---
title: "Who cites Piyush Sharma — page 3 — 2,380 citing papers"
description: "2,380 papers of the Elamur Research library cite the works of Piyush Sharma, found in their bibliographies · page 3 of 4 · 201–300; the most…"
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---
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# Who cites Piyush Sharma

2,405 citations of their works from 2,380 papers of our library (of the 149,439 whose bibliographies we read) · 378 with a page here, the most cited first · page 3 of 4 · 201–300 · [← Piyush Sharma](https://md.research.elamur.ai/free/en/authors/piyush-sharma/)

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201. **[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 · 129 citations*
202. **[Swiss-Judgment-Prediction: A Multilingual Legal Judgment Prediction Benchmark](https://md.research.elamur.ai/free/en/papers/niklaus-2021-swiss-judgment-prediction-multilingual-legal/) [Natural Legal Language Processing Workshop](https://md.research.elamur.ai/free/en/venues/nllp/)**Joel Niklaus, Ilias Chalkidis, Matthias Stürmer*2021 · 129 citations*
203. [**LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models arXiv:2407.07895**Feng Li, Renrui Zhang, Hao Zhang, et al.*2024 · 127 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-llava-next-interleave-tackling-multi/)
204. **[Mini-Gemini: Mining the Potential of Multi-modality Vision Language Models](https://md.research.elamur.ai/free/en/papers/li-2024-mini-gemini-mining-potential-multi/) [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-pattern-analysis-and-machine-intelligence/)**Yanwei Li, Yuechen Zhang, Chengyao Wang, et al.*2024 · 123 citations*
205. **[The Moral Integrity Corpus: A Benchmark for Ethical Dialogue Systems](https://md.research.elamur.ai/free/en/papers/ziems-2022-moral-integrity-corpus-benchmark-ethical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Caleb Ziems, Jane A. Yu, Yi-Chia Wang, et al.*2022 · 122 citations*
206. **[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 · 122 citations*
207. **[Logical Fallacy Detection](https://md.research.elamur.ai/free/en/papers/jin-2022-logical-fallacy-detection/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhijing Jin, Abhinav Lalwani, Tejas Vaidhya, et al.*2022 · 119 citations*
208. **[End-to-End Training of Neural Retrievers for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/sachan-2021-end-end-training-neural-retrievers/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Devendra Sachan, Mostofa Patwary, Mohammad Shoeybi, et al.*2021 · 116 citations*
209. **[Unmasking Contextual Stereotypes: Measuring and Mitigating BERT's Gender Bias](https://md.research.elamur.ai/free/en/papers/bartl-2020-unmasking-contextual-stereotypes-measuring-mitigating/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Marion Bartl, Malvina Nissim, Albert Gatt*2020 · 116 citations*
210. [**ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning arXiv:2111.10952**Vamsi Aribandi, Yi Tay, Tal Schuster, et al.*2021 · 114 citations*](https://md.research.elamur.ai/free/en/papers/aribandi-2021-ext5-towards-extreme-multi-task/)
211. **[WiCE: Real-World Entailment for Claims in Wikipedia](https://md.research.elamur.ai/free/en/papers/kamoi-2023-wice-real-world-entailment-claims/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ryo Kamoi, Tanya Goyal, Juan Diego Rodriguez, et al.*2023 · 113 citations*
212. [**Efficient Large Scale Language Modeling with Mixtures of Experts arXiv:2112.10684**Mikel Artetxe, Shruti Bhosale, Naman Goyal, et al.*2021 · 113 citations*](https://md.research.elamur.ai/free/en/papers/artetxe-2021-efficient-large-scale-language-modeling/)
213. **[mPLUG-DocOwl 1.5: Unified Structure Learning for OCR-free Document Understanding](https://md.research.elamur.ai/free/en/papers/hu-2024-mplug-docowl-1-5-unified/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Anwen Hu, Haiyang Xu, Jiabo Ye, et al.*2024 · 111 citations*
214. **[French CrowS-Pairs: Extending a challenge dataset for measuring social bias in masked language models to a language other than English](https://md.research.elamur.ai/free/en/papers/neveol-2022-french-crows-pairs-extending-challenge/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aurélie Névéol, Yoann Dupont, Julien Bezançon, et al.*2022 · 107 citations*
215. [**A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & Toxicity arXiv:2305.13169**Shayne Longpre, Gregory Yauney, Emily Reif, et al.*2023 · 104 citations*](https://md.research.elamur.ai/free/en/papers/longpre-2023-pretrainer-s-guide-training-data/)
