---
title: "Who cites Jian Zhang — page 4 — 3,396 papers of our library"
description: "3,396 papers of the Elamur Research library cite the works of Jian Zhang, found in their bibliographies · page 4 of 5 · 301–400; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/jian-zhang/cited-by/page/4/"
---
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# Who cites Jian Zhang

3,401 citations of their works from 3,396 papers of our library (of the 141,840 whose bibliographies we read) · 447 with a page here, the most cited first · page 4 of 5 · 301–400 · [← Jian Zhang](https://md.research.elamur.ai/free/en/authors/jian-zhang/)

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301. **[SCROLLS: Standardized CompaRison Over Long Language Sequences](https://md.research.elamur.ai/free/en/papers/shaham-2022-scrolls-standardized-comparison-over-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Uri Shaham, Elad Segal, Maor Ivgi, et al.*2022 · 162 citations*
302. [**A Span-Extraction Dataset for Chinese Machine Reading Comprehension arXiv:1810.07366 · EMNLP 2019 5886-5891**Yiming Cui, Ting Liu, Wanxiang Che, et al.*2018 · 158 citations*](https://md.research.elamur.ai/free/en/papers/cui-2018-span-extraction-dataset-chinese/)
303. **[DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 156 citations*
304. **[doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset](https://md.research.elamur.ai/free/en/papers/feng-2020-doc2dial-goal-oriented-document-grounded/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Song Feng, Hui Wan, Chulaka Gunasekara, et al.*2020 · 152 citations*
305. **[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 · 152 citations*
306. **[INFOTABS: Inference on Tables as Semi-structured Data](https://md.research.elamur.ai/free/en/papers/gupta-2020-infotabs-inference-tables-as-semi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Vivek Gupta, Maitrey Mehta, Pegah Nokhiz, et al.*2020 · 150 citations*
307. [**TORQUE: A Reading Comprehension Dataset of Temporal Ordering Questions**Qiang Ning, Hao Wu, Rujun Han, et al.*2020 · 150 citations*](https://md.research.elamur.ai/free/en/papers/ning-2020-torque-reading-comprehension-dataset-temporal/)
308. **[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*
309. **[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 · 149 citations*
310. **[MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse Languages](https://md.research.elamur.ai/free/en/papers/zhang-2023-miracl-multilingual-retrieval-dataset-covering/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo, et al.*2023 · 148 citations*
311. **[Towards Question-Answering as an Automatic Metric for Evaluating the Content Quality of a Summary](https://md.research.elamur.ai/free/en/papers/deutsch-2021-question-answering-as-automatic-metric/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Daniel Deutsch, Tania Bedrax-Weiss, Dan Roth*2021 · 148 citations*
312. **[Fast, Effective, and Self-Supervised: Transforming Masked Language Models into Universal Lexical and Sentence Encoders](https://md.research.elamur.ai/free/en/papers/liu-2021-fast-effective-self-supervised-transforming/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Fangyu Liu, Ivan Vulić, Anna Korhonen, et al.*2021 · 147 citations*
313. [**Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature arXiv:2310.05130**Guangsheng Bao, Yanbin Zhao, Zhiyang Teng, et al.*2023 · 146 citations*](https://md.research.elamur.ai/free/en/papers/bao-2023-fast-detectgpt-efficient-zero-shot/)
314. **[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 · 146 citations*
315. **[Understanding Dataset Design Choices for Multi-hop Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2019-understanding-dataset-design-choices-multi/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jifan Chen, Greg Durrett*2019 · 146 citations*
316. **[Evaluating Correctness and Faithfulness of Instruction-Following Models for Question Answering](https://md.research.elamur.ai/free/en/papers/adlakha-2024-evaluating-correctness-faithfulness-instruction-following/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vaibhav Adlakha, Parishad BehnamGhader, Xing Han Lu, et al.*2024 · 145 citations*
317. **[Context-faithful Prompting for Large Language Models](https://md.research.elamur.ai/free/en/papers/zhou-2023-context-faithful-prompting-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenxuan Zhou, Sheng Zhang, Hoifung Poon, et al.*2023 · 145 citations*
318. **[UNQOVERing Stereotyping Biases via Underspecified Questions](https://md.research.elamur.ai/free/en/papers/li-2020-unqovering-stereotyping-biases-underspecified-questions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tao Li, Daniel Khashabi, Tushar Khot, et al.*2020 · 145 citations*
