🧑‍🔬 Who cites Thomas Kollar

662 citations of their works from 571 papers of our library (of the 149,439 whose bibliographies we read) · 87 with a page here, the most cited first · ← Thomas Kollar

1. The Llama 3 Herd of ModelsarXiv:2407.21783Aaron Grattafiori, Abhimanyu Dubey, Abhinav Jauhri, et al.2024 · 7,682 citations
2. Semantic Parsing on Freebase from Question-Answer PairsConference on Empirical Methods in Natural Language Processing (EMNLP)Jonathan Berant, Andrew Chou, Roy Frostig, et al.2013 · 2,331 citations
3. Neural Module NetworksIEEE Computer Society Conference on Computer Vision and Pattern RecognitionJacob Andreas, Marcus Rohrbach, Trevor Darrell, et al.2015 · 1,140 citations
4. Compositional Semantic Parsing on Semi-Structured TablesAnnual Meeting of the Association for Computational Linguistics (ACL)Panupong Pasupat, Percy Liang2015 · 918 citations
5. A simple neural network module for relational reasoningarXiv:1706.01427Adam Santoro, David Raposo, David G. T. Barrett, et al.2017 · 632 citations
6. Learning to Compose Neural Networks for Question AnsweringConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Jacob Andreas, Marcus Rohrbach, Trevor Darrell, et al.2016 · 573 citations
7. LLaVA-OneVision: Easy Visual Task TransferarXiv:2408.03326Bo Li, Yuanhan Zhang, Dong Guo, et al.2024 · 477 citations
8. Kimi k1.5: Scaling Reinforcement Learning with LLMsarXiv:2501.12599Kimi Team, Angang Du, Bofei Gao, et al.2025 · 431 citations
9. Scaling Semantic Parsers with On-the-Fly Ontology MatchingConference on Empirical Methods in Natural Language Processing (EMNLP)Tom Kwiatkowski, Eunsol Choi, Yoav Artzi, et al.2013 · 363 citations
10. Modeling Biological Processes for Reading ComprehensionConference on Empirical Methods in Natural Language Processing (EMNLP)Jonathan Berant, Vivek Srikumar, Pei-Chun Chen, et al.2014 · 292 citations
11. RedPajama: an Open Dataset for Training Large Language ModelsConference on Neural Information Processing Systems (NeurIPS)Maurice Weber, Daniel Fu, Quentin Anthony, et al.2024 · 260 citations
12. Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language ModelsIEEE Computer Society Conference on Computer Vision and Pattern RecognitionMatt Deitke, Christopher Clark, Sangho Lee, et al.2024 · 216 citations
13. What matters when building vision-language models?Conference on Neural Information Processing Systems (NeurIPS)Hugo Laurençon, Leo Tronchon, Matthieu Cord, et al.2024 · 212 citations
14. Cambrian-1: A Fully Open, Vision-Centric Exploration of Multimodal LLMsConference on Neural Information Processing Systems (NeurIPS)Shengbang Tong, Ellis Brown, Penghao Wu, et al.2024 · 208 citations
15. Towards Faithful Model Explanation in NLP: A SurveyComputational LinguisticsQing Lyu, Marianna Apidianaki, Chris Callison-Burch2024 · 197 citations
16. 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 · 191 citations
17. SmolLM2: When Smol Goes Big — Data-Centric Training of a Small Language ModelarXiv:2502.02737Loubna Ben Allal, Anton Lozhkov, Elie Bakouch, et al.2025 · 181 citations
18. Olmo 3arXiv:2512.13961Team Olmo: Allyson Ettinger, Amanda Bertsch, Bailey Kuehl, et al.2025 · 130 citations
19. Fanar: An Arabic-Centric Multimodal Generative AI PlatformarXiv:2501.13944Fanar Team: Ummar Abbas, Mohammad Shahmeer Ahmad, Firoj Alam, et al.2025 · 127 citations
20. FAST: Efficient Action Tokenization for Vision-Language-Action ModelsarXiv:2501.09747Karl Pertsch, Kyle Stachowicz, Brian Ichter, et al.2025 · 123 citations
21. OpenThoughts: Data Recipes for Reasoning ModelsarXiv:2506.04178Etash Guha, Ryan Marten, Sedrick Keh, et al.2025 · 122 citations
22. FineWeb2: One Pipeline to Scale Them All — Adapting Pre-Training Data Processing to Every LanguagearXiv:2506.20920Guilherme Penedo, Hynek Kydliček, Vinko Sabolčec, et al.2025 · 99 citations
