---
title: "Who cites Adam: A Method for Stochastic Optimization — page 4"
description: "10,909 papers of the Elamur Research library cite «Adam: A Method for Stochastic Optimization», found in their bibliographies · page 4 of 12…"
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---
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# Who cites «Adam: A Method for Stochastic Optimization»

10,909 papers of our library cite it (of the 149,439 whose bibliographies we read) · 1123 with a page here, the most cited first · page 4 of 12 · 301–400 · [← back to «Adam: A Method for Stochastic Optimization»](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/)

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301. [**ZeRO-Offload: Democratizing Billion-Scale Model Training arXiv:2101.06840**Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, et al.*2021 · 309 citations*](https://md.research.elamur.ai/free/en/papers/ren-2021-zero-offload-democratizing-billion-scale/)
302. [**Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow arXiv:1805.08949**Pengcheng Yin, Bowen Deng, Edgar Chen, et al.*2018 · 308 citations*](https://md.research.elamur.ai/free/en/papers/yin-2018-learning-mine-aligned-code-natural/)
303. **[Muppet: Massive Multi-task Representations with Pre-Finetuning](https://md.research.elamur.ai/free/en/papers/aghajanyan-2021-muppet-massive-multi-task-representations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Armen Aghajanyan, Anchit Gupta, Akshat Shrivastava, et al.*2021 · 307 citations*
304. **[SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization](https://md.research.elamur.ai/free/en/papers/jiang-2020-smart-robust-efficient-fine-tuning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haoming Jiang, Pengcheng He, Weizhu Chen, et al.*2020 · 304 citations*
305. [**UDPipe 2.0 Prototype at CoNLL 2018 UD Shared Task**Milan Straka*2018 · 303 citations*](https://md.research.elamur.ai/free/en/papers/straka-2018-udpipe-2-0-prototype-conll/)
306. **[Which argument is more convincing? Analyzing and predicting convincingness of Web arguments using bidirectional LSTM](https://md.research.elamur.ai/free/en/papers/habernal-2016-which-argument-is-more-convincing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ivan Habernal, Iryna Gurevych*2016 · 303 citations*
307. **[A Novel Bi-directional Interrelated Model for Joint Intent Detection and Slot Filling](https://md.research.elamur.ai/free/en/papers/e-2019-novel-bi-directional-interrelated-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Haihong E, Peiqing Niu, Zhongfu Chen, et al.*2019 · 302 citations*
308. [**Exploration by Random Network Distillation arXiv:1810.12894**Yuri Burda, Harrison Edwards, Amos Storkey, et al.*2018 · 302 citations*](https://md.research.elamur.ai/free/en/papers/burda-2018-exploration-random-network-distillation/)
309. **[Incorporating Discrete Translation Lexicons into Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/arthur-2016-incorporating-discrete-translation-lexicons-into/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Philip Arthur, Graham Neubig, Satoshi Nakamura*2016 · 302 citations*
310. **[DialogSum: A Real-Life Scenario Dialogue Summarization Dataset](https://md.research.elamur.ai/free/en/papers/chen-2021-dialogsum-real-life-scenario-dialogue/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yulong Chen, Yang Liu, Liang Chen, et al.*2021 · 301 citations*
311. **[MoEL: Mixture of Empathetic Listeners](https://md.research.elamur.ai/free/en/papers/lin-2019-moel-mixture-empathetic-listeners/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaojiang Lin, Andrea Madotto, Jamin Shin, et al.*2019 · 301 citations*
312. **[Inter-sentence Relation Extraction with Document-level Graph Convolutional Neural Network](https://md.research.elamur.ai/free/en/papers/sahu-2019-inter-sentence-relation-extraction-document/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sunil Kumar Sahu, Fenia Christopoulou, Makoto Miwa, et al.*2019 · 300 citations*
313. **[Deep Exhaustive Model for Nested Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/sohrab-2018-deep-exhaustive-model-nested-named/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mohammad Golam Sohrab, Makoto Miwa*2018 · 300 citations*
314. **[Paraphrase Generation with Deep Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/li-2018-paraphrase-generation-deep-reinforcement-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zichao Li, Xin Jiang, Lifeng Shang, et al.*2018 · 300 citations*
315. [**FlauBERT: Unsupervised Language Model Pre-training for French arXiv:1912.05372**Hang Le, Loïc Vial, Jibril Frej, et al.*2019 · 299 citations*](https://md.research.elamur.ai/free/en/papers/le-2019-flaubert-unsupervised-language-model-pre/)
