Noah Y. Siegel

28 papers A* 4Misc 1Journal 20Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
A Positive Case for Faithfulness: LLM Self-Explanations Help Predict Model Behavior.
CoRR
Harry Mayne, Justin Singh Kang, Dewi Gould, Kannan Ramchandran, Adam Mahdi, Noah Y. Siegel
2025 J jnl
Advancing Event Forecasting through Massive Training of Large Language Models: Challenges, Solutions, and Broader Impacts.
CoRR
Sang-Woo Lee, Sohee Yang, Donghyun Kwak, Noah Y. Siegel
2025 J jnl
Faithfulness of LLM Self-Explanations for Commonsense Tasks: Larger Is Better, and Instruction-Tuning Allows Trade-Offs but Not Pareto Dominance.
CoRR
Noah Y. Siegel, Nicolas Heess, María Pérez-Ortiz, Oana-Maria Camburu
2025 — conf
LLMs Can Covertly Sandbag on Capability Evaluations Against Chain-of-Thought Monitoring.
IJCNLP-AACL (Short Papers)
Chloe Li, Noah Y. Siegel
2025 J jnl
LLMs Can Covertly Sandbag on Capability Evaluations Against Chain-of-Thought Monitoring.
CoRR
Chloe Li, Mary Phuong, Noah Y. Siegel
2024 J jnl
Learning agile soccer skills for a bipedal robot with deep reinforcement learning.
Sci. Robotics
Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Jan Humplik, Markus Wulfmeier, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess
2024 A* conf
On scalable oversight with weak LLMs judging strong LLMs.
NeurIPS
Zachary Kenton, Noah Y. Siegel, János Kramár, Jonah Brown-Cohen, Samuel Albanie, Jannis Bulian, Rishabh Agarwal, David Lindner, Yunhao Tang, Noah D. Goodman, Rohin Shah
2024 J jnl
On scalable oversight with weak LLMs judging strong LLMs.
CoRR
Zachary Kenton, Noah Y. Siegel, János Kramár, Jonah Brown-Cohen, Samuel Albanie, Jannis Bulian, Rishabh Agarwal, David Lindner, Yunhao Tang, Noah D. Goodman, Rohin Shah
2024 J jnl
The Effect of Model Size on LLM Post-hoc Explainability via LIME.
CoRR
Henning Heyen, Amy Widdicombe, Noah Y. Siegel, María Pérez-Ortiz, Philip C. Treleaven
2024 — conf
The Probabilities Also Matter: A More Faithful Metric for Faithfulness of Free-Text Explanations in Large Language Models.
ACL (Short Papers)
Noah Y. Siegel, Oana-Maria Camburu, Nicolas Heess, María Pérez-Ortiz
2024 J jnl
The Probabilities Also Matter: A More Faithful Metric for Faithfulness of Free-Text Explanations in Large Language Models.
CoRR
Noah Y. Siegel, Oana-Maria Camburu, Nicolas Heess, María Pérez-Ortiz
2023 J jnl
Learning Agile Soccer Skills for a Bipedal Robot with Deep Reinforcement Learning.
CoRR
Tuomas Haarnoja, Ben Moran, Guy Lever, Sandy H. Huang, Dhruva Tirumala, Markus Wulfmeier, Jan Humplik, Saran Tunyasuvunakool, Noah Y. Siegel, Roland Hafner, Michael Bloesch, Kristian Hartikainen, Arunkumar Byravan, Leonard Hasenclever, Yuval Tassa, Fereshteh Sadeghi, Nathan Batchelor, Federico Casarini, Stefano Saliceti, Charles Game, Neil Sreendra, Kushal Patel, Marlon Gwira, Andrea Huber, Nicole Hurley, Francesco Nori, Raia Hadsell, Nicolas Heess
2022 J jnl
From motor control to team play in simulated humanoid football.
Sci. Robotics
Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess
2022 J jnl
Imitate and Repurpose: Learning Reusable Robot Movement Skills From Human and Animal Behaviors.
