---
title: "Who cites Adam: A Method for Stochastic Optimization — page 6"
description: "10,909 papers of the Elamur Research library cite «Adam: A Method for Stochastic Optimization», found in their bibliographies · page 6 of 12…"
canonical: "https://research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/6/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/6/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Adam: A Method for Stochastic Optimization](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/) / [cited by](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/) / page 6

# 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 6 of 12 · 501–600 · [← back to «Adam: A Method for Stochastic Optimization»](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/)

[← prev](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/5/) [1](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/) … [5](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/5/) **6** [7](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/7/) … [10](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/10/) [11](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/11/) [12](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/12/) [next →](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/7/)

501. **[Curriculum Learning for Domain Adaptation in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2019-curriculum-learning-domain-adaptation-neural/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xuan Zhang, Pamela Shapiro, Gaurav Kumar, et al.*2019 · 169 citations*
502. **[Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-paragraph-level-rationale-extraction-through/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ilias Chalkidis, Manos Fergadiotis, Dimitrios Tsarapatsanis, et al.*2021 · 168 citations*
503. **[AMR Parsing via Graph-Sequence Iterative Inference](https://md.research.elamur.ai/free/en/papers/cai-2020-amr-parsing-graph-sequence-iterative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Deng Cai, Wai Lam*2020 · 168 citations*
504. [**SantaCoder: don't reach for the stars! arXiv:2301.03988**Loubna Ben Allal, Raymond Li, Denis Kocetkov, et al.*2023 · 167 citations*](https://md.research.elamur.ai/free/en/papers/allal-2023-santacoder-don-t-reach-stars/)
505. **[Hallucinated but Factual! Inspecting the Factuality of Hallucinations in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/cao-2022-hallucinated-but-factual-inspecting-factuality/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Meng Cao, Yue Dong, Jackie Cheung*2022 · 167 citations*
506. **[“I'm sorry to hear that”: Finding New Biases in Language Models with a Holistic Descriptor Dataset](https://md.research.elamur.ai/free/en/papers/smith-2022-i-m-sorry-hear-that/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eric Michael Smith, Melissa Hall, Melanie Kambadur, et al.*2022 · 167 citations*
507. **[Structure-Grounded Pretraining for Text-to-SQL](https://md.research.elamur.ai/free/en/papers/deng-2021-structure-grounded-pretraining-text-sql/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xiang Deng, Ahmed Hassan Awadallah, Christopher Meek, et al.*2021 · 167 citations*
508. **[Submodular Optimization-based Diverse Paraphrasing and its Effectiveness in Data Augmentation](https://md.research.elamur.ai/free/en/papers/kumar-2019-submodular-optimization-based-diverse-paraphrasing/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ashutosh Kumar, Satwik Bhattamishra, Manik Bhandari, et al.*2019 · 167 citations*
509. **[Target-Guided Open-Domain Conversation](https://md.research.elamur.ai/free/en/papers/tang-2019-target-guided-open-domain-conversation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianheng Tang, Tiancheng Zhao, Chenyan Xiong, et al.*2019 · 166 citations*
510. **[Cross-Target Stance Classification with Self-Attention Networks](https://md.research.elamur.ai/free/en/papers/xu-2018-cross-target-stance-classification-self/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chang Xu, Cecile Paris, Surya Nepal, et al.*2018 · 166 citations*
511. **[Can We Automate Scientific Reviewing?](https://md.research.elamur.ai/free/en/papers/yuan-2021-automate-scientific-reviewing/) [Journal of Artificial Intelligence Research](https://md.research.elamur.ai/free/en/venues/journal-of-artificial-intelligence-research/)**Weizhe Yuan, Pengfei Liu, Graham Neubig*2021 · 165 citations*
