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Who cites Andy Davis

2,112 citations of their works from 2,080 papers of our library (of the 149,439 whose bibliographies we read) · 215 with a page here, the most cited first · page 2 of 3 · 101–200 · ← Andy Davis

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  1. Character-Level Language Modeling with Deeper Self-AttentionProceedings of the AAAI Conference on Artificial IntelligenceRami Al-Rfou, Dokook Choe, Noah Constant, et al.2018 · 138 citations
  2. AdaMix: Mixture-of-Adaptations for Parameter-efficient Model TuningConference on Empirical Methods in Natural Language Processing (EMNLP)Yaqing Wang, Sahaj Agarwal, Subhabrata Mukherjee, et al.2022 · 135 citations
  3. Scaling Down to Scale Up: A Guide to Parameter-Efficient Fine-TuningarXiv:2303.15647Vladislav Lialin, Vijeta Deshpande, Xiaowei Yao, et al.2023 · 129 citations
  4. Scaling Vision with Sparse Mixture of ExpertsarXiv:2106.05974Carlos Riquelme, Joan Puigcerver, Basil Mustafa, et al.2021 · 128 citations
  5. Learning to Represent Programs with GraphsarXiv:1711.00740Miltiadis Allamanis, Marc Brockschmidt, Mahmoud Khademi2017 · 127 citations
  6. Making Neural QA as Simple as Possible but not SimplerarXiv:1703.04816Dirk Weissenborn, Georg Wiese, Laura Seiffe2017 · 122 citations
  7. ChID: A Large-scale Chinese IDiom Dataset for Cloze TestAnnual Meeting of the Association for Computational Linguistics (ACL)Chujie Zheng, Minlie Huang, Aixin Sun2019 · 119 citations
  8. Platypus: Quick, Cheap, and Powerful Refinement of LLMsarXiv:2308.07317Ariel N. Lee, Cole J. Hunter, Nataniel Ruiz2023 · 117 citations
  9. Mixture-of-Agents Enhances Large Language Model CapabilitiesarXiv:2406.04692Junlin Wang, Jue Wang, Ben Athiwaratkun, et al.2024 · 116 citations
  10. MoEfication: Transformer Feed-forward Layers are Mixtures of ExpertsFindings of the Association for Computational LinguisticsZhengyan Zhang, Yankai Lin, Zhiyuan Liu, et al.2022 · 115 citations
  11. Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language ModelsarXiv:2208.03306Margaret Li, Suchin Gururangan, Tim Dettmers, et al.2022 · 114 citations
  12. Entity Linking in 100 LanguagesConference on Empirical Methods in Natural Language Processing (EMNLP)Jan A. Botha, Zifei Shan, Daniel Gillick2020 · 114 citations
  13. A Survey on Efficient Inference for Large Language ModelsarXiv:2404.14294Zixuan Zhou, Xuefei Ning, Ke Hong, et al.2024 · 113 citations
  14. Efficient Large Scale Language Modeling with Mixtures of ExpertsarXiv:2112.10684Mikel Artetxe, Shruti Bhosale, Naman Goyal, et al.2021 · 113 citations
  15. Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to SystemsACM Computing SurveysXupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.2023 · 110 citations
  16. LoraHub: Efficient Cross-Task Generalization via Dynamic LoRA CompositionarXiv:2307.13269Chengsong Huang, Qian Liu, Bill Yuchen Lin, et al.2023 · 108 citations
  17. A Pretrainer's Guide to Training Data: Measuring the Effects of Data Age, Domain Coverage, Quality, & ToxicityarXiv:2305.13169Shayne Longpre, Gregory Yauney, Emily Reif, et al.2023 · 104 citations
  18. Sparse Upcycling: Training Mixture-of-Experts from Dense CheckpointsarXiv:2212.05055Aran Komatsuzaki, Joan Puigcerver, James Lee-Thorp, et al.2022 · 98 citations
