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Diffusion LLMs have emerged as a promising alternative to conventional autoregressive LLMs, offering significant potential for improved runtime efficiency.
The viterbi algorithm
G. D. Forney · 1973
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Z3: an efficient smt solver
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A general-purpose algorithm for constrained sequential inference
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala · 2019
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush · 2020
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Structured denoising diffusion models in discrete state-spaces
Jacob Austin, Daniel D. Johnson, Jonathan Ho, Daniel Tarlow, and Rianne van den Berg · 2021
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Evaluating large language models trained on code, 2021
Chen et. al · 2021
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Synchromesh: Reliable code generation from pre-trained language models
Gabriel Poesia, Alex Polozov, Vu Le, Ashish Tiwari, Gustavo Soares, Christopher Meek, and Sumit Gulwani · 2022
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Xiaochuang Han, Sachin Kumar, and Yulia Tsvetkov · 2023
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Validating large language models with RELM
Michael Kuchnik, Virginia Smith, and George Amvrosiadis · 2023
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Sequential Monte Carlo steering of large language models using probabilistic programs
Alexander K Lew, Tan Zhi-Xuan, Gabriel Grand, and Vikash Mansinghka · 2023
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Liangming Pan, Alon Albalak, Xinyi Wang, and William Yang Wang · 2023
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Efficient guided generation for large language models
Brandon T Willard and Rémi Louf · 2023
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Leandojo: Theorem proving with retrieval-augmented language models, 2023
Kaiyu Yang, Aidan M. Swope, Alex Gu, Rahul Chalamala, Peiyang Song, Shixing Yu, Saad Godil, Ryan Prenger, and Anima Anandkumar · 2023
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XGrammar: Flexible and efficient structured generation engine for large language models
Grammar-aligned decoding
Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick, Nadia Polikarpova, and Loris D’Antoni · 2024
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever · 2024
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Block diffusion: Interpolating between autoregressive and diffusion language models
Marianne Arriola, Subham Sekhar Sahoo, Aaron Gokaslan, Zhihan Yang, Zhixuan Qi, Jiaqi Han, Justin T Chiu, and Volodymyr Kuleshov · 2025
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CRANE: Reasoning with constrained LLM generation
Debangshu Banerjee, Tarun Suresh, Shubham Ugare, Sasa Misailovic, and Gagandeep Singh · 2025
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Michael Cardei, Jacob K Christopher, Thomas Hartvigsen, Brian R. Bartoldson, Bhavya Kailkhura, and Ferdinando Fioretto · 2025
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Automata-based constraints for language model decoding
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json-mode-eval, 2024
NousResearch · 2024
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Grammar-aligned decoding
Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick, Nadia Polikarpova, and Loris D’Antoni
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SynCode: Improving LLM code generation with grammar augmentation
Shubham Ugare, Tarun Suresh, Hangoo Kang, Sasa Misailovic, and Gagandeep Singh
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Syncode: Llm generation with grammar augmentation, 2024b
Shubham Ugare, Tarun Suresh, Hangoo Kang, Sasa Misailovic, and Gagandeep Singh
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Syntactic and semantic control of large language models via sequential Monte Carlo
João Loula, Benjamin LeBrun, Li Du, Ben Lipkin, Clemente Pasti, Gabriel Grand, Tianyu Liu, Yahya Emara, Marjorie Freedman, Jason Eisner, Ryan Cotterell, Vikash Mansinghka, Alex Lew, Tim Vieira, and Tim O’Donnell · 2025
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