---
title: "Who cites Jimmy Lei Ba — page 5 — 14,084 papers of our library"
description: "14,084 papers of the Elamur Research library cite the works of Jimmy Lei Ba, found in their bibliographies · page 5 of 19 · 401–500; the most…"
canonical: "https://research.elamur.ai/free/en/authors/jimmy-lei-ba/cited-by/page/5/"
---
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# Who cites Jimmy Lei Ba

15,364 citations of their works from 14,084 papers of our library (of the 149,439 whose bibliographies we read) · 1,840 with a page here, the most cited first · page 5 of 19 · 401–500 · [← Jimmy Lei Ba](https://md.research.elamur.ai/free/en/authors/jimmy-lei-ba/)

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401. **[Improving Multimodal Named Entity Recognition via Entity Span Detection with Unified Multimodal Transformer](https://md.research.elamur.ai/free/en/papers/yu-2020-improving-multimodal-named-entity-recognition/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jianfei Yu, Jing Jiang, Li Yang, et al.*2020 · 342 citations*
402. **[SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/liu-2021-simcls-simple-framework-contrastive-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Liu, Pengfei Liu*2021 · 341 citations*
403. **[Certified Robustness to Adversarial Word Substitutions](https://md.research.elamur.ai/free/en/papers/jia-2019-certified-robustness-adversarial-word-substitutions/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Robin Jia, Aditi Raghunathan, Kerem Göksel, et al.*2019 · 340 citations*
404. [**Compressive Transformers for Long-Range Sequence Modelling arXiv:1911.05507**Jack W. Rae, Anna Potapenko, Siddhant M. Jayakumar, et al.*2019 · 340 citations*](https://md.research.elamur.ai/free/en/papers/rae-2019-compressive-transformers-long-range-sequence/)
405. **[RLPrompt: Optimizing Discrete Text Prompts with Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/deng-2022-rlprompt-optimizing-discrete-text-prompts/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Mingkai Deng, Jianyu Wang, Cheng-Ping Hsieh, et al.*2022 · 338 citations*
406. [**Progress & Compress: A scalable framework for continual learning arXiv:1805.06370**Jonathan Schwarz, Jelena Luketina, Wojciech M. Czarnecki, et al.*2018 · 338 citations*](https://md.research.elamur.ai/free/en/papers/schwarz-2018-progress-compress-scalable-framework-continual/)
407. **[Sentence Compression by Deletion with LSTMs](https://md.research.elamur.ai/free/en/papers/filippova-2015-sentence-compression-deletion-lstms/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Katja Filippova, Enrique Alfonseca, Carlos A. Colmenares, et al.*2015 · 338 citations*
408. [**An Actor-Critic Algorithm for Sequence Prediction arXiv:1607.07086**Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu, et al.*2016 · 335 citations*](https://md.research.elamur.ai/free/en/papers/bahdanau-2016-actor-critic-algorithm-sequence-prediction/)
409. [**Scaling Speech Technology to 1,000+ Languages arXiv:2305.13516**Vineel Pratap, Andros Tjandra, Bowen Shi, et al.*2023 · 334 citations*](https://md.research.elamur.ai/free/en/papers/pratap-2023-scaling-speech-technology-1-000/)
410. **[Frames: a corpus for adding memory to goal-oriented dialogue systems](https://md.research.elamur.ai/free/en/papers/asri-2017-frames-corpus-adding-memory-goal/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Layla El Asri, Hannes Schulz, Shikhar Sharma, et al.*2017 · 333 citations*
411. [**ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2107.02137**Yu Sun, Shuohuan Wang, Shikun Feng, et al.*2021 · 332 citations*](https://md.research.elamur.ai/free/en/papers/sun-2021-ernie-3-0-large/)
412. **[Unsupervised Domain Clusters in Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/aharoni-2020-unsupervised-domain-clusters-pretrained-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Roee Aharoni, Yoav Goldberg*2020 · 330 citations*
413. **[A Graph-to-Sequence Model for AMR-to-Text Generation](https://md.research.elamur.ai/free/en/papers/song-2018-graph-sequence-model-amr-text/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Linfeng Song, Yue Zhang, Zhiguo Wang, et al.*2018 · 330 citations*
414. **[Selective Encoding for Abstractive Sentence Summarization](https://md.research.elamur.ai/free/en/papers/zhou-2017-selective-encoding-abstractive-sentence-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingyu Zhou, Nan Yang, Furu Wei, et al.*2017 · 330 citations*
415. **[Unsupervised Pretraining for Sequence to Sequence Learning](https://md.research.elamur.ai/free/en/papers/ramachandran-2017-unsupervised-pretraining-sequence-sequence-learning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Prajit Ramachandran, Peter Liu, Quoc Le*2017 · 327 citations*
416. **[UTMOS: UTokyo-SaruLab System for VoiceMOS Challenge 2022](https://md.research.elamur.ai/free/en/papers/saeki-2022-utmos-utokyo-sarulab-system-voicemos/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Takaaki Saeki, Detai Xin, Wataru Nakata, et al.*2022 · 324 citations*
417. **[Controlling Output Length in Neural Encoder-Decoders](https://md.research.elamur.ai/free/en/papers/kikuchi-2016-controlling-output-length-neural-encoder/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuta Kikuchi, Graham Neubig, Ryohei Sasano, et al.*2016 · 324 citations*