  19. TextGrad: Automatic "Differentiation" via TextarXiv:2406.07496Mert Yuksekgonul, Federico Bianchi, Joseph Boen, et al.2024 · 96 citations
  20. LoRAMoE: Alleviating World Knowledge Forgetting in Large Language Models via MoE-Style PluginAnnual Meeting of the Association for Computational Linguistics (ACL)Shihan Dou, Enyu Zhou, Yan Liu, et al.2024 · 93 citations
  21. Accelerating Distributed MoE Training and Inference with LinaarXiv:2210.17223Jiamin Li, Yimin Jiang, Yibo Zhu, et al.2022 · 92 citations
  22. Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xudong Lu, Qi Liu, Yuhui Xu, et al.2024 · 88 citations
  23. Liger Kernel: Efficient Triton Kernels for LLM TrainingarXiv:2410.10989Pin-Lun Hsu, Yun Dai, Vignesh Kothapalli, et al.2024 · 87 citations
  24. LLaMA-MoE: Building Mixture-of-Experts from LLaMA with Continual Pre-TrainingConference on Empirical Methods in Natural Language Processing (EMNLP)Tong Zhu, Xiaoye Qu, Daize Dong, et al.2024 · 85 citations
  25. Deep Models for Arabic Dialect Identification on Benchmarked DataInternational Conference on Computational Linguistics (COLING)Mohamed Elaraby, Muhammad Abdul-Mageed2018 · 85 citations
  26. CoLT5: Faster Long-Range Transformers with Conditional ComputationConference on Empirical Methods in Natural Language Processing (EMNLP)Joshua Ainslie, Tao Lei, Michiel de Jong, et al.2023 · 84 citations
  27. Language Modeling for Morphologically Rich Languages: Character-Aware Modeling for Word-Level PredictionTransactions of the Association for Computational Linguistics (TACL)Daniela Gerz, Ivan Vulić, Edoardo Ponti, et al.2018 · 82 citations
  28. 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
  29. Large Language Models in Law: A SurveyarXiv:2312.03718Jinqi Lai, Wensheng Gan, Jiayang Wu, et al.2023 · 80 citations
  30. SOLAR 10.7B: Scaling Large Language Models with Simple yet Effective Depth Up-ScalingarXiv:2312.15166Dahyun Kim, Chanjun Park, Sanghoon Kim, et al.2023 · 77 citations
  31. TASO: Optimizing Deep Learning Computation with Automatic Generation of Graph SubstitutionsSOSP 2019Zhihao Jia, Oded Padon, James Thomas, et al.2019 · 72 citations
  32. Mixture-of-Experts Meets Instruction Tuning:A Winning Combination for Large Language ModelsarXiv:2305.14705Sheng Shen, Le Hou, Yanqi Zhou, et al.2023 · 70 citations
  33. Are you serious?: Rhetorical Questions and Sarcasm in Social Media DialogShereen Oraby, Vrindavan Harrison, Amita Misra, et al.2017 · 70 citations
  34. Pushing Mixture of Experts to the Limit: Extremely Parameter Efficient MoE for Instruction TuningarXiv:2309.05444Ted Zadouri, Ahmet Ustun, Arash Ahmadian, et al.2023 · 69 citations
  35. OpenMoE: An Early Effort on Open Mixture-of-Experts Language ModelsarXiv:2402.01739Fuzhao Xue, Zian Zheng, Yao Fu, et al.2024 · 64 citations