319. [**Executable Code Actions Elicit Better LLM Agents arXiv:2402.01030**Xingyao Wang, Yangyi Chen, Lifan Yuan, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-executable-code-actions-elicit-better/)
320. **[TopiOCQA: Open-domain Conversational Question Answering with Topic Switching](https://md.research.elamur.ai/free/en/papers/adlakha-2022-topiocqa-open-domain-conversational-question/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Vaibhav Adlakha, Shehzaad Dhuliawala, Kaheer Suleman, et al.*2022 · 143 citations*
321. **[Dense X Retrieval: What Retrieval Granularity Should We Use?](https://md.research.elamur.ai/free/en/papers/chen-2024-dense-x-retrieval-what-retrieval/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tong Chen, Hongwei Wang, Sihao Chen, et al.*2024 · 142 citations*
322. [**Rethinking embedding coupling in pre-trained language models arXiv:2010.12821**Hyung Won Chung, Thibault Févry, Henry Tsai, et al.*2020 · 142 citations*](https://md.research.elamur.ai/free/en/papers/chung-2020-rethinking-embedding-coupling-pre-trained/)
323. **[Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance?](https://md.research.elamur.ai/free/en/papers/ravichander-2021-probing-probing-paradigm-does-probing/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Abhilasha Ravichander, Yonatan Belinkov, Eduard Hovy*2021 · 141 citations*
324. **[Molweni: A Challenge Multiparty Dialogues-based Machine Reading Comprehension Dataset with Discourse Structure](https://md.research.elamur.ai/free/en/papers/li-2020-molweni-challenge-multiparty-dialogues-based/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Jiaqi Li, Ming Liu, Min-Yen Kan, et al.*2020 · 141 citations*
325. **[TURINGBENCH: A Benchmark Environment for Turing Test in the Age of Neural Text Generation](https://md.research.elamur.ai/free/en/papers/uchendu-2021-turingbench-benchmark-environment-turing-test/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Adaku Uchendu, Zeyu Ma, Thai Le, et al.*2021 · 140 citations*
326. **[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 · 140 citations*
327. **[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*
328. **[Inoculation by Fine-Tuning: A Method for Analyzing Challenge Datasets](https://md.research.elamur.ai/free/en/papers/liu-2019-inoculation-fine-tuning-method-analyzing/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nelson F. Liu, Roy Schwartz, Noah A. Smith*2019 · 137 citations*
329. [**Detecting Language Model Attacks with Perplexity arXiv:2308.14132**Gabriel Alon, Michael Kamfonas*2023 · 136 citations*](https://md.research.elamur.ai/free/en/papers/alon-2023-detecting-language-model-attacks-perplexity/)
330. [**Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models arXiv:2212.08037**Bernd Bohnet, Vinh Q. Tran, Pat Verga, et al.*2022 · 136 citations*](https://md.research.elamur.ai/free/en/papers/bohnet-2022-attributed-question-answering-evaluation-modeling/)
331. **[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 · 136 citations*
332. [**Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models arXiv:2404.18796**Pat Verga, Sebastian Hofstatter, Sophia Althammer, et al.*2024 · 134 citations*](https://md.research.elamur.ai/free/en/papers/verga-2024-replacing-judges-juries-evaluating-llm/)
333. **[Few-Shot Self-Rationalization with Natural Language Prompts](https://md.research.elamur.ai/free/en/papers/marasovic-2022-few-shot-self-rationalization-natural/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ana Marasovic, Iz Beltagy, Doug Downey, et al.*2022 · 134 citations*
334. **[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 · 134 citations*
335. **[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*
336. [**Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches arXiv:1904.01172**Shane Storks, Qiaozi Gao, Joyce Y. Chai*2019 · 134 citations*](https://md.research.elamur.ai/free/en/papers/storks-2019-recent-advances-natural-language-inference/)
337. **[Open Domain Question Answering over Tables via Dense Retrieval](https://md.research.elamur.ai/free/en/papers/herzig-2021-open-domain-question-answering-over/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Jonathan Herzig, Thomas Müller, Syrine Krichene, et al.*2021 · 133 citations*
338. **[Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension](https://md.research.elamur.ai/free/en/papers/sun-2019-investigating-prior-knowledge-challenging/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Kai Sun, Dian Yu, Dong Yu, et al.*2019 · 133 citations*
339. **[What to Pre-Train on? Efficient Intermediate Task Selection](https://md.research.elamur.ai/free/en/papers/poth-2021-what-pre-train-efficient-intermediate/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Clifton Poth, Jonas Pfeiffer, Andreas Rücklé, et al.*2021 · 132 citations*
