Notes on the Reward Representation of Posterior Updates
Fuente:
arXiv
Guardado en:
| Autor principal: | Ortega, Pedro A. |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
BaNEL: Exploration Posteriors for Generative Modeling Using Only Negative Rewards
por: Lee, Sangyun, et al.
Publicado: (2025)
por: Lee, Sangyun, et al.
Publicado: (2025)
Debiasing Reward Models by Representation Learning with Guarantees
por: Ng, Ignavier, et al.
Publicado: (2025)
por: Ng, Ignavier, et al.
Publicado: (2025)
Auxiliary Reward Generation with Transition Distance Representation Learning
por: Li, Siyuan, et al.
Publicado: (2024)
por: Li, Siyuan, et al.
Publicado: (2024)
Representation Without Reward: A JEPA Audit for LLM Fine-Tuning
por: Sengupta, Biswa
Publicado: (2026)
por: Sengupta, Biswa
Publicado: (2026)
Temporal Representations for Exploration: Learning Complex Exploratory Behavior without Extrinsic Rewards
por: Mohamed, Faisal, et al.
Publicado: (2026)
por: Mohamed, Faisal, et al.
Publicado: (2026)
Knowledge Adaptation as Posterior Correction
por: Khan, Mohammad Emtiyaz
Publicado: (2025)
por: Khan, Mohammad Emtiyaz
Publicado: (2025)
Can We Really Learn One Representation to Optimize All Rewards?
por: Zheng, Chongyi, et al.
Publicado: (2026)
por: Zheng, Chongyi, et al.
Publicado: (2026)
Amortized In-Context Bayesian Posterior Estimation
por: Mittal, Sarthak, et al.
Publicado: (2025)
por: Mittal, Sarthak, et al.
Publicado: (2025)
Posterior Label Smoothing for Node Classification
por: Heo, Jaeseung, et al.
Publicado: (2024)
por: Heo, Jaeseung, et al.
Publicado: (2024)
SVRG and Beyond via Posterior Correction
por: Daheim, Nico, et al.
Publicado: (2025)
por: Daheim, Nico, et al.
Publicado: (2025)
Intrinsic Reward Policy Optimization for Sparse-Reward Environments
por: Cho, Minjae, et al.
Publicado: (2026)
por: Cho, Minjae, et al.
Publicado: (2026)
Attention-Based Reward Shaping for Sparse and Delayed Rewards
por: Holmes, Ian, et al.
Publicado: (2025)
por: Holmes, Ian, et al.
Publicado: (2025)
Reward Hacking Mitigation using Verifiable Composite Rewards
por: Tarek, Mirza Farhan Bin, et al.
Publicado: (2025)
por: Tarek, Mirza Farhan Bin, et al.
Publicado: (2025)
Repairing Reward Functions with Feedback to Mitigate Reward Hacking
por: Hatgis-Kessell, Stephane, et al.
Publicado: (2025)
por: Hatgis-Kessell, Stephane, et al.
Publicado: (2025)
Reward Centering
por: Naik, Abhishek, et al.
Publicado: (2024)
por: Naik, Abhishek, et al.
Publicado: (2024)
Adversarial Reward Auditing for Active Detection and Mitigation of Reward Hacking
por: Beigi, Mohammad, et al.
Publicado: (2026)
por: Beigi, Mohammad, et al.
Publicado: (2026)
Solving Diffusion Inverse Problems with Restart Posterior Sampling
por: Ahmed, Bilal, et al.
Publicado: (2025)
por: Ahmed, Bilal, et al.
Publicado: (2025)
Intentional Updates for Streaming Reinforcement Learning
por: Sharifnassab, Arsalan, et al.
Publicado: (2026)
por: Sharifnassab, Arsalan, et al.
Publicado: (2026)
SemiReward: A General Reward Model for Semi-supervised Learning
por: Li, Siyuan, et al.
Publicado: (2023)
por: Li, Siyuan, et al.
Publicado: (2023)
Trust Region Reward Optimization and Proximal Inverse Reward Optimization Algorithm
por: Chen, Yang, et al.
Publicado: (2025)
por: Chen, Yang, et al.
Publicado: (2025)
Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment
por: Wang, Chaoqi, et al.
Publicado: (2025)
por: Wang, Chaoqi, et al.
Publicado: (2025)
Tiered Reward: Designing Rewards for Specification and Fast Learning of Desired Behavior
por: Zhou, Zhiyuan, et al.
Publicado: (2022)
por: Zhou, Zhiyuan, et al.