23. GLM-5: from Vibe Coding to Agentic EngineeringarXiv:2602.15763Aohan Zeng, Xin Lv, Zhenyu Hou, et al.2026 · 95 citations
24. How to Train Long-Context Language Models (Effectively)Annual Meeting of the Association for Computational Linguistics (ACL)Tianyu Gao, Alexander Wettig, Howard Yen, et al.2025 · 89 citations
25. Small Language Models: Survey, Measurements, and InsightsarXiv:2409.15790Zhenyan Lu, Xiang Li, Dongqi Cai, et al.2024 · 88 citations
26. MoBA: Mixture of Block Attention for Long-Context LLMsConference on Neural Information Processing Systems (NeurIPS)Enzhe Lu, Zhejun Jiang, Jingyuan Liu, et al.2025 · 80 citations
27. A Bayesian Model of Grounded Color SemanticsTransactions of the Association for Computational Linguistics (TACL)Brian McMahan, Matthew Stone2015 · 75 citations
28. Apertus: Democratizing Open and Compliant LLMs for Global Language EnvironmentsAnnual Meeting of the Association for Computational Linguistics (ACL)Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.2026 · 68 citations
29. Seed1.5-VL Technical ReportarXiv:2505.07062Dong Guo, Faming Wu, Feida Zhu, et al.2025 · 67 citations
30. Macro Grammars and Holistic Triggering for Efficient Semantic ParsingConference on Empirical Methods in Natural Language Processing (EMNLP)Yuchen Zhang, Panupong Pasupat, Percy Liang2017 · 67 citations
31. Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining DatasetAnnual Meeting of the Association for Computational Linguistics (ACL)Dan Su, Kezhi Kong, Ying Lin, et al.2025 · 65 citations
32. mmBERT: A Modern Multilingual Encoder with Annealed Language LearningarXiv:2509.06888Marc Marone, Orion Weller, William Fleshman, et al.2025 · 59 citations
33. Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling LawsarXiv:2401.00448Nikhil Sardana, Jacob Portes, Sasha Doubov, et al.2024 · 57 citations
34. RegMix: Data Mixture as Regression for Language Model Pre-trainingarXiv:2407.01492Qian Liu, Xiaosen Zheng, Niklas Muennighoff, et al.2024 · 57 citations
35. Hymba: A Hybrid-head Architecture for Small Language ModelsarXiv:2411.13676Xin Dong, Yonggan Fu, Shizhe Diao, et al.2024 · 50 citations
36. Scaling Laws with Vocabulary: Larger Models Deserve Larger VocabulariesarXiv:2407.13623Chaofan Tao, Qian Liu, Longxu Dou, et al.2024 · 46 citations
37. olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language ModelsarXiv:2502.18443Jake Poznanski, Aman Rangapur, Jon Borchardt, et al.2025 · 44 citations
38. Stop Looking for “Important Tokens” in Multimodal Language Models: Duplication Matters MoreConference on Empirical Methods in Natural Language Processing (EMNLP)Zichen Wen, Yifeng Gao, Shaobo Wang, et al.2025 · 44 citations
39. Paloma: A Benchmark for Evaluating Language Model FitConference on Neural Information Processing Systems (NeurIPS)Ian Magnusson, Akshita Bhagia, Valentin Hofmann, et al.2023 · 42 citations
40. Observational Scaling Laws and the Predictability of Language Model PerformancearXiv:2405.10938Yangjun Ruan, Chris J. Maddison, Tatsunori Hashimoto2024 · 40 citations
41. Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer ModelsarXiv:2504.03624NVIDIA: Aaron Blakeman, Aarti Basant, Abhinav Khattar, et al.2025 · 38 citations
42. MiMo-VL Technical ReportarXiv:2506.03569Xiaomi LLM-Core Team, Zihao Yue, Zhenru Lin, et al.2025 · 33 citations
43. Scaling Laws and Compute-Optimal Training Beyond Fixed Training DurationsConference on Neural Information Processing Systems (NeurIPS)Alexander Hägele, Elie Bakouch, Atli Kosson, et al.2024 · 31 citations
44. Planning, Inference and Pragmatics in Sequential Language GamesTransactions of the Association for Computational Linguistics (TACL)Fereshte Khani, Noah D. Goodman, Percy Liang2018 · 31 citations
45. Towards Effective and Efficient Continual Pre-training of Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Jie Chen, Zhipeng Chen, Jiapeng Wang, et al.2025 · 29 citations
