---
title: "Who cites Quoc Viet Le — page 8 — 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 8 of 54 · 701–800; 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 8 of 54 · 701–800 · [← Quoc Viet Le](https://md.research.elamur.ai/free/en/authors/quoc-viet-le/)

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701. **[Large Language Models are Few-Shot Clinical Information Extractors](https://md.research.elamur.ai/free/en/papers/agrawal-2022-large-language-models-few-shot/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Monica Agrawal, Stefan Hegselmann, Hunter Lang, et al.*2022 · 384 citations*
702. **[A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers](https://md.research.elamur.ai/free/en/papers/dasigi-2021-dataset-information-seeking-questions-answers/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Pradeep Dasigi, Kyle Lo, Iz Beltagy, et al.*2021 · 384 citations*
703. [**Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy arXiv:2305.15294**Zhihong Shao, Yeyun Gong, Yelong Shen, et al.*2023 · 383 citations*](https://md.research.elamur.ai/free/en/papers/shao-2023-enhancing-retrieval-augmented-large-language/)
704. **[Tool Learning with Foundation Models](https://md.research.elamur.ai/free/en/papers/qin-2023-tool-learning-foundation-models/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Yujia Qin, Shengding Hu, Yankai Lin, et al.*2023 · 383 citations*
705. **[ViperGPT: Visual Inference via Python Execution for Reasoning](https://md.research.elamur.ai/free/en/papers/suris-2023-vipergpt-visual-inference-python-execution/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Didac Suris, Sachit Menon, Carl Vondrick*2023 · 383 citations*
706. **[FastBERT: a Self-distilling BERT with Adaptive Inference Time](https://md.research.elamur.ai/free/en/papers/liu-2020-fastbert-self-distilling-bert-adaptive/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weijie Liu, Peng Zhou, Zhiruo Wang, et al.*2020 · 383 citations*
707. [**Representation Learning: A Review and New Perspectives arXiv:1206.5538**Yoshua Bengio, Aaron Courville, Pascal Vincent*2012 · 383 citations*](https://md.research.elamur.ai/free/en/papers/bengio-2012-representation-learning-review-new-perspectives/)
708. **[Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity](https://md.research.elamur.ai/free/en/papers/jeong-2024-adaptive-rag-learning-adapt-retrieval/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Soyeong Jeong, Jinheon Baek, Sukmin Cho, et al.*2024 · 382 citations*
709. **[Emerging Cross-lingual Structure in Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/conneau-2020-emerging-cross-lingual-structure-pretrained/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alexis Conneau, Shijie Wu, Haoran Li, et al.*2020 · 382 citations*
710. [**HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data arXiv:2004.07347**Wenhu Chen, Hanwen Zha, Zhiyu Chen, et al.*2020 · 382 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-hybridqa-dataset-multi-hop-question/)
711. **[Many Languages, One Parser](https://md.research.elamur.ai/free/en/papers/ammar-2016-many-languages-one-parser/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Waleed Ammar, George Mulcaire, Miguel Ballesteros, et al.*2016 · 382 citations*
712. **[A Survey on Model Compression for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2024-survey-model-compression-large-language/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Xunyu Zhu, Jian Li, Yong Liu, et al.*2024 · 381 citations*
713. **[VILA: On Pre-training for Visual Language Models](https://md.research.elamur.ai/free/en/papers/lin-2023-vila-pre-training-visual-language/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Ji Lin, Hongxu Yin, Wei Ping, et al.*2023 · 381 citations*
714. **[Language Understanding for Text-based Games Using Deep Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/narasimhan-2015-language-understanding-text-based-games/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Karthik Narasimhan, Tejas Kulkarni, Regina Barzilay*2015 · 380 citations*
715. **[From Paraphrase Database to Compositional Paraphrase Model and Back](https://md.research.elamur.ai/free/en/papers/wieting-2015-paraphrase-database-compositional-paraphrase-model/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**John Wieting, Mohit Bansal, Kevin Gimpel, et al.*2015 · 379 citations*
