Elamur Research⌕
☰
home / authors / Yadollah Yaghoobzadeh / cited by / page 2

Who cites Yadollah Yaghoobzadeh

1,236 citations of their works from 1,229 papers of our library (of the 141,840 whose bibliographies we read) · 181 with a page here, the most cited first · page 2 of 2 · 101–181 · ← Yadollah Yaghoobzadeh

1 2

  1. DataComp-LM: In search of the next generation of training sets for language modelsConference on Neural Information Processing Systems (NeurIPS)Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.2024 · 156 citations
  2. ReConcile: Round-Table Conference Improves Reasoning via Consensus among Diverse LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Justin Chen, Swarnadeep Saha, Mohit Bansal2024 · 154 citations
  3. Language Model Behavior: A Comprehensive SurveyComputational LinguisticsTyler A. Chang, Benjamin K. Bergen2024 · 148 citations
  4. Phi-4-Mini Technical Report: Compact yet Powerful Multimodal Language Models via Mixture-of-LoRAsarXiv:2503.01743Microsoft, Abdelrahman Abouelenin, Atabak Ashfaq, et al.2025 · 145 citations
  5. Self-Evaluation Guided Beam Search for ReasoningConference on Neural Information Processing Systems (NeurIPS)Yuxi Xie, Kenji Kawaguchi, Yiran Zhao, et al.2023 · 145 citations
  6. Unleashing the Emergent Cognitive Synergy in Large Language Models: A Task-Solving Agent through Multi-Persona Self-CollaborationarXiv:2307.05300Zhenhailong Wang, Shaoguang Mao, Wenshan Wu, et al.2023 · 139 citations
  7. A Roadmap to Pluralistic AlignmentarXiv:2402.05070Taylor Sorensen, Jared Moore, Jillian Fisher, et al.2024 · 135 citations
  8. Self-Knowledge Guided Retrieval Augmentation for Large Language ModelsFindings of the Association for Computational LinguisticsYile Wang, Peng Li, Maosong Sun, et al.2023 · 135 citations
  9. InFoBench: Evaluating Instruction Following Ability in Large Language ModelsFindings of the Association for Computational LinguisticsYiwei Qin, Kaiqiang Song, Yebowen Hu, et al.2024 · 133 citations
  10. To CoT or not to CoT? Chain-of-thought helps mainly on math and symbolic reasoningarXiv:2409.12183Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, et al.2024 · 133 citations
  11. FLUTE: Figurative Language Understanding through Textual ExplanationsConference on Empirical Methods in Natural Language Processing (EMNLP)Tuhin Chakrabarty, Arkadiy Saakyan, Debanjan Ghosh, et al.2022 · 132 citations
  12. Exploring Collaboration Mechanisms for LLM Agents: A Social Psychology ViewAnnual Meeting of the Association for Computational Linguistics (ACL)Jintian Zhang, Xin Xu, Ningyu Zhang, et al.2024 · 131 citations
  13. Faithful Logical Reasoning via Symbolic Chain-of-ThoughtAnnual Meeting of the Association for Computational Linguistics (ACL)Jundong Xu, Hao Fei, Liangming Pan, et al.2024 · 129 citations
  14. ZeroSCROLLS: A Zero-Shot Benchmark for Long Text UnderstandingFindings of the Association for Computational LinguisticsUri Shaham, Maor Ivgi, Avia Efrat, et al.2023 · 129 citations
  15. Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataFindings of the Association for Computational LinguisticsKashun Shum, Shizhe Diao, Tong Zhang2023 · 128 citations
  16. Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 128 citations
  17. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 128 citations
  18. Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow InstructionsarXiv:2309.07875Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio, et al.2023 · 124 citations
  19. Large Language Model Alignment: A SurveyarXiv:2309.15025Tianhao Shen, Renren Jin, Yufei Huang, et al.2023 · 123 citations
  20. Large Language Models Understand and Can be Enhanced by Emotional StimuliarXiv:2307.11760Cheng Li, Jindong Wang, Yixuan Zhang, et al.2023 · 114 citations
