---
title: "Who cites Quoc Viet Le — page 9 — 30,072 papers of our library"
description: "30,072 papers of the Elamur Research library cite the works of Quoc Viet Le, found in their bibliographies · page 9 of 54 · 801–900; the most…"
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---
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# Who cites Quoc Viet Le

47,619 citations of their works from 30,072 papers of our library (of the 149,439 whose bibliographies we read) · 5,372 with a page here, the most cited first · page 9 of 54 · 801–900 · [← Quoc Viet Le](https://md.research.elamur.ai/free/en/authors/quoc-viet-le/)

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801. [**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/)
802. [**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/)
803. **[DREAM: A Challenge Data Set and Models for Dialogue-Based Reading Comprehension](https://md.research.elamur.ai/free/en/papers/sun-2019-dream-challenge-data-set-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Kai Sun, Dian Yu, Jianshu Chen, et al.*2019 · 334 citations*
804. [**Generating Wikipedia by Summarizing Long Sequences arXiv:1801.10198**Peter J. Liu, Mohammad Saleh, Etienne Pot, et al.*2018 · 334 citations*](https://md.research.elamur.ai/free/en/papers/liu-2018-generating-wikipedia-summarizing-long-sequences/)
805. [**LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention arXiv:2303.16199**Renrui Zhang, Jiaming Han, Chris Liu, et al.*2023 · 333 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-llama-adapter-efficient-fine-tuning/)
806. [**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/)
807. [**GraphCodeBERT: Pre-training Code Representations with Data Flow arXiv:2009.08366**Daya Guo, Shuo Ren, Shuai Lu, et al.*2021 · 332 citations*](https://md.research.elamur.ai/free/en/papers/guo-2021-graphcodebert-pre-training-code-representations/)
808. [**The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence arXiv:2002.06177**Gary Marcus*2020 · 332 citations*](https://md.research.elamur.ai/free/en/papers/marcus-2020-next-decade-ai-four/)
809. [**HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal arXiv:2402.04249**Mantas Mazeika, Long Phan, Xuwang Yin, et al.*2024 · 330 citations*](https://md.research.elamur.ai/free/en/papers/mazeika-2024-harmbench-standardized-evaluation-framework-automated/)
810. **[Language Is Not All You Need: Aligning Perception with Language Models](https://md.research.elamur.ai/free/en/papers/huang-2023-language-all-need-aligning-perception/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Shaohan Huang, Li Dong, Wenhui Wang, et al.*2023 · 330 citations*
811. **[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*
812. **[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*
813. **[Search-based Neural Structured Learning for Sequential Question Answering](https://md.research.elamur.ai/free/en/papers/iyyer-2017-search-based-neural-structured-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mohit Iyyer, Wen-tau Yih, Ming-Wei Chang*2017 · 330 citations*
814. **[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*
815. **[Massively Multilingual Transfer for NER](https://md.research.elamur.ai/free/en/papers/rahimi-2019-massively-multilingual-transfer-ner/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Afshin Rahimi, Yuan Li, Trevor Cohn*2019 · 329 citations*
816. [**A Neural Network Approach to Context-Sensitive Generation of Conversational Responses arXiv:1506.06714**Alessandro Sordoni, Michel Galley, Michael Auli, et al.*2015 · 329 citations*](https://md.research.elamur.ai/free/en/papers/sordoni-2015-neural-network-approach-context-sensitive/)
817. [**Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models arXiv:2303.04671**Chenfei Wu, Shengming Yin, Weizhen Qi, et al.*2023 · 328 citations*](https://md.research.elamur.ai/free/en/papers/wu-2023-visual-chatgpt-talking-drawing-editing/)
818. [**Discovering Language Model Behaviors with Model-Written Evaluations arXiv:2212.09251**Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.*2022 · 328 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-discovering-language-model-behaviors-model/)
819. **[Unsupervised Corpus Aware Language Model Pre-training for Dense Passage Retrieval](https://md.research.elamur.ai/free/en/papers/gao-2022-unsupervised-corpus-aware-language-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luyu Gao, Jamie Callan*2022 · 328 citations*
820. **[Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/lu-2023-chameleon-plug-play-compositional-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Pan Lu, Baolin Peng, Hao Cheng, et al.*2023 · 327 citations*
821. **[Faith and Fate: Limits of Transformers on Compositionality](https://md.research.elamur.ai/free/en/papers/dziri-2023-faith-fate-limits-transformers-compositionality/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Nouha Dziri, Ximing Lu, Melanie Sclar, et al.*2023 · 327 citations*