512. **[Sustainable Modular Debiasing of Language Models](https://md.research.elamur.ai/free/en/papers/lauscher-2021-sustainable-modular-debiasing-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anne Lauscher, Tobias Lueken, Goran Glavaš*2021 · 165 citations*
513. **[Stronger Baselines for Trustable Results in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/denkowski-2017-stronger-baselines-trustable-results-neural/) [Workshop on Neural Machine Translation](https://md.research.elamur.ai/free/en/venues/workshop-on-neural-machine-translation/)**Michael Denkowski, Graham Neubig*2017 · 165 citations*
514. **[Controllable Text Simplification with Explicit Paraphrasing](https://md.research.elamur.ai/free/en/papers/maddela-2021-controllable-text-simplification-explicit-paraphrasing/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Mounica Maddela, Fernando Alva-Manchego, Wei Xu*2021 · 164 citations*
515. **[Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution](https://md.research.elamur.ai/free/en/papers/barhom-2019-revisiting-joint-modeling-cross-document/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shany Barhom, Vered Shwartz, Alon Eirew, et al.*2019 · 164 citations*
516. [**Neural Language Correction with Character-Based Attention arXiv:1603.09727**Ziang Xie, Anand Avati, Naveen Arivazhagan, et al.*2016 · 164 citations*](https://md.research.elamur.ai/free/en/papers/xie-2016-neural-language-correction-character-based/)
517. **[Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation](https://md.research.elamur.ai/free/en/papers/huang-2019-achieving-verified-robustness-symbol-substitutions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Po-Sen Huang, Robert Stanforth, Johannes Welbl, et al.*2019 · 163 citations*
518. **[Machine Translationese: Effects of Algorithmic Bias on Linguistic Complexity in Machine Translation](https://md.research.elamur.ai/free/en/papers/vanmassenhove-2021-machine-translationese-effects-algorithmic-bias/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Eva Vanmassenhove, Dimitar Shterionov, Matthew Gwilliam*2021 · 162 citations*
519. **[On Negative Interference in Multilingual Models: Findings and A Meta-Learning Treatment](https://md.research.elamur.ai/free/en/papers/wang-2020-negative-interference-multilingual-models-findings/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zirui Wang, Zachary C. Lipton, Yulia Tsvetkov*2020 · 162 citations*
520. **[Towards Persona-Based Empathetic Conversational Models](https://md.research.elamur.ai/free/en/papers/zhong-2020-persona-based-empathetic-conversational-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Peixiang Zhong, Chen Zhang, Hao Wang, et al.*2020 · 162 citations*
521. **[Multi-Source Cross-Lingual Model Transfer: Learning What to Share](https://md.research.elamur.ai/free/en/papers/chen-2019-multi-source-cross-lingual-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xilun Chen, Ahmed Hassan Awadallah, Hany Hassan, et al.*2019 · 162 citations*
522. **[On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models](https://md.research.elamur.ai/free/en/papers/michel-2019-evaluation-adversarial-perturbations-sequence-sequence/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Paul Michel, Xian Li, Graham Neubig, et al.*2019 · 162 citations*
523. [**PipeDream: Fast and Efficient Pipeline Parallel DNN Training arXiv:1806.03377**Aaron Harlap, Deepak Narayanan, Amar Phanishayee, et al.*2018 · 162 citations*](https://md.research.elamur.ai/free/en/papers/harlap-2018-pipedream-fast-efficient-pipeline-parallel/)
524. **[LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression](https://md.research.elamur.ai/free/en/papers/pan-2024-llmlingua-2-data-distillation-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, et al.*2024 · 161 citations*
525. **[Extreme Adaptation for Personalized Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/michel-2018-extreme-adaptation-personalized-neural-machine/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Paul Michel, Graham Neubig*2018 · 161 citations*
526. [**Unsupervised Text Style Transfer using Language Models as Discriminators arXiv:1805.11749**Zichao Yang, Zhiting Hu, Chris Dyer, et al.*2018 · 161 citations*](https://md.research.elamur.ai/free/en/papers/yang-2018-unsupervised-text-style-transfer-using/)
