ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2011.08827
  4. Cited By
Avoiding Tampering Incentives in Deep RL via Decoupled Approval

Avoiding Tampering Incentives in Deep RL via Decoupled Approval

17 November 2020
J. Uesato
Ramana Kumar
Victoria Krakovna
Tom Everitt
Richard Ngo
Shane Legg
ArXivPDFHTML

Papers citing "Avoiding Tampering Incentives in Deep RL via Decoupled Approval"

5 / 5 papers shown
Title
Sailing AI by the Stars: A Survey of Learning from Rewards in Post-Training and Test-Time Scaling of Large Language Models
Sailing AI by the Stars: A Survey of Learning from Rewards in Post-Training and Test-Time Scaling of Large Language Models
Xiaobao Wu
LRM
72
1
0
05 May 2025
MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking
MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking
Sebastian Farquhar
Vikrant Varma
David Lindner
David Elson
Caleb Biddulph
Ian Goodfellow
Rohin Shah
82
1
0
22 Jan 2025
Defining and Characterizing Reward Hacking
Defining and Characterizing Reward Hacking
Joar Skalse
Nikolaus H. R. Howe
Dmitrii Krasheninnikov
David M. Krueger
57
54
0
27 Sep 2022
AI safety via debate
AI safety via debate
G. Irving
Paul Christiano
Dario Amodei
199
199
0
02 May 2018
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Chelsea Finn
Pieter Abbeel
Sergey Levine
OOD
252
11,677
0
09 Mar 2017
1