822. **[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*
823. [**CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing arXiv:2305.11738**Zhibin Gou, Zhihong Shao, Yeyun Gong, et al.*2023 · 326 citations*](https://md.research.elamur.ai/free/en/papers/gou-2023-critic-large-language-models-self/)
824. **[Robust Neural Machine Translation with Doubly Adversarial Inputs](https://md.research.elamur.ai/free/en/papers/cheng-2019-robust-neural-machine-translation-doubly/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yong Cheng, Lu Jiang, Wolfgang Macherey*2019 · 325 citations*
825. **[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*
826. [**Text and Code Embeddings by Contrastive Pre-Training arXiv:2201.10005**Arvind Neelakantan, Tao Xu, Raul Puri, et al.*2022 · 323 citations*](https://md.research.elamur.ai/free/en/papers/neelakantan-2022-text-code-embeddings-contrastive-pre/)
827. [**Carbon Emissions and Large Neural Network Training arXiv:2104.10350**David Patterson, Joseph Gonzalez, Quoc Le, et al.*2021 · 323 citations*](https://md.research.elamur.ai/free/en/papers/patterson-2021-carbon-emissions-large-neural-network/)
828. [**Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning arXiv:2503.09516**Bowen Jin, Hansi Zeng, Zhenrui Yue, et al.*2025 · 322 citations*](https://md.research.elamur.ai/free/en/papers/jin-2025-search-r1-training-llms-reason/)
829. **[LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion](https://md.research.elamur.ai/free/en/papers/jiang-2023-llm-blender-ensembling-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dongfu Jiang, Xiang Ren, Bill Yuchen Lin*2023 · 321 citations*
830. **[Attaining the Unattainable? Reassessing Claims of Human Parity in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/toral-2018-attaining-unattainable-reassessing-claims-human/) [Conference on Machine Translation: Research Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-research-papers/)**Antonio Toral, Sheila Castilho, Ke Hu, et al.*2018 · 321 citations*
831. **[Paraphrasing Revisited with Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/mallinson-2017-paraphrasing-revisited-neural-machine-translation/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jonathan Mallinson, Rico Sennrich, Mirella Lapata*2017 · 321 citations*
832. [**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/)
833. **[MM-LLMs: Recent Advances in MultiModal Large Language Models](https://md.research.elamur.ai/free/en/papers/zhang-2024-mm-llms-recent-advances-multimodal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Duzhen Zhang, Yahan Yu, Jiahua Dong, et al.*2024 · 320 citations*
834. **[How many data points is a prompt worth?](https://md.research.elamur.ai/free/en/papers/scao-2021-how-many-data-points-is/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Teven Le Scao, Alexander Rush*2021 · 320 citations*
835. **[Probing Pretrained Language Models for Lexical Semantics](https://md.research.elamur.ai/free/en/papers/vulic-2020-probing-pretrained-language-models-lexical/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ivan Vulić, Edoardo Maria Ponti, Robert Litschko, et al.*2020 · 320 citations*
836. **[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*
837. **[Decoding with Large-Scale Neural Language Models Improves Translation](https://md.research.elamur.ai/free/en/papers/vaswani-2013-decoding-large-scale-neural-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ashish Vaswani, Yinggong Zhao, Victoria Fossum, et al.*2013 · 318 citations*
838. **[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*
839. [**WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation arXiv:2201.05955**Alisa Liu, Swabha Swayamdipta, Noah A. Smith, et al.*2022 · 317 citations*](https://md.research.elamur.ai/free/en/papers/liu-2022-wanli-worker-ai-collaboration-natural/)
840. **[Choosing Transfer Languages for Cross-Lingual Learning](https://md.research.elamur.ai/free/en/papers/lin-2019-choosing-transfer-languages-cross-lingual/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, et al.*2019 · 317 citations*
841. **[An Empirical Comparison of Domain Adaptation Methods for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chu-2017-empirical-comparison-domain-adaptation-methods/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chenhui Chu, Raj Dabre, Sadao Kurohashi*2017 · 317 citations*
842. [**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/)
843. [**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/)
844. **[WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning](https://md.research.elamur.ai/free/en/papers/srinivasan-2021-wit-wikipedia-based-image-text/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Krishna Srinivasan, Karthik Raman, Jiecao Chen, et al.*2021 · 315 citations*