527. **[MultiEURLEX - A multi-lingual and multi-label legal document classification dataset for zero-shot cross-lingual transfer](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-multieurlex-multi-lingual-multi-label/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ilias Chalkidis, Manos Fergadiotis, Ion Androutsopoulos*2021 · 160 citations*
528. [**Unsupervised Translation of Programming Languages arXiv:2006.03511**Marie-Anne Lachaux, Baptiste Roziere, Lowik Chanussot, et al.*2020 · 160 citations*](https://md.research.elamur.ai/free/en/papers/lachaux-2020-unsupervised-translation-programming-languages/)
529. **[Inferring Which Medical Treatments Work from Reports of Clinical Trials](https://md.research.elamur.ai/free/en/papers/lehman-2019-inferring-which-medical-treatments-work/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Eric Lehman, Jay DeYoung, Regina Barzilay, et al.*2019 · 160 citations*
530. [**Frame-Semantic Parsing with Softmax-Margin Segmental RNNs and a Syntactic Scaffold arXiv:1706.09528**Swabha Swayamdipta, Sam Thomson, Chris Dyer, et al.*2017 · 160 citations*](https://md.research.elamur.ai/free/en/papers/swayamdipta-2017-frame-semantic-parsing-softmax-margin/)
531. **[Testing the Predictions of Surprisal Theory in 11 Languages](https://md.research.elamur.ai/free/en/papers/wilcox-2023-testing-predictions-surprisal-theory-11/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ethan G. Wilcox, Tiago Pimentel, Clara Meister, et al.*2023 · 159 citations*
532. [**Semantic Neural Machine Translation Using AMR**Linfeng Song, Daniel Gildea, Yue Zhang, et al.*2019 · 159 citations*](https://md.research.elamur.ai/free/en/papers/song-2019-semantic-neural-machine-translation-amr/)
533. **[MEGATRON-CNTRL: Controllable Story Generation with External Knowledge Using Large-Scale Language Models](https://md.research.elamur.ai/free/en/papers/xu-2020-megatron-cntrl-controllable-story-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Peng Xu, Mostofa Patwary, Mohammad Shoeybi, et al.*2020 · 158 citations*
534. **[Norm-Based Curriculum Learning for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/liu-2020-norm-based-curriculum-learning-neural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuebo Liu, Houtim Lai, Derek F. Wong, et al.*2020 · 158 citations*
535. [**Moshi: a speech-text foundation model for real-time dialogue arXiv:2410.00037**Alexandre Defossez, Laurent Mazare, Manu Orsini, et al.*2024 · 157 citations*](https://md.research.elamur.ai/free/en/papers/defossez-2024-moshi-speech-text-foundation-model/)
536. **[On Hallucination and Predictive Uncertainty in Conditional Language Generation](https://md.research.elamur.ai/free/en/papers/xiao-2021-hallucination-predictive-uncertainty-conditional-language/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yijun Xiao, William Yang Wang*2021 · 157 citations*
537. **[Reducing Quantity Hallucinations in Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/zhao-2020-reducing-quantity-hallucinations-abstractive-summarization/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zheng Zhao, Shay B. Cohen, Bonnie Webber*2020 · 157 citations*
538. **[Revisiting Character-Based Neural Machine Translation with Capacity and Compression](https://md.research.elamur.ai/free/en/papers/cherry-2018-revisiting-character-based-neural-machine/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Colin Cherry, George Foster, Ankur Bapna, et al.*2018 · 156 citations*
539. **[Colors in Context: A Pragmatic Neural Model for Grounded Language Understanding](https://md.research.elamur.ai/free/en/papers/monroe-2017-colors-context-pragmatic-neural-model/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Will Monroe, Robert X.D. Hawkins, Noah D. Goodman, et al.*2017 · 156 citations*
540. **[Effective Domain Mixing for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/britz-2017-effective-domain-mixing-neural-machine/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Denny Britz, Quoc Le, Reid Pryzant*2017 · 156 citations*
541. **[Answering Complex Open-domain Questions Through Iterative Query Generation](https://md.research.elamur.ai/free/en/papers/qi-2019-answering-complex-open-domain-questions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Peng Qi, Xiaowen Lin, Leo Mehr, et al.*2019 · 155 citations*
542. **[Generating Sentences from Disentangled Syntactic and Semantic Spaces](https://md.research.elamur.ai/free/en/papers/bao-2019-generating-sentences-disentangled-syntactic-semantic/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu Bao, Hao Zhou, Shujian Huang, et al.*2019 · 154 citations*