340. **[Task-aware Retrieval with Instructions](https://md.research.elamur.ai/free/en/papers/asai-2023-task-aware-retrieval-instructions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Akari Asai, Timo Schick, Patrick Lewis, et al.*2023 · 131 citations*
341. **[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 · 131 citations*
342. **[It's Morphin' Time! Combating Linguistic Discrimination with Inflectional Perturbations](https://md.research.elamur.ai/free/en/papers/tan-2020-it-s-morphin-time-combating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Samson Tan, Shafiq Joty, Min-Yen Kan, et al.*2020 · 130 citations*
343. **[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*
344. **[ZeroSCROLLS: A Zero-Shot Benchmark for Long Text Understanding](https://md.research.elamur.ai/free/en/papers/shaham-2023-zeroscrolls-zero-shot-benchmark-long/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Uri Shaham, Maor Ivgi, Avia Efrat, et al.*2023 · 129 citations*
345. **[GO FIGURE: A Meta Evaluation of Factuality in Summarization](https://md.research.elamur.ai/free/en/papers/gabriel-2021-go-figure-meta-evaluation-factuality/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Saadia Gabriel, Asli Celikyilmaz, Rahul Jha, et al.*2021 · 129 citations*
346. **[MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data](https://md.research.elamur.ai/free/en/papers/zhao-2022-multihiertt-numerical-reasoning-over-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yilun Zhao, Yunxiang Li, Chenying Li, et al.*2022 · 128 citations*
347. **[Improving Factual Consistency of Abstractive Summarization via Question Answering](https://md.research.elamur.ai/free/en/papers/nan-2021-improving-factual-consistency-abstractive-summarization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Feng Nan, Cicero Nogueira dos Santos, Henghui Zhu, et al.*2021 · 128 citations*
348. **[ERNIE-M: Enhanced Multilingual Representation by Aligning Cross-lingual Semantics with Monolingual Corpora](https://md.research.elamur.ai/free/en/papers/ouyang-2020-ernie-m-enhanced-multilingual/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xuan Ouyang, Shuohuan Wang, Chao Pang, et al.*2020 · 127 citations*
349. **[Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/chen-2020-open-domain-question-answering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Danqi Chen, Wen-tau Yih*2020 · 127 citations*
350. **[Learning Dense Representations of Phrases at Scale](https://md.research.elamur.ai/free/en/papers/lee-2021-learning-dense-representations-phrases-scale/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinhyuk Lee, Mujeen Sung, Jaewoo Kang, et al.*2021 · 126 citations*
351. [**Nomic Embed: Training a Reproducible Long Context Text Embedder arXiv:2402.01613**Zach Nussbaum, John X. Morris, Brandon Duderstadt, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/nussbaum-2024-nomic-embed-training-reproducible-long/)
352. [**τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains arXiv:2406.12045**Shunyu Yao, Noah Shinn, Pedram Razavi, et al.*2024 · 123 citations*](https://md.research.elamur.ai/free/en/papers/yao-2024-tau-bench-benchmark-tool/)
353. **[Better Rewards Yield Better Summaries: Learning to Summarise Without References](https://md.research.elamur.ai/free/en/papers/bohm-2019-better-rewards-yield-better-summaries/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Florian Böhm, Yang Gao, Christian M. Meyer, et al.*2019 · 123 citations*
354. **[Automatic Argument Quality Assessment - New Datasets and Methods](https://md.research.elamur.ai/free/en/papers/toledo-2019-automatic-argument-quality-assessment-new/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Assaf Toledo, Shai Gretz, Edo Cohen-Karlik, et al.*2019 · 122 citations*
355. **[ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts](https://md.research.elamur.ai/free/en/papers/asai-2022-attempt-parameter-efficient-multi-task/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Akari Asai, Mohammadreza Salehi, Matthew Peters, et al.*2022 · 121 citations*
356. **[DocNLI: A Large-scale Dataset for Document-level Natural Language Inference](https://md.research.elamur.ai/free/en/papers/yin-2021-docnli-large-scale-dataset-document/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wenpeng Yin, Dragomir Radev, Caiming Xiong*2021 · 121 citations*
357. **[I-BERT: Integer-only BERT Quantization](https://md.research.elamur.ai/free/en/papers/kim-2021-i-bert-integer-only-bert/) [International Conference on Machine Learning (ICML)](https://md.research.elamur.ai/free/en/venues/international-conference-on-machine-learning/)**Sehoon Kim, Amir Gholami, Zhewei Yao, et al.*2021 · 120 citations*
358. [**Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering arXiv:2306.04136**Jinheon Baek, Alham Fikri Aji, Amir Saffari*2023 · 119 citations*](https://md.research.elamur.ai/free/en/papers/baek-2023-knowledge-augmented-language-model-prompting/)
