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A wide range of LM applications require generating text that conforms to syntactic or semantic constraints.
Unsupervised part of speech inference with particle filters
Gregory Dubbin and Phil Blunsom · 1907
Earlier work this paper cites.
Fine-tuning language models from human preferences
Daniel M Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B Brown, Alec Radford, Dario Amodei, Paul Christiano, and Geoffrey Irving · 1909
Earlier work this paper cites.
Plug and play language models: A simple approach to controlled text generation
Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, and Rosanne Liu · 1912
Earlier work this paper cites.
A generalization of sampling without replacement from a finite universe
Daniel G. Horvitz and Donovan J. Thompson · 1952
Earlier work this paper cites.
An Efficient Context-Free Parsing Algorithm
Jay Earley · 1968
Earlier work this paper cites.
STRIPS: A new approach to the application of theorem proving to problem solving
Richard E Fikes and Nils J Nilsson · 1971
Earlier work this paper cites.
Introduction to Automata Theory, Languages and Computation
John E. Hopcroft and Jeffrey D. Ullman · 1979
Earlier work this paper cites.
SMILES, a chemical language and information system
David Weininger · 1988
Earlier work this paper cites.
PDDL—the planning domain definition language
Malik Ghallab, Adele Howe, Craig Knoblock, Drew McDermott, Ashwin Ram, Manuela Veloso, Daniel Weld, and David Wilkins · 1998
Earlier work this paper cites.
Semiring parsing
Joshua Goodman · 1999
Earlier work this paper cites.
Whole-sentence exponential language models: A vehicle for linguistic-statistical integration
Ronald Rosenfeld, Stanley Chen, and Xiaojin Zhu · 2001
Earlier work this paper cites.
An efficient probabilistic context-free parsing algorithm that computes prefix probabilities
Andreas Stolcke · 2002
Earlier work this paper cites.
VAL: Automatic plan validation, continuous effects and mixed initiative planning using PDDL
R. Howey, D. Long, and M. Fox · 2004
Earlier work this paper cites.
The fast downward planning system
Malte Helmert · 2006
Earlier work this paper cites.
The pseudo-marginal approach for efficient monte carlo computations
Christophe Andrieu and Gareth O. Roberts · 2009
Earlier work this paper cites.
A particle filter algorithm for Bayesian wordsegmentation
Benjamin Börschinger and Mark Johnson · 2011
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Quantifying the chemical beauty of drugs
G. Richard Bickerton, Gaia V. Paolini, Jérémy Besnard, Sorel Muresan, and Andrew L. Hopkins · 2012
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Enumeration of 166 billion organic small molecules in the chemical universe database GDB-17
Lars Ruddigkeit, Ruud Van Deursen, Lorenz C Blum, and Jean-Louis Reymond · 2012
Earlier work this paper cites.
A log-linear model for unsupervised text normalization
Yi Yang and Jacob Eisenstein · 2013
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A Bayesian model for generative transition-based dependency parsing
Jan Buys and Phil Blunsom · 2015
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The sample size required in importance sampling
Sourav Chatterjee and Persi Diaconis · 2018
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Neural particle smoothing for sampling from conditional sequence models
Chu-Cheng Lin and Jason Eisner · 2018
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Automatic alignment of sequential Monte Carlo inference in higher-order probabilistic programs
Daniel Lundén, David Broman, Fredrik Ronquist, and Lawrence M Murray · 2018
Earlier work this paper cites.
Probabilistic programming with programmable inference
Vikash K Mansinghka, Ulrich Schaechtle, Shivam Handa, Alexey Radul, Yutian Chen, and Martin Rinard · 2018
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Spider: A large-scale human-labeled dataset for complex and cross-domain semantic parsing and text-to-SQL task
Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, Qingning Yao, Shanelle Roman, Zilin Zhang, and Dragomir Radev · 2018
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A general-purpose algorithm for constrained sequential inference
Daniel Deutsch, Shyam Upadhyay, and Dan Roth · 2019
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CGMH: Constrained sentence generation by metropolis-hastings sampling
Ning Miao, Hao Zhou, Lili Mou, Rui Yan, and Lei Li · 2019
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Elements of sequential monte carlo
Christian A. Naesseth, Fredrik Lindsten, and Thomas B. Schön · 2019
Earlier work this paper cites.
