learning beyond Masked Language Modeling","created":"2022-04-08","cited_by_count":16},{"id":"2210.05193","title":"Viterbi Decoding of Directed Acyclic Transformer for Non-Autoregressive Machine Translation","created":"2022-10-11","cited_by_count":13},{"id":"2305.15273","title":"Revisiting Token Dropping Strategy in Efficient BERT Pretraining","created":"2023-05-24","cited_by_count":11},{"id":"2302.02060","title":"Representation Deficiency in Masked Language Modeling","created":"2023-02-04","cited_by_count":10},{"id":"2204.03243","title":"Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators","created":"2022-04-07","cited_by_count":9},{"id":"2304.11791","title":"Directed Acyclic Transformer Pre-training for High-quality Non-autoregressive Text Generation","created":"2023-04-24","cited_by_count":8},{"id":"2211.04898","title":"Mask More and Mask Later: Efficient Pre-training of Masked Language Models by Disentangling the [MASK] Token","created":"2022-11-09","cited_by_count":7},{"id":"2403.12995","title":"ESM All-Atom: Multi-scale Protein Language Model for Unified Molecular Modeling","created":"2024-03-05","cited_by_count":7},{"id":"2004.08097","title":"Fast and Accurate Deep Bidirectional Language Representations for Unsupervised Learning","created":"2020-04-17","cited_by_count":6},{"id":"2011.01900","title":"Warped Language Models for Noise Robust Language Understanding","created":"2020-11-03","cited_by_count":6},{"id":"2203.00286","title":"\"Is Whole Word Masking Always Better for Chinese BERT?\": Probing on Chinese Grammatical Error Correction","created":"2022-03-01","cited_by_count":4},{"id":"2412.05569","title":"SMI-Editor: Edit-based SMILES Language Model with Fragment-level Supervision","created":"2024-12-07","cited_by_count":3}],"next_cursor":null}