  36. MiMo-V2-Flash Technical ReportarXiv:2601.02780Xiaomi LLM-Core Team; Bangjun Xiao; Bingquan Xia; Bo Yang; Bofei Gao; Bowen Shen; Chen Zhang; Chenhong He; Chiheng Lou; Fuli Luo; Gang Wang; Gang Xie; Hailin Zhang; Hanglong Lv; Hanyu Li; Heyu Chen; Hongshen Xu; Houbin Zhang; Huaqiu Liu; Jiangshan Duo; Jianyu Wei; Jiebao Xiao; Jinhao Dong; Jun Shi; Junhao Hu; Kainan Bao; Kang Zhou; Lei Li; Liang Zhao; Linghao Zhang; Peidian Li; Qianli Chen; Shaohui Liu; Shihua Yu; Shijie Cao; Shimao Chen; Shouqiu Yu; Shuo Liu; Tianling Zhou; Weijiang Su; Weikun Wang; Wenhan Ma; Xiangwei Deng; Bohan Mao; Bowen Ye; Can Cai; Chenghua Wang; Chengxuan Zhu; Chong Ma; Chun Chen; Chunan Li; Dawei Zhu; Deshan Xiao; Dong Zhang; Duo Zhang; Fangyue Liu; Feiyu Yang; Fengyuan Shi; Guoan Wang; Hao Tian; Hao Wu; Heng Qu; Hongfei Yi; Hongxu An; Hongyi Guan; Xing Zhang; Yifan Song; Yihan Yan; Yihao Zhao; Yingchun Lai; Yizhao Gao; Yu Cheng; Yuanyuan Tian; Yudong Wang; Zhen Tang; Zhengju Tang; Zhengtao Wen; Zhichao Song; Zhixian Zheng; Zihan Jiang; Jian Wen; Jiarui Sun; Jiawei Li; Jinlong Xue; Jun Xia; Kai Fang; Menghang Zhu; Nuo Chen; Qian Tu; Qihao Zhang; Qiying Wang; Rang Li; Rui Ma; Shaolei Zhang; Shengfan Wang; Shicheng Li; Shuhao Gu; Shuhuai Ren; Sirui Deng; Tao Guo; Tianyang Lu; Weiji Zhuang; Weikang Zhang; Weimin Xiong; Wenshan Huang; Wenyu Yang; Xin Zhang; Xing Yong; Xu Wang; Xueyang Xie; Yilin Jiang; Yixin Yang; Yongzhe He; Yu Tu; Yuanliang Dong; Yuchen Liu; Yue Ma; Yue Yu; Yuxing Xiang; Zhaojun Huang; Zhenru Lin; Zhipeng Xu; Zhiyang Chen; Zhonghua Deng; Zihan Zhang;, Zihao Yue2026 · 60 citations
  37. Highly Effective Arabic Diacritization using Sequence to Sequence ModelingConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Hamdy Mubarak, Ahmed Abdelali, Hassan Sajjad, et al.2019 · 51 citations
  38. MathChat: Converse to Tackle Challenging Math Problems with LLM AgentsarXiv:2306.01337Yiran Wu; Feiran Jia; Shaokun Zhang; Hangyu Li; Erkang Zhu; Yue Wang; Yin Tat Lee; Richard Peng; Qingyun Wu;, Chi Wang2023 · 46 citations
  39. Cross-Domain Generalization of Neural Constituency ParsersDaniel Fried, Nikita Kitaev, Dan Klein2019 · 46 citations
  40. PanGu-{\Sigma}: Towards Trillion Parameter Language Model with Sparse Heterogeneous ComputingarXiv:2303.10845Xiaozhe Ren, Pingyi Zhou, Xinfan Meng, et al.2023 · 40 citations
  41. Fire-Flyer AI-HPC: A Cost-Effective Software-Hardware Co-Design for Deep Learning2012 International Conference for High Performance Computing, Networking, Storage and AnalysisWei An, Xiao Bi, Guanting Chen, et al.2024 · 34 citations
  42. Symbolic Learning Enables Self-Evolving AgentsarXiv:2406.18532Wangchunshu Zhou, Yixin Ou, Shengwei Ding, et al.2024 · 34 citations
  43. A Survey of Small Language ModelsarXiv:2410.20011Chien Van Nguyen, Xuan Shen, Ryan Aponte, et al.2024 · 31 citations
  44. PropSegmEnt: A Large-Scale Corpus for Proposition-Level Segmentation and Entailment RecognitionFindings of the Association for Computational LinguisticsSihao Chen, Senaka Buthpitiya, Alex Fabrikant, et al.2023 · 31 citations
  45. Jamba-1.5: Hybrid Transformer-Mamba Models at ScalearXiv:2408.12570Jamba Team: Barak Lenz, Alan Arazi, Amir Bergman, et al.2024 · 30 citations
  46. JetMoE: Reaching Llama2 Performance with 0.1M DollarsarXiv:2404.07413Yikang Shen, Zhen Guo, Tianle Cai, et al.2024 · 28 citations
  47. A Survey on Asking Clarification Questions Datasets in Conversational SystemsAnnual Meeting of the Association for Computational Linguistics (ACL)Hossein A. Rahmani, Xi Wang, Yue Feng, et al.2023 · 28 citations
  48. 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
  49. Distillation Scaling LawsarXiv:2502.08606Dan Busbridge, Amitis Shidani, Floris Weers, et al.2025 · 26 citations