216. **[Transformers for Tabular Data Representation: A Survey of Models and Applications](https://md.research.elamur.ai/free/en/papers/badaro-2023-transformers-tabular-data-representation-survey/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Gilbert Badaro, Mohammed Saeed, Paolo Papotti*2023 · 104 citations*
217. [**minicons: Enabling Flexible Behavioral and Representational Analyses of Transformer Language Models arXiv:2203.13112**Kanishka Misra*2022 · 102 citations*](https://md.research.elamur.ai/free/en/papers/misra-2022-minicons-enabling-flexible-behavioral-representational/)
218. **[On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations](https://md.research.elamur.ai/free/en/papers/cao-2022-intrinsic-extrinsic-fairness-evaluation-metrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, et al.*2022 · 100 citations*
219. **[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*
220. [**Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints arXiv:2212.05055**Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, et al.*2022 · 98 citations*](https://md.research.elamur.ai/free/en/papers/komatsuzaki-2022-sparse-upcycling-training-mixture-experts/)
221. **[True Few-Shot Learning with Prompts–-A Real-World Perspective](https://md.research.elamur.ai/free/en/papers/schick-2022-true-few-shot-learning-prompts/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Timo Schick, Hinrich Schütze*2022 · 96 citations*
222. **[Crossmodal-3600: A Massively Multilingual Multimodal Evaluation Dataset](https://md.research.elamur.ai/free/en/papers/thapliyal-2022-crossmodal-3600-massively-multilingual-multimodal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ashish V. Thapliyal, Jordi Pont Tuset, Xi Chen, et al.*2022 · 95 citations*
223. [**SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning**Roshanak Mirzaee, Hossein Rajaby Faghihi, Qiang Ning, et al.*2021 · 95 citations*](https://md.research.elamur.ai/free/en/papers/mirzaee-2021-spartqa-textual-question-answering-benchmark/)
224. [**InternLM-XComposer2: Mastering Free-form Text-Image Composition and Comprehension in Vision-Language Large Model arXiv:2401.16420**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 94 citations*](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-mastering-free/)
225. [**Auto-GPT for Online Decision Making: Benchmarks and Additional Opinions arXiv:2306.02224**Hui Yang, Sifu Yue, Yunzhong He*2023 · 94 citations*](https://md.research.elamur.ai/free/en/papers/yang-2023-auto-gpt-online-decision-making/)
226. **[A Report on the 2020 Sarcasm Detection Shared Task](https://md.research.elamur.ai/free/en/papers/ghosh-2020-report-2020-sarcasm-detection-shared/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Debanjan Ghosh, Avijit Vajpayee, Smaranda Muresan*2020 · 92 citations*
227. [**InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition arXiv:2309.15112**Pan Zhang, Xiaoyi Dong, Bin Wang, et al.*2023 · 87 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2023-internlm-xcomposer-vision-language/)
228. **[Scaling Laws vs Model Architectures: How does Inductive Bias Influence Scaling?](https://md.research.elamur.ai/free/en/papers/tay-2023-scaling-laws-vs-model-architectures/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yi Tay, Mostafa Dehghani, Samira Abnar, et al.*2023 · 86 citations*
229. **[ORCA: A Challenging Benchmark for Arabic Language Understanding](https://md.research.elamur.ai/free/en/papers/elmadany-2023-orca-challenging-benchmark-arabic-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**AbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed*2023 · 83 citations*
230. [**Survey of Vulnerabilities in Large Language Models Revealed by Adversarial Attacks arXiv:2310.10844**Erfan Shayegani, Md Abdullah Al Mamun, Yu Fu, et al.*2023 · 83 citations*](https://md.research.elamur.ai/free/en/papers/shayegani-2023-survey-vulnerabilities-large-language-models/)
231. **[Domain Adaptation with Pre-trained Transformers for Query-Focused Abstractive Text Summarization](https://md.research.elamur.ai/free/en/papers/laskar-2022-domain-adaptation-pre-trained-transformers/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Md Tahmid Rahman Laskar, Enamul Hoque, Jimmy Xiangji Huang*2022 · 76 citations*
232. **[Structural Persistence in Language Models: Priming as a Window into Abstract Language Representations](https://md.research.elamur.ai/free/en/papers/sinclair-2022-structural-persistence-language-models-priming/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Arabella Sinclair, Jaap Jumelet, Willem Zuidema, et al.*2022 · 74 citations*