845. **[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*
846. **[On the Practical Computational Power of Finite Precision RNNs for Language Recognition](https://md.research.elamur.ai/free/en/papers/weiss-2018-practical-computational-power-finite-precision/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gail Weiss, Yoav Goldberg, Eran Yahav*2018 · 313 citations*
847. [**Hallucination is Inevitable: An Innate Limitation of Large Language Models arXiv:2401.11817**Ziwei Xu, Sanjay Jain, Mohan Kankanhalli*2024 · 312 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-hallucination-inevitable-innate-limitation-large/)
848. **[The Power of Noise: Redefining Retrieval for RAG Systems](https://md.research.elamur.ai/free/en/papers/cuconasu-2024-power-noise-redefining-retrieval-rag/) [International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR)](https://md.research.elamur.ai/free/en/venues/international-acm-sigir-conference-on-research-and-development-in-information/)**Florin Cuconasu, Giovanni Trappolini, Federico Siciliano, et al.*2024 · 312 citations*
849. **[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*
850. [**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/)
851. [**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/)
852. **[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*
853. [**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/)
854. [**Multimodal Chain-of-Thought Reasoning in Language Models arXiv:2302.00923**Zhuosheng Zhang, Aston Zhang, Mu Li, et al.*2023 · 308 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-multimodal-chain-thought-reasoning-language/)
855. **[UNIMO: Towards Unified-Modal Understanding and Generation via Cross-Modal Contrastive Learning](https://md.research.elamur.ai/free/en/papers/li-2021-unimo-unified-modal-understanding-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wei Li, Can Gao, Guocheng Niu, et al.*2021 · 308 citations*
856. **[A Survey of Domain Adaptation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/chu-2018-survey-domain-adaptation-neural-machine/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Chenhui Chu, Rui Wang*2018 · 308 citations*
857. [**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/)
858. **[Identifying beneficial task relations for multi-task learning in deep neural networks](https://md.research.elamur.ai/free/en/papers/bingel-2017-identifying-beneficial-task-relations-multi/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Joachim Bingel, Anders Søgaard*2017 · 308 citations*
859. **[Samanantar: The Largest Publicly Available Parallel Corpora Collection for 11 Indic Languages](https://md.research.elamur.ai/free/en/papers/ramesh-2022-samanantar-largest-publicly-available-parallel/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Gowtham Ramesh, Sumanth Doddapaneni, Aravinth Bheemaraj, et al.*2022 · 307 citations*
860. **[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*
861. **[AugGPT: Leveraging ChatGPT for Text Data Augmentation](https://md.research.elamur.ai/free/en/papers/dai-2023-auggpt-leveraging-chatgpt-text-data/) [IEEE Transactions on Big Data](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-big-data/)**Haixing Dai; Zhengliang Liu; Wenxiong Liao; Xiaoke Huang; Yihan Cao; Zihao Wu; Lin Zhao; Shaochen Xu; Wei Liu; Ninghao Liu; Sheng Li; Dajiang Zhu; Hongmin Cai; Lichao Sun; Quanzheng Li; Dinggang Shen; Tianming Liu;, Xiang Li*2023 · 306 citations*
862. **[OCRBench: On the Hidden Mystery of OCR in Large Multimodal Models](https://md.research.elamur.ai/free/en/papers/liu-2023-ocrbench-hidden-mystery-ocr-large/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**Yuliang Liu, Zhang Li, Mingxin Huang, et al.*2023 · 306 citations*
863. **[SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer](https://md.research.elamur.ai/free/en/papers/vu-2022-spot-better-frozen-model-adaptation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tu Vu, Brian Lester, Noah Constant, et al.*2022 · 306 citations*
864. **[Nested Named Entity Recognition Revisited](https://md.research.elamur.ai/free/en/papers/katiyar-2018-nested-named-entity-recognition-revisited/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Arzoo Katiyar, Claire Cardie*2018 · 306 citations*
865. [**Chain-of-Verification Reduces Hallucination in Large Language Models arXiv:2309.11495**Shehzaad Dhuliawala, Mojtaba Komeili, Jing Xu, et al.*2023 · 305 citations*](https://md.research.elamur.ai/free/en/papers/dhuliawala-2023-chain-verification-reduces-hallucination-large/)
866. [**PromptRobust: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts arXiv:2306.04528**Kaijie Zhu, Jindong Wang, Jiaheng Zhou, et al.*2023 · 305 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2023-promptrobust-towards-evaluating-robustness-large/)