  50. Predicting In-Game Actions from Interviews of NBA PlayersComputational LinguisticsNadav Oved, Amir Feder, Roi Reichart2020 · 24 citations
  51. Demons in the Detail: On Implementing Load Balancing Loss for Training Specialized Mixture-of-Expert ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zihan Qiu, Zeyu Huang, Bo Zheng, et al.2025 · 21 citations
  52. ModuleFormer: Modularity Emerges from Mixture-of-ExpertsarXiv:2306.04640Yikang Shen, Zheyu Zhang, Tianyou Cao, et al.2023 · 21 citations
  53. CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and AugmentationTransactions of the Association for Computational Linguistics (TACL)Ingo Ziegler, Abdullatif Köksal, Desmond Elliott, et al.2025 · 20 citations
  54. Few-Shot Anaphora Resolution in Scientific Protocols via Mixtures of In-Context ExpertsFindings of the Association for Computational LinguisticsNghia T. Le, Fan Bai, Alan Ritter2022 · 20 citations
  55. Deep Contextualized Pairwise Semantic Similarity for Arabic Language QuestionsProceedings - International Conference on Tools with Artificial Intelligence, TAIHesham Al-Bataineh, Wael Farhan, Ahmad Mustafa, et al.2019 · 16 citations
  56. ConPET: Continual Parameter-Efficient Tuning for Large Language ModelsarXiv:2309.14763Chenyang Song, Xu Han, Zheni Zeng, et al.2023 · 14 citations
  57. ARBML: Democratizing Arabic Natural Language Processing ToolsWorkshop for NLP Open Source Software (NLP-OSS)Zaid Alyafeai, Maged S. Al-Shaibani2020 · 14 citations
  58. Maximize Your Data's Potential: Enhancing LLM Accuracy with Two-Phase PretrainingarXiv:2412.15285Steven Feng, Shrimai Prabhumoye, Kezhi Kong, et al.2024 · 12 citations
  59. Locate, Steer, and Improve: A Practical Survey of Actionable Mechanistic Interpretability in Large Language ModelsFindings of the Association for Computational LinguisticsHengyuan Zhang, Zhihao Zhang, Ercong Nie, et al.2026 · 9 citations
  60. Faster MoE LLM Inference for Extremely Large ModelsFindings of the Association for Computational LinguisticsHaoqi Yang, Luohe Shi, Qiwei Li, et al.2026 · 8 citations
  61. Pangu Ultra MoE: How to Train Your Big MoE on Ascend NPUsarXiv:2505.04519Yehui Tang, Yichun Yin, Yaoyuan Wang, et al.2025 · 8 citations
  62. Fine-tuning Large Language Models with Limited Data: A Survey and Practical GuideTransactions of the Association for Computational Linguistics (TACL)Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe, et al.2026 · 7 citations
  63. MoM: Linear Sequence Modeling with Mixture-of-MemoriesarXiv:2502.13685Jusen Du, Weigao Sun, Disen Lan, et al.2025 · 7 citations
  64. GRIN: GRadient-INformed MoEarXiv:2409.12136Liyuan Liu, Young Jin Kim, Shuohang Wang, et al.2024 · 7 citations
  65. PROPER: A Progressive Learning Framework for Personalized Large Language Models with Group-Level AdaptationAnnual Meeting of the Association for Computational Linguistics (ACL)Linhai Zhang, Jialong Wu, Deyu Zhou, et al.2025 · 6 citations
  66. A Characterwise Windowed Approach to Hebrew Morphological SegmentationAmir Zeldes2018 · 6 citations
  67. Let's CONFER: A Dataset for Evaluating Natural Language Inference Models on CONditional InFERence and PresuppositionarXiv:2506.06133Tara Azin, Daniel Dumitrescu, Diana Inkpen, et al.2025 · 4 citations
