---
title: "Who cites Sarath Chandar — 583 papers of our library"
description: "583 papers of the Elamur Research library cite the works of Sarath Chandar, found in their bibliographies; the most cited first."
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---
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# Who cites Sarath Chandar

589 citations of their works from 583 papers of our library (of the 149,439 whose bibliographies we read) · 73 with a page here, the most cited first · [← Sarath Chandar](https://md.research.elamur.ai/free/en/authors/sarath-chandar/)

1. **[Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization](https://md.research.elamur.ai/free/en/papers/selvaraju-2016-grad-cam-visual-explanations-deep/) [International Journal of Computer Vision](https://md.research.elamur.ai/free/en/venues/international-journal-of-computer-vision/)**Ramprasaath R. Selvaraju, Michael Cogswell, Abhishek Das, et al.*2016 · 6,394 citations*
2. **[Lost in the Middle: How Language Models Use Long Contexts](https://md.research.elamur.ai/free/en/papers/liu-2023-lost-middle-language-models-use/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Nelson F. Liu, Kevin Lin, John Hewitt, et al.*2023 · 2,584 citations*
3. **[Recent Advances in Natural Language Processing via Large Pre-Trained Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/min-2021-recent-advances-natural-language-processing/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Bonan Min, Hayley Ross, Elior Sulem, et al.*2021 · 1,556 citations*
4. **[Adversarial NLI: A New Benchmark for Natural Language Understanding](https://md.research.elamur.ai/free/en/papers/nie-2020-adversarial-nli-new-benchmark-natural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yixin Nie, Adina Williams, Emily Dinan, et al.*2020 · 1,296 citations*
5. [**A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly arXiv:2312.02003**Yifan Yao, Jinhao Duan, Kaidi Xu, et al.*2023 · 1,186 citations*](https://md.research.elamur.ai/free/en/papers/yao-2023-survey-large-language-model-llm/)
6. **[Learning to Ask: Neural Question Generation for Reading Comprehension](https://md.research.elamur.ai/free/en/papers/du-2017-learning-ask-neural-question-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinya Du, Junru Shao, Claire Cardie*2017 · 917 citations*
7. **[Meta-Learning for Low-Resource Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gu-2018-meta-learning-low-resource-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jiatao Gu, Yong Wang, Yun Chen, et al.*2018 · 456 citations*
8. [**The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes arXiv:2005.04790**Douwe Kiela, Hamed Firooz, Aravind Mohan, et al.*2020 · 420 citations*](https://md.research.elamur.ai/free/en/papers/kiela-2020-hateful-memes-challenge-detecting-hate/)
9. **[Question Answering on Freebase via Relation Extraction and Textual Evidence](https://md.research.elamur.ai/free/en/papers/xu-2016-question-answering-freebase-relation-extraction/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kun Xu, Siva Reddy, Yansong Feng, et al.*2016 · 360 citations*
10. [**Discovering Language Model Behaviors with Model-Written Evaluations arXiv:2212.09251**Ethan Perez, Sam Ringer, Kamilė Lukošiūtė, et al.*2022 · 328 citations*](https://md.research.elamur.ai/free/en/papers/perez-2022-discovering-language-model-behaviors-model/)
11. **[AugGPT: Leveraging ChatGPT for Text Data Augmentation](https://md.research.elamur.ai/free/en/papers/dai-2023-auggpt-leveraging-chatgpt-text-data/) [IEEE Transactions on Big Data](https://md.research.elamur.ai/free/en/venues/ieee-transactions-on-big-data/)**Haixing Dai; Zhengliang Liu; Wenxiong Liao; Xiaoke Huang; Yihan Cao; Zihao Wu; Lin Zhao; Shaochen Xu; Wei Liu; Ninghao Liu; Sheng Li; Dajiang Zhu; Hongmin Cai; Lichao Sun; Quanzheng Li; Dinggang Shen; Tianming Liu;, Xiang Li*2023 · 306 citations*