316. **[Entity Linking via Joint Encoding of Types, Descriptions, and Context](https://md.research.elamur.ai/free/en/papers/gupta-2017-entity-linking-joint-encoding-types/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nitish Gupta, Sameer Singh, Dan Roth*2017 · 299 citations*
317. **[Connecting the Dots: Document-level Neural Relation Extraction with Edge-oriented Graphs](https://md.research.elamur.ai/free/en/papers/christopoulou-2019-connecting-dots-document-level-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fenia Christopoulou, Makoto Miwa, Sophia Ananiadou*2019 · 298 citations*
318. **[Copied Monolingual Data Improves Low-Resource Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/currey-2017-copied-monolingual-data-improves-low/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Anna Currey, Antonio Valerio Miceli Barone, Kenneth Heafield*2017 · 298 citations*
319. **[BanglaBERT: Language Model Pretraining and Benchmarks for Low-Resource Language Understanding Evaluation in Bangla](https://md.research.elamur.ai/free/en/papers/bhattacharjee-2022-banglabert-language-model-pretraining-benchmarks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Abhik Bhattacharjee, Tahmid Hasan, Wasi Ahmad, et al.*2022 · 296 citations*
320. **[HAT: Hardware-Aware Transformers for Efficient Natural Language Processing](https://md.research.elamur.ai/free/en/papers/wang-2020-hat-hardware-aware-transformers-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Hanrui Wang, Zhanghao Wu, Zhijian Liu, et al.*2020 · 294 citations*
321. **[QAFactEval: Improved QA-Based Factual Consistency Evaluation for Summarization](https://md.research.elamur.ai/free/en/papers/fabbri-2022-qafacteval-improved-qa-based-factual/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Alexander Fabbri, Chien-Sheng Wu, Wenhao Liu, et al.*2022 · 292 citations*
322. **[Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning](https://md.research.elamur.ai/free/en/papers/yang-2020-simple-effective-few-shot-named/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yi Yang, Arzoo Katiyar*2020 · 292 citations*
323. **[Target-oriented Opinion Words Extraction with Target-fused Neural Sequence Labeling](https://md.research.elamur.ai/free/en/papers/fan-2019-target-oriented-opinion-words-extraction/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Zhifang Fan, Zhen Wu, Xin-Yu Dai, et al.*2019 · 291 citations*
324. **[Ranking Sentences for Extractive Summarization with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/narayan-2018-ranking-sentences-extractive-summarization-reinforcement/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Shashi Narayan, Shay B. Cohen, Mirella Lapata*2018 · 290 citations*
325. **[SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2018-switchout-efficient-data-augmentation-algorithm/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xinyi Wang, Hieu Pham, Zihang Dai, et al.*2018 · 290 citations*
326. **[GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification](https://md.research.elamur.ai/free/en/papers/zhou-2019-gear-graph-based-evidence-aggregating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jie Zhou, Xu Han, Cheng Yang, et al.*2019 · 289 citations*
327. **[Learning to Translate in Real-time with Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gu-2017-learning-translate-real-time-neural/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jiatao Gu, Graham Neubig, Kyunghyun Cho, et al.*2017 · 289 citations*
328. [**Analysing Mathematical Reasoning Abilities of Neural Models arXiv:1904.01557**David Saxton, Edward Grefenstette, Felix Hill, et al.*2019 · 288 citations*](https://md.research.elamur.ai/free/en/papers/saxton-2019-analysing-mathematical-reasoning-abilities-neural/)
329. [**Hierarchical Multiscale Recurrent Neural Networks arXiv:1609.01704**Junyoung Chung, Sungjin Ahn, Yoshua Bengio*2016 · 288 citations*](https://md.research.elamur.ai/free/en/papers/chung-2016-hierarchical-multiscale-recurrent-neural-networks/)
330. [**An Explanation of In-context Learning as Implicit Bayesian Inference arXiv:2111.02080**Sang Michael Xie, Aditi Raghunathan, Percy Liang, et al.*2021 · 286 citations*](https://md.research.elamur.ai/free/en/papers/xie-2021-explanation-context-learning-implicit-bayesian/)
331. [**Cloze-driven Pretraining of Self-attention Networks arXiv:1903.07785**Alexei Baevski, Sergey Edunov, Yinhan Liu, et al.*2019 · 286 citations*](https://md.research.elamur.ai/free/en/papers/baevski-2019-cloze-driven-pretraining-self-attention/)
332. [**Structured Denoising Diffusion Models in Discrete State-Spaces arXiv:2107.03006**Jacob Austin, Daniel D. Johnson, Jonathan Ho, et al.*2021 · 284 citations*](https://md.research.elamur.ai/free/en/papers/austin-2021-structured-denoising-diffusion-models-discrete/)