  68. Pangu Pro MoE: Mixture of Grouped Experts for Efficient SparsityarXiv:2505.21411Yehui Tang, Xiaosong Li, Fangcheng Liu, et al.2025 · 4 citations
  69. Automatically Detecting Reduced-formed English Pronunciations by Using Deep LearningWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Lei Chen, Chenglin Jiang, Yiwei Gu, et al.2022 · 4 citations
  70. DeepSTL — From English Requirements to Signal Temporal LogicarXiv:2109.10294Jie He, Ezio Bartocci, Dejan Ničkovic, et al.2021 · 4 citations
  71. The University of Texas System Submission for the Code-Switching Workshop Shared Task 2018Workshop on Computational Approaches to Linguistic Code-SwitchingFlorian Janke, Tongrui Li, Eric Rincón, et al.2018 · 4 citations
  72. CuBridge: An LLM-Based Framework for Understanding and Reconstructing High-Performance Attention KernelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xing Ma, Yangjie Zhou, Wu Sun, et al.2026 · 3 citations
  73. Self-Evolving Multi-Agent Systems via Textual BackpropagationFindings of the Association for Computational LinguisticsXiaowen Ma, Yunpu Ma, Chenyang Lin, et al.2026 · 3 citations
  74. SiPOS: A Benchmark Dataset for Sindhi Part-of-Speech TaggingRecent Advances in Natural Language Processing (RANLP)Wazir Ali, Zenglin Xu, Jay Kumar2021 · 3 citations
  75. A Sovereign, Open-Source Foundation Model for German and EnglisharXiv:2607.09424Soofi-Team: Benedikt Droste, David Fitzek, Ruben Harle, et al.2026 · 2 citations
  76. Behavior-Aware Item Modeling via Dynamic Procedural Solution Representations for Knowledge TracingFindings of the Association for Computational LinguisticsJun Seo, Sangwon Ryu, Heejin Do, et al.2026 · 2 citations
  77. Kenji-Endo: a BabyLM @EVALITAEvaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final WorkshopCalogero Jerik Scozzaro, Matteo Rinaldi, Gianluca Mittone, et al.2026 · 2 citations
  78. Red-Bandit: Test-Time Adaptation for LLM Red-Teaming via Bandit-Guided LoRA ExpertsAnnual Meeting of the Association for Computational Linguistics (ACL)Christos Ziakas, Nicholas Loo, Nishita Jain, et al.2026 · 2 citations
  79. Attention-based sequence-to-sequence model for speech recognition: development of state-of-the-art system on LibriSpeech and its application to non-native EnglisharXiv:1810.13088Yan Yin, Ramon Prieto, Bin Wang, et al.2018 · 2 citations
  80. BSCodec: A Band-Split Neural Codec for High-Quality Universal Audio ReconstructionFindings of the Association for Computational LinguisticsHaoran Wang, Jiatong Shi, Jinchuan Tian, et al.2026 · 1 citation
  81. CuMA: Aligning LLMs with Sparse Cultural Values via Demographic-Aware Mixture of AdaptersAnnual Meeting of the Association for Computational Linguistics (ACL)Ao Sun, Xiaoyu Wang, Zhe Tan, et al.2026 · 1 citation
  82. Discovering and Causally Validating Emotion-Sensitive Neurons in Large Audio-Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Xiutian Zhao, Björn Schuller, Berrak Sisman2026 · 1 citation
  83. From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for TibetanAnnual Meeting of the Association for Computational Linguistics (ACL)Lei Yang, Leiyu Pan, Bojian Xiong, et al.2026 · 1 citation
  84. H3Fusion: Helpful, Harmless, Honest Fusion of Aligned LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Selim Furkan Tekin, Fatih Ilhan, Sihao Hu, et al.2026 · 1 citation