543. **[Modeling Multi-turn Conversation with Deep Utterance Aggregation](https://md.research.elamur.ai/free/en/papers/zhang-2018-modeling-multi-turn-conversation-deep/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zhuosheng Zhang, Jiangtong Li, Pengfei Zhu, et al.*2018 · 154 citations*
544. **[Compositional Sequence Labeling Models for Error Detection in Learner Writing](https://md.research.elamur.ai/free/en/papers/rei-2016-compositional-sequence-labeling-models-error/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Marek Rei, Helen Yannakoudakis*2016 · 154 citations*
545. **[Fine-Tuning Language Models with Just Forward Passes](https://md.research.elamur.ai/free/en/papers/malladi-2023-fine-tuning-language-models-just/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Sadhika Malladi, Tianyu Gao, Eshaan Nichani, et al.*2023 · 153 citations*
546. **[Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning](https://md.research.elamur.ai/free/en/papers/wang-2023-label-words-anchors-information-flow/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lean Wang, Lei Li, Damai Dai, et al.*2023 · 153 citations*
547. **[Multilingual Autoregressive Entity Linking](https://md.research.elamur.ai/free/en/papers/cao-2022-multilingual-autoregressive-entity-linking/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nicola De Cao, Ledell Wu, Kashyap Popat, et al.*2022 · 153 citations*
548. **[Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing](https://md.research.elamur.ai/free/en/papers/wang-2019-cross-lingual-bert-transformation-zero/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuxuan Wang, Wanxiang Che, Jiang Guo, et al.*2019 · 153 citations*
549. [**LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech arXiv:1904.02882**Heiga Zen, Viet Dang, Rob Clark, et al.*2019 · 153 citations*](https://md.research.elamur.ai/free/en/papers/zen-2019-libritts-corpus-derived-librispeech-text/)
550. [**Generative Verifiers: Reward Modeling as Next-Token Prediction arXiv:2408.15240**Lunjun Zhang, Arian Hosseini, Hritik Bansal, et al.*2024 · 152 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-generative-verifiers-reward-modeling-as/)
551. **[ProsocialDialog: A Prosocial Backbone for Conversational Agents](https://md.research.elamur.ai/free/en/papers/kim-2022-prosocialdialog-prosocial-backbone-conversational-agents/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Hyunwoo Kim, Youngjae Yu, Liwei Jiang, et al.*2022 · 152 citations*
552. **[Neural Path Hunter: Reducing Hallucination in Dialogue Systems via Path Grounding](https://md.research.elamur.ai/free/en/papers/dziri-2021-neural-path-hunter-reducing-hallucination/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nouha Dziri, Andrea Madotto, Osmar Zaïane, et al.*2021 · 152 citations*
553. **[HyperTree Proof Search for Neural Theorem Proving](https://md.research.elamur.ai/free/en/papers/lample-2022-hypertree-proof-search-neural-theorem/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Guillaume Lample, Marie-Anne Lachaux, Thibaut Lavril, et al.*2022 · 151 citations*
554. **[Investigating Pretrained Language Models for Graph-to-Text Generation](https://md.research.elamur.ai/free/en/papers/ribeiro-2021-investigating-pretrained-language-models-graph/) [Workshop on Natural Language Processing for Conversational AI](https://md.research.elamur.ai/free/en/venues/nlp4convai/)**Leonardo F. R. Ribeiro, Martin Schmitt, Hinrich Schütze, et al.*2021 · 151 citations*
555. **[Regularization techniques for fine-tuning in neural machine translation](https://md.research.elamur.ai/free/en/papers/barone-2017-regularization-techniques-fine-tuning-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Antonio Valerio Miceli Barone, Barry Haddow, Ulrich Germann, et al.*2017 · 151 citations*
556. **[CPM: A Large-scale Generative Chinese Pre-trained Language Model](https://md.research.elamur.ai/free/en/papers/zhang-2020-cpm-large-scale-generative/) [AI Open](https://md.research.elamur.ai/free/en/venues/ai-open/)**Zhengyan Zhang, Xu Han, Hao Zhou, et al.*2020 · 150 citations*
557. **[Investigating Meta-Learning Algorithms for Low-Resource Natural Language Understanding Tasks](https://md.research.elamur.ai/free/en/papers/dou-2019-investigating-meta-learning-algorithms-low/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zi-Yi Dou, Keyi Yu, Antonios Anastasopoulos*2019 · 150 citations*