418. **[When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion](https://md.research.elamur.ai/free/en/papers/voita-2019-when-good-translation-is-wrong/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Elena Voita, Rico Sennrich, Ivan Titov*2019 · 323 citations*
419. [**ALFWorld: Aligning Text and Embodied Environments for Interactive Learning arXiv:2010.03768**Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, et al.*2020 · 322 citations*](https://md.research.elamur.ai/free/en/papers/shridhar-2020-alfworld-aligning-text-embodied-environments/)
420. [**Multi-task Sequence to Sequence Learning arXiv:1511.06114**Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, et al.*2015 · 321 citations*](https://md.research.elamur.ai/free/en/papers/luong-2015-multi-task-sequence-sequence-learning/)
421. [**Document Expansion by Query Prediction arXiv:1904.08375**Rodrigo Nogueira, Wei Yang, Jimmy Lin, et al.*2019 · 320 citations*](https://md.research.elamur.ai/free/en/papers/nogueira-2019-document-expansion-query-prediction/)
422. **[Self-collaboration Code Generation via ChatGPT](https://md.research.elamur.ai/free/en/papers/dong-2023-self-collaboration-code-generation/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Yihong Dong; Xue Jiang; Zhi Jin;, Ge Li*2023 · 319 citations*
423. **[Improving Hypernymy Detection with an Integrated Path-based and Distributional Method](https://md.research.elamur.ai/free/en/papers/shwartz-2016-improving-hypernymy-detection-integrated-path/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vered Shwartz, Yoav Goldberg, Ido Dagan*2016 · 319 citations*
424. **[How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources](https://md.research.elamur.ai/free/en/papers/wang-2023-far-camels-go-exploring-state/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yizhong Wang, Hamish Ivison, Pradeep Dasigi, et al.*2023 · 317 citations*
425. [**MEDITRON-70B: Scaling Medical Pretraining for Large Language Models arXiv:2311.16079**Zeming Chen, Alejandro Hernandez Cano, Angelika Romanou, et al.*2023 · 315 citations*](https://md.research.elamur.ai/free/en/papers/chen-2023-meditron-70b-scaling-medical-pretraining/)
426. [**Flow Straight and Fast: Learning to Generate and Transfer Data with Rectified Flow arXiv:2209.03003**Xingchao Liu, Chengyue Gong, Qiang Liu*2022 · 315 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-flow-straight-fast-learning-generate/)
427. **[Neural Natural Language Inference Models Enhanced with External Knowledge](https://md.research.elamur.ai/free/en/papers/chen-2018-neural-natural-language-inference-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, et al.*2018 · 315 citations*
428. **[Good-Enough Compositional Data Augmentation](https://md.research.elamur.ai/free/en/papers/andreas-2020-good-enough-compositional-data-augmentation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jacob Andreas*2020 · 313 citations*
429. **[A Transformer-based approach to Irony and Sarcasm detection](https://md.research.elamur.ai/free/en/papers/potamias-2019-transformer-based-approach-irony-sarcasm/) [Neural Computing and Applications](https://md.research.elamur.ai/free/en/venues/neural-computing-and-applications/)**Rolandos Alexandros Potamias, Georgios Siolas, Andreas - Georgios Stafylopatis*2019 · 312 citations*
430. **[Multi-hop Reading Comprehension through Question Decomposition and Rescoring](https://md.research.elamur.ai/free/en/papers/min-2019-multi-hop-reading-comprehension-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sewon Min, Victor Zhong, Luke Zettlemoyer, et al.*2019 · 312 citations*
431. [**S2ORC: The Semantic Scholar Open Research Corpus arXiv:1911.02782**Kyle Lo, Lucy Lu Wang, Mark Neumann, et al.*2019 · 312 citations*](https://md.research.elamur.ai/free/en/papers/lo-2019-s2orc-semantic-scholar-open-research/)
432. [**The Dawn of LMMs: Preliminary Explorations with GPT-4V(ision) arXiv:2309.17421**Zhengyuan Yang, Linjie Li, Kevin Lin, et al.*2023 · 311 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-dawn-lmms-preliminary-explorations-gpt/)
433. **[A Minimal Span-Based Neural Constituency Parser](https://md.research.elamur.ai/free/en/papers/stern-2017-minimal-span-based-neural-constituency/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mitchell Stern, Jacob Andreas, Dan Klein*2017 · 311 citations*
434. **[Byte Pair Encoding is Suboptimal for Language Model Pretraining](https://md.research.elamur.ai/free/en/papers/bostrom-2020-byte-pair-encoding-is-suboptimal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaj Bostrom, Greg Durrett*2020 · 310 citations*
435. [**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/)
436. [**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/)
437. **[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*
438. **[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*
439. **[Globally Coherent Text Generation with Neural Checklist Models](https://md.research.elamur.ai/free/en/papers/kiddon-2016-globally-coherent-text-generation-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Chloé Kiddon, Luke Zettlemoyer, Yejin Choi*2016 · 304 citations*
440. [**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/)
441. **[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*
