Elamur Research⌕
☰
home / authors / Luke Zettlemoyer / all works / page 4

Luke Zettlemoyer — all works

370 works · page 4 of 4 · 301–370 · ← Luke Zettlemoyer

1 2 3 4

  1. Train for Truth, Keep the Skills: Binary Retrieval-Augmented Reward Mitigates Hallucinations ↗arXiv (Cornell University) · no summary yetTong Chen et al.2025 · 2 citations
  2. Mixture-of-Mamba: Enhancing Multi-Modal State-Space Models with Modality-Aware Sparsity ↗arXiv (Cornell University) · no summary yetWeixin Liang et al.2025 · 2 citations
  3. Computational Tradeoffs in Image Synthesis: Diffusion, Masked-Token, and Next-Token Prediction ↗arXiv (Cornell University) · no summary yetMaciej Kilian, Jampani, Varun, Luke Zettlemoyer2024 · 2 citations
  4. The Gender-GAP Pipeline: A Gender-Aware Polyglot Pipeline for Gender Characterisation in 55 Languages ↗Proceedings of the Eighth Conference on Machine Translation · no summary yetBenjamin Muller et al.2023 · 2 citations
  5. Combinatory Categorial Grammars for Robust Natural Language Processing ↗no summary yetMark J. Steedman et al.2013 · 2 citations
  6. RevMiner: An Extractive Interface for Navigating Reviews on a Smartphone ↗no summary yetJeff Huang et al.2012 · 2 citations
  7. Interactive learning of relation extractors with weak supervision ↗no summary yetDaniel S. Weld, Luke Zettlemoyer, Raphael Hoffmann2012 · 2 citations
  8. Fast Byte Latent Transformer ↗arXiv (Cornell University) · no summary yetJulie Kallini et al.2026 · 1 citation
  9. JobBench: Aligning Agent Work With Human Will ↗arXiv (Cornell University) · no summary yetYuetai Li et al.2026 · 1 citation
  10. Slicing and Dicing: Configuring Optimal Mixtures of Experts ↗arXiv (Cornell University) · no summary yetMargaret Li et al.2026 · 1 citation
  11. Verifiable Visual Rewards Transfer from Synthetic Scenes to Natural Prompts ↗arXiv (Cornell University) · no summary yetShuyue Stella Li et al.2026 · 1 citation
  12. Compute Optimal Tokenization ↗arXiv (Cornell University) · no summary yetTomasz Limisiewicz et al.2026 · 1 citation
  13. Retrofitting language models to operate over bytes ↗Nature · no summary yetBenjamin Minixhofer et al.2026 · 1 citation
  14. Prefix Sliding for efficient test-time scaling ↗arXiv (Cornell University) · no summary yetNiklas Muennighoff et al.2026 · 1 citation
  15. ParaPO: Aligning Language Models to Reduce Verbatim Reproduction of Pre-training Data ↗arXiv (Cornell University) · no summary yetTong Chen et al.2025 · 1 citation
  16. Latent Speech-Text Transformer ↗arXiv (Cornell University) · no summary yetYen-Ju Lu et al.2025 · 1 citation
  17. When Worse is Better: Navigating the Compression Generation Trade-off In Visual Tokenization ↗neural information processing systems · no summary yetVivek Ramanujan et al.2025 · 1 citation
  18. Few-shot Mining of Naturally Occurring Inputs and Outputs ↗arXiv (Cornell University) · no summary yetJoshi, Mandar et al.2022 · 1 citation
  19. Reducing Target Group Bias in Hate Speech Detectors ↗arXiv (Cornell University) · no summary yetDarsh Shah et al.2021 · 1 citation
  20. Grounding Antonym Adjective Pairs through Interaction ↗no summary yetMaxwell Forbes et al.2014 · 1 citation
  21. Lightly Supervised Learning of Procedural Dialog System ↗no summary yetSvitlana Volkova et al.2013 · 1 citation
  22. Learning context-dependent mappings from sentences to logical forms ↗no summary yetLuke Zettlemoyer, Michael Collins2009 · 1 citation
  23. Learning Planning Rules in Stochastic Worlds ↗National Conference on Artificial Intelligence · no summary yetLuke Zettlemoyer, Hanna Pasula, Leslie Pack Kaelbling2005 · 1 citation
  24. Unified Text-Image Generation with Weakness-Targeted Post-Training ↗arXiv (Cornell University) · no summary yetJiahui Chen et al.2026
  25. Micro Language Models Enable Instant Responses ↗arXiv (Cornell University) · no summary yetWen Cheng et al.2026
  26. Scaling Participation in Modular AI Systems ↗arXiv (Cornell University) · no summary yetShangbin Feng et al.2026
  27. Anchored Decoding: Provably Reducing Copyright Risk for Any Language Model ↗arXiv (Cornell University) · no summary yetJacqueline He et al.2026
  28. Knowledge Distillation During Mid-Training Favors Reasoning over Factual Recall ↗arXiv:2609.01532 · no summary yetJacqueline He et al.2026
  29. Data Scarcity and Model Sparsity: Mixtures-of-Experts Overfit More to Repeated Data ↗arXiv (Cornell University) · no summary yetAtindra Jha et al.2026
  30. M*: A Modular, Extensible, Serving System for Multimodal Models ↗arXiv (Cornell University) · no summary yetAtindra Jha et al.2026
  31. Improving MoE Compute Efficiency by Composing Weight and Data Sparsity ↗arXiv (Cornell University) · no summary yetMaciej Kilian et al.2026
  32. Spokes: Optimizing for Diverse Pretraining Data Selection ↗arXiv (Cornell University) · no summary yetClarence Lee et al.2026
  33. ExploreNet: Learning Where to Explore in Diffusion GRPO ↗arXiv (Cornell University) · no summary yetShuyue Stella Li et al.2026
