Who cites Di He
- SimCSE: Simple Contrastive Learning of Sentence EmbeddingsConference on Empirical Methods in Natural Language Processing (EMNLP)Tianyu Gao, Xingcheng Yao, Danqi Chen2021 · 3,922 citations
- On the Sentence Embeddings from Pre-trained Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP)Bohan Li, Hao Zhou, Junxian He, et al.2020 · 831 citations
- ConSERT: A Contrastive Framework for Self-Supervised Sentence Representation TransferAnnual Meeting of the Association for Computational Linguistics (ACL)Yuanmeng Yan, Rumei Li, Sirui Wang, et al.2021 · 648 citations
- Improving Massively Multilingual Neural Machine Translation and Zero-Shot TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Biao Zhang, Philip Williams, Ivan Titov, et al.2020 · 474 citations
- Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and InferencearXiv:2412.13663Benjamin Warner, Antoine Chaffin, Benjamin Clavié, et al.2024 · 355 citations
- Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic LanguagesTransactions of the Association for Computational Linguistics (TACL)Gowtham Ramesh, Sumanth Doddapaneni, Aravinth Bheemaraj, et al.2022 · 307 citations
- Multilingual Translation from Denoising Pre-TrainingFindings of the Association for Computational LinguisticsYuqing Tang, Chau Tran, Xian Li, et al.2021 · 219 citations
- IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian LanguagesarXiv:2305.16307Jay Gala, Pranjal A. Chitale, Raghavan AK, et al.2023 · 200 citations
- COCO-LM: Correcting and Contrasting Text Sequences for Language Model PretrainingarXiv:2102.08473Yu Meng, Chenyan Xiong, Payal Bajaj, et al.2021 · 196 citations
- Norm-Based Curriculum Learning for Neural Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Xuebo Liu, Houtim Lai, Derek F. Wong, et al.2020 · 158 citations
- All Bark and No Bite: Rogue Dimensions in Transformer Language Models Obscure Representational QualityConference on Empirical Methods in Natural Language Processing (EMNLP)William Timkey, Marten van Schijndel2021 · 139 citations
- Analyzing Transformers in Embedding SpaceAnnual Meeting of the Association for Computational Linguistics (ACL)Guy Dar, Mor Geva, Ankit Gupta, et al.2023 · 129 citations
- The case for 4-bit precision: k-bit Inference Scaling LawsarXiv:2212.09720Tim Dettmers, Luke Zettlemoyer2022 · 119 citations
- On Generalization in Coreference ResolutionShubham Toshniwal, Patrick Xia, Sam Wiseman, et al.2021 · 62 citations
- Scaling Laws with Vocabulary: Larger Models Deserve Larger VocabulariesarXiv:2407.13623Chaofan Tao, Qian Liu, Longxu Dou, et al.2024 · 42 citations
- Facebook AI's WMT21 News Translation Task SubmissionConference on Machine Translation (WMT)Chau Tran, Shruti Bhosale, James Cross, et al.2021 · 42 citations
- MiqraBERT: Regression-Based Sentence-BERT Finetuning for Biblical Hebrew Parallel DetectionDavid M. Smiley2026
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