---
title: "Who cites Priya Goyal — 1,326 papers of our library"
description: "1,326 papers of the Elamur Research library cite the works of Priya Goyal, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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# Who cites Priya Goyal

1,346 citations of their works from 1,326 papers of our library (of the 149,439 whose bibliographies we read) · 138 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Priya Goyal](https://md.research.elamur.ai/free/en/authors/priya-goyal/)

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1. **[Momentum Contrast for Unsupervised Visual Representation Learning](https://md.research.elamur.ai/free/en/papers/he-2019-momentum-contrast-unsupervised-visual-representation/) [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/)**Kaiming He, Haoqi Fan, Yuxin Wu, et al.*2019 · 13,302 citations*
2. [**YOLOv4: Optimal Speed and Accuracy of Object Detection arXiv:2004.10934**Alexey Bochkovskiy, Chien-Yao Wang, Hong-Yuan Mark Liao*2020 · 10,403 citations*](https://md.research.elamur.ai/free/en/papers/bochkovskiy-2020-yolov4-optimal-speed-accuracy-object/)
3. [**A Simple Framework for Contrastive Learning of Visual Representations arXiv:2002.05709**Ting Chen, Simon Kornblith, Mohammad Norouzi, et al.*2020 · 8,000 citations*](https://md.research.elamur.ai/free/en/papers/chen-2020-simple-framework-contrastive-learning-visual/)
4. **[Learning Transferable Architectures for Scalable Image Recognition](https://md.research.elamur.ai/free/en/papers/zoph-2017-learning-transferable-architectures-scalable-image/) [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/)**Barret Zoph, Vijay Vasudevan, Jonathon Shlens, et al.*2017 · 6,583 citations*
5. **[Emerging Properties in Self-Supervised Vision Transformers](https://md.research.elamur.ai/free/en/papers/caron-2021-emerging-properties-self-supervised-vision/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Mathilde Caron, Hugo Touvron, Ishan Misra, et al.*2021 · 6,046 citations*
6. [**mixup: Beyond Empirical Risk Minimization arXiv:1710.09412**Hongyi Zhang, Moustapha Cisse, Yann N. Dauphin, et al.*2017 · 4,928 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2017-mixup-empirical-risk-minimization/)
7. **[Scalable Diffusion Models with Transformers](https://md.research.elamur.ai/free/en/papers/peebles-2022-scalable-diffusion-models-transformers/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**William Peebles, Saining Xie*2022 · 2,670 citations*
8. **[Designing Network Design Spaces](https://md.research.elamur.ai/free/en/papers/radosavovic-2020-designing-network-design-spaces/) [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/)**Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, et al.*2020 · 2,040 citations*
9. [**DINOv2: Learning Robust Visual Features without Supervision arXiv:2304.07193**Maxime Oquab, Timothee Darcet, Theo Moutakanni, et al.*2023 · 1,513 citations*](https://md.research.elamur.ai/free/en/papers/oquab-2023-dinov2-learning-robust-visual-features/)
10. [**TVM: An Automated End-to-End Optimizing Compiler for Deep Learning arXiv:1802.04799**Tianqi Chen, Thierry Moreau, Ziheng Jiang, et al.*2018 · 1,384 citations*](https://md.research.elamur.ai/free/en/papers/chen-2018-tvm-automated-end-end-optimizing/)
11. [**Segment Anything arXiv:2304.02643**Alexander Kirillov, Eric Mintun, Nikhila Ravi, et al.*2023 · 960 citations*](https://md.research.elamur.ai/free/en/papers/kirillov-2023-segment-anything/)
12. **[PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transformation and Graph Compilation](https://md.research.elamur.ai/free/en/papers/ansel-2024-pytorch-2-faster-machine-learning/) [ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS)](https://md.research.elamur.ai/free/en/venues/acm-international-conference-on-architectural-support-for-programming-languages/)**Jason Ansel, Edward Yang, Horace He, et al.*2024 · 946 citations*
13. **[Scaling Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/ott-2018-scaling-neural-machine-translation/) [Conference on Machine Translation: Research Papers](https://md.research.elamur.ai/free/en/venues/conference-on-machine-translation-research-papers/)**Myle Ott, Sergey Edunov, David Grangier, et al.*2018 · 826 citations*