716. **[Paragraph-level Neural Question Generation with Maxout Pointer and Gated Self-attention Networks](https://md.research.elamur.ai/free/en/papers/zhao-2018-paragraph-level-neural-question-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yao Zhao, Xiaochuan Ni, Yuanyuan Ding, et al.*2018 · 377 citations*
717. **[Multilingual Models for Compositional Distributed Semantics](https://md.research.elamur.ai/free/en/papers/hermann-2014-multilingual-models-compositional-distributed-semantics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Karl Moritz Hermann, Phil Blunsom*2014 · 377 citations*
718. [**A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications arXiv:2402.07927**Pranab Sahoo; Ayush Kumar Singh; Sriparna Saha; Vinija Jain; Samrat Mondal;, Aman Chadha*2024 · 375 citations*](https://md.research.elamur.ai/free/en/papers/sahoo-2024-systematic-survey-prompt-engineering-large/)
719. [**Logic-LM: Empowering Large Language Models with Symbolic Solvers for Faithful Logical Reasoning arXiv:2305.12295**Liangming Pan, Alon Albalak, Xinyi Wang, et al.*2023 · 374 citations*](https://md.research.elamur.ai/free/en/papers/pan-2023-logic-lm-empowering-large-language/)
720. **[What makes a good conversation? How controllable attributes affect human judgments](https://md.research.elamur.ai/free/en/papers/see-2019-what-makes-good-conversation-how/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Abigail See, Stephen Roller, Douwe Kiela, et al.*2019 · 374 citations*
721. **[Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations](https://md.research.elamur.ai/free/en/papers/zhong-2019-knowledge-enriched-transformer-emotion-detection/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Peixiang Zhong, Di Wang, Chunyan Miao*2019 · 373 citations*
722. [**The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery arXiv:2408.06292**Chris Lu, Cong Lu, Robert Tjarko Lange, et al.*2024 · 372 citations*](https://md.research.elamur.ai/free/en/papers/lu-2024-ai-scientist-fully-automated/)
723. [**WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct arXiv:2308.09583**Haipeng Luo, Qingfeng Sun, Can Xu, et al.*2023 · 372 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-wizardmath-empowering-mathematical-reasoning-large/)
724. [**Massively Multilingual Neural Machine Translation arXiv:1903.00089**Roee Aharoni, Melvin Johnson, Orhan Firat*2019 · 372 citations*](https://md.research.elamur.ai/free/en/papers/aharoni-2019-massively-multilingual-neural-machine-translation/)
725. [**PaLI: A Jointly-Scaled Multilingual Language-Image Model arXiv:2209.06794**Xi Chen, Xiao Wang, Soravit Changpinyo, et al.*2022 · 371 citations*](https://md.research.elamur.ai/free/en/papers/chen-2022-pali-jointly-scaled-multilingual-language/)
726. **[Metaphor Detection with Cross-Lingual Model Transfer](https://md.research.elamur.ai/free/en/papers/tsvetkov-2014-metaphor-detection-cross-lingual-model/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yulia Tsvetkov, Leonid Boytsov, Anatole Gershman, et al.*2014 · 371 citations*
727. **[Text2Event: Controllable Sequence-to-Structure Generation for End-to-end Event Extraction](https://md.research.elamur.ai/free/en/papers/lu-2021-text2event-controllable-sequence-structure-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yaojie Lu, Hongyu Lin, Jin Xu, et al.*2021 · 370 citations*
728. [**Training Tips for the Transformer Model arXiv:1804.00247 · The Prague Bulletin of Mathematical Linguistics 110, April 2018, pp. 43-70**Martin Popel, Ondřej Bojar*2018 · 370 citations*](https://md.research.elamur.ai/free/en/papers/popel-2018-training-tips-transformer-model/)
729. [**Taming Throughput-Latency Tradeoff in LLM Inference with Sarathi-Serve OSDI 2024**Amey Agrawal, Nitin Kedia, Ashish Panwar, et al.*2024 · 369 citations*](https://md.research.elamur.ai/free/en/papers/agrawal-2024-taming-throughput-latency-tradeoff-llm/)
730. [**Augmented Language Models: a Survey arXiv:2302.07842**Grégoire Mialon, Roberto Dessì, Maria Lomeli, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/mialon-2023-augmented-language-models-survey/)
731. [**Orca: Progressive Learning from Complex Explanation Traces of GPT-4 arXiv:2306.02707**Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar, et al.*2023 · 369 citations*](https://md.research.elamur.ai/free/en/papers/mukherjee-2023-orca-progressive-learning-complex-explanation/)
732. **[The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics](https://md.research.elamur.ai/free/en/papers/gehrmann-2021-gem-benchmark-natural-language-generation/) [Workshop on Generation, Evaluation and Metrics (GEM)](https://md.research.elamur.ai/free/en/venues/gem/)**Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal, et al.*2021 · 369 citations*