12. **[Learning Joint Multilingual Sentence Representations with Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/schwenk-2017-learning-joint-multilingual-sentence-representations/) [Workshop on Representation Learning for NLP](https://md.research.elamur.ai/free/en/venues/repl4nlp/)**Holger Schwenk, Matthijs Douze*2017 · 295 citations*
13. **[PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them](https://md.research.elamur.ai/free/en/papers/lewis-2021-paq-65-million-probably-asked/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Lewis, Yuxiang Wu, Linqing Liu, et al.*2021 · 288 citations*
14. **[Answer-focused and Position-aware Neural Question Generation](https://md.research.elamur.ai/free/en/papers/sun-2018-answer-focused-position-aware-neural/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Xingwu Sun, Jing Liu, Yajuan Lyu, et al.*2018 · 255 citations*
15. **[An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Jiaao Chen, Derek Tam, Colin Raffel, et al.*2023 · 254 citations*
16. **[Harvesting Paragraph-level Question-Answer Pairs from Wikipedia](https://md.research.elamur.ai/free/en/papers/du-2018-harvesting-paragraph-level-question-answer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xinya Du, Claire Cardie*2018 · 232 citations*
17. **[Tracking the World State with Recurrent Entity Networks](https://md.research.elamur.ai/free/en/papers/henaff-2016-tracking-world-state-recurrent-entity/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Mikael Henaff, Jason Weston, Arthur Szlam, et al.*2016 · 228 citations*
18. **[DAGA: Data Augmentation with a Generation Approach for Low-resource Tagging Tasks](https://md.research.elamur.ai/free/en/papers/ding-2020-daga-data-augmentation-generation-approach/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Bosheng Ding, Linlin Liu, Lidong Bing, et al.*2020 · 203 citations*
19. **[Generative Data Augmentation for Commonsense Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2020-generative-data-augmentation-commonsense-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yiben Yang, Chaitanya Malaviya, Jared Fernandez, et al.*2020 · 198 citations*
20. **[Addressing Semantic Drift in Question Generation for Semi-Supervised Question Answering](https://md.research.elamur.ai/free/en/papers/zhang-2019-addressing-semantic-drift-question-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shiyue Zhang, Mohit Bansal*2019 · 174 citations*
21. [**REFINER: Reasoning Feedback on Intermediate Representations arXiv:2304.01904**Debjit Paul, Mete Ismayilzada, Maxime Peyrard, et al.*2023 · 156 citations*](https://md.research.elamur.ai/free/en/papers/paul-2023-refiner-reasoning-feedback-intermediate-representations/)
22. **[Measure and Improve Robustness in NLP Models: A Survey](https://md.research.elamur.ai/free/en/papers/wang-2022-measure-improve-robustness-nlp-models/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Xuezhi Wang, Haohan Wang, Diyi Yang*2022 · 148 citations*
23. **[Out of Order: How important is the sequential order of words in a sentence in Natural Language Understanding tasks?](https://md.research.elamur.ai/free/en/papers/pham-2021-out-order-how-important-is/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Thang Pham, Trung Bui, Long Mai, et al.*2021 · 148 citations*
24. **[Multimodal Pretraining Unmasked: A Meta-Analysis and a Unified Framework of Vision-and-Language BERTs](https://md.research.elamur.ai/free/en/papers/bugliarello-2021-multimodal-pretraining-unmasked-meta-analysis/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Emanuele Bugliarello, Ryan Cotterell, Naoaki Okazaki, et al.*2021 · 141 citations*
25. **[Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description](https://md.research.elamur.ai/free/en/papers/elliott-2017-findings-second-shared-task-multimodal/) [Conference on Machine Translation (WMT)](https://md.research.elamur.ai/free/en/venues/wmt/)**Desmond Elliott, Stella Frank, Loïc Barrault, et al.*2017 · 137 citations*