14. **[Dice Loss for Data-imbalanced NLP Tasks](https://md.research.elamur.ai/free/en/papers/li-2020-dice-loss-data-imbalanced-nlp/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaoya Li, Xiaofei Sun, Yuxian Meng, et al.*2020 · 735 citations*
15. **[Progressive Differentiable Architecture Search: Bridging the Depth Gap between Search and Evaluation](https://md.research.elamur.ai/free/en/papers/chen-2019-progressive-differentiable-architecture-search-bridging/) [IEEE/CVF International Conference on Computer Vision (ICCV)](https://md.research.elamur.ai/free/en/venues/ieee-cvf-international-conference-on-computer-vision-iccv/)**Xin Chen, Lingxi Xie, Jun Wu, et al.*2019 · 732 citations*
16. [**Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations MAPL 2019**Philippe Tillet, H. T. Kung, David Cox*2019 · 729 citations*](https://md.research.elamur.ai/free/en/papers/tillet-2019-triton-intermediate-language-compiler-tiled/)
17. [**Horovod: fast and easy distributed deep learning in TensorFlow arXiv:1802.05799**Alexander Sergeev, Mike Del Balso*2018 · 695 citations*](https://md.research.elamur.ai/free/en/papers/sergeev-2018-horovod-fast-easy-distributed-deep/)
18. [**The Secret Sharer: Evaluating and Testing Unintended Memorization in Neural Networks arXiv:1802.08232**Nicholas Carlini, Chang Liu, Ulfar Erlingsson, et al.*2018 · 692 citations*](https://md.research.elamur.ai/free/en/papers/carlini-2018-secret-sharer-evaluating-testing-unintended/)
19. [**Regularizing and Optimizing LSTM Language Models arXiv:1708.02182**Stephen Merity, Nitish Shirish Keskar, Richard Socher*2017 · 633 citations*](https://md.research.elamur.ai/free/en/papers/merity-2017-regularizing-optimizing-lstm-language-models/)
20. [**Masked Autoencoders Are Scalable Vision Learners arXiv:2111.06377**Kaiming He, Xinlei Chen, Saining Xie, et al.*2021 · 596 citations*](https://md.research.elamur.ai/free/en/papers/he-2021-masked-autoencoders-scalable-vision-learners/)
21. [**Training data-efficient image transformers & distillation through attention arXiv:2012.12877**Hugo Touvron, Matthieu Cord, Matthijs Douze, et al.*2020 · 524 citations*](https://md.research.elamur.ai/free/en/papers/touvron-2020-training-data-efficient-image-transformers/)
22. [**Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection arXiv:2303.05499**Shilong Liu, Zhaoyang Zeng, Tianhe Ren, et al.*2023 · 472 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-grounding-dino-marrying-dino-grounded/)
23. [**Evaluating Modern GPU Interconnect: PCIe, NVLink, NV-SLI, NVSwitch and GPUDirect arXiv:1903.04611**Ang Li, Shuaiwen Leon Song, Jieyang Chen, et al.*2019 · 372 citations*](https://md.research.elamur.ai/free/en/papers/li-2019-evaluating-modern-gpu-interconnect-pcie/)
24. [**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/)
25. [**Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes arXiv:1807.11205**Xianyan Jia, Shutao Song, Wei He, et al.*2018 · 348 citations*](https://md.research.elamur.ai/free/en/papers/jia-2018-highly-scalable-deep-learning-training/)
26. **[TextCaps: a Dataset for Image Captioning with Reading Comprehension](https://md.research.elamur.ai/free/en/papers/sidorov-2020-textcaps-dataset-image-captioning-reading/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Oleksii Sidorov, Ronghang Hu, Marcus Rohrbach, et al.*2020 · 331 citations*
27. [**Tensor Comprehensions: Framework-Agnostic High-Performance Machine Learning Abstractions arXiv:1802.04730**Nicolas Vasilache, Oleksandr Zinenko, Theodoros Theodoridis, et al.*2018 · 323 citations*](https://md.research.elamur.ai/free/en/papers/vasilache-2018-tensor-comprehensions-framework-agnostic-high/)
28. [**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/)
29. [**Llemma: An Open Language Model For Mathematics arXiv:2310.10631**Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.*2023 · 286 citations*](https://md.research.elamur.ai/free/en/papers/azerbayev-2023-llemma-open-language-model-mathematics/)
