Saved in:
| Main Authors: | Li, Fanxing, Sun, Fangyu, Zhang, Tianbao, Zou, Danping |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2501.14513 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
VisFly: An Efficient and Versatile Simulator for Training Vision-based Flight
by: Li, Fanxing, et al.
Published: (2024)
by: Li, Fanxing, et al.
Published: (2024)
VisFly-Lab: Unified Differentiable Framework for First-Order Reinforcement Learning of Quadrotor Control
by: Li, Fanxing, et al.
Published: (2026)
by: Li, Fanxing, et al.
Published: (2026)
First Order Model-Based RL through Decoupled Backpropagation
by: Amigo, Joseph, et al.
Published: (2025)
by: Amigo, Joseph, et al.
Published: (2025)
Aligning Text-to-Image Diffusion Models with Reward Backpropagation
by: Prabhudesai, Mihir, et al.
Published: (2023)
by: Prabhudesai, Mihir, et al.
Published: (2023)
Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
by: Xie, Tianbao, et al.
Published: (2023)
by: Xie, Tianbao, et al.
Published: (2023)
From Demonstrations to Rewards: Test-Time Prompt Optimization for VLM Reward Models
by: Gumbsch, Christian, et al.
Published: (2026)
by: Gumbsch, Christian, et al.
Published: (2026)
TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance
by: Liu, Yuyang, et al.
Published: (2025)
by: Liu, Yuyang, et al.
Published: (2025)
ORSO: Accelerating Reward Design via Online Reward Selection and Policy Optimization
by: Zhang, Chen Bo Calvin, et al.
Published: (2024)
by: Zhang, Chen Bo Calvin, et al.
Published: (2024)
Assigning Credit with Partial Reward Decoupling in Multi-Agent Proximal Policy Optimization
by: Kapoor, Aditya, et al.
Published: (2024)
by: Kapoor, Aditya, et al.
Published: (2024)
Diffusion-Reward Adversarial Imitation Learning
by: Lai, Chun-Mao, et al.
Published: (2024)
by: Lai, Chun-Mao, et al.
Published: (2024)
Redistributing Rewards Across Time and Agents for Multi-Agent Reinforcement Learning
by: Kapoor, Aditya, et al.
Published: (2025)
by: Kapoor, Aditya, et al.
Published: (2025)
Constraints as Rewards: Reinforcement Learning for Robots without Reward Functions
by: Ishihara, Yu, et al.
Published: (2025)
by: Ishihara, Yu, et al.
Published: (2025)
StableTracker: Learning to Stably Track Target via Differentiable Simulation
by: Li, Fanxing, et al.
Published: (2025)
by: Li, Fanxing, et al.
Published: (2025)
Guided Policy Optimization under Partial Observability
by: Li, Yueheng, et al.
Published: (2025)
by: Li, Yueheng, et al.
Published: (2025)
Robot Policy Learning with Temporal Optimal Transport Reward
by: Fu, Yuwei, et al.
Published: (2024)
by: Fu, Yuwei, et al.
Published: (2024)
Confounding Robust Continuous Control via Automatic Reward Shaping
by: Juliani, Mateo, et al.
Published: (2026)
by: Juliani, Mateo, et al.
Published: (2026)
Simple but Stable, Fast and Safe: Achieve End-to-end Control by High-Fidelity Differentiable Simulation
by: Li, Fanxing, et al.
Published: (2026)
by: Li, Fanxing, et al.
Published: (2026)
Robometer: Scaling General-Purpose Robotic Reward Models via Trajectory Comparisons
by: Liang, Anthony, et al.
Published: (2026)
by: Liang, Anthony, et al.
Published: (2026)
Curriculum Reinforcement Learning for Quadrotor Racing with Random Obstacles
by: Sun, Fangyu, et al.
Published: (2026)
by: Sun, Fangyu, et al.
Published: (2026)
Reward-Punishment Reinforcement Learning with Maximum Entropy
by: Wang, Jiexin, et al.
Published: (2024)
by: Wang, Jiexin, et al.
Published: (2024)
Residual Reward Models for Preference-based Reinforcement Learning
by: Cao, Chenyang, et al.
Published: (2025)
by: Cao, Chenyang, et al.
Published: (2025)
DISCOVER: Automated Curricula for Sparse-Reward Reinforcement Learning
by: Diaz-Bone, Leander, et al.