733. **[An Analysis of Encoder Representations in Transformer-Based Machine Translation](https://md.research.elamur.ai/free/en/papers/raganato-2018-analysis-encoder-representations-transformer-based/) [EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP](https://md.research.elamur.ai/free/en/venues/emnlp-workshop-blackboxnlp-analyzing-and-interpreting-neural-networks-for-nlp/)**Alessandro Raganato, Jörg Tiedemann*2018 · 369 citations*
734. **[Improving the Transformer Translation Model with Document-Level Context](https://md.research.elamur.ai/free/en/papers/zhang-2018-improving-transformer-translation-model-document/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiacheng Zhang, Huanbo Luan, Maosong Sun, et al.*2018 · 369 citations*
735. [**Revisiting Few-sample BERT Fine-tuning arXiv:2006.05987**Tianyi Zhang, Felix Wu, Arzoo Katiyar, et al.*2020 · 368 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2020-revisiting-few-sample-bert-fine/)
736. **[Combining Language and Vision with a Multimodal Skip-gram Model](https://md.research.elamur.ai/free/en/papers/lazaridou-2015-combining-language-vision-multimodal-skip/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Angeliki Lazaridou, Nghia The Pham, Marco Baroni*2015 · 368 citations*
737. **[A Survey on Large Language Models for Code Generation](https://md.research.elamur.ai/free/en/papers/jiang-2024-survey-large-language-models-code/) [ACM Transactions on Software Engineering and Methodology](https://md.research.elamur.ai/free/en/venues/acm-transactions-on-software-engineering-and-methodology/)**Juyong Jiang, Fan Wang, Jiasi Shen, et al.*2024 · 367 citations*
738. **[Parameter-Efficient Transfer Learning with Diff Pruning](https://md.research.elamur.ai/free/en/papers/guo-2021-parameter-efficient-transfer-learning-diff/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Demi Guo, Alexander Rush, Yoon Kim*2021 · 367 citations*
739. **[Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor](https://md.research.elamur.ai/free/en/papers/honovich-2023-unnatural-instructions-tuning-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Or Honovich, Thomas Scialom, Omer Levy, et al.*2023 · 366 citations*
740. [**Large Language Models Struggle to Learn Long-Tail Knowledge arXiv:2211.08411**Nikhil Kandpal, Haikang Deng, Adam Roberts, et al.*2022 · 366 citations*](https://md.research.elamur.ai/free/en/papers/kandpal-2022-large-language-models-struggle-learn/)
741. **[VideoChat: Chat-Centric Video Understanding](https://md.research.elamur.ai/free/en/papers/li-2023-videochat-chat-centric-video-understanding/) [Science China Information Sciences](https://md.research.elamur.ai/free/en/venues/science-china-information-sciences/)**KunChang Li, Yinan He, Yi Wang, et al.*2023 · 365 citations*
742. **[The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English](https://md.research.elamur.ai/free/en/papers/guzman-2019-flores-evaluation-datasets-low-resource/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Francisco Guzmán, Peng-Jen Chen, Myle Ott, et al.*2019 · 365 citations*
743. [**How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks**Divyansh Kaushik, Zachary C. Lipton*2018 · 364 citations*](https://md.research.elamur.ai/free/en/papers/kaushik-2018-how-much-reading-does-reading/)
744. [**Improving alignment of dialogue agents via targeted human judgements arXiv:2209.14375**Amelia Glaese, Nat McAleese, Maja Trębacz, et al.*2022 · 362 citations*](https://md.research.elamur.ai/free/en/papers/glaese-2022-improving-alignment-dialogue-agents-targeted/)
745. **[Adversarial Training for Unsupervised Bilingual Lexicon Induction](https://md.research.elamur.ai/free/en/papers/zhang-2017-adversarial-training-unsupervised-bilingual-lexicon/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Meng Zhang, Yang Liu, Huanbo Luan, et al.*2017 · 362 citations*
746. **[Synthetic QA Corpora Generation with Roundtrip Consistency](https://md.research.elamur.ai/free/en/papers/alberti-2019-synthetic-qa-corpora-generation-roundtrip/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chris Alberti, Daniel Andor, Emily Pitler, et al.*2019 · 361 citations*
747. **[Universal Neural Machine Translation for Extremely Low Resource Languages](https://md.research.elamur.ai/free/en/papers/gu-2018-universal-neural-machine-translation-extremely/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jiatao Gu, Hany Hassan, Jacob Devlin, et al.*2018 · 361 citations*