30. [**Beyond Data and Model Parallelism for Deep Neural Networks SysML 2019**Zhihao Jia, Matei Zaharia, Alex Aiken*2018 · 280 citations*](https://md.research.elamur.ai/free/en/papers/jia-2018-beyond-data-model-parallelism-deep/)
31. [**Demystifying Parallel and Distributed Deep Learning: An In-Depth Concurrency Analysis ACM Computing Surveys 2019**Tal Ben-Nun, Torsten Hoefler*2018 · 275 citations*](https://md.research.elamur.ai/free/en/papers/nun-2018-demystifying-parallel-distributed-deep-learning/)
32. [**Learning to Optimize Tensor Programs arXiv:1805.08166**Tianqi Chen, Lianmin Zheng, Eddie Yan, et al.*2019 · 269 citations*](https://md.research.elamur.ai/free/en/papers/chen-2019-learning-optimize-tensor-programs/)
33. **[Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition](https://md.research.elamur.ai/free/en/papers/shen-2021-locate-label-two-stage-identifier/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yongliang Shen, Xinyin Ma, Zeqi Tan, et al.*2021 · 232 citations*
34. **[Understanding the Difficulty of Training Transformers](https://md.research.elamur.ai/free/en/papers/liu-2020-understanding-difficulty-training-transformers/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Liyuan Liu, Xiaodong Liu, Jianfeng Gao, et al.*2020 · 231 citations*
35. **[Generating Fact Checking Explanations](https://md.research.elamur.ai/free/en/papers/atanasova-2020-generating-fact-checking-explanations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pepa Atanasova, Jakob Grue Simonsen, Christina Lioma, et al.*2020 · 220 citations*
36. [**Autoformalization with Large Language Models arXiv:2205.12615**Yuhuai Wu, Albert Q. Jiang, Wenda Li, et al.*2022 · 204 citations*](https://md.research.elamur.ai/free/en/papers/wu-2022-autoformalization-large-language-models/)
37. **[Findings of the 2021 Conference on Machine Translation (WMT21)](https://md.research.elamur.ai/free/en/papers/akhbardeh-2021-findings-2021-conference-machine-translation/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Farhad Akhbardeh, Arkady Arkhangorodsky, Magdalena Biesialska, et al.*2021 · 189 citations*
38. [**Analysis of Large-Scale Multi-Tenant GPU Clusters for DNN Training Workloads arXiv:1901.05758**Myeongjae Jeon, Shivaram Venkataraman, Amar Phanishayee, et al.*2019 · 179 citations*](https://md.research.elamur.ai/free/en/papers/jeon-2019-analysis-large-scale-multi-tenant/)
39. **[Document-Level Relation Extraction with Adaptive Focal Loss and Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/tan-2022-document-level-relation-extraction-adaptive/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Qingyu Tan, Ruidan He, Lidong Bing, et al.*2022 · 169 citations*
40. [**PipeDream: Fast and Efficient Pipeline Parallel DNN Training arXiv:1806.03377**Aaron Harlap, Deepak Narayanan, Amar Phanishayee, et al.*2018 · 162 citations*](https://md.research.elamur.ai/free/en/papers/harlap-2018-pipedream-fast-efficient-pipeline-parallel/)
41. **[Fine-Tuning Language Models with Just Forward Passes](https://md.research.elamur.ai/free/en/papers/malladi-2023-fine-tuning-language-models-just/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Sadhika Malladi, Tianyu Gao, Eshaan Nichani, et al.*2023 · 153 citations*
42. [**Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning arXiv:2105.04165**Pan Lu, Ran Gong, Shibiao Jiang, et al.*2021 · 139 citations*](https://md.research.elamur.ai/free/en/papers/lu-2021-inter-gps-interpretable-geometry-problem/)
43. **[An Improved Baseline for Sentence-level Relation Extraction](https://md.research.elamur.ai/free/en/papers/zhou-2022-improved-baseline-sentence-level-relation/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Wenxuan Zhou, Muhao Chen*2022 · 124 citations*
44. [**Skywork-Reward: Bag of Tricks for Reward Modeling in LLMs arXiv:2410.18451**Chris Yuhao Liu, Liang Zeng, Jiacai Liu, et al.*2024 · 112 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-skywork-reward-bag-tricks/)
45. [**ImageNet Training in Minutes arXiv:1709.05011**Yang You, Zhao Zhang, Cho-Jui Hsieh, et al.*2017 · 112 citations*](https://md.research.elamur.ai/free/en/papers/you-2017-imagenet-training-minutes/)