359. **[UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning](https://md.research.elamur.ai/free/en/papers/masry-2023-unichart-universal-vision-language-pretrained/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ahmed Masry, Parsa Kavehzadeh, Xuan Long Do, et al.*2023 · 119 citations*
360. **[ChID: A Large-scale Chinese IDiom Dataset for Cloze Test](https://md.research.elamur.ai/free/en/papers/zheng-2019-chid-large-scale-chinese/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chujie Zheng, Minlie Huang, Aixin Sun*2019 · 119 citations*
361. **[Analyzing Compositionality-Sensitivity of NLI Models](https://md.research.elamur.ai/free/en/papers/nie-2018-analyzing-compositionality-sensitivity-nli-models/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Yixin Nie, Yicheng Wang, Mohit Bansal*2018 · 119 citations*
362. [**Pretraining Language Models with Human Preferences arXiv:2302.08582**Tomasz Korbak, Kejian Shi, Angelica Chen, et al.*2023 · 118 citations*](https://md.research.elamur.ai/free/en/papers/korbak-2023-pretraining-language-models-human-preferences/)
363. **[KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/yu-2022-kg-fid-infusing-knowledge-graph/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Donghan Yu, Chenguang Zhu, Yuwei Fang, et al.*2022 · 115 citations*
364. **[MoEfication: Transformer Feed-forward Layers are Mixtures of Experts](https://md.research.elamur.ai/free/en/papers/zhang-2022-moefication-transformer-feed-forward-layers/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengyan Zhang, Yankai Lin, Zhiyuan Liu, et al.*2022 · 115 citations*
365. [**Continual Pre-Training for Cross-Lingual LLM Adaptation: Enhancing Japanese Language Capabilities arXiv:2404.17790**Kazuki Fujii, Taishi Nakamura, Mengsay Loem, et al.*2024 · 114 citations*](https://md.research.elamur.ai/free/en/papers/fujii-2024-continual-pre-training-cross-lingual/)
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367. **[MLSUM: The Multilingual Summarization Corpus](https://md.research.elamur.ai/free/en/papers/scialom-2020-mlsum-multilingual-summarization-corpus/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, et al.*2020 · 114 citations*
368. [**Crowdsourcing Question-Answer Meaning Representations**Julian Michael, Gabriel Stanovsky, Luheng He, et al.*2018 · 112 citations*](https://md.research.elamur.ai/free/en/papers/michael-2018-crowdsourcing-question-answer-meaning-representations/)
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370. **[Logic-Guided Data Augmentation and Regularization for Consistent Question Answering](https://md.research.elamur.ai/free/en/papers/asai-2020-logic-guided-data-augmentation-regularization/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Akari Asai, Hannaneh Hajishirzi*2020 · 111 citations*
371. [**Olmo 3 arXiv:2512.13961**Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.*2025 · 109 citations*](https://md.research.elamur.ai/free/en/papers/ettinger-2025-olmo-3/)
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373. [**Evaluating the Performance of Large Language Models on GAOKAO Benchmark arXiv:2305.12474**Xiaotian Zhang, Chunyang Li, Yi Zong, et al.*2023 · 109 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-evaluating-performance-large-language/)
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375. **[Learning to Retrieve In-Context Examples for Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-learning-retrieve-context-examples-large/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Liang Wang, Nan Yang, Furu Wei*2024 · 103 citations*
376. **[Parallel Context Windows for Large Language Models](https://md.research.elamur.ai/free/en/papers/ratner-2023-parallel-context-windows-large-language/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nir Ratner, Yoav Levine, Yonatan Belinkov, et al.*2023 · 102 citations*
377. **[Look at the First Sentence: Position Bias in Question Answering](https://md.research.elamur.ai/free/en/papers/ko-2020-look-first-sentence-position-bias/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Miyoung Ko, Jinhyuk Lee, Hyunjae Kim, et al.*2020 · 102 citations*
378. **[Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering Evaluation](https://md.research.elamur.ai/free/en/papers/bulian-2022-tomayto-tomahto-beyond-token-level/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jannis Bulian, Christian Buck, Wojciech Gajewski, et al.*2022 · 100 citations*
379. **[Understanding by Understanding Not: Modeling Negation in Language Models](https://md.research.elamur.ai/free/en/papers/hosseini-2021-understanding-understanding-not-modeling-negation/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Arian Hosseini, Siva Reddy, Dzmitry Bahdanau, et al.*2021 · 98 citations*