26. **[SIMMC 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal Conversations](https://md.research.elamur.ai/free/en/papers/kottur-2021-simmc-2-0-task-oriented/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Satwik Kottur, Seungwhan Moon, Alborz Geramifard, et al.*2021 · 114 citations*
27. [**Neural Networks and the Chomsky Hierarchy arXiv:2207.02098**Grégoire Delétang, Anian Ruoss, Jordi Grau-Moya, et al.*2022 · 112 citations*](https://md.research.elamur.ai/free/en/papers/deletang-2022-neural-networks-chomsky-hierarchy/)
28. [**The Galactic Dependencies Treebanks: Getting More Data by Synthesizing New Languages**Dingquan Wang, Jason Eisner*2016 · 99 citations*](https://md.research.elamur.ai/free/en/papers/wang-2016-galactic-dependencies-treebanks-getting-more/)
29. **[DialFact: A Benchmark for Fact-Checking in Dialogue](https://md.research.elamur.ai/free/en/papers/gupta-2022-dialfact-benchmark-fact-checking-dialogue/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Prakhar Gupta, Chien-Sheng Wu, Wenhao Liu, et al.*2022 · 97 citations*
30. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
31. **[CoDraw: Collaborative Drawing as a Testbed for Grounded Goal-driven Communication](https://md.research.elamur.ai/free/en/papers/kim-2019-codraw-collaborative-drawing-as-testbed/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jin-Hwa Kim, Nikita Kitaev, Xinlei Chen, et al.*2019 · 94 citations*
32. **[NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation](https://md.research.elamur.ai/free/en/papers/dhole-2023-nl-augmenter-framework-task-sensitive/) [Northern European Journal of Language Technology](https://md.research.elamur.ai/free/en/venues/northern-european-journal-of-language-technology/)**Kaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.*2023 · 86 citations*
33. **[What Context Features Can Transformer Language Models Use?](https://md.research.elamur.ai/free/en/papers/connor-2021-what-context-features-can-transformer/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joe O'Connor, Jacob Andreas*2021 · 77 citations*
34. **[A Natural Language Corpus of Common Grounding under Continuous and Partially-Observable Context](https://md.research.elamur.ai/free/en/papers/udagawa-2019-natural-language-corpus-common-grounding/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Takuma Udagawa, Akiko Aizawa*2019 · 68 citations*
35. [**Evaluation of OpenAI o1: Opportunities and Challenges of AGI arXiv:2409.18486**Tianyang Zhong, Zhengliang Liu, Yi Pan, et al.*2024 · 64 citations*](https://md.research.elamur.ai/free/en/papers/zhong-2024-evaluation-openai-o1-opportunities-challenges/)
36. [**mmBERT: A Modern Multilingual Encoder with Annealed Language Learning arXiv:2509.06888**Marc Marone, Orion Weller, William Fleshman, et al.*2025 · 59 citations*](https://md.research.elamur.ai/free/en/papers/marone-2025-mmbert-modern-multilingual-encoder-annealed/)
37. **[The PhotoBook Dataset: Building Common Ground through Visually-Grounded Dialogue](https://md.research.elamur.ai/free/en/papers/haber-2019-photobook-dataset-building-common-ground/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Janosch Haber, Tim Baumgärtner, Ece Takmaz, et al.*2019 · 53 citations*
38. **[Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/ma-2025-pragmatics-era-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bolei Ma, Yuting Li, Wei Zhou, et al.*2025 · 49 citations*
39. **[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*
40. **[Data Augmentation using Transformers and Similarity Measures for Improving Arabic Text Classification](https://md.research.elamur.ai/free/en/papers/refai-2022-data-augmentation-using-transformers-similarity/) [IEEE Access](https://md.research.elamur.ai/free/en/venues/ieee-access/)**Dania Refai, Saleh Abo-Soud, Mohammad Abdel-Rahman*2022 · 35 citations*