CoRR
Steven Bohez, Saran Tunyasuvunakool, Philemon Brakel, Fereshteh Sadeghi, Leonard Hasenclever, Yuval Tassa, Emilio Parisotto, Jan Humplik, Tuomas Haarnoja, Roland Hafner, Markus Wulfmeier, Michael Neunert, Ben Moran, Noah Y. Siegel, Andrea Huber, Francesco Romano, Nathan Batchelor, Federico Casarini, Josh Merel, Raia Hadsell, Nicolas Heess
2022 J jnl
Solving math word problems with process- and outcome-based feedback.
CoRR
Jonathan Uesato, Nate Kushman, Ramana Kumar, H. Francis Song, Noah Y. Siegel, Lisa Wang, Antonia Creswell, Geoffrey Irving, Irina Higgins
2021 A* conf
Data-efficient Hindsight Off-policy Option Learning.
ICML
Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller
2021 J jnl
From Motor Control to Team Play in Simulated Humanoid Football.
CoRR
Siqi Liu, Guy Lever, Zhe Wang, Josh Merel, S. M. Ali Eslami, Daniel Hennes, Wojciech M. Czarnecki, Yuval Tassa, Shayegan Omidshafiei, Abbas Abdolmaleki, Noah Y. Siegel, Leonard Hasenclever, Luke Marris, Saran Tunyasuvunakool, H. Francis Song, Markus Wulfmeier, Paul Muller, Tuomas Haarnoja, Brendan D. Tracey, Karl Tuyls, Thore Graepel, Nicolas Heess
2020 J jnl
"What, not how": Solving an under-actuated insertion task from scratch.
CoRR
Giulia Vezzani, Michael Neunert, Markus Wulfmeier, Rae Jeong, Thomas Lampe, Noah Y. Siegel, Roland Hafner, Abbas Abdolmaleki, Martin A. Riedmiller, Francesco Nori
2020 — conf
Compositional Transfer in Hierarchical Reinforcement Learning.
Robotics: Science and Systems
Markus Wulfmeier, Abbas Abdolmaleki, Roland Hafner, Jost Tobias Springenberg, Michael Neunert, Noah Y. Siegel, Tim Hertweck, Thomas Lampe, Nicolas Heess, Martin A. Riedmiller
2020 A* conf
Critic Regularized Regression.
NeurIPS
Ziyu Wang, Alexander Novikov, Konrad Zolna, Josh Merel, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
2020 J jnl
Critic Regularized Regression.
CoRR
Ziyu Wang, Alexander Novikov, Konrad Zolna, Jost Tobias Springenberg, Scott E. Reed, Bobak Shahriari, Noah Y. Siegel, Josh Merel, Çaglar Gülçehre, Nicolas Heess, Nando de Freitas
2020 J jnl
Data-efficient Hindsight Off-policy Option Learning.
CoRR
Markus Wulfmeier, Dushyant Rao, Roland Hafner, Thomas Lampe, Abbas Abdolmaleki, Tim Hertweck, Michael Neunert, Dhruva Tirumala, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller
2020 A* conf
Keep Doing What Worked: Behavior Modelling Priors for Offline Reinforcement Learning.
ICLR
Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin A. Riedmiller
2020 J jnl
Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning.
CoRR
Noah Y. Siegel, Jost Tobias Springenberg, Felix Berkenkamp, Abbas Abdolmaleki, Michael Neunert, Thomas Lampe, Roland Hafner, Nicolas Heess, Martin A. Riedmiller
2020 J jnl
Simple Sensor Intentions for Exploration.
CoRR
Tim Hertweck, Martin A. Riedmiller, Michael Bloesch, Jost Tobias Springenberg, Noah Y. Siegel, Markus Wulfmeier, Roland Hafner, Nicolas Heess
2019 Misc conf
Imagined Value Gradients: Model-Based Policy Optimization with Tranferable Latent Dynamics Models.
CoRL
Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller
2019 J jnl
Imagined Value Gradients: Model-Based Policy Optimization with Transferable Latent Dynamics Models.
CoRR
Arunkumar Byravan, Jost Tobias Springenberg, Abbas Abdolmaleki, Roland Hafner, Michael Neunert, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller
2019 J jnl
Regularized Hierarchical Policies for Compositional Transfer in Robotics.
CoRR
Markus Wulfmeier, Abbas Abdolmaleki, Roland Hafner, Jost Tobias Springenberg, Michael Neunert, Tim Hertweck, Thomas Lampe, Noah Y. Siegel, Nicolas Heess, Martin A. Riedmiller