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Luke Zettlemoyer — most-cited papers & profile · Generative Models
← authors
·
overview
Luke Zettlemoyer
14
papers ·
40
citations ·
84
h-index
University of Washington · University of Chicago · Seattle University
Google Scholar ↗
Semantic Scholar ↗
OpenAlex ↗
Most-cited papers
RA-DIT: Retrieval-Augmented Dual Instruction Tuning
2023 · 15 citations
LIMA: Less Is More for Alignment
2023 · 12 citations
Trusting Your Evidence: Hallucinate Less with Context-aware Decoding
2023 · 7 citations
Learning Programmatic Idioms for Scalable Semantic Parsing
2019 · 4 citations
Scaling Retrieval-Based Language Models with a Trillion-Token Datastore
2024 · 2 citations
DR Tulu: Reinforcement Learning with Evolving Rubrics for Deep Research
2025
Olmo 3
2025
DreamGen: Unlocking Generalization in Robot Learning through Video World Models
2025
Latent Action Pretraining from Videos
2024
Shepherd: A Critic for Language Model Generation
2023
Self-Alignment with Instruction Backtranslation
2023
In-Context Pretraining: Language Modeling Beyond Document Boundaries
2023
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
2024
Better Alignment with Instruction Back-and-Forth Translation
2024
Topics
Training Techniques
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Fine-Tuning
RAG
In-Context Learning
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Model Architecture
Human-Robot Interaction
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