Published: (2025)
by: Diaz-Bone, Leander, et al.
Published: (2025)
Subwords as Skills: Tokenization for Sparse-Reward Reinforcement Learning
by: Yunis, David, et al.
Published: (2023)
by: Yunis, David, et al.
Published: (2023)
Adaptive Querying for Reward Learning from Human Feedback
by: Anand, Yashwanthi, et al.
Published: (2024)
by: Anand, Yashwanthi, et al.
Published: (2024)
Observation Adaptation via Annealed Importance Resampling for Partially Observable Markov Decision Processes
by: Zhang, Yunuo, et al.
Published: (2025)
by: Zhang, Yunuo, et al.
Published: (2025)
RDAR: Reward-Driven Agent Relevance Estimation for Autonomous Driving
by: Bosio, Carlo, et al.
Published: (2025)
by: Bosio, Carlo, et al.
Published: (2025)
CaRL: Learning Scalable Planning Policies with Simple Rewards
by: Jaeger, Bernhard, et al.
Published: (2025)
by: Jaeger, Bernhard, et al.
Published: (2025)
Batch Active Learning of Reward Functions from Human Preferences
by: Bıyık, Erdem, et al.
Published: (2024)
by: Bıyık, Erdem, et al.
Published: (2024)
Enabling Option Learning in Sparse Rewards with Hindsight Experience Replay
by: Romio, Gabriel, et al.
Published: (2026)
by: Romio, Gabriel, et al.
Published: (2026)
DrS: Learning Reusable Dense Rewards for Multi-Stage Tasks
by: Mu, Tongzhou, et al.
Published: (2024)
by: Mu, Tongzhou, et al.
Published: (2024)
TOPReward: Token Probabilities as Hidden Zero-Shot Rewards for Robotics
by: Chen, Shirui, et al.
Published: (2026)
by: Chen, Shirui, et al.
Published: (2026)
Not Only Rewards But Also Constraints: Applications on Legged Robot Locomotion
by: Kim, Yunho, et al.
Published: (2023)
by: Kim, Yunho, et al.
Published: (2023)
A Generalized Acquisition Function for Preference-based Reward Learning
by: Ellis, Evan, et al.
Published: (2024)
by: Ellis, Evan, et al.
Published: (2024)
Reward Learning from Suboptimal Demonstrations with Applications in Surgical Electrocautery
by: Karimi, Zohre, et al.
Published: (2024)
by: Karimi, Zohre, et al.
Published: (2024)
Can We Really Learn One Representation to Optimize All Rewards?
by: Zheng, Chongyi, et al.
Published: (2026)
by: Zheng, Chongyi, et al.
Published: (2026)
A Review of Reward Functions for Reinforcement Learning in the context of Autonomous Driving
by: Abouelazm, Ahmed, et al.
Published: (2024)
by: Abouelazm, Ahmed, et al.
Published: (2024)
LORD: Large Models based Opposite Reward Design for Autonomous Driving
by: Ye, Xin, et al.
Published: (2024)
by: Ye, Xin, et al.
Published: (2024)
Causally Robust Reward Learning from Reason-Augmented Preference Feedback
by: Hwang, Minjune, et al.
Published: (2026)
by: Hwang, Minjune, et al.
Published: (2026)
Learning to Recover: Dynamic Reward Shaping with Wheel-Leg Coordination for Fallen Robots
by: Deng, Boyuan, et al.
Published: (2025)
by: Deng, Boyuan, et al.
Published: (2025)
DreamSmooth: Improving Model-based Reinforcement Learning via Reward Smoothing
by: Lee, Vint, et al.
Published: (2023)
by: Lee, Vint, et al.
Published: (2023)
Similar Items
-
VisFly: An Efficient and Versatile Simulator for Training Vision-based Flight
by: Li, Fanxing, et al.
Published: (2024) -
VisFly-Lab: Unified Differentiable Framework for First-Order Reinforcement Learning of Quadrotor Control
by: Li, Fanxing, et al.
Published: (2026) -
First Order Model-Based RL through Decoupled Backpropagation
by: Amigo, Joseph, et al.
Published: (2025) -
Aligning Text-to-Image Diffusion Models with Reward Backpropagation
by: Prabhudesai, Mihir, et al.
Published: (2023) -
Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
by: Xie, Tianbao, et al.
Published: (2023)