  21. Ground-Truth Labels Matter: A Deeper Look into Input-Label DemonstrationsConference on Empirical Methods in Natural Language Processing (EMNLP)Kang Min Yoo, Junyeob Kim, Hyuhng Joon Kim, et al.2022 · 113 citations
  22. LMMs-Eval: Reality Check on the Evaluation of Large Multimodal ModelsFindings of the Association for Computational LinguisticsKaichen Zhang, Bo Li, Peiyuan Zhang, et al.2025 · 110 citations
  23. Evaluating the Performance of Large Language Models on GAOKAO BenchmarkarXiv:2305.12474Xiaotian Zhang, Chunyang Li, Yi Zong, et al.2023 · 109 citations
  24. MMTEB: Massive Multilingual Text Embedding BenchmarkarXiv:2502.13595Kenneth Enevoldsen, Isaac Chung, Imene Kerboua, et al.2025 · 101 citations
  25. Inverse Scaling: When Bigger Isn't BetterarXiv:2306.09479 · Transactions on Machine Learning Research (TMLR), 10/2023, https://openreview.net/forum?id=DwgRm72GQFIan R. McKenzie, Alexander Lyzhov, Michael Pieler, et al.2023 · 99 citations
  26. WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the WildarXiv:2406.04770Bill Yuchen Lin, Yuntian Deng, Khyathi Chandu, et al.2024 · 95 citations
  27. Boosting Language Models Reasoning with Chain-of-Knowledge PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianing Wang, Qiushi Sun, Xiang Li, et al.2024 · 94 citations
  28. MAmmoTH2: Scaling Instructions from the WebConference on Neural Information Processing Systems (NeurIPS)Xiang Yue, Tuney Zheng, Ge Zhang, et al.2024 · 94 citations
  29. FLASK: Fine-grained Language Model Evaluation based on Alignment Skill SetsarXiv:2307.10928Seonghyeon Ye, Doyoung Kim, Sungdong Kim, et al.2023 · 94 citations
  30. LLMs Are Few-Shot In-Context Low-Resource Language LearnersConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Samuel Cahyawijaya, Holy Lovenia, Pascale Fung2024 · 92 citations
  31. INSTRUCTEVAL: Towards Holistic Evaluation of Instruction-Tuned Large Language ModelsarXiv:2306.04757Yew Ken Chia, Pengfei Hong, Lidong Bing, et al.2023 · 92 citations
  32. PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM InferenceFindings of the Association for Computational LinguisticsDongjie Yang, Xiaodong Han, Yan Gao, et al.2024 · 91 citations
  33. WildTeaming at Scale: From In-the-Wild Jailbreaks to (Adversarially) Safer Language ModelsConference on Neural Information Processing Systems (NeurIPS)Liwei Jiang, Kavel Rao, Seungju Han, et al.2024 · 89 citations
  34. “My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language ModelsFindings of the Association for Computational LinguisticsXinpeng Wang, Bolei Ma, Chengzhi Hu, et al.2024 · 89 citations
  35. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 88 citations
  36. NLPositionality: Characterizing Design Biases of Datasets and ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Sebastin Santy, Jenny Liang, Ronan Le Bras, et al.2023 · 88 citations
  37. A Survey on Data Selection for Language ModelsarXiv:2402.16827Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.2024 · 85 citations
  38. BUFFET: Benchmarking Large Language Models for Few-shot Cross-lingual TransferConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Akari Asai, Sneha Kudugunta, Xinyan Yu, et al.2024 · 85 citations
  39. LLMs cannot find reasoning errors, but can correct them given the error locationFindings of the Association for Computational LinguisticsGladys Tyen, Hassan Mansoor, Victor Carbune, et al.2024 · 85 citations
  40. SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural ReasoningConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Bin Wang, Zhengyuan Liu, Xin Huang, et al.2024 · 85 citations
  41. NL-Augmenter: A Framework for Task-Sensitive Natural Language AugmentationNorthern European Journal of Language TechnologyKaustubh Dhole, Varun Gangal, Sebastian Gehrmann, et al.2023 · 85 citations