41. **[Word Representation Learning in Multimodal Pre-Trained Transformers: An Intrinsic Evaluation](https://md.research.elamur.ai/free/en/papers/pezzelle-2021-word-representation-learning-multimodal-pre/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Sandro Pezzelle, Ece Takmaz, Raquel Fernández*2021 · 25 citations*
42. [**Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and Challenges arXiv:2309.12426**Vinay Samuel, Houda Aynaou, Arijit Ghosh Chowdhury, et al.*2023 · 16 citations*](https://md.research.elamur.ai/free/en/papers/samuel-2023-llms-augment-low-resource-reading/)
43. **[An Annotated Corpus of Reference Resolution for Interpreting Common Grounding](https://md.research.elamur.ai/free/en/papers/udagawa-2019-annotated-corpus-reference-resolution-interpreting/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Takuma Udagawa, Akiko Aizawa*2019 · 14 citations*
44. **[Maintaining Common Ground in Dynamic Environments](https://md.research.elamur.ai/free/en/papers/udagawa-2021-maintaining-common-ground-dynamic-environments/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Takuma Udagawa, Akiko Aizawa*2021 · 13 citations*
45. [**Maximize Your Data's Potential: Enhancing LLM Accuracy with Two-Phase Pretraining arXiv:2412.15285**Steven Feng, Shrimai Prabhumoye, Kezhi Kong, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/feng-2024-maximize-data-s-potential-enhancing/)
46. **[A Rigorous Evaluation of LLM Data Generation Strategies for Low-Resource Languages](https://md.research.elamur.ai/free/en/papers/anikina-2025-rigorous-evaluation-llm-data-generation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Tatiana Anikina, Jan Cegin, Jakub Simko, et al.*2025 · 11 citations*
47. **[Less is More: Mitigate Spurious Correlations for Open-Domain Dialogue Response Generation Models by Causal Discovery](https://md.research.elamur.ai/free/en/papers/feng-2023-less-is-more-mitigate-spurious/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tao Feng, Lizhen Qu, Gholamreza Haffari*2023 · 11 citations*
48. **[Position: LLMs Can be Good Tutors in English Education](https://md.research.elamur.ai/free/en/papers/ye-2025-position-llms-can-be-good/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jingheng Ye, Shen Wang, Deqing Zou, et al.*2025 · 9 citations*
49. **[Culturally-Nuanced Story Generation for Reasoning in Low-Resource Languages: The Case of Javanese and Sundanese](https://md.research.elamur.ai/free/en/papers/pranida-2025-culturally-nuanced-story-generation-reasoning/) [Workshop on Multilingual Representation Learning](https://md.research.elamur.ai/free/en/venues/mrl/)**Salsabila Zahirah Pranida, Rifo Ahmad Genadi, Fajri Koto*2025 · 8 citations*
50. **[Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide](https://md.research.elamur.ai/free/en/papers/szep-2026-fine-tuning-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe, et al.*2026 · 7 citations*
51. **[New Encoders for German Trained from Scratch: Comparing ModernGBERT with Converted LLM2Vec Models](https://md.research.elamur.ai/free/en/papers/wunderle-2026-new-encoders-german-trained-scratch/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Julia Wunderle, Anton Ehrmanntraut, Jan Pfister, et al.*2026 · 7 citations*
52. [**TinyR1-32B-Preview: Boosting Accuracy with Branch-Merge Distillation arXiv:2503.04872**Lin Sun, Guangxiang Zhao, Xiaoqi Jian, et al.*2025 · 7 citations*](https://md.research.elamur.ai/free/en/papers/sun-2025-tinyr1-32b-preview-boosting-accuracy/)
53. **[Abed at KSAA-RD Shared Task: Enhancing Arabic Word Embedding with Modified BERT Multilingual](https://md.research.elamur.ai/free/en/papers/qaddoumi-2023-abed-ksaa-rd-shared-task/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Abdelrahim Qaddoumi*2023 · 6 citations*
54. [**DeepSTL — From English Requirements to Signal Temporal Logic arXiv:2109.10294**Jie He, Ezio Bartocci, Dejan Ničkovic, et al.*2021 · 4 citations*](https://md.research.elamur.ai/free/en/papers/he-2021-deepstl-english-requirements-signal-temporal/)