An Introduction to Sequential Monte Carlo , volume 4
Nicolas Chopin and Omiros Papaspiliopoulos · 2020
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If beam search is the answer, what was the question?
Clara Meister, Tim Vieira, and Ryan Cotterell · 2020
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Do you have the right scissors? tailoring pre-trained language models via Monte-Carlo methods
Ning Miao, Yuxuan Song, Hao Zhou, and Lei Li · 2020
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Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano · 2020
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Language generation via combinatorial constraint satisfaction: A tree search enhanced Monte-Carlo approach
Maosen Zhang, Nan Jiang, Lei Li, and Yexiang Xue · 2020
Earlier work this paper cites.
You should evaluate your language model on marginal likelihood over tokenisations
Kris Cao and Laura Rimell · 2021
Earlier work this paper cites.
Controlled text generation as continuous optimization with multiple constraints
Sachin Kumar, Eric Malmi, Aliaksei Severyn, and Yulia Tsvetkov · 2021
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WebGPT: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, Xu Jiang, Karl Cobbe, Tyna Eloundou, Gretchen Krueger, Kevin Button, Matthew Knight, Benjamin Chess, and John Schulman · 2021
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A plug-and-play method for controlled text generation
Damian Pascual, Beni Egressy, Clara Meister, Ryan Cotterell, and Roger Wattenhofer · 2021
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Constrained language models yield few-shot semantic parsers
Richard Shin, Christopher Lin, Sam Thomson, Charles Chen Jr, Subhro Roy, Emmanouil Antonios Platanios, Adam Pauls, Dan Klein, Jason Eisner, and Benjamin Van Durme · 2021
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FUDGE: Controlled text generation with future discriminators
Kevin Yang and Dan Klein · 2021
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Do as I can, not as I say: Grounding language in robotic affordances
Michael Ahn, Anthony Brohan, Noah Brown, Yevgen Chebotar, Omar Cortes, Byron David, Chelsea Finn, Chuyuan Fu, Keerthana Gopalakrishnan, Karol Hausman, Alex Herzog, Daniel Ho, Jasmine Hsu, Julian Ibarz, Brian Ichter, Alex Irpan, Eric Jang, Rosario Jauregui Ruano, Kyle Jeffrey, Sally Jesmonth, Nikhil J Joshi, Ryan Julian, Dmitry Kalashnikov, Yuheng Kuang, Kuang-Huei Lee, Sergey Levine, Yao Lu, Linda Luu, Carolina Parada, Peter Pastor, Jornell Quiambao, Kanishka Rao, Jarek Rettinghouse, Diego Reyes, Pierre Sermanet, Nicolas Sievers, Clayton Tan, Alexander Toshev, Vincent Vanhoucke, Fei Xia, Ted Xiao, Peng Xu, Sichun Xu, Mengyuan Yan, and Andy Zeng · 2022
Efficient guided generation for large language models
Brandon T Willard and Rémi Louf · 2023
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Learning adaptive planning representations with natural language guidance
Lionel Wong, Jiayuan Mao, Pratyusha Sharma, Zachary S Siegel, Jiahai Feng, Noa Korneev, Joshua B Tenenbaum, and Jacob Andreas · 2023
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Translating natural language to planning goals with large-language models
Yaqi Xie, Chen Yu, Tongyao Zhu, Jinbin Bai, Ze Gong, and Harold Soh · 2023
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The neuro-symbolic inverse planning engine (NIPE): Modeling probabilistic social inferences from linguistic inputs
Lance Ying, Katherine M Collins, Megan Wei, Cedegao E Zhang, Tan Zhi-Xuan, Adrian Weller, Joshua B Tenenbaum, and Lionel Wong · 2023
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Constitutional AI: Harmlessness from AI feedback