46. Nemotron 3 Nano: Open, Efficient Mixture-of-Experts Hybrid Mamba-Transformer Model for Agentic ReasoningarXiv:2512.20848NVIDIA: Aaron Blakeman, Aaron Grattafiori, Aarti Basant, et al.2025 · 27 citations
47. Distillation Scaling LawsarXiv:2502.08606Dan Busbridge, Amitis Shidani, Floris Weers, et al.2025 · 26 citations
48. LLaVA Steering: Visual Instruction Tuning with 500x Fewer Parameters through Modality Linear Representation-SteeringAnnual Meeting of the Association for Computational Linguistics (ACL)Jinhe Bi, Yujun Wang, Haokun Chen, et al.2025 · 24 citations
49. RWKV-7 "Goose" with Expressive Dynamic State EvolutionarXiv:2503.14456Bo Peng, Ruichong Zhang, Daniel Goldstein, et al.2025 · 23 citations
50. MiniCPM4: Ultra-Efficient LLMs on End DevicesarXiv:2506.07900MiniCPM Team, Chaojun Xiao, Yuxuan Li, et al.2025 · 22 citations
51. Scaling Latent Reasoning via Looped Language ModelsarXiv:2510.25741Rui-Jie Zhu, Zixuan Wang, Kai Hua, et al.2025 · 22 citations
52. The Vector Grounding ProblemarXiv:2304.01481Dimitri Coelho Mollo, Raphael Milliere2023 · 20 citations
53. Resolving Discrepancies in Compute-Optimal Scaling of Language ModelsConference on Neural Information Processing Systems (NeurIPS)Tomer Porian, Mitchell Wortsman, Jenia Jitsev, et al.2024 · 19 citations
54. Dataset Decomposition: Faster LLM Training with Variable Sequence Length CurriculumConference on Neural Information Processing Systems (NeurIPS)Hadi Pouransari, Chun-Liang Li, Jen-Hao Rick Chang, et al.2024 · 16 citations
55. A Survey on Latent ReasoningarXiv:2507.06203Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, et al.2025 · 15 citations
56. Rethinking Reflection in Pre-TrainingarXiv:2504.04022Essential AI: Darsh J Shah, Peter Rushton, Somanshu Singla, et al.2025 · 15 citations
57. Maximize Your Data's Potential: Enhancing LLM Accuracy with Two-Phase PretrainingarXiv:2412.15285Steven Feng, Shrimai Prabhumoye, Kezhi Kong, et al.2024 · 12 citations
58. MiniPLM: Knowledge Distillation for Pre-Training Language ModelsarXiv:2410.17215Yuxian Gu, Hao Zhou, Fandong Meng, et al.2024 · 12 citations
59. Why do LLaVA Vision-Language Models Reply to Images in English?Findings of the Association for Computational LinguisticsMusashi Hinck, Carolin Holtermann, Matthew Lyle Olson, et al.2024 · 12 citations
60. Centurio: On Drivers of Multilingual Ability of Large Vision-Language ModelAnnual Meeting of the Association for Computational Linguistics (ACL)Gregor Geigle, Florian Schneider, Carolin Holtermann, et al.2025 · 9 citations
61. Bilingual Adaptation of Monolingual Foundation ModelsarXiv:2407.12869Gurpreet Gosal, Yishi Xu, Gokul Ramakrishnan, et al.2024 · 7 citations
62. Arabic Stable LM: Adapting Stable LM 2 1.6B to ArabicarXiv:2412.04277Zaid Alyafeai, Michael Pieler, Hannah Teufel, et al.2024 · 6 citations
63. Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive TasksAnnual Meeting of the Association for Computational Linguistics (ACL)Wenqi Zhang, Mengna Wang, Gangao Liu, et al.2026 · 5 citations
64. Aleph-Alpha-GermanWeb: Improving German-language LLM pre-training with model-based data curation and synthetic data generationConference of the European Chapter of the Association for Computational Linguistics (EACL)Thomas F Burns, Letitia Parcalabescu, Stephan Waeldchen, et al.2026 · 4 citations
65. Lizard: An Efficient Linearization Framework for Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Chien Van Nguyen, Huy Huu Nguyen, Ruiyi Zhang, et al.2026 · 2 citations
66. QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented GenerationFindings of the Association for Computational LinguisticsDehai Min, Kailin Zhang, Tongtong Wu, et al.2026 · 2 citations
67. The olmOCR Project: Building Fully Open OCR using VLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Jake Poznanski, Kyle Lo, Luca Soldaini2026 · 2 citations
68. Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Kailai Yang, Xiao Liu, Lei Ji, et al.2026 · 1 citation
69. KletterMix: Climbing Toward High-Quality German Pretraining Data - The Full ReportarXiv:2606.03773Maurice Kraus, Ruben Harle, Sebastian Sztwiertnia, et al.2026 · 1 citation
70. Libra-VLA: Achieving Learning Equilibrium via Asynchronous Coarse-to-Fine Dual-SystemAnnual Meeting of the Association for Computational Linguistics (ACL)Yifei Wei, Linqing Zhong, Yi Liu, et al.2026 · 1 citation
71. Biomed-Enriched: Data-Efficient Biomedical Pretraining via Paragraph-Level AnnotationFindings of the Association for Computational LinguisticsRian Touchent, Nathan Godey, Éric Villemonte de la Clergerie2026
72. Bring the Apple, Not the Sofa: Impact of Irrelevant Context in Embodied AI Commands on VLA ModelsConference of the European Chapter of the Association for Computational Linguistics (EACL)Andrey Moskalenko, Daria Pugacheva, Denis Shepelev, et al.2026
73. Context-Aware Language Understanding in Human-Robot Dialogue with LLMsInternational Workshop on Spoken Dialogue System TechnologySvetlana Stoyanchev, Youmna Farag, Simon Keizer, et al.2026
74. Dialectal Filtering: Synthesizing Kurdish Corpora for Low-Resource Varieties by Utilizing “Noise” in Large Textual DataLanguage Resources and Evaluation Conference (LREC)Christian Schuler, Raman Ahmad, Ānrán Wáng, et al.2026
75. Frame2KG: A Benchmark and Evaluation Toolkit for Interpretable Frame-to-Graph GenerationLanguage Resources and Evaluation Conference (LREC)Lewis N. Watson, Carl Strathearn, Kenny Mitchell, et al.2026
76. GOAT: A Training Framework for Goal-Oriented Agent with ToolsFindings of the Association for Computational LinguisticsHyunji Min, Sangwon Jung, Junyoung Sung, et al.2026
77. Limited Linguistic Diversity in Embodied AI DatasetsAnnual Meeting of the Association for Computational Linguistics (ACL)Selma Liliane Wanna, Agnes Luhtaru, Jonathan Salfity, et al.2026
78. MIRTH: Mutual-Information Reasoning with Temporal Hubs for Vision-Language-Action AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Hao Sun, Yu Song, Teng Shiyu, et al.2026
79. Probing the Dynamics of Syntactic Ability Acquisition Throughout LLM PretrainingHiroshi Matsuda, Masayuki Asahara2026
80. Rethinking Data Mixture for Large Language Models: A Comprehensive Survey and New PerspectivesFindings of the Association for Computational LinguisticsYajiao Liu, Congliang Chen, Junchi Yang, et al.2026
81. Rewriting History: A Recipe for Interventional Analyses to Study Data Effects on Model BehaviorTransactions of the Association for Computational Linguistics (TACL)Rahul Nadkarni, Yanai Elazar, Hila Gonen, et al.2026
82. SciPedia: Unlocking the Value of Scientific Data for Pre-trainingAnnual Meeting of the Association for Computational Linguistics (ACL)Yiwei Qin, Zhen Huang, Tiantian Mi, et al.2026
83. SELECting over Tokens: Curating Pre-training Data at Scale via Token ClassificationAnnual Meeting of the Association for Computational Linguistics (ACL)Xin Tong, Weidong Zhang, Jiaang Li, et al.2026
84. Systematic Evaluation of the Quality of Synthetic Clinical Notes Rephrased by LLMs at Million-Note ScaleBioNLPJinghui Liu, Sarvesh Soni, Anthony Nguyen2026
85. UniGeM: Unifying Data Selection and Mixing via Geometric Exploration and MiningFindings of the Association for Computational LinguisticsChanghao Wang, Yunfeiyu, Xinhao Yao, et al.2026
86. VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-EvaluationFindings of the Association for Computational LinguisticsSeongheon Park, Changdae Oh, Hyeong Kyu Choi, et al.2026
87. Embodied Intelligence Systems Based on Large Models: A Survey (基于大模型的具身智能系统综述)Acta Automatica Sinica (自动化学报)Wensheng Wang (王文晟), Ning Tan (谭宁), Kai Huang (黄凯), et al.2025

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