55. **[Lost in Execution: On the Multilingual Robustness of Tool Calling in Large Language Models](https://md.research.elamur.ai/free/en/papers/luo-2026-lost-execution-multilingual-robustness-tool/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zheng Luo, T Pranav Kutralingam, Ogochukwu N. Okoani, et al.*2026 · 3 citations*
56. **[Pretraining and Benchmarking Modern Encoders for Latvian](https://md.research.elamur.ai/free/en/papers/znotins-2026-pretraining-benchmarking-modern-encoders-latvian/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Arturs Znotins*2026 · 3 citations*
57. **[On the Utility of Pretraining Language Models on Synthetic Data](https://md.research.elamur.ai/free/en/papers/inciarte-2024-utility-pretraining-language-models-synthetic/) [Arabic Natural Language Processing Conference (ArabicNLP)](https://md.research.elamur.ai/free/en/venues/arabicnlp/)**Alcides Alcoba Inciarte, Sang Yun Kwon, El Moatez Billah Nagoudi, et al.*2024 · 3 citations*
58. **[DeepSemantics at SemEval-2026 Task 9: Label-Wise Optimization with Adaptive Focal Loss for Polarization Manifestation Identification](https://md.research.elamur.ai/free/en/papers/tiao-2026-deepsemantics-semeval-2026-task-9/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Eliasse Tiao, Josue R. Edou, Mahugnon A. L. Gohouede*2026 · 1 citation*
59. **[NeoAraBERT: A Modern Foundation Model for Arabic Embeddings with Diacritics-Aware Tokenization and POS-Targeted Masking](https://md.research.elamur.ai/free/en/papers/chakra-2026-neoarabert-modern-foundation-model-arabic/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Chadi Abou Chakra, Hadi Khaled Hamoud, Osama Rakan Al Mraikhat, et al.*2026 · 1 citation*
60. **[Template-assisted Contrastive Learning of Task-oriented Dialogue Sentence Embeddings](https://md.research.elamur.ai/free/en/papers/oh-2026-template-assisted-contrastive-learning-task/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Minsik Oh, Jiwei Li, Guoyin Wang*2026 · 1 citation*
61. **[DREAM: A Multicultural Multimodal Dataset Linking Dialogues and Realistic Image Sequences](https://md.research.elamur.ai/free/en/papers/mallo-2026-dream-multicultural-multimodal-dataset-linking/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Juan Mallo, Marcos Estecha-Garitagoitia, Ricardo Cordoba, et al.*2026*
62. **[Multilingual-To-Multimodal (M2M): Unlocking New Languages with Monolingual Text](https://md.research.elamur.ai/free/en/papers/pasi-2026-multilingual-multimodal-m2m-unlocking-new/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Piyush Singh Pasi*2026*
63. **[NLP-CIMAT at SemEval-2026 Task 9: LLM-Based One-Shot and Cross-Lingual Data Augmentation for Polarization Detection](https://md.research.elamur.ai/free/en/papers/reyes-2026-nlp-cimat-semeval-2026-task/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Miriam Calderon-Reyes, Fernando Sanchez-Vega, Adrian Pastor Lopez Monroy*2026*
64. **[PAIR: A Pilot Dataset for Dual Perspective-based Video-Grounded Dialogue and Reconciliation](https://md.research.elamur.ai/free/en/papers/watson-2026-pair-pilot-dataset-dual-perspective/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Lewis N. Watson, Carl Strathearn, Kenny Mitchell, et al.*2026*
65. **[PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data](https://md.research.elamur.ai/free/en/papers/xiong-2026-puzzleclone-dsl-powered-framework-synthesizing/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Xiong, Yanwei Huang, Rongjunchen Zhang, et al.*2026*
66. [**Recent Advances in Text-attributed Graph Learning via Large Models (大模型驱动的文本属性图学习研究进展) Acta Automatica Sinica (自动化学报)**Yanping Zheng (郑艳萍), Jiarui Ji (季嘉蕊), Yuwei Hu (胡雨韦), et al.*2026*](https://md.research.elamur.ai/free/en/papers/zheng-2026-recent-advances-text/)
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