333. **[Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work?](https://md.research.elamur.ai/free/en/papers/pruksachatkun-2020-intermediate-task-transfer-learning-pretrained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yada Pruksachatkun, Jason Phang, Haokun Liu, et al.*2020 · 281 citations*
334. **[Multi-Sentence Argument Linking](https://md.research.elamur.ai/free/en/papers/ebner-2020-multi-sentence-argument-linking/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Seth Ebner, Patrick Xia, Ryan Culkin, et al.*2020 · 281 citations*
335. [**Thinking Fast and Slow with Deep Learning and Tree Search arXiv:1705.08439**Thomas Anthony, Zheng Tian, David Barber*2017 · 281 citations*](https://md.research.elamur.ai/free/en/papers/anthony-2017-thinking-fast-slow-deep-learning/)
336. [**Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering arXiv:1911.10470**Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, et al.*2019 · 280 citations*](https://md.research.elamur.ai/free/en/papers/asai-2019-learning-retrieve-reasoning-paths-over/)
337. **[MIME: MIMicking Emotions for Empathetic Response Generation](https://md.research.elamur.ai/free/en/papers/majumder-2020-mime-mimicking-emotions-empathetic-response/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Navonil Majumder, Pengfei Hong, Shanshan Peng, et al.*2020 · 278 citations*
338. **[Logic Tensor Networks](https://md.research.elamur.ai/free/en/papers/badreddine-2020-logic-tensor-networks/) [Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/artificial-intelligence/)**Samy Badreddine, Artur d'Avila Garcez, Luciano Serafini, et al.*2020 · 276 citations*
339. [**InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training arXiv:2007.07834**Zewen Chi, Li Dong, Furu Wei, et al.*2020 · 275 citations*](https://md.research.elamur.ai/free/en/papers/chi-2020-infoxlm-information-theoretic-framework-cross/)
340. [**Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis ACM Computing Surveys 2019**Tal Ben-Nun, Torsten Hoefler*2018 · 275 citations*](https://md.research.elamur.ai/free/en/papers/nun-2018-demystifying-parallel-distributed-deep-learning/)
341. **[Text Classification Using Label Names Only: A Language Model Self-Training Approach](https://md.research.elamur.ai/free/en/papers/meng-2020-text-classification-label-names-only/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Meng, Yunyi Zhang, Jiaxin Huang, et al.*2020 · 274 citations*
342. **[Reinforced Mnemonic Reader for Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/hu-2017-reinforced-mnemonic-reader-machine-reading/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Minghao Hu, Yuxing Peng, Zhen Huang, et al.*2017 · 273 citations*
343. **[GPT3Mix: Leveraging Large-scale Language Models for Text Augmentation](https://md.research.elamur.ai/free/en/papers/yoo-2021-gpt3mix-leveraging-large-scale-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kang Min Yoo, Dongju Park, Jaewook Kang, et al.*2021 · 270 citations*
344. **[Efficient Dialogue State Tracking by Selectively Overwriting Memory](https://md.research.elamur.ai/free/en/papers/kim-2020-efficient-dialogue-state-tracking-selectively/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sungdong Kim, Sohee Yang, Gyuwan Kim, et al.*2020 · 270 citations*
345. [**MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies arXiv:2404.06395**Shengding Hu, Yuge Tu, Xu Han, et al.*2024 · 269 citations*](https://md.research.elamur.ai/free/en/papers/hu-2024-minicpm-unveiling-potential-small-language/)
346. **[Zero-Shot Stance Detection: A Dataset and Model using Generalized Topic Representations](https://md.research.elamur.ai/free/en/papers/allaway-2020-zero-shot-stance-detection-dataset/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Emily Allaway, Kathleen McKeown*2020 · 269 citations*
347. [**CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review arXiv:2103.06268**Dan Hendrycks, Collin Burns, Anya Chen, et al.*2021 · 268 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-cuad-expert-annotated-nlp-dataset/)
348. **[A Dual Reinforcement Learning Framework for Unsupervised Text Style Transfer](https://md.research.elamur.ai/free/en/papers/luo-2019-dual-reinforcement-learning-framework-unsupervised/) [International Joint Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/international-joint-conference-on-artificial-intelligence/)**Fuli Luo, Peng Li, Jie Zhou, et al.*2019 · 266 citations*
349. **[Summarizing Opinions: Aspect Extraction Meets Sentiment Prediction and They Are Both Weakly Supervised](https://md.research.elamur.ai/free/en/papers/angelidis-2018-summarizing-opinions-aspect-extraction-meets/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Stefanos Angelidis, Mirella Lapata*2018 · 266 citations*