380. **[AraELECTRA: Pre-Training Text Discriminators for Arabic Language Understanding](https://md.research.elamur.ai/free/en/papers/antoun-2021-araelectra-pre-training-text-discriminators/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Wissam Antoun, Fady Baly, Hazem Hajj*2021 · 97 citations*
381. **[WebGLM: Towards An Efficient Web-Enhanced Question Answering System with Human Preferences](https://md.research.elamur.ai/free/en/papers/liu-2023-webglm-efficient-web-enhanced/) [ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD)](https://md.research.elamur.ai/free/en/venues/acm-sigkdd-conference-on-knowledge-discovery-and-data-mining-kdd/)**Xiao Liu, Hanyu Lai, Hao Yu, et al.*2023 · 95 citations*
382. **[Probing Across Time: What Does RoBERTa Know and When?](https://md.research.elamur.ai/free/en/papers/liu-2021-probing-across-time-what-does/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Leo Z. Liu, Yizhong Wang, Jungo Kasai, et al.*2021 · 94 citations*
383. **[Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models](https://md.research.elamur.ai/free/en/papers/khot-2021-text-modular-networks-learning-decompose/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Tushar Khot, Daniel Khashabi, Kyle Richardson, et al.*2021 · 94 citations*
384. **[Efficient Long-Text Understanding with Short-Text Models](https://md.research.elamur.ai/free/en/papers/ivgi-2023-efficient-long-text-understanding-short/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Maor Ivgi, Uri Shaham, Jonathan Berant*2023 · 93 citations*
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386. [**SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning**Roshanak Mirzaee, Hossein Rajaby Faghihi, Qiang Ning, et al.*2021 · 93 citations*](https://md.research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/)
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388. **[JGLUE: Japanese General Language Understanding Evaluation](https://md.research.elamur.ai/free/en/papers/kurihara-2022-jglue-japanese-general-language-understanding/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kentaro Kurihara, Daisuke Kawahara, Tomohide Shibata*2022 · 90 citations*
389. **[CODAH: An Adversarially-Authored Question Answering Dataset for Common Sense](https://md.research.elamur.ai/free/en/papers/chen-2019-codah-adversarially-authored-question-answering/) [Workshop on Evaluating Vector Space Representations for NLP](https://md.research.elamur.ai/free/en/venues/workshop-on-evaluating-vector-space-representations-for-nlp/)**Michael Chen, Mike D'Arcy, Alisa Liu, et al.*2019 · 90 citations*
390. **[Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI](https://md.research.elamur.ai/free/en/papers/tian-2021-diagnosing-first-order-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jidong Tian, Yitian Li, Wenqing Chen, et al.*2021 · 86 citations*
391. **[BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual Transfer](https://md.research.elamur.ai/free/en/papers/asai-2024-buffet-benchmarking-large-language-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Akari Asai, Sneha Kudugunta, Xinyan Yu, et al.*2024 · 85 citations*
392. **[SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2024-seaeval-multilingual-foundation-models-cross/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Bin Wang, Zhengyuan Liu, Xin Huang, et al.*2024 · 85 citations*
393. **[DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering](https://md.research.elamur.ai/free/en/papers/neeman-2023-disentqa-disentangling-parametric-contextual-knowledge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ella Neeman, Roee Aharoni, Or Honovich, et al.*2023 · 84 citations*
394. [**PreCo: A Large-scale Dataset in Preschool Vocabulary for Coreference Resolution**Hong Chen, Zhenhua Fan, Hao Lu, et al.*2018 · 84 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-preco-large-scale-dataset-preschool/)
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397. **[QADiscourse - Discourse Relations as QA Pairs: Representation, Crowdsourcing and Baselines](https://md.research.elamur.ai/free/en/papers/pyatkin-2020-qadiscourse-discourse-relations-as-qa/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Valentina Pyatkin, Ayal Klein, Reut Tsarfaty, et al.*2020 · 77 citations*
398. [**Bridging Anaphora Resolution as Question Answering**Yufang Hou*2020 · 76 citations*](https://md.research.elamur.ai/free/en/papers/hou-2020-bridging-anaphora-resolution-as-question/)
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400. **[KMMLU: Measuring Massive Multitask Language Understanding in Korean](https://md.research.elamur.ai/free/en/papers/son-2025-kmmlu-measuring-massive-multitask-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Guijin Son, Hanwool Lee, Sungdong Kim, et al.*2025 · 72 citations*

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