442. **[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*
443. [**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/)
444. **[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*
445. [**InternLM2 Technical Report arXiv:2403.17297**Zheng Cai, Maosong Cao, Haojiong Chen, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-internlm2-technical-report/)
446. [**Challenges and Applications of Large Language Models arXiv:2307.10169**Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.*2023 · 301 citations*](https://md.research.elamur.ai/free/en/papers/kaddour-2023-challenges-applications-large-language-models/)
447. **[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*
448. **[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*
449. **[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*
450. **[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*
451. **[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*
452. [**On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes arXiv:2306.13649**Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.*2023 · 299 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2023-policy-distillation-language-models-learning/)
453. [**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/)
454. **[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*
455. **[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*
456. **[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*
457. **[xLSTM: Extended Long Short-Term Memory](https://md.research.elamur.ai/free/en/papers/beck-2024-xlstm-extended-long-short-term/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Maximilian Beck, Korbinian Pöppel, Markus Spanring, et al.*2024 · 296 citations*
458. **[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*
459. **[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*
460. **[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*
461. **[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*
462. **[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*
463. **[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*
464. **[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*
465. **[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*
466. **[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*
467. [**SPICE: Semantic Propositional Image Caption Evaluation arXiv:1607.08822**Peter Anderson, Basura Fernando, Mark Johnson, et al.*2016 · 289 citations*](https://md.research.elamur.ai/free/en/papers/anderson-2016-spice-semantic-propositional-image-caption/)
468. [**A Review of Large Language Models and Autonomous Agents in Chemistry arXiv:2407.01603**Mayk Caldas Ramos, Christopher J. Collison, Andrew D. White*2024 · 288 citations*](https://md.research.elamur.ai/free/en/papers/ramos-2024-review-large-language-models-autonomous/)
469. **[Two are Better than One: Joint Entity and Relation Extraction with Table-Sequence Encoders](https://md.research.elamur.ai/free/en/papers/wang-2020-two-are-better-than-one/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jue Wang, Wei Lu*2020 · 288 citations*
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473. [**A Hierarchical Neural Autoencoder for Paragraphs and Documents arXiv:1506.01057**Jiwei Li, Minh-Thang Luong, Dan Jurafsky*2015 · 287 citations*](https://md.research.elamur.ai/free/en/papers/li-2015-hierarchical-neural-autoencoder-paragraphs-documents/)
474. [**Llemma: An Open Language Model For Mathematics arXiv:2310.10631**Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.*2023 · 286 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-llemma-open-language-model-mathematics/)
475. [**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/)
476. [**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/)
477. **[BAM! Born-Again Multi-Task Networks for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/clark-2019-bam-born-again-multi-task/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kevin Clark, Minh-Thang Luong, Urvashi Khandelwal, et al.*2019 · 285 citations*
478. [**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/)
479. [**Prometheus: Inducing Fine-grained Evaluation Capability in Language Models arXiv:2310.08491**Seungone Kim, Jamin Shin, Yejin Cho, et al.*2023 · 281 citations*](https://md.research.elamur.ai/free/en/papers/kim-2023-prometheus-inducing-fine-grained-evaluation/)
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481. **[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*
482. [**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/)
483. [**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/)
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485. [**Medusa: Simple LLM Inference Acceleration Framework with Multiple Decoding Heads arXiv:2401.10774**Tianle Cai, Yuhong Li, Zhengyang Geng, et al.*2024 · 278 citations*](https://md.research.elamur.ai/free/en/papers/cai-2024-medusa-simple-llm-inference-acceleration/)
486. **[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*
487. **[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*
488. [**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/)
489. [**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/)
490. **[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*
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