:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Wang, Muyao, Xie, Zeke, Nakayama, Hideki
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2605.28203
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Channel Matters: Estimating Channel Influence for Multivariate Time Series
by: Wang, Muyao, et al.
Published: (2024)

MangaFlow: An End-to-End Agentic Framework for Controllable Story to Manga Generation
by: Wang, Muyao, et al.
Published: (2026)

Advanced Weakly-Supervised Formula Exploration for Neuro-Symbolic Mathematical Reasoning
by: Wu, Yuxuan, et al.
Published: (2025)

Mano: Restriking Manifold Optimization for LLM Training
by: Gu, Yufei, et al.
Published: (2026)

Training One Model to Master Cross-Level Agentic Actions via Reinforcement Learning
by: He, Kaichen, et al.
Published: (2025)

Dimension-Free Saddle-Point Escape in Muon
by: Long, Yanlin, et al.
Published: (2026)

A Comprehensive Information-Decomposition Analysis of Large Vision-Language Models
by: Xiu, Lixin, et al.
Published: (2026)

Treating Brain-inspired Memories as Priors for Diffusion Model to Forecast Multivariate Time Series
by: Wang, Muyao, et al.
Published: (2024)

Understanding Data Influence with Differential Approximation
by: Tan, Haoru, et al.
Published: (2025)

Considering Nonstationary within Multivariate Time Series with Variational Hierarchical Transformer for Forecasting
by: Wang, Muyao, et al.
Published: (2024)

Weak-to-Strong Diffusion with Reflection
by: Bai, Lichen, et al.
Published: (2025)

Boulder2Vec: Modeling Climber Performances in Professional Bouldering Competitions
by: Baron, Ethan, et al.
Published: (2024)

Multiphysics Bench: Benchmarking and Investigating Scientific Machine Learning for Multiphysics PDEs
by: Yang, Changfan, et al.
Published: (2025)

FunPRM: Function-as-Step Process Reward Model with Meta Reward Correction for Code Generation
by: Zhang, Ruiyi, et al.
Published: (2026)

Reward Models Are Secretly Value Functions: Temporally Coherent Reward Modeling
by: Nikulkov, Alex
Published: (2026)

CRAFT: Aligning Diffusion Models with Fine-Tuning Is Easier Than You Think
by: Sun, Zening, et al.
Published: (2026)

Goal-Driven Reward by Video Diffusion Models for Reinforcement Learning
by: Wang, Qi, et al.
Published: (2025)

Video2Reward: Generating Reward Function from Videos for Legged Robot Behavior Learning
by: Zeng, Runhao, et al.
Published: (2024)

Zigzag Diffusion Sampling: Diffusion Models Can Self-Improve via Self-Reflection
by: Bai, Lichen, et al.
Published: (2024)

Self-Refining Video Sampling
by: Jang, Sangwon, et al.
Published: (2026)

ODIN: Disentangled Reward Mitigates Hacking in RLHF
by: Chen, Lichang, et al.
Published: (2024)

Disentanglement and Assessment of Shortcuts in Ophthalmological Retinal Imaging Exams
by: Fernandes, Leonor, et al.
Published: (2025)

Interpretable Preferences via Multi-Objective Reward Modeling and Mixture-of-Experts
by: Wang, Haoxiang, et al.
Published: (2024)

USO: Unified Style and Subject-Driven Generation via Disentangled and Reward Learning
by: Wu, Shaojin, et al.
Published: (2025)

Uncertainty-aware Reward Model: Teaching Reward Models to Know What is Unknown
by: Lou, Xingzhou, et al.
Published: (2024)

Disentangled World Models: Learning to Transfer Semantic Knowledge from Distracting Videos for Reinforcement Learning
by: Wang, Qi, et al.
Published: (2025)

FunReason: Enhancing Large Language Models' Function Calling via Self-Refinement Multiscale Loss and Automated Data Refinement
by: Hao, Bingguang, et al.
Published: (2025)

Selective Preference Optimization via Token-Level Reward Function Estimation
by: Yang, Kailai, et al.
Published: (2024)

Diffusion Reward: Learning Rewards via Conditional Video Diffusion
by: Huang, Tao, et al.
Published: (2023)

Harness Local Rewards for Global Benefits: Effective Text-to-Video Generation Alignment with Patch-level Reward Models
by: Wang, Shuting, et al.
Published: (2025)

On the Overlooked Pitfalls of Weight Decay and How to Mitigate Them: A Gradient-Norm Perspective
by: Xie, Zeke, et al.
Published: (2020)

Interpretable Reward Model via Sparse Autoencoder
by: Zhang, Shuyi, et al.
Published: (2025)

Controllable Video Generation with Provable Disentanglement
by: Shen, Yifan, et al.
Published: (2025)

Dancing with Still Images: Video Distillation via Static-Dynamic Disentanglement
by: Wang, Ziyu, et al.
Published: (2023)

Pre-trained Molecular Language Models with Random Functional Group Masking
by: Peng, Tianhao, et al.
Published: (2024)

SoliReward: Mitigating Susceptibility to Reward Hacking and Annotation Noise in Video Generation Reward Models
by: Lian, Jiesong, et al.
Published: (2025)

Robust Reward Alignment via Hypothesis Space Batch Cutting
by: Xie, Zhixian, et al.
Published: (2025)

Graph-based Unsupervised Disentangled Representation Learning via Multimodal Large Language Models
by: Xie, Baao, et al.
Published: (2024)

Parent-Guided Semantic Reward Model (PGSRM): Embedding-Based Reward Functions for Reinforcement Learning of Transformer Language Models
by: Plashchinsky, Alexandr
Published: (2025)

R2IF: Aligning Reasoning with Decisions via Composite Rewards for Interpretable LLM Function Calling
by: Cheng, Aijia, et al.
Published: (2026)