748. **[BRIO: Bringing Order to Abstractive Summarization](https://md.research.elamur.ai/free/en/papers/liu-2022-brio-bringing-order-abstractive-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Liu, Pengfei Liu, Dragomir Radev, et al.*2022 · 360 citations*
749. [**ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate arXiv:2308.07201**Chi-Min Chan, Weize Chen, Yusheng Su, et al.*2023 · 359 citations*](https://md.research.elamur.ai/free/en/papers/chan-2023-chateval-better-llm-based/)
750. **[RARR: Researching and Revising What Language Models Say, Using Language Models](https://md.research.elamur.ai/free/en/papers/gao-2023-rarr-researching-revising-what-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Luyu Gao, Zhuyun Dai, Panupong Pasupat, et al.*2023 · 359 citations*
751. **[XGLUE: A New Benchmark Dataset for Cross-lingual Pre-training, Understanding and Generation](https://md.research.elamur.ai/free/en/papers/liang-2020-xglue-new-benchmark-dataset-cross/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yaobo Liang, Nan Duan, Yeyun Gong, et al.*2020 · 358 citations*
752. **[Multilingual Constituency Parsing with Self-Attention and Pre-Training](https://md.research.elamur.ai/free/en/papers/kitaev-2019-multilingual-constituency-parsing-self-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nikita Kitaev, Steven Cao, Dan Klein*2019 · 358 citations*
753. [**Mind the GAP: A Balanced Corpus of Gendered Ambiguous Pronouns**Kellie Webster, Marta Recasens, Vera Axelrod, et al.*2018 · 358 citations*](https://md.research.elamur.ai/free/en/papers/webster-2018-mind-gap-balanced-corpus-gendered/)
754. **[Zero-Resource Translation with Multi-Lingual Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/firat-2016-zero-resource-translation-multi-lingual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Orhan Firat, Baskaran Sankaran, Yaser Al-onaizan, et al.*2016 · 356 citations*
755. **[SnapKV: LLM Knows What You are Looking for Before Generation](https://md.research.elamur.ai/free/en/papers/li-2024-snapkv-llm-knows-looking-before/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Yuhong Li, Yingbing Huang, Bowen Yang, et al.*2024 · 355 citations*
756. [**Fine-tuning Aligned Language Models Compromises Safety, Even When Users Do Not Intend To! arXiv:2310.03693**Xiangyu Qi, Yi Zeng, Tinghao Xie, et al.*2023 · 355 citations*](https://md.research.elamur.ai/free/en/papers/qi-2023-fine-tuning-aligned-language-models/)
757. [**Solving math word problems with process- and outcome-based feedback arXiv:2211.14275**Jonathan Uesato, Nate Kushman, Ramana Kumar, et al.*2022 · 355 citations*](https://md.research.elamur.ai/free/en/papers/uesato-2022-solving-math-word-problems-process/)
758. **[Towards Mitigating LLM Hallucination via Self Reflection](https://md.research.elamur.ai/free/en/papers/ji-2023-mitigating-llm-hallucination-self-reflection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ziwei Ji, Tiezheng Yu, Yan Xu, et al.*2023 · 354 citations*
759. **[Internet-Augmented Dialogue Generation](https://md.research.elamur.ai/free/en/papers/komeili-2022-internet-augmented-dialogue-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Mojtaba Komeili, Kurt Shuster, Jason Weston*2022 · 354 citations*
760. **[Faithful Chain-of-Thought Reasoning](https://md.research.elamur.ai/free/en/papers/lyu-2023-faithful-chain-thought-reasoning/) [International Joint Conference on Natural Language Processing (IJCNLP)](https://md.research.elamur.ai/free/en/venues/ijcnlp/)**Qing Lyu, Shreya Havaldar, Adam Stein, et al.*2023 · 353 citations*
761. **[Simultaneously Self-Attending to All Mentions for Full-Abstract Biological Relation Extraction](https://md.research.elamur.ai/free/en/papers/verga-2018-simultaneously-self-attending-all-mentions/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Patrick Verga, Emma Strubell, Andrew McCallum*2018 · 353 citations*
762. **[Exploring Neural Text Simplification Models](https://md.research.elamur.ai/free/en/papers/nisioi-2017-exploring-neural-text-simplification-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sergiu Nisioi, Sanja Štajner, Simone Paolo Ponzetto, et al.*2017 · 353 citations*
763. **[What to talk about and how? Selective Generation using LSTMs with Coarse-to-Fine Alignment](https://md.research.elamur.ai/free/en/papers/mei-2016-what-talk-about-how-selective/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Hongyuan Mei, Mohit Bansal, Matthew R. Walter*2016 · 353 citations*