233. [**CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark arXiv:2106.08087**Ningyu Zhang, Mosha Chen, Zhen Bi, et al.*2021 · 71 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2021-cblue-chinese-biomedical-language/)
234. **[NormBank: A Knowledge Bank of Situational Social Norms](https://md.research.elamur.ai/free/en/papers/ziems-2023-normbank-knowledge-bank-situational-social/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Caleb Ziems, Jane Dwivedi-Yu, Yi-Chia Wang, et al.*2023 · 69 citations*
235. [**CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese arXiv:2001.04351**Liang Xu, Yu tong, Qianqian Dong, et al.*2020 · 69 citations*](https://md.research.elamur.ai/free/en/papers/xu-2020-cluener2020-fine-grained-named/)
236. **[Towards Faithful Neural Table-to-Text Generation with Content-Matching Constraints](https://md.research.elamur.ai/free/en/papers/wang-2020-faithful-neural-table-text-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhenyi Wang, Xiaoyang Wang, Bang An, et al.*2020 · 67 citations*
237. [**ERNIE 3.0 Titan: Exploring Larger-scale Knowledge Enhanced Pre-training for Language Understanding and Generation arXiv:2112.12731**Shuohuan Wang, Yu Sun, Yang Xiang, et al.*2021 · 63 citations*](https://md.research.elamur.ai/free/en/papers/wang-2021-ernie-3-0-titan/)
238. [**Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering**Najoung Kim, Ellie Pavlick, Burcu Karagol Ayan, et al.*2021 · 63 citations*](https://md.research.elamur.ai/free/en/papers/kim-2021-which-linguist-invented-lightbulb-presupposition/)
239. [**ALLaVA: Harnessing GPT4V-Synthesized Data for Lite Vision-Language Models arXiv:2402.11684**Guiming Hardy Chen, Shunian Chen, Ruifei Zhang, et al.*2024 · 62 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-allava-harnessing-gpt4v-synthesized-data/)
240. [**Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use Cases arXiv:2303.14742**Yunjie Ji, Yong Deng, Yan Gong, et al.*2023 · 62 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-exploring-impact-instruction-data/)
241. [**Building a Bridge: A Method for Image-Text Sarcasm Detection Without Pretraining on Image-Text Data Proceedings of the First International Workshop on Natural Language Processing Beyond Text**Xinyu Wang, Xiaowen Sun, Tan Yang, et al.*2020 · 62 citations*](https://md.research.elamur.ai/free/en/papers/wang-2020-building-bridge-method-image-text/)
242. **[A Family of Pretrained Transformer Language Models for Russian](https://md.research.elamur.ai/free/en/papers/zmitrovich-2024-family-pretrained-transformer-language-models/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Dmitry Zmitrovich, Aleksandr Abramov, Andrey Kalmykov, et al.*2024 · 60 citations*
243. [**MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark arXiv:2402.04788**Dongping Chen, Ruoxi Chen, Shilin Zhang, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-mllm-judge-assessing-multimodal-llm/)
244. [**Investigating the Catastrophic Forgetting in Multimodal Large Language Models arXiv:2309.10313**Yuexiang Zhai, Shengbang Tong, Xiao Li, et al.*2023 · 59 citations*](https://md.research.elamur.ai/free/en/papers/zhai-2023-investigating-catastrophic-forgetting-multimodal-large/)
245. [**MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning arXiv:2309.07915**Haozhe Zhao, Zefan Cai, Shuzheng Si, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/zhao-2023-mmicl-empowering-vision-language-model/)
246. **[InternLM-XComposer2-4KHD: A Pioneering Large Vision-Language Model Handling Resolutions from 336 Pixels to 4K HD](https://md.research.elamur.ai/free/en/papers/dong-2024-internlm-xcomposer2-4khd-pioneering/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Xiaoyi Dong, Pan Zhang, Yuhang Zang, et al.*2024 · 54 citations*
247. [**SciGraphQA: A Large-Scale Synthetic Multi-Turn Question-Answering Dataset for Scientific Graphs arXiv:2308.03349**Shengzhi Li, Nima Tajbakhsh*2023 · 50 citations*](https://md.research.elamur.ai/free/en/papers/li-2023-scigraphqa-large-scale-synthetic-multi/)
248. **[Puzzle Solving using Reasoning of Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/giadikiaroglou-2024-puzzle-solving-reasoning-large-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Panagiotis Giadikiaroglou, Maria Lymperaiou, Giorgos Filandrianos, et al.*2024 · 48 citations*