46. **[End-to-End Bias Mitigation by Modelling Biases in Corpora](https://md.research.elamur.ai/free/en/papers/mahabadi-2020-end-end-bias-mitigation-modelling/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Rabeeh Karimi Mahabadi, Yonatan Belinkov, James Henderson*2020 · 111 citations*
47. [**DAPPLE: A Pipelined Data Parallel Approach for Training Large Models arXiv:2007.01045**Shiqing Fan, Yi Rong, Chen Meng, et al.*2020 · 107 citations*](https://md.research.elamur.ai/free/en/papers/fan-2020-dapple-pipelined-data-parallel-approach/)
48. [**IconQA: A New Benchmark for Abstract Diagram Understanding and Visual Language Reasoning arXiv:2110.13214**Pan Lu, Liang Qiu, Jiaqi Chen, et al.*2021 · 103 citations*](https://md.research.elamur.ai/free/en/papers/lu-2021-iconqa-new-benchmark-abstract-diagram/)
49. [**A Survey of Confidence Estimation and Calibration in Large Language Models arXiv:2311.08298**Jiahui Geng, Fengyu Cai, Yuxia Wang, et al.*2023 · 97 citations*](https://md.research.elamur.ai/free/en/papers/geng-2023-survey-confidence-estimation-calibration-large/)
50. [**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/)
51. [**Zeus: Understanding and Optimizing GPU Energy Consumption of DNN Training arXiv:2208.06102**Jie You, Jae-Won Chung, Mosharaf Chowdhury*2022 · 82 citations*](https://md.research.elamur.ai/free/en/papers/you-2022-zeus-understanding-optimizing-gpu-energy/)
52. [**Large Language Model Routing with Benchmark Datasets arXiv:2309.15789**Tal Shnitzer, Anthony Ou, Mirian Silva, et al.*2023 · 63 citations*](https://md.research.elamur.ai/free/en/papers/shnitzer-2023-large-language-model-routing-benchmark/)
53. **[On the limit of English conversational speech recognition](https://md.research.elamur.ai/free/en/papers/tuske-2021-limit-english-conversational-speech-recognition/) [Interspeech](https://md.research.elamur.ai/free/en/venues/interspeech-usb/)**Zoltan Tuske, George Saon, Brian Kingsbury*2021 · 49 citations*
54. [**Stable LM 2 1.6B Technical Report arXiv:2402.17834**Marco Bellagente, Jonathan Tow, Dakota Mahan, et al.*2024 · 46 citations*](https://md.research.elamur.ai/free/en/papers/bellagente-2024-stable-lm-2-1-6b/)
55. [**Hunyuan-Large: An Open-Source MoE Model with 52 Billion Activated Parameters by Tencent arXiv:2411.02265**Xingwu Sun, Yanfeng Chen, Yiqing Huang, et al.*2024 · 25 citations*](https://md.research.elamur.ai/free/en/papers/sun-2024-hunyuan-large-open-source/)
56. **[Resolving Discrepancies in Compute-Optimal Scaling of Language Models](https://md.research.elamur.ai/free/en/papers/porian-2024-resolving-discrepancies-compute-optimal-scaling/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Tomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.*2024 · 19 citations*
57. **[Stanceosaurus: Classifying Stance Towards Multicultural Misinformation](https://md.research.elamur.ai/free/en/papers/zheng-2022-stanceosaurus-classifying-stance-multicultural-misinformation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jonathan Zheng, Ashutosh Baheti, Tarek Naous, et al.*2022 · 16 citations*
58. **[Influences on LLM Calibration: A Study of Response Agreement, Loss Functions, and Prompt Styles](https://md.research.elamur.ai/free/en/papers/xia-2025-influences-llm-calibration-study-response/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuxi Xia, Pedro Henrique Luz De Araujo, Klim Zaporojets, et al.*2025 · 11 citations*
59. **[CS-UM6P at SemEval-2022 Task 6: Transformer-based Models for Intended Sarcasm Detection in English and Arabic](https://md.research.elamur.ai/free/en/papers/mahdaouy-2022-cs-um6p-semeval-2022-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Abdelkader El Mahdaouy, Abdellah El Mekki, Kabil Essefar, et al.*2022 · 11 citations*
60. **[The IDC System for Sentiment Classification and Sarcasm Detection in Arabic](https://md.research.elamur.ai/free/en/papers/israeli-2021-idc-system-sentiment-classification-sarcasm/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Abraham Israeli, Yotam Nahum, Shai Fine, et al.*2021 · 10 citations*