Publicado: (2022)
Bootstrapped Reward Shaping
por: Adamczyk, Jacob, et al.
Publicado: (2025)
por: Adamczyk, Jacob, et al.
Publicado: (2025)
Neural Reward Machines
por: Umili, Elena, et al.
Publicado: (2024)
por: Umili, Elena, et al.
Publicado: (2024)
Numeric Reward Machines
por: Levina, Kristina, et al.
Publicado: (2024)
por: Levina, Kristina, et al.
Publicado: (2024)
Regularized Offline Policy Optimization with Posterior Hybrid Bayesian Belief
por: Lin, Hongqiang, et al.
Publicado: (2026)
por: Lin, Hongqiang, et al.
Publicado: (2026)
Uncertainty-aware Evaluation of Auxiliary Anomalies with the Expected Anomaly Posterior
por: Perini, Lorenzo, et al.
Publicado: (2024)
por: Perini, Lorenzo, et al.
Publicado: (2024)
Efficient Approximate Posterior Sampling with Annealed Langevin Monte Carlo
por: Parulekar, Advait, et al.
Publicado: (2025)
por: Parulekar, Advait, et al.
Publicado: (2025)
What Fundamental Structure in Reward Functions Enables Efficient Sparse-Reward Learning?
por: Shihab, Ibne Farabi, et al.
Publicado: (2025)
por: Shihab, Ibne Farabi, et al.
Publicado: (2025)
Which Rewards Matter? Reward Selection for Reinforcement Learning under Limited Feedback
por: Chaudhari, Shreyas, et al.
Publicado: (2025)
por: Chaudhari, Shreyas, et al.
Publicado: (2025)
The Update-Equivalence Framework for Decision-Time Planning
por: Sokota, Samuel, et al.
Publicado: (2023)
por: Sokota, Samuel, et al.
Publicado: (2023)
RationalRewards: Reasoning Rewards Scale Visual Generation Both Training and Test Time
por: Wang, Haozhe, et al.
Publicado: (2026)
por: Wang, Haozhe, et al.
Publicado: (2026)
MemReward: Graph-Based Experience Memory for LLM Reward Prediction with Limited Labels
por: Luo, Tianyang, et al.
Publicado: (2026)
por: Luo, Tianyang, et al.
Publicado: (2026)
Towards Improving Reward Design in RL: A Reward Alignment Metric for RL Practitioners
por: Muslimani, Calarina, et al.
Publicado: (2025)
por: Muslimani, Calarina, et al.
Publicado: (2025)
InfoRM: Mitigating Reward Hacking in RLHF via Information-Theoretic Reward Modeling
por: Miao, Yuchun, et al.
Publicado: (2024)
por: Miao, Yuchun, et al.
Publicado: (2024)
PRDP: Proximal Reward Difference Prediction for Large-Scale Reward Finetuning of Diffusion Models
por: Deng, Fei, et al.
Publicado: (2024)
por: Deng, Fei, et al.
Publicado: (2024)
When Distance Distracts: Representation Distance Bias in BT-Loss for Reward Models
por: Xie, Tong, et al.
Publicado: (2025)
por: Xie, Tong, et al.
Publicado: (2025)
Efficient LLM Reasoning via Variational Posterior Guidance with Efficiency Awareness
por: Chen, Zizhao, et al.
Publicado: (2026)
por: Chen, Zizhao, et al.
Publicado: (2026)
Posterior Mean Matching: Generative Modeling through Online Bayesian Inference
por: Salazar, Sebastian, et al.
Publicado: (2024)
por: Salazar, Sebastian, et al.
Publicado: (2024)
Coupled Data and Measurement Space Dynamics for Enhanced Diffusion Posterior Sampling
por: Hamidi, Shayan Mohajer, et al.
Publicado: (2025)
por: Hamidi, Shayan Mohajer, et al.
Publicado: (2025)
Ejemplares similares
-
BaNEL: Exploration Posteriors for Generative Modeling Using Only Negative Rewards
por: Lee, Sangyun, et al.
Publicado: (2025) -
Debiasing Reward Models by Representation Learning with Guarantees
por: Ng, Ignavier, et al.
Publicado: (2025) -
Auxiliary Reward Generation with Transition Distance Representation Learning
por: Li, Siyuan, et al.
Publicado: (2024) -
Representation Without Reward: A JEPA Audit for LLM Fine-Tuning
por: Sengupta, Biswa
Publicado: (2026) -
Temporal Representations for Exploration: Learning Complex Exploratory Behavior without Extrinsic Rewards
por: Mohamed, Faisal, et al.
Publicado: (2026)