Q-Probe: A Lightweight Approach to Reward Maximization for Language
Models

Q-Probe: A Lightweight Approach to Reward Maximization for Language Models

22 February 2024

Martin Wattenberg

David Brandfonbrener

Papers citing "Q-Probe: A Lightweight Approach to Reward Maximization for Language Models"

10 / 10 papers shown

Title
Steering Your Generalists: Improving Robotic Foundation Models via Value Guidance Mitsuhiko Nakamoto Oier Mees Aviral Kumar Sergey Levine OffRL 79 13 0 17 Oct 2024
Truthful Aggregation of LLMs with an Application to Online Advertising Ermis Soumalias Michael J. Curry Sven Seuken 39 11 0 09 May 2024
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models Avi Singh John D. Co-Reyes Rishabh Agarwal Ankesh Anand Piyush Patil ... Yamini Bansal Ethan Dyer Behnam Neyshabur Jascha Narain Sohl-Dickstein Noah Fiedel ALM LRM ReLM SyDa 157 144 0 11 Dec 2023
Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned Deep Ganguli Liane Lovitt John Kernion Amanda Askell Yuntao Bai ... Nicholas Joseph Sam McCandlish C. Olah Jared Kaplan Jack Clark 225 444 0 23 Aug 2022
Offline RL for Natural Language Generation with Implicit Language Q Learning Charles Burton Snell Ilya Kostrikov Yi Su Mengjiao Yang Sergey Levine OffRL 125 102 0 05 Jun 2022
Training language models to follow instructions with human feedback Long Ouyang Jeff Wu Xu Jiang Diogo Almeida Carroll L. Wainwright ... Amanda Askell Peter Welinder Paul Christiano Jan Leike Ryan J. Lowe OSLM ALM 313 11,953 0 04 Mar 2022
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason W. Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter F. Xia Ed H. Chi Quoc Le Denny Zhou LM&Ro LRM AI4CE ReLM 361 8,495 0 28 Jan 2022
$Understanding Dataset Difficulty with $\mathcal{V}$-Usable Information$ Understanding Dataset Difficulty with $\mathcal{V}$ -Usable Information Kawin Ethayarajh Yejin Choi Swabha Swayamdipta 164 157 0 16 Oct 2021
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity Yao Lu Max Bartolo Alastair Moore Sebastian Riedel Pontus Stenetorp AILaw LRM 279 1,121 0 18 Apr 2021
Probing Classifiers: Promises, Shortcomings, and Advances Yonatan Belinkov 226 405 0 24 Feb 2021