  42. ORCA: A Challenging Benchmark for Arabic Language UnderstandingFindings of the Association for Computational LinguisticsAbdelRahim Elmadany, ElMoatez Billah Nagoudi, Muhammad Abdul-Mageed2023 · 83 citations
  43. Style Over Substance: Evaluation Biases for Large Language ModelsInternational Conference on Computational Linguistics (COLING)Minghao Wu, Alham Fikri Aji2025 · 77 citations
  44. KoBBQ: Korean Bias Benchmark for Question AnsweringTransactions of the Association for Computational Linguistics (TACL)Jiho Jin, Jiseon Kim, Nayeon Lee, et al.2024 · 77 citations
  45. PUB: A Pragmatics Understanding Benchmark for Assessing LLMs' Pragmatics CapabilitiesSettaluri Sravanthi, Meet Doshi, Pavan Tankala, et al.2024 · 75 citations
  46. MEGAVERSE: Benchmarking Large Language Models Across Languages, Modalities, Models and TasksConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Sanchit Ahuja, Divyanshu Aggarwal, Varun Gumma, et al.2024 · 74 citations
  47. AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Harsh Trivedi, Tushar Khot, Mareike Hartmann, et al.2024 · 73 citations
  48. INCLUDE: Evaluating Multilingual Language Understanding with Regional KnowledgearXiv:2411.19799Angelika Romanou, Negar Foroutan, Anna Sotnikova, et al.2024 · 73 citations
  49. AlignBench: Benchmarking Chinese Alignment of Large Language ModelsarXiv:2311.18743Xiao Liu, Xuanyu Lei, Shengyuan Wang, et al.2023 · 73 citations
  50. ScandEval: A Benchmark for Scandinavian Natural Language ProcessingNordic Conference on Computational Linguistics (NoDaLiDa)Dan Nielsen2023 · 73 citations
  51. KMMLU: Measuring Massive Multitask Language Understanding in KoreanConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Guijin Son, Hanwool Lee, Sungdong Kim, et al.2025 · 72 citations
  52. MediQ: Question-Asking LLMs and a Benchmark for Reliable Interactive Clinical ReasoningConference on Neural Information Processing Systems (NeurIPS)Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, et al.2024 · 70 citations
  53. Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language ModelsarXiv:2305.14705Sheng Shen, Le Hou, Yanqi Zhou, et al.2023 · 69 citations
  54. Knowledge of Knowledge: Exploring Known-Unknowns Uncertainty with Large Language ModelsFindings of the Association for Computational LinguisticsAlfonso Amayuelas, Kyle Wong, Liangming Pan, et al.2024 · 66 citations
  55. CValues: Measuring the Values of Chinese Large Language Models from Safety to ResponsibilityarXiv:2307.09705Guohai Xu, Jiayi Liu, Ming Yan, et al.2023 · 63 citations
  56. Exploring the Impact of Instruction Data Scaling on Large Language Models: An Empirical Study on Real-World Use CasesarXiv:2303.14742Yunjie Ji, Yong Deng, Yan Gong, et al.2023 · 62 citations
  57. Large Language Model Routing with Benchmark DatasetsarXiv:2309.15789Tal Shnitzer, Anthony Ou, Mirian Silva, et al.2023 · 61 citations
  58. CMB: A Comprehensive Medical Benchmark in ChinesearXiv:2308.08833Xidong Wang, Guiming Hardy Chen, Dingjie Song, et al.2023 · 54 citations
  59. Language acquisition: do children and language models follow similar learning stages?arXiv:2306.03586Linnea Evanson, Yair Lakretz, Jean-Rémi King2023 · 53 citations
  60. Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling LawsarXiv:2401.00448Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.2024 · 51 citations
  61. Metaphor Understanding Challenge Dataset for LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiaoyu Tong, Rochelle Choenni, Martha Lewis, et al.2024 · 47 citations
  62. Transcending Scaling Laws with 0.1% Extra ComputearXiv:2210.11399Yi Tay, Jason Wei, Hyung Won Chung, et al.2022 · 41 citations
  63. SemEval-2025 Task 1: AdMIRe - Advancing Multimodal Idiomaticity RepresentationInternational Workshop on Semantic Evaluation (SemEval)Thomas Pickard, Aline Villavicencio, Maggie Mi, et al.2025 · 30 citations