Yuntao Bai, Saurav Kadavath, Sandipan Kundu, Amanda Askell, Jackson Kernion, Andy Jones, Anna Chen, Anna Goldie, Azalia Mirhoseini, Cameron McKinnon, Carol Chen, Catherine Olsson, Christopher Olah, Danny Hernandez, Dawn Drain, Deep Ganguli, Dustin Li, Eli Tran-Johnson, Ethan Perez, Jamie Kerr, Jared Mueller, Jeffrey Ladish, Joshua Landau, Kamal Ndousse, Kamile Lukosuite, Liane Lovitt, Michael Sellitto, Nelson Elhage, Nicholas Schiefer, Noemi Mercado, Nova DasSarma, Robert Lasenby, Robin Larson, Sam Ringer, Scott Johnston, Shauna Kravec, Sheer El Showk, Stanislav Fort, Tamera Lanham, Timothy Telleen-Lawton, Tom Conerly, Tom Henighan, Tristan Hume, Samuel R. Bowman, Zac Hatfield-Dodds, Ben Mann, Dario Amodei, Nicholas Joseph, Sam McCandlish, Tom Brown, and Jared Kaplan · 2022
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Language models can learn complex molecular distributions
Daniel Flam-Shepherd, Kevin Zhu, and Alán Aspuru-Guzik · 2022
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A high-level programming language for generative protein design
Brian Hie, Salvatore Candido, Zeming Lin, Ori Kabeli, Roshan Rao, Nikita Smetanin, Tom Sercu, and Alexander Rives · 2022
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RL with KL penalties is better viewed as Bayesian inference
Tomasz Korbak, Ethan Perez, and Christopher Buckley · 2022
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Rankgen: Improving text generation with large ranking models
Kalpesh Krishna, Yapei Chang, John Wieting, and Mohit Iyyer · 2022
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Gradient-based constrained sampling from language models
Sachin Kumar, Biswajit Paria, and Yulia Tsvetkov · 2022
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Sixo: Smoothing inference with twisted objectives
Dieterich Lawson, Allan Raventós, Andrew Warrington, and Scott Linderman · 2022
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Rui Zheng, Shihan Dou, Songyang Gao, Yuan Hua, Wei Shen, Binghai Wang, Yan Liu, Senjie Jin, Qin Liu, Yuhao Zhou, Limao Xiong, Lu Chen, Zhiheng Xi, Nuo Xu, Wenbin Lai, Minghao Zhu, Cheng Chang, Zhangyue Yin, Rongxiang Weng, Wensen Cheng, Haoran Huang, Tianxiang Sun, Hang Yan, Tao Gui, Qi Zhang, Xipeng Qiu, and Xuanjing Huang · 2023
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Large language models are human-level prompt engineers
Yongchao Zhou, Andrei Ioan Muresanu, Ziwen Han, Keiran Paster, Silviu Pitis, Harris Chan, and Jimmy Ba · 2023
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Principled reinforcement learning with human feedback from pairwise or K K -wise comparisons
Banghua Zhu, Michael Jordan, and Jiantao Jiao · 2023
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Constructing a BPE tokenization DFA
Martin Berglund, Willeke Martens, and Brink Van der Merwe · 2024
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Are more LLM calls all you need? towards the scaling properties of compound AI systems
Lingjiao Chen, Jared Quincy Davis, Boris Hanin, Peter Bailis, Ion Stoica, Matei A. Zaharia, and James Y. Zou · 2024
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Linearly controlled language generation with performative guarantees
Emily Cheng, Marco Baroni, and Carmen Amo Alonso · 2024
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Principled gradient-based MCMC for conditional sampling of text
Li Du, Afra Amini, Lucas Torroba Hennigen, Xinyan Velocity Yu, Holden Lee, Jason Eisner, and Ryan Cotterell · 2024
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Bonbon alignment for large language models and the sweetness of best-of-n sampling
Lin Gui, Cristina Garbacea, and Victor Veitch · 2024
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Automata-based constraints for language model decoding
Terry Koo, Frederick Liu, and Luheng He · 2024
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RDKit: Open-source cheminformatics software
Greg Landrum · 2024
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Let’s verify step by step
Hunter Lightman, Vineet Kosaraju, Yuri Burda, Harrison Edwards, Bowen Baker, Teddy Lee, Jan Leike, John Schulman, Ilya Sutskever, and Karl Cobbe · 2024