61. [**PanGu-π Pro:Rethinking Optimization and Architecture for Tiny Language Models arXiv:2402.02791**Yehui Tang, Kai Han, Fangcheng Liu, et al.*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/tang-2024-pangu-pi-pro-rethinking/)
62. **[Dialect & Sentiment Identification in Nuanced Arabic Tweets Using an Ensemble of Prompt-based, Fine-tuned, and Multitask BERT-Based Models](https://md.research.elamur.ai/free/en/papers/salam-2022-dialect-sentiment-identification-nuanced-arabic/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Reem Abdel-Salam*2022 · 8 citations*
63. **[Multi-Label Classification for Implicit Discourse Relation Recognition](https://md.research.elamur.ai/free/en/papers/long-2024-multi-label-classification-implicit-discourse/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Wanqiu Long, N. Siddharth, Bonnie Webber*2024 · 7 citations*
64. **[Re-Examining FactBank: Predicting the Author's Presentation of Factuality](https://md.research.elamur.ai/free/en/papers/murzaku-2022-re-examining-factbank-predicting-author/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**John Murzaku, Peter Zeng, Magdalena Markowska, et al.*2022 · 7 citations*
65. **[RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization](https://md.research.elamur.ai/free/en/papers/dong-2026-rl-plus-countering-capability-boundary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yihong Dong, Xue Jiang, Yongding Tao, et al.*2026 · 6 citations*
66. [**Deep Multi-Task Models for Misogyny Identification and Categorization on Arabic Social Media arXiv:2206.08407**Abdelkader El Mahdaouy, Abdellah El Mekki, Ahmed Oumar, et al.*2022 · 6 citations*](https://md.research.elamur.ai/free/en/papers/mahdaouy-2022-deep-multi-task-models-misogyny/)
67. [**Improving Arabic Multi-Label Emotion Classification using Stacked Embeddings and Hybrid Loss Function arXiv:2410.03979**Muhammad Azeem Aslam, Wang Jun, Nisar Ahmed, et al.*2024 · 5 citations*](https://md.research.elamur.ai/free/en/papers/aslam-2024-improving-arabic-multi-label-emotion/)
68. **[Ahmed and Khalil at NADI 2022: Transfer Learning and Addressing Class Imbalance for Arabic Dialect Identification and Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/oumar-2022-ahmed-khalil-nadi-2022-transfer/) [Arabic Natural Language Processing Workshop (WANLP)](https://md.research.elamur.ai/free/en/venues/wanlp/)**Ahmed Oumar, Khalil Mrini*2022 · 5 citations*
69. [**Stanceosaurus: Classifying Stance Towards Multilingual Misinformation arXiv:2210.15954**Jonathan Zheng; Ashutosh Baheti; Tarek Naous; Wei Xu;, Alan Ritter*2022 · 5 citations*](https://md.research.elamur.ai/free/en/papers/zheng-2022-stanceosaurus-classifying-stance-towards-multilingual/)
70. **[HiddenGuard: Fine-Grained Safe Generation with Specialized Representation Router](https://md.research.elamur.ai/free/en/papers/mei-2026-hiddenguard-fine-grained-safe-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lingrui Mei, Shenghua Liu, Yiwei Wang, et al.*2026 · 4 citations*
71. **[ProFit: Leveraging High-Value Signals in SFT via Probability-Guided Token Selection](https://md.research.elamur.ai/free/en/papers/liu-2026-profit-leveraging-high-value-signals/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tao Liu, Taiqiang Wu, Runming Yang, et al.*2026 · 4 citations*
72. **[GOF at Qur'an QA 2022: Towards an Efficient Question Answering For The Holy Qu'ran In The Arabic Language Using Deep Learning-Based Approach](https://md.research.elamur.ai/free/en/papers/mostafa-2022-gof-qur-qa-2022-efficient/) [Workshop on Open-Source Arabic Corpora and Processing Tools with Shared Tasks](https://md.research.elamur.ai/free/en/venues/osact/)**Ali Mostafa, Omar Mohamed*2022 · 4 citations*
73. **[Meta-Learning based Deferred Optimisation for Sentiment and Emotion aware Multi-modal Dialogue Act Classification](https://md.research.elamur.ai/free/en/papers/saha-2022-meta-learning-based-deferred-optimisation/) [Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (AACL)](https://md.research.elamur.ai/free/en/venues/aacl/)**Tulika Saha, Aditya Prakash Patra, Sriparna Saha, et al.*2022 · 4 citations*
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