A Probabilistic Inference Approach to Inference-Time Scaling of LLMs using Particle-Based Monte Carlo Methods

A Probabilistic Inference Approach to Inference-Time Scaling of LLMs using Particle-Based Monte Carlo Methods

3 February 2025

Shivchander Sudalairaj

Akash Srivastava

Papers citing "A Probabilistic Inference Approach to Inference-Time Scaling of LLMs using Particle-Based Monte Carlo Methods"

8 / 8 papers shown

Title
Learning Extrapolative Sequence Transformations from Markov Chains Sophia Hager Aleem Khan Andrew Wang Nicholas Andrews BDL 12 0 0 26 May 2025
Token-Level Uncertainty Estimation for Large Language Model Reasoning Tunyu Zhang Haizhou Shi Yibin Wang Hengyi Wang Xiaoxiao He ... Ligong Han Kai Xu Huatian Zhang Dimitris N. Metaxas Hao Wang LRM 47 0 0 16 May 2025
Soft Best-of-n Sampling for Model Alignment C. M. Verdun Alex Oesterling Himabindu Lakkaraju Flavio du Pin Calmon BDL 340 0 0 06 May 2025
Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo João Loula Benjamin LeBrun Li Du Ben Lipkin Clemente Pasti ... Ryan Cotterel Vikash K. Mansinghka Alexander K. Lew Tim Vieira Timothy J. O'Donnell 71 4 0 17 Apr 2025
Fast Controlled Generation from Language Models with Adaptive Weighted Rejection Sampling Benjamin Lipkin Benjamin LeBrun Jacob Hoover Vigly João Loula David R. MacIver ... Ryan Cotterell Vikash K. Mansinghka Timothy J. O'Donnell Alexander K. Lew Tim Vieira 53 0 0 07 Apr 2025
Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters Charlie Snell Jaehoon Lee Kelvin Xu Aviral Kumar LRM 95 576 0 06 Aug 2024
Advancing LLM Reasoning Generalists with Preference Trees Lifan Yuan Ganqu Cui Hanbin Wang Ning Ding Xingyao Wang ... Zhenghao Liu Bowen Zhou Hao Peng Zhiyuan Liu Maosong Sun LRM 82 109 0 02 Apr 2024
Scaling Laws for Neural Language Models Jared Kaplan Sam McCandlish T. Henighan Tom B. Brown B. Chess R. Child Scott Gray Alec Radford Jeff Wu Dario Amodei 430 4,662 0 23 Jan 2020