558. **[Do latent tree learning models identify meaningful structure in sentences?](https://md.research.elamur.ai/free/en/papers/williams-2018-do-latent-tree-learning-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Adina Williams, Andrew Drozdov, Samuel R. Bowman*2018 · 149 citations*
559. **[Out of Order: How important is the sequential order of words in a sentence in Natural Language Understanding tasks?](https://md.research.elamur.ai/free/en/papers/pham-2021-out-order-how-important-is/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Thang Pham, Trung Bui, Long Mai, et al.*2021 · 148 citations*
560. **[Sequence-to-Sequence Generation for Spoken Dialogue via Deep Syntax Trees and Strings](https://md.research.elamur.ai/free/en/papers/dusek-2016-sequence-sequence-generation-spoken-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ondřej Dušek, Filip Jurčíček*2016 · 148 citations*
561. [**AudioLDM: Text-to-Audio Generation with Latent Diffusion Models arXiv:2301.12503**Haohe Liu, Zehua Chen, Yi Yuan, et al.*2023 · 147 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-audioldm-text-audio-generation-latent/)
562. **[UniK-QA: Unified Representations of Structured and Unstructured Knowledge for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/oguz-2022-unik-qa-unified-representations-structured/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Barlas Oguz, Xilun Chen, Vladimir Karpukhin, et al.*2022 · 147 citations*
563. **[Quality-Aware Decoding for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/fernandes-2022-quality-aware-decoding-neural-machine/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Patrick Fernandes, António Farinhas, Ricardo Rei, et al.*2022 · 146 citations*
564. **[SGM: Sequence Generation Model for Multi-label Classification](https://md.research.elamur.ai/free/en/papers/yang-2018-sgm-sequence-generation-model-multi/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Pengcheng Yang, Xu Sun, Wei Li, et al.*2018 · 146 citations*
565. [**JudgeLM: Fine-tuned Large Language Models are Scalable Judges arXiv:2310.17631**Lianghui Zhu, Xinggang Wang, Xinlong Wang*2023 · 145 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-judgelm-fine-tuned-large-language/)
566. **[Zero-shot Neural Passage Retrieval via Domain-targeted Synthetic Question Generation](https://md.research.elamur.ai/free/en/papers/ma-2021-zero-shot-neural-passage-retrieval/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Ji Ma, Ivan Korotkov, Yinfei Yang, et al.*2021 · 144 citations*
567. **[GRADE: Automatic Graph-Enhanced Coherence Metric for Evaluating Open-Domain Dialogue Systems](https://md.research.elamur.ai/free/en/papers/huang-2020-grade-automatic-graph-enhanced-coherence/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Lishan Huang, Zheng Ye, Jinghui Qin, et al.*2020 · 144 citations*
568. **[Dynamic Entity Representations in Neural Language Models](https://md.research.elamur.ai/free/en/papers/ji-2017-dynamic-entity-representations-neural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yangfeng Ji, Chenhao Tan, Sebastian Martschat, et al.*2017 · 144 citations*
569. **[Full Parameter Fine-tuning for Large Language Models with Limited Resources](https://md.research.elamur.ai/free/en/papers/lv-2024-full-parameter-fine-tuning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kai Lv, Yuqing Yang, Tengxiao Liu, et al.*2024 · 143 citations*
570. **[Avoiding Reasoning Shortcuts: Adversarial Evaluation, Training, and Model Development for Multi-Hop QA](https://md.research.elamur.ai/free/en/papers/jiang-2019-avoiding-reasoning-shortcuts-adversarial-evaluation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yichen Jiang, Mohit Bansal*2019 · 143 citations*
571. [**Measuring the Intrinsic Dimension of Objective Landscapes arXiv:1804.08838**Chunyuan Li, Heerad Farkhoor, Rosanne Liu, et al.*2018 · 143 citations*](https://md.research.elamur.ai/free/en/papers/li-2018-measuring-intrinsic-dimension-objective-landscapes/)
572. **[A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation](https://md.research.elamur.ai/free/en/papers/liu-2022-token-level-reference-free-hallucination/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tianyu Liu, Yizhe Zhang, Chris Brockett, et al.*2022 · 142 citations*