867. [**CoNLL-SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection in 52 Languages CoNLL-SIGMORPHON 2017 Shared Task**Ryan, Cotterell*2017 · 305 citations*](https://md.research.elamur.ai/free/en/papers/cotterell-2017-sigmorphon-reinflection-52/)
868. **[Large Language Models are Better Reasoners with Self-Verification](https://md.research.elamur.ai/free/en/papers/weng-2023-large-language-models-are-better/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yixuan Weng, Minjun Zhu, Fei Xia, et al.*2023 · 304 citations*
869. **[Multi-step Jailbreaking Privacy Attacks on ChatGPT](https://md.research.elamur.ai/free/en/papers/li-2023-multi-step-jailbreaking-privacy-attacks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Haoran Li, Dadi Guo, Wei Fan, et al.*2023 · 304 citations*
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871. **[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*
872. **[Character-LLM: A Trainable Agent for Role-Playing](https://md.research.elamur.ai/free/en/papers/shao-2023-character-llm-trainable-agent-role/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yunfan Shao, Linyang Li, Junqi Dai, et al.*2023 · 303 citations*
873. **[Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering](https://md.research.elamur.ai/free/en/papers/wang-2019-multi-passage-bert-globally-normalized/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhiguo Wang, Patrick Ng, Xiaofei Ma, et al.*2019 · 303 citations*
874. **[Learning to Write with Cooperative Discriminators](https://md.research.elamur.ai/free/en/papers/holtzman-2018-learning-write-cooperative-discriminators/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ari Holtzman, Jan Buys, Maxwell Forbes, et al.*2018 · 303 citations*
875. [**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/)
876. **[Unpaired Sentiment-to-Sentiment Translation: A Cycled Reinforcement Learning Approach](https://md.research.elamur.ai/free/en/papers/xu-2018-unpaired-sentiment-sentiment-translation-cycled/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jingjing Xu, Xu Sun, Qi Zeng, et al.*2018 · 303 citations*
877. **[Evaluating Verifiability in Generative Search Engines](https://md.research.elamur.ai/free/en/papers/liu-2023-evaluating-verifiability-generative-search-engines/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Nelson Liu, Tianyi Zhang, Percy Liang*2023 · 302 citations*
878. [**Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language arXiv:2204.00598**Andy Zeng, Maria Attarian, Brian Ichter, et al.*2022 · 302 citations*](https://md.research.elamur.ai/free/en/papers/zeng-2022-socratic-models-composing-zero-shot/)
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880. **[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*
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882. [**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/)
883. [**Retrieval-Augmented Generation for AI-Generated Content: A Survey arXiv:2402.19473**Penghao Zhao, Hailin Zhang, Qinhan Yu, et al.*2024 · 301 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2024-retrieval-augmented-generation-ai-generated/)
884. [**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/)
885. **[Canine: Pre-training an Efficient Tokenization-Free Encoder for Language Representation](https://md.research.elamur.ai/free/en/papers/clark-2022-canine-pre-training-efficient-tokenization/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jonathan H. Clark, Dan Garrette, Iulia Turc, et al.*2022 · 301 citations*
886. **[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*
887. **[Style Transformer: Unpaired Text Style Transfer without Disentangled Latent Representation](https://md.research.elamur.ai/free/en/papers/dai-2019-style-transformer-unpaired-text-style/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ning Dai, Jianze Liang, Xipeng Qiu, et al.*2019 · 301 citations*
888. **[Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting](https://md.research.elamur.ai/free/en/papers/qin-2024-large-language-models-are-effective/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhen Qin, Rolf Jagerman, Kai Hui, et al.*2024 · 300 citations*
889. **[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*
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891. **[Bridging the Gap between Training and Inference for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/zhang-2019-bridging-gap-between-training-inference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wen Zhang, Yang Feng, Fandong Meng, et al.*2019 · 299 citations*
892. [**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/)
893. **[Entity-Based Knowledge Conflicts in Question Answering](https://md.research.elamur.ai/free/en/papers/longpre-2021-entity-based-knowledge-conflicts-question/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shayne Longpre, Kartik Perisetla, Anthony Chen, et al.*2021 · 298 citations*
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