  64. Observational Scaling Laws and the Predictability of Language Model PerformancearXiv:2405.10938Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto2024 · 30 citations
  65. Prediction of Arabic Legal Rulings using Large Language ModelsarXiv:2310.10260Adel Ammar, Anis Koubaa, Bilel Benjdira, et al.2023 · 27 citations
  66. The Quantization Model of Neural ScalingarXiv:2303.13506Eric J. Michaud, Ziming Liu, Uzay Girit, et al.2023 · 27 citations
  67. Construction Grammar Provides Unique Insight into Neural Language ModelsInternational Workshop on Construction Grammars and NLPLeonie Weissweiler, Taiqi He, Naoki Otani, et al.2023 · 26 citations
  68. Do Large Language Models Understand Word Senses?Domenico Meconi, Simone Stirpe, Federico Martelli2025 · 18 citations
  69. Dialogue Discourse Parsing as Generation: A Sequence-to-Sequence LLM-based ApproachAnnual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)Chuyuan Li, Yuwei Yin, Giuseppe Carenini2024 · 11 citations
  70. A Survey of Idiom Datasets for Psycholinguistic and Computational ResearchConference on Natural Language ProcessingMichael Flor, Xinyi Liu, Anna Feldman2025 · 5 citations
  71. ITUNLP at MWE-2026 AdMIRe 2: A Zero-Shot LLM Pipeline for Multimodal Idiom Understanding and RankingWorkshop on Multiword Expressions (MWE)Atakan Site, Oğuz Ali Arslan, Gülşen Eryiğit2026 · 1 citation
  72. SynthLLM: An LLM-based Scalable Synthetic Data Generation Pipeline for Low-Resource LanguagesLanguage Resources and Evaluation Conference (LREC)Solmaz Panahi, Vasudevan Nedumpozhimana, John Kelleher2026 · 1 citation
  73. Construction Grammar Evidence for How LLMs Use Context-Directed Extrapolation to Solve TasksInternational Workshop on Construction Grammars and NLPHarish Tayyar Madabushi, Claire Bonial2025 · 1 citation
  74. EduBench: A Portuguese Benchmark for Open-Ended Discursive Question AnsweringLanguage Resources and Evaluation Conference (LREC)Pedro Henrique Paiola, Luís Gabriel Damiati Mendes, Bruno de Oliveira Monchelato, et al.2026
  75. EIFFEL: a novel benchmark to measure bias of English heavy training on French idiomatic expressionsAnnual Meeting of the Association for Computational Linguistics (ACL)Charlotte Noel, Nicholas Asher, Olivier Gouvert, et al.2026
  76. Open-access Dataset on Acceptability Ratings of Korean Clausal Constructions by Humans and GPT ModelsLanguage Resources and Evaluation Conference (LREC)Gyu-Ho Shin, Soo-Hwan Lee, Chanyoung Lee2026
  77. Persona-Aware Evaluation of Cognitive Bias in LLMs: From Benchmark to Applied Decision-MakingLanguage Resources and Evaluation Conference (LREC)Katsumasa Yoshikawa, Junya Takayama, Takato Yamazaki2026
  78. Sentiment Analysis and Language Models for KwanyamaLanguage Resources and Evaluation Conference (LREC)Ndapa Nakashole2026
  79. When Words Don't Mean What They Say: Figurative Understanding in Bengali IdiomsLanguage Resources and Evaluation Conference (LREC)Adib Sakhawat, Shamim Ara Parveen, Md Ruhul Amin, et al.2026
  80. ZIP: Quantifying Which Words Matter in Zero-Shot Instructional PromptsJoint Conference on Lexical and Computational Semantics (*SEM)Nikta Gohari Sadr, Sangmitra Madhusudan, Arash Asgari, et al.2026
  81. Complexity factors of language models in reading comprehension: a controlled experiment (Étude des facteurs de complexité des modèles de langage dans une tâche de compréhension de lecture à l'aide d'une expérience contrôlée sémantiquement)JEP-TALN-RECITAL (the French-speaking conferences on speech and natural language processing)Elie Antoine, Frederic Bechet, Géraldine Damnati, et al.2024

1 2

1,048 more citing papers of our library have no page here yet.

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/yadollah-yaghoobzadeh/cited-by/page/2/