  34. SPADE: Self-Play in Adaptive Synthetic Executable Environments ↗arXiv (Cornell University) · no summary yetBo Liu et al.2026
  35. Tuna-2: Pixel Embeddings Beat Vision Encoders for Multimodal Understanding and Generation ↗arXiv (Cornell University) · no summary yetZhiheng Liu et al.2026
  36. When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis ↗arXiv (Cornell University) · no summary yetKaiyuan Liu et al.2026
  37. Gecko: An Efficient Neural Architecture Inherently Processing Sequences with Arbitrary Lengths ↗arXiv (Cornell University) · no summary yetXuezhe Ma et al.2026
  38. Breaking the Token Ceiling: Distilling Smaller, Stronger Byte Models ↗arXiv (Cornell University) · no summary yetKalyani Marathe et al.2026
  39. WaiT for the Signal: Simple Frequency-Aware Flow-Matching ↗arXiv (Cornell University) · no summary yetKrunoslav Lehman Pavasovic et al.2026
  40. Context Language Models ↗arXiv (Cornell University) · no summary yetRulin Shao et al.2026
  41. Vision-Language Grounding as Bidirectional Concept Correspondence ↗arXiv (Cornell University) · no summary yetJieyu Zhang et al.2026
  42. High Accuracy, Less Talk (HALT): Reliable LLMs through Capability-Aligned Finetuning ↗arXiv (Cornell University) · no summary yetTim Franzmeyer et al.2025
  43. TV2TV: A Unified Framework for Interleaved Language and Video Generation ↗arXiv (Cornell University) · no summary yetXiaochuang Han et al.2025
  44. Self-Improving VLM Judges Without Human Annotations ↗arXiv (Cornell University) · no summary yetInna Wanyin Lin et al.2025
  45. Rethinking Data Use in Large Language Models ↗Computational Linguistics · no summary yetSewon Min, Hannaneh Hajishirzi, Luke Zettlemoyer2025
  46. Negative Token Merging: Image-based Adversarial Feature Guidance ↗arXiv (Cornell University) · no summary yetJaskirat Singh et al.2024
  47. DESCGEN: A Distantly Supervised Dataset for Generating Abstractive Entity Descriptions ↗arXiv (Cornell University) · no summary yetWeijia Shi, Joshi, Mandar, Luke Zettlemoyer2021
  48. © The Author(s) 2013 ↗no summary yetAntoine Bordes et al.2016
  49. Semantic Parsing for Information Extraction ↗no summary yetEunsol Choi, Tom Kwiatkowski, Luke Zettlemoyer2016
  50. Multi-Label Learning with Posterior Regularization ↗no summary yetXi Victoria Lin et al.2016
  51. 状況認識:画像理解のための視覚意味役割ラベリング【Powered by NICT】 ↗IEEE Conference Proceedings · no summary yetYatskar Mark, Luke Zettlemoyer, Farhadi Ali2016
  52. Integrated Intelligence: Robot Instruction via Interactive Grounded Learning ↗no summary yetLuke Zettlemoyer, Dieter Fox2016
  53. Chapter Nineteen Visual Generalization in Programming by Example ↗no summary yetRobert St. Amant et al.2015
  54. ADJP Adjective phrase ADVP Adverb phrase ↗no summary yetLuke Zettlemoyer et al.2015
  55. Talking to Robots: Learning to Ground ↗no summary yetCynthia Matuszek et al.2014
  56. Learning Probabilistic Planning Rules ↗no summary yetHanna Pasula, Luke Zettlemoyer, Leslie Pack Kaelbling2014
  57. n Sequence Models ↗no summary yetLuke Zettlemoyer et al.2014
  58. Interactive Learning of Relation Extractors with Weak Supervision Finding and Leveraging Implicit References in a Web Search Engine for Programmers Model Selection for Support Vector Machines ↗no summary yetRaphael Hoffmann et al.2013
  59. Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (2008) Lifted Probabilistic Inference with Counting Formulas ↗no summary yetBrian Milch et al.2013
  60. Learning to Relate Literal and Sentimental Descriptions of Visual Properties ↗Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · no summary yetMark Yatskar et al.2013
  61. joint localization and clustering ↗no summary yetMach Learn et al.2012
  62. and their parts ↗no summary yetMach Learn et al.2012
  63. Learning to Parse Natural Language to a Robot Execution System ↗no summary yetCynthia Matuszek et al.2012
  64. Learning strips operators from noisy and incomplete observations. arXiv preprint arXiv:1210.4889 ↗no summary yetLuke Zettlemoyer2012
  65. IBOTS: Agent Control Through the User Interface ↗no summary yetLuke Zettlemoyer, Robert St. Amant, Martin S. Dulberg2011
  66. Kaelbling. Learning symbolic models of stochastic domains ↗no summary yetHanna Pasula, Luke Zettlemoyer, Leslie Pack Kaelbling2008
  67. Kaelbling. Learning planning rules in noisy stochastic worlds ↗no summary yetLuke Zettlemoyer, Hanna Pasula, Leslie Pack Kaelbling2005
  68. User Interface Softbots ↗National Conference on Artificial Intelligence · no summary yetRobert St. Amant, Luke Zettlemoyer2000
  69. The MITRE Corporation, “A Proposed VDLT Traffic Model for Capacity Simulation”, AMCP/WG-D/5 WP-16 ↗no summary yetJoël P. Grégoire, Luke Zettlemoyer, James C. Lester1999
  70. Explanatory Lifelike Avatars: Performing User Centered Tasks ↗no summary yetJames C. Lester et al.1999

1 2 3 4

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/authors/luke-zettlemoyer/works/page/4/