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AI Controller Interface
Michal Moskal, Madan Musuvathi, and Emre Kıcıman · 2024
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Controlled decoding from language models
Sidharth Mudgal, Jong Lee, Harish Ganapathy, YaGuang Li, Tao Wang, Yanping Huang, Zhifeng Chen, Heng-Tze Cheng, Michael Collins, Trevor Strohman, Jilin Chen, Alex Beutel, and Ahmad Beirami · 2024
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partialsmiles: A validating SMILES parser, with support for incomplete SMILES, 2024
Noel O’Boyle · 2024
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Grammar-aligned decoding
Kanghee Park, Jiayu Wang, Taylor Berg-Kirkpatrick, Nadia Polikarpova, and Loris D’Antoni · 2024
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Preference fine-tuning of LLMs should leverage suboptimal, on-policy data
Fahim Tajwar, Anikait Singh, Archit Sharma, Rafael Rafailov, Jeff Schneider, Tengyang Xie, Stefano Ermon, Chelsea Finn, and Aviral Kumar · 2024
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Zhi Rui Tam, Cheng-Kuang Wu, Yi-Lin Tsai, Chieh-Yen Lin, Hung-yi Lee, and Yun-Nung Chen · 2024
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SynCode: Improving LLM code generation with grammar augmentation
Shubham Ugare, Tarun Suresh, Hangoo Kang, Sasa Misailovic, and Gagandeep Singh · 2024
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From language models over tokens to language models over characters
Tim Vieira, Ben LeBrun, Mario Giulianelli, Juan Luis Gastaldi, Brian DuSell, John Terilla, Timothy J O’Donnell, and Ryan Cotterell · 2024
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Grammar prompting for domain-specific language generation with large language models
Bailin Wang, Zi Wang, Xuezhi Wang, Yuan Cao, Rif A Saurous, and Yoon Kim · 2024
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Deepseek-prover: Advancing theorem proving in llms through large-scale synthetic data
Huajian Xin, Daya Guo, Zhihong Shao, Zhizhou Ren, Qihao Zhu, Bo Liu, Chong Ruan, Wenda Li, and Xiaodan Liang · 2024
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Iterative preference learning from human feedback: Bridging theory and practice for RLHF under KL-constraint
Wei Xiong, Hanze Dong, Chenlu Ye, Ziqi Wang, Han Zhong, Heng Ji, Nan Jiang, and Tong Zhang · 2024
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PROC2PDDL: Open-domain planning representations from texts
Tianyi Zhang, Li Zhang, Zhaoyi Hou, Ziyu Wang, Yuling Gu, Peter Clark, Chris Callison-Burch, and Niket Tandon · 2024
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Probabilistic inference in language models via twisted sequential Monte Carlo
Stephen Zhao, Rob Brekelmans, Alireza Makhzani, and Roger Baker Grosse · 2024
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SGLang: Efficient execution of structured language model programs
Lianmin Zheng, Liangsheng Yin, Zhiqiang Xie, Chuyue Sun, Jeff Huang, Cody Hao Yu, Shiyi Cao, Christos Kozyrakis, Ion Stoica, Joseph E. Gonzalez, Clark Barrett, and Ying Sheng · 2024
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Pragmatic instruction following and goal assistance via cooperative language-guided inverse planning
Tan Zhi-Xuan, Lance Ying, Vikash Mansinghka, and Joshua B Tenenbaum · 2024
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Planetarium: A rigorous benchmark for translating text to structured planning languages
Max Zuo, Francisco Piedrahita Velez, Xiaochen Li, Michael L Littman, and Stephen H Bach · 2024
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Variational best-of- N N alignment
Afra Amini, Tim Vieira, Elliott Ash, and Ryan Cotterell · 2025
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Evaluation of best-of-n sampling strategies for language model alignment
Yuki Ichihara, Yuu Jinnai, Tetsuro Morimura, Kenshi Abe, Kaito Ariu, Mitsuki Sakamoto, and Eiji Uchibe · 2025
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