  85. LocuPrompt at SemEval-2026 Task 7: A Multilingual Prompting Framework for Cross-Cultural Everyday Knowledge in LLMsInternational Workshop on Semantic Evaluation (SemEval)Ningjingke Ning2026 · 1 citation
  86. Modeling Annotator Disagreement with Demographic-Aware Experts and Synthetic PerspectivesAnnual Meeting of the Association for Computational Linguistics (ACL)Yinuo Xu, Veronica Derricks, Allison Earl, et al.2026 · 1 citation
  87. RISER: Orchestrating Latent Reasoning Skills for Adaptive Activation SteeringFindings of the Association for Computational LinguisticsWencheng Ye, Xiaoyang Yuan, Yi Bin, et al.2026 · 1 citation
  88. A Learnable Skill Combination Strategy for Multi-task Learning in Natural Language UnderstandingFindings of the Association for Computational LinguisticsZhe Yang, Yi Huang, Yaqin Chen, et al.2026
  89. Capability Decomposition for Unified Information Extraction via Hierarchical Mixture-of-ExpertsAnnual Meeting of the Association for Computational Linguistics (ACL)Jing Zhou, Peng Wang, Wenjun Ke, et al.2026
  90. COMPEL: Compensated Mixture-of-Experts Pruning with Expert-Layer distributionFindings of the Association for Computational LinguisticsSeohee Yoon, Yong Suk Choi2026
  91. Component Transfer Can Exceed Full Model Performance: Investigating Post-Trained Mixture-of-ExpertsWorkshop on Generation, Evaluation and Metrics (GEM)Rabin Tiwari2026
  92. DeepPavlov Strikes Back: A Toolkit for Improving LLM Reliability and TrustworthinessConference of the European Chapter of the Association for Computational Linguistics (EACL)Evgenii Nikolaev, Timur Ionov, Anna Korzanova, et al.2026
  93. FreeChunker: A Cross-Granularity Chunking FrameworkFindings of the Association for Computational LinguisticsZhang Wenxuan, Yuan-Hao Jiang, Yang Cao, et al.2026
  94. Improved Policy Optimization for Mixture-of-Experts Models: Importance Sampling and Rewarding from an Expert-Centric PerspectiveFindings of the Association for Computational LinguisticsYining Qian, Jinpeng Li, Fei Mi, et al.2026
  95. Infinity-MoE: Generalizing Mixture of Experts to Infinite ExpertsConference of the European Chapter of the Association for Computational Linguistics (EACL)Shota Takashiro, Takeshi Kojima, Shohei Taniguchi, et al.2026
  96. Mitigating Tokenization-Induced Distance Distortion in Long-Context Multilingual Machine TranslationAnnual Meeting of the Association for Computational Linguistics (ACL)Khotso Selialia, Antoine Nzeyimana, Fatima M. Anwar2026
  97. Mixture of Heterogeneous Grouped Experts for Language ModelingAnnual Meeting of the Association for Computational Linguistics (ACL)Zhicheng Ma, Xiang Liu, Zhaoxiang Liu, et al.2026
  98. ModularMoE: Fast LLM Customization with Parameter-Sharing Mixture-of-Experts for Low-Resource SettingsFindings of the Association for Computational LinguisticsJiaxing Liu, Qi Qi, Haifeng Sun, et al.2026
  99. MUTANT: A Recipe for Multilingual Tokenizer DesignAnnual Meeting of the Association for Computational Linguistics (ACL)Souvik Rana, Ashish Kulkarni, Arul Menezes, et al.2026
  100. pQuant: Towards Effective Low-Bit Language Models via Decoupled Linear Quantization-Aware TrainingFindings of the Association for Computational LinguisticsWenzheng Zhang, Bingzheng Liu2026

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