249. **[ANLIzing the Adversarial Natural Language Inference Dataset](https://md.research.elamur.ai/free/en/papers/williams-2022-anlizing-adversarial-natural-language-inference/) [Society for Computation in Linguistics (SCiL)](https://md.research.elamur.ai/free/en/venues/scil/)**Adina Williams, Tristan Thrush, Douwe Kiela*2022 · 48 citations*
250. **[Metaphor Understanding Challenge Dataset for LLMs](https://md.research.elamur.ai/free/en/papers/tong-2024-metaphor-understanding-challenge-dataset-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoyu Tong, Rochelle Choenni, Martha Lewis, et al.*2024 · 47 citations*
251. [**Language models scale reliably with over-training and on downstream tasks arXiv:2403.08540**Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/gadre-2024-language-models-scale-reliably-over/)
252. **[Fact Checking with Insufficient Evidence](https://md.research.elamur.ai/free/en/papers/atanasova-2022-fact-checking-insufficient-evidence/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2022 · 46 citations*
253. [**NVLM: Open Frontier-Class Multimodal LLMs arXiv:2409.11402**Wenliang Dai, Nayeon Lee, Boxin Wang, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/dai-2024-nvlm-open-frontier-class-multimodal/)
254. **[Polysemy–-Evidence from Linguistics, Behavioral Science, and Contextualized Language Models](https://md.research.elamur.ai/free/en/papers/haber-2024-polysemy-evidence-linguistics-behavioral-science/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Janosch Haber, Massimo Poesio*2024 · 44 citations*
255. [**Large Multilingual Models Pivot Zero-Shot Multimodal Learning across Languages arXiv:2308.12038**Jinyi Hu, Yuan Yao, Chongyi Wang, et al.*2023 · 43 citations*](https://md.research.elamur.ai/free/en/papers/hu-2023-large-multilingual-models-pivot-zero/)
256. **[Pragmatic competence of pre-trained language models through the lens of discourse connectives](https://md.research.elamur.ai/free/en/papers/pandia-2021-pragmatic-competence-pre-trained-language/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Lalchand Pandia, Yan Cong, Allyson Ettinger*2021 · 42 citations*
257. [**DeepSeek: Paradigm Shifts and Technical Evolution in Large AI Models arXiv:2507.09955**Luolin Xiong, Haofen Wang, Xi Chen, et al.*2025 · 41 citations*](https://md.research.elamur.ai/free/en/papers/xiong-2025-deepseek-paradigm-shifts-technical/)
258. **[MoCa: Measuring Human-Language Model Alignment on Causal and Moral Judgment Tasks](https://md.research.elamur.ai/free/en/papers/nie-2023-moca-measuring-human-language-model/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Allen Nie, Yuhui Zhang, Atharva Amdekar, et al.*2023 · 41 citations*
259. **[A Few Topical Tweets are Enough for Effective User Stance Detection](https://md.research.elamur.ai/free/en/papers/samih-2021-few-topical-tweets-are-enough/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Younes Samih, Kareem Darwish*2021 · 40 citations*
260. [**InternLM-XComposer-2.5: A Versatile Large Vision Language Model Supporting Long-Contextual Input and Output arXiv:2407.03320**Pan Zhang, Xiaoyi Dong, Yuhang Zang, et al.*2024 · 39 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2024-internlm-xcomposer-2-5/)
261. [**Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models arXiv:2504.03624**NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.*2025 · 38 citations*](https://md.research.elamur.ai/free/en/papers/blakeman-2025-nemotron-h-family-accurate-efficient/)
262. **[Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches](https://md.research.elamur.ai/free/en/papers/fried-2023-pragmatics-language-grounding-phenomena-tasks/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Daniel Fried, Nicholas Tomlin, Jennifer Hu, et al.*2023 · 38 citations*
263. [**DziriBERT: a Pre-trained Language Model for the Algerian Dialect arXiv:2109.12346**Amine Abdaoui, Mohamed Berrimi, Mourad Oussalah, et al.*2021 · 38 citations*](https://md.research.elamur.ai/free/en/papers/abdaoui-2021-dziribert-pre-trained-language-model/)
264. **[Transformer-based Context-aware Sarcasm Detection in Conversation Threads from Social Media](https://md.research.elamur.ai/free/en/papers/dong-2020-transformer-based-context-aware-sarcasm/) [Workshop on Figurative Language Processing](https://md.research.elamur.ai/free/en/venues/figlang/)**Xiangjue Dong, Changmao Li, Jinho D. Choi*2020 · 35 citations*
265. [**ERNIE-ViLG: Unified Generative Pre-training for Bidirectional Vision-Language Generation arXiv:2112.15283**Han Zhang, Weichong Yin, Yewei Fang, et al.*2021 · 33 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2021-ernie-vilg-unified-generative/)