350. **[Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network](https://md.research.elamur.ai/free/en/papers/hou-2020-few-shot-slot-tagging-collapsed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yutai Hou, Wanxiang Che, Yongkui Lai, et al.*2020 · 265 citations*
351. **[Unicoder: A Universal Language Encoder by Pre-training with Multiple Cross-lingual Tasks](https://md.research.elamur.ai/free/en/papers/huang-2019-unicoder-universal-language-encoder-pre/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Haoyang Huang, Yaobo Liang, Nan Duan, et al.*2019 · 265 citations*
352. **[Deep Recurrent Models with Fast-Forward Connections for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhou-2016-deep-recurrent-models-fast-forward/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jie Zhou, Ying Cao, Xuguang Wang, et al.*2016 · 265 citations*
353. [**A General Theoretical Paradigm to Understand Learning from Human Preferences arXiv:2310.12036**Mohammad Gheshlaghi Azar, Mark Rowland, Bilal Piot, et al.*2023 · 263 citations*](https://md.research.elamur.ai/free/en/papers/azar-2023-general-theoretical-paradigm-understand-learning/)
354. **[Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsing](https://md.research.elamur.ai/free/en/papers/lin-2020-bridging-textual-tabular-data-cross/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xi Victoria Lin, Richard Socher, Caiming Xiong*2020 · 263 citations*
355. **[Monotonic Infinite Lookback Attention for Simultaneous Machine Translation](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-monotonic-infinite-lookback-attention-simultaneous/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Naveen Arivazhagan, Colin Cherry, Wolfgang Macherey, et al.*2019 · 263 citations*
356. **[Selective Attention for Context-aware Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/maruf-2019-selective-attention-context-aware-neural/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Sameen Maruf, André F. T. Martins, Gholamreza Haffari*2019 · 263 citations*
357. **[Zero-shot User Intent Detection via Capsule Neural Networks](https://md.research.elamur.ai/free/en/papers/xia-2018-zero-shot-user-intent-detection/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Congying Xia, Chenwei Zhang, Xiaohui Yan, et al.*2018 · 263 citations*
358. **[MAVEN: A Massive General Domain Event Detection Dataset](https://md.research.elamur.ai/free/en/papers/wang-2020-maven-massive-general-domain-event/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xiaozhi Wang, Ziqi Wang, Xu Han, et al.*2020 · 261 citations*
359. [**Wan: Open and Advanced Large-Scale Video Generative Models arXiv:2503.20314**Team Wan, Ang Wang, Baole Ai, et al.*2025 · 260 citations*](https://md.research.elamur.ai/free/en/papers/wan-2025-wan-open-advanced-large-scale/)
360. **[RedPajama: an Open Dataset for Training Large Language Models](https://md.research.elamur.ai/free/en/papers/weber-2024-redpajama-open-dataset-training-large/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maurice Weber, Daniel Fu, Quentin Anthony, et al.*2024 · 260 citations*
361. **[Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual](https://md.research.elamur.ai/free/en/papers/he-2019-unlearn-dataset-bias-natural-language/) [Workshop on Deep Learning Approaches for Low-Resource NLP](https://md.research.elamur.ai/free/en/venues/workshop-on-deep-learning-approaches-for-low-resource-nlp/)**He He, Sheng Zha, Haohan Wang*2019 · 260 citations*
362. **[Mapping Language to Code in Programmatic Context](https://md.research.elamur.ai/free/en/papers/iyer-2018-mapping-language-code-programmatic-context/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, et al.*2018 · 260 citations*
363. [**LexGLUE: A Benchmark Dataset for Legal Language Understanding in English arXiv:2110.00976**Ilias Chalkidis; Abhik Jana; Dirk Hartung; Michael Bommarito; Ion Androutsopoulos; Daniel Martin Katz;, Nikolaos Aletras*2021 · 258 citations*](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-lexglue-benchmark-dataset-legal-language/)
364. **[Contrastive Learning for Many-to-many Multilingual Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/pan-2021-contrastive-learning-many-many-multilingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiao Pan, Mingxuan Wang, Liwei Wu, et al.*2021 · 256 citations*
365. **[RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking](https://md.research.elamur.ai/free/en/papers/ren-2021-rocketqav2-joint-training-method-dense/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ruiyang Ren, Yingqi Qu, Jing Liu, et al.*2021 · 256 citations*
366. **[CorefQA: Coreference Resolution as Query-based Span Prediction](https://md.research.elamur.ai/free/en/papers/wu-2020-corefqa-coreference-resolution-as-query/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Wu, Fei Wang, Arianna Yuan, et al.*2020 · 256 citations*
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