573. **[Beyond Black & White: Leveraging Annotator Disagreement via Soft-Label Multi-Task Learning](https://md.research.elamur.ai/free/en/papers/fornaciari-2021-beyond-black-white-leveraging-annotator/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tommaso Fornaciari, Alexandra Uma, Silviu Paun, et al.*2021 · 142 citations*
574. **[Paragraph-level Simplification of Medical Texts](https://md.research.elamur.ai/free/en/papers/devaraj-2021-paragraph-level-simplification-medical-texts/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ashwin Devaraj, Iain Marshall, Byron Wallace, et al.*2021 · 140 citations*
575. **[Investigating Entity Knowledge in BERT with Simple Neural End-To-End Entity Linking](https://md.research.elamur.ai/free/en/papers/broscheit-2019-investigating-entity-knowledge-bert-simple/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Samuel Broscheit*2019 · 140 citations*
576. **[ERICA: Improving Entity and Relation Understanding for Pre-trained Language Models via Contrastive Learning](https://md.research.elamur.ai/free/en/papers/qin-2021-erica-improving-entity-relation-understanding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yujia Qin, Yankai Lin, Ryuichi Takanobu, et al.*2021 · 139 citations*
577. [**Deep Network Guided Proof Search arXiv:1701.06972 (In Thomas Eiter and David Sands, editors, 21st International Conference on Logic for Programming, Artificial Intelligence and Reasoning (LPAR-21). EPiC Series in Computing, vol. 46, pages 85-105, EasyChair, 2017. ISSN 2398-7340)**Sarah Loos, Geoffrey Irving, Christian Szegedy, et al.*2017 · 139 citations*](https://md.research.elamur.ai/free/en/papers/loos-2017-deep-network-guided-proof-search/)
578. [**Deep Learning for Symbolic Mathematics arXiv:1912.01412**Guillaume Lample, François Charton*2019 · 138 citations*](https://md.research.elamur.ai/free/en/papers/lample-2019-deep-learning-symbolic-mathematics/)
579. **[Question Answering by Reasoning Across Documents with Graph Convolutional Networks](https://md.research.elamur.ai/free/en/papers/cao-2019-question-answering-reasoning-across-documents/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nicola De Cao, Wilker Aziz, Ivan Titov*2019 · 138 citations*
580. **[Extracting Latent Steering Vectors from Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/subramani-2022-extracting-latent-steering-vectors-pretrained/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nishant Subramani, Nivedita Suresh, Matthew Peters*2022 · 137 citations*
581. [**Lost in Translation: Loss and Decay of Linguistic Richness in Machine Translation Proceedings of Machine Translation Summit XVII: Research Track**Eva Vanmassenhove, Dimitar Shterionov, Andy Way*2019 · 137 citations*](https://md.research.elamur.ai/free/en/papers/vanmassenhove-2019-lost-translation-loss-decay-linguistic/)
582. **[A Simple and Effective Unified Encoder for Document-Level Machine Translation](https://md.research.elamur.ai/free/en/papers/ma-2020-simple-effective-unified-encoder-document/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shuming Ma, Dongdong Zhang, Ming Zhou*2020 · 136 citations*
583. **[Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models](https://md.research.elamur.ai/free/en/papers/yang-2021-be-careful-about-poisoned-word/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Wenkai Yang, Lei Li, Zhiyuan Zhang, et al.*2021 · 135 citations*
584. **[Affective and Contextual Embedding for Sarcasm Detection](https://md.research.elamur.ai/free/en/papers/babanejad-2020-affective-contextual-embedding-sarcasm-detection/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Nastaran Babanejad, Heidar Davoudi, Aijun An, et al.*2020 · 135 citations*
585. **[Enhancing Zero-shot and Few-shot Stance Detection with Commonsense Knowledge Graph](https://md.research.elamur.ai/free/en/papers/liu-2021-enhancing-zero-shot-few-shot/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Rui Liu, Zheng Lin, Yutong Tan, et al.*2021 · 134 citations*
586. **[Semantic Graphs for Generating Deep Questions](https://md.research.elamur.ai/free/en/papers/pan-2020-semantic-graphs-generating-deep-questions/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liangming Pan, Yuxi Xie, Yansong Feng, et al.*2020 · 134 citations*
587. [**EuroLLM: Multilingual Language Models for Europe arXiv:2409.16235**Pedro Henrique Martins, Patrick Fernandes, Joao Alves, et al.*2024 · 133 citations*](https://md.research.elamur.ai/free/en/papers/martins-2024-eurollm-multilingual-language-models-europe/)