266. **[Probing Contextual Language Models for Common Ground with Visual Representations](https://md.research.elamur.ai/free/en/papers/ilharco-2021-probing-contextual-language-models-common/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Gabriel Ilharco, Rowan Zellers, Ali Farhadi, et al.*2021 · 33 citations*
267. [**The Life Cycle of Knowledge in Big Language Models: A Survey arXiv:2303.07616 · Machine Intelligence Research. vol. 21, no. 2, pp. 217-238, 2024**Boxi Cao, Hongyu Lin, Xianpei Han, et al.*2023 · 31 citations*](https://md.research.elamur.ai/free/en/papers/cao-2023-life-cycle-knowledge-big-language/)
268. **[Evaluating Document Coherence Modeling](https://md.research.elamur.ai/free/en/papers/shen-2021-evaluating-document-coherence-modeling/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Aili Shen, Meladel Mistica, Bahar Salehi, et al.*2021 · 30 citations*
269. [**One Law, Many Languages: Benchmarking Multilingual Legal Reasoning for Judicial Support arXiv:2306.09237**Ronja Stern, Vishvaksenan Rasiah, Veton Matoshi, et al.*2023 · 29 citations*](https://md.research.elamur.ai/free/en/papers/stern-2023-one-law-many-languages-benchmarking/)
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276. [**Sentiment Analysis through LLM Negotiations arXiv:2311.01876**Xiaofei Sun, Xiaoya Li, Shengyu Zhang, et al.*2023 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-sentiment-analysis-through-llm-negotiations/)
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278. [**Scaling Latent Reasoning via Looped Language Models arXiv:2510.25741**Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.*2025 · 22 citations*](https://md.research.elamur.ai/free/en/papers/zhu-2025-scaling-latent-reasoning-looped-language/)
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282. [**An Empirical Study of Metrics to Measure Representational Harms in Pre-Trained Language Models arXiv:2301.09211**Saghar Hosseini, Hamid Palangi, Ahmed Hassan Awadallah*2023 · 19 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-2023-empirical-study-metrics-measure-representational/)
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284. [**A Survey on Automated Sarcasm Detection on Twitter arXiv:2202.02516**Bleau Moores, Vijay Mago*2022 · 19 citations*](https://md.research.elamur.ai/free/en/papers/moores-2022-survey-automated-sarcasm-detection-twitter/)
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289. [**SaudiBERT: A Large Language Model Pretrained on Saudi Dialect Corpora arXiv:2405.06239**Faisal Qarah*2024 · 14 citations*](https://md.research.elamur.ai/free/en/papers/qarah-2024-saudibert-large-language-model-pretrained/)
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293. [**DuReader_robust: A Chinese Dataset Towards Evaluating Robustness and Generalization of Machine Reading Comprehension in Real-World Applications arXiv:2004.11142**Hongxuan Tang, Hongyu Li, Jing Liu, et al.*2020 · 13 citations*](https://md.research.elamur.ai/free/en/papers/tang-2020-dureader-robust-chinese-dataset/)
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296. **[Speciesist Language and Nonhuman Animal Bias in English Masked Language Models](https://md.research.elamur.ai/free/en/papers/takeshita-2022-speciesist-language-nonhuman-animal-bias/) [Information Processing & Management](https://md.research.elamur.ai/free/en/venues/information-processing-management/)**Masashi Takeshita, Rafal Rzepka, Kenji Araki*2022 · 11 citations*
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298. [**Investigating Forgetting in Pre-Trained Representations Through Continual Learning arXiv:2305.05968**Yun Luo, Zhen Yang, Xuefeng Bai, et al.*2023 · 10 citations*](https://md.research.elamur.ai/free/en/papers/luo-2023-investigating-forgetting-pre-trained-representations/)
299. **[RTQA : Recursive Thinking for Complex Temporal Knowledge Graph Question Answering with Large Language Models](https://md.research.elamur.ai/free/en/papers/gong-2025-rtqa-recursive-thinking-complex-temporal/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaoyan Gong, Juan Li, Zhiqiang Liu, et al.*2025 · 9 citations*
300. **[PECO: Examining Single Sentence Label Leakage in Natural Language Inference Datasets through Progressive Evaluation of Cluster Outliers](https://md.research.elamur.ai/free/en/papers/saxon-2023-peco-examining-single-sentence-label/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Michael Saxon, Xinyi Wang, Wenda Xu, et al.*2023 · 9 citations*

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