764. [**TinyLlama: An Open-Source Small Language Model arXiv:2401.02385**Peiyuan Zhang, Guangtao Zeng, Tianduo Wang, et al.*2024 · 352 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-tinyllama-open-source-small-language/)
765. **[Do NLP Models Know Numbers? Probing Numeracy in Embeddings](https://md.research.elamur.ai/free/en/papers/wallace-2019-do-nlp-models-know-numbers/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eric Wallace, Yizhong Wang, Sujian Li, et al.*2019 · 352 citations*
766. **[An Interactive Multi-Task Learning Network for End-to-End Aspect-Based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/he-2019-interactive-multi-task-learning-network/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruidan He, Wee Sun Lee, Hwee Tou Ng, et al.*2019 · 351 citations*
767. [**Reformulating Unsupervised Style Transfer as Paraphrase Generation**Kalpesh Krishna, John Wieting, Mohit Iyyer*2020 · 350 citations*](https://md.research.elamur.ai/free/en/papers/krishna-2020-reformulating-unsupervised-style-transfer-as/)
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775. **[Visual Programming: Compositional visual reasoning without training](https://md.research.elamur.ai/free/en/papers/gupta-2022-visual-programming-compositional-visual-reasoning/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Tanmay Gupta, Aniruddha Kembhavi*2022 · 347 citations*
776. **[Directed Acyclic Graph Network for Conversational Emotion Recognition](https://md.research.elamur.ai/free/en/papers/shen-2021-directed-acyclic-graph-network-conversational/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weizhou Shen, Siyue Wu, Yunyi Yang, et al.*2021 · 346 citations*
777. **[Representation Learning for Text-level Discourse Parsing](https://md.research.elamur.ai/free/en/papers/ji-2014-representation-learning-text-level-discourse/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yangfeng Ji, Jacob Eisenstein*2014 · 346 citations*
778. [**Complexity-Based Prompting for Multi-Step Reasoning arXiv:2210.00720**Yao Fu, Hao Peng, Ashish Sabharwal, et al.*2022 · 345 citations*](https://md.research.elamur.ai/free/en/papers/fu-2022-complexity-based-prompting-multi-step/)
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780. [**MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities arXiv:2308.02490**Weihao Yu, Zhengyuan Yang, Linjie Li, et al.*2023 · 344 citations*](https://md.research.elamur.ai/free/en/papers/yu-2023-mm-vet-evaluating-large-multimodal/)
781. **[Teaching Small Language Models to Reason](https://md.research.elamur.ai/free/en/papers/magister-2023-teaching-small-language-models-reason/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lucie Charlotte Magister, Jonathan Mallinson, Jakub Adamek, et al.*2023 · 343 citations*
782. **[Generating Natural Questions About an Image](https://md.research.elamur.ai/free/en/papers/mostafazadeh-2016-generating-natural-questions-about-image/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nasrin Mostafazadeh, Ishan Misra, Jacob Devlin, et al.*2016 · 343 citations*
783. **[Are Emergent Abilities of Large Language Models a Mirage?](https://md.research.elamur.ai/free/en/papers/schaeffer-2023-emergent-abilities-large-language-models/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Rylan Schaeffer, Brando Miranda, Sanmi Koyejo*2023 · 342 citations*
784. [**DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models arXiv:2512.02556**DeepSeek-AI, Aixin Liu, Aoxue Mei, et al.*2025 · 341 citations*](https://md.research.elamur.ai/free/en/papers/deepseek-ai-2025-deepseek-v3-2-pushing/)
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786. [**WARP: Word-level Adversarial ReProgramming arXiv:2101.00121**Karen Hambardzumyan, Hrant Khachatrian, Jonathan May*2021 · 340 citations*](https://md.research.elamur.ai/free/en/papers/hambardzumyan-2021-warp-word-level-adversarial-reprogramming/)
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790. **[LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models](https://md.research.elamur.ai/free/en/papers/jiang-2023-llmlingua-compressing-prompts-accelerated-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, et al.*2023 · 338 citations*
791. **[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*
792. **[Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT](https://md.research.elamur.ai/free/en/papers/smit-2020-combining-automatic-labelers-expert-annotations/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Akshay Smit, Saahil Jain, Pranav Rajpurkar, et al.*2020 · 338 citations*
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