588. **[STEMM: Self-learning with Speech-text Manifold Mixup for Speech Translation](https://md.research.elamur.ai/free/en/papers/fang-2022-stemm-self-learning-speech-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingkai Fang, Rong Ye, Lei Li, et al.*2022 · 133 citations*
589. **[Does Gender Matter? Towards Fairness in Dialogue Systems](https://md.research.elamur.ai/free/en/papers/liu-2020-does-gender-matter-fairness-dialogue/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Haochen Liu, Jamell Dacon, Wenqi Fan, et al.*2020 · 133 citations*
590. **[Constrained Decoding for Neural NLG from Compositional Representations in Task-Oriented Dialogue](https://md.research.elamur.ai/free/en/papers/balakrishnan-2019-constrained-decoding-neural-nlg-compositional/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Anusha Balakrishnan, Jinfeng Rao, Kartikeya Upasani, et al.*2019 · 133 citations*
591. **[Stance Detection with Hierarchical Attention Network](https://md.research.elamur.ai/free/en/papers/sun-2018-stance-detection-hierarchical-attention-network/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Qingying Sun, Zhongqing Wang, Qiaoming Zhu, et al.*2018 · 133 citations*
592. **[Language Models that Seek for Knowledge: Modular Search & Generation for Dialogue and Prompt Completion](https://md.research.elamur.ai/free/en/papers/shuster-2022-language-models-that-seek-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kurt Shuster, Mojtaba Komeili, Leonard Adolphs, et al.*2022 · 132 citations*
593. **[Text2Mol: Cross-Modal Molecule Retrieval with Natural Language Queries](https://md.research.elamur.ai/free/en/papers/edwards-2021-text2mol-cross-modal-molecule-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Carl Edwards, ChengXiang Zhai, Heng Ji*2021 · 132 citations*
594. **[Syntax-Guided Controlled Generation of Paraphrases](https://md.research.elamur.ai/free/en/papers/kumar-2020-syntax-guided-controlled-generation-paraphrases/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ashutosh Kumar, Kabir Ahuja, Raghuram Vadapalli, et al.*2020 · 131 citations*
595. **[Efficient Nearest Neighbor Language Models](https://md.research.elamur.ai/free/en/papers/he-2021-efficient-nearest-neighbor-language-models/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Junxian He, Graham Neubig, Taylor Berg-Kirkpatrick*2021 · 130 citations*
596. **[Learning Compact Metrics for MT](https://md.research.elamur.ai/free/en/papers/pu-2021-learning-compact-metrics-mt/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Amy Pu, Hyung Won Chung, Ankur Parikh, et al.*2021 · 130 citations*
597. **[Scheduled Multi-Task Learning: From Syntax to Translation](https://md.research.elamur.ai/free/en/papers/kiperwasser-2018-scheduled-multi-task-learning-syntax/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Eliyahu Kiperwasser, Miguel Ballesteros*2018 · 130 citations*
598. **[MAGE: Machine-generated Text Detection in the Wild](https://md.research.elamur.ai/free/en/papers/li-2024-mage-machine-generated-text-detection/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yafu Li, Qintong Li, Leyang Cui, et al.*2024 · 129 citations*
599. [**Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-Tuning arXiv:2303.15647**Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.*2023 · 129 citations*](https://md.research.elamur.ai/free/en/papers/lialin-2023-scaling-down-scale-up-guide/)
600. **[Annotation, Modelling and Analysis of Fine-Grained Emotions on a Stance and Sentiment Detection Corpus](https://md.research.elamur.ai/free/en/papers/schuff-2017-annotation-modelling-analysis-fine-grained/) [Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis](https://md.research.elamur.ai/free/en/venues/wassa/)**Hendrik Schuff, Jeremy Barnes, Julian Mohme, et al.*2017 · 129 citations*

[← prev](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/5/) [1](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/) … [5](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/5/) **6** [7](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/7/) … [10](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/10/) [11](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/11/) [12](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/12/) [next →](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/cited-by/page/7/)

- [← back to](https://md.research.elamur.ai/free/en/papers/kingma-2014-adam-method-stochastic-optimization/) — Adam: A Method for Stochastic Optimization