:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Cameron, Chris, Wang, Wangzheng, Ivanov, Nikita, Bhattacharyya, Ashmita, Chételat, Didier, Zhang, Yingxue
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	https://arxiv.org/abs/2604.18839
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

A Balanced Neuro-Symbolic Approach for Commonsense Abductive Logic
por: Cotnareanu, Joseph, et al.
Publicado: (2026)

Looping Back to Move Forward: Recursive Transformers for Efficient and Flexible Large Multimodal Models
por: Xu, Ruihan, et al.
Publicado: (2026)

GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection
por: Zhang, Zhanguang, et al.
Publicado: (2024)

Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
por: Zheng, Huaixiu Steven, et al.
Publicado: (2023)

AdaptiveStep: Automatically Dividing Reasoning Step through Model Confidence
por: Liu, Yuliang, et al.
Publicado: (2025)

Learning to Generate Formally Verifiable Step-by-Step Logic Reasoning via Structured Formal Intermediaries
por: Chen, Luoxin, et al.
Publicado: (2026)

Generalized Back-Stepping Experience Replay in Sparse-Reward Environments
por: Lyu, Guwen, et al.
Publicado: (2024)

Do Latent-CoT Models Think Step-by-Step? A Mechanistic Study on Sequential Reasoning Tasks
por: Liang, Jia, et al.
Publicado: (2026)

Boosting Deductive Reasoning with Step Signals In RLHF
por: Li, Jialian, et al.
Publicado: (2024)

Denoising Score Distillation: From Noisy Diffusion Pretraining to One-Step High-Quality Generation
por: Chen, Tianyu, et al.
Publicado: (2025)

The Graph's Apprentice: Teaching an LLM Low Level Knowledge for Circuit Quality Estimation
por: Moravej, Reza, et al.
Publicado: (2024)

A Step Back: Prefix Importance Ratio Stabilizes Policy Optimization
por: Lei, Shiye, et al.
Publicado: (2026)

Optimizing Mastery Learning by Fast-Forwarding Over-Practice Steps
por: Xia, Meng, et al.
Publicado: (2025)

One-Step is Enough: Sparse Autoencoders for Text-to-Image Diffusion Models
por: Surkov, Viacheslav, et al.
Publicado: (2024)

Abductive Reasoning with Probabilistic Commonsense
por: Cotnareanu, Joseph, et al.
Publicado: (2026)

Denoising Particle Filters: Learning State Estimation with Single-Step Objectives
por: Röstel, Lennart, et al.
Publicado: (2026)

One-Step Offline Distillation of Diffusion-based Models via Koopman Modeling
por: Berman, Nimrod, et al.
Publicado: (2025)

Diffusion World Model: Future Modeling Beyond Step-by-Step Rollout for Offline Reinforcement Learning
por: Ding, Zihan, et al.
Publicado: (2024)

Step-level Denoising-time Diffusion Alignment with Multiple Objectives
por: Zhang, Qi, et al.
Publicado: (2026)

Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
por: Lai, Xin, et al.
Publicado: (2024)

LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently
por: Zhang, Yuanhe, et al.
Publicado: (2025)

The Signal is in the Steps: Local Scoring for Reasoning Data Selection
por: Just, Hoang Anh, et al.
Publicado: (2025)

LLM Reasoning with Process Rewards for Outcome-Guided Steps
por: Rezaei, Mohammad, et al.
Publicado: (2026)

Characteristic Learning for Provable One Step Generation
por: Ding, Zhao, et al.
Publicado: (2024)

Multi-Step Reasoning with Large Language Models, a Survey
por: Plaat, Aske, et al.
Publicado: (2024)

Offline Reinforcement Learning for LLM Multi-Step Reasoning
por: Wang, Huaijie, et al.
Publicado: (2024)

Fine-Tuning and Prompt Optimization: Two Great Steps that Work Better Together
por: Soylu, Dilara, et al.
Publicado: (2024)

Step Back to Leap Forward: Self-Backtracking for Boosting Reasoning of Language Models
por: Yang, Xiao-Wen, et al.
Publicado: (2025)

Discrete MeanFlow: One-Step Generation via Conditional Transition Kernels
por: Khan, Fairoz Nower, et al.
Publicado: (2026)

One-Step Generative Policies with Q-Learning: A Reformulation of MeanFlow
por: Wang, Zeyuan, et al.
Publicado: (2025)

Boosting Maximum Entropy Reinforcement Learning via One-Step Flow Matching
por: Li, Zeqiao, et al.
Publicado: (2026)

Scalable, Explainable and Provably Robust Anomaly Detection with One-Step Flow Matching
por: Li, Zhong, et al.
Publicado: (2025)

Deciphering Scientific Reasoning Steps from Outcome Data for Molecule Optimization
por: Liu, Zequn, et al.
Publicado: (2026)

Step-KTO: Optimizing Mathematical Reasoning through Stepwise Binary Feedback
por: Lin, Yen-Ting, et al.
Publicado: (2025)

InnerThoughts: Disentangling Representations and Predictions in Large Language Models
por: Chételat, Didier, et al.
Publicado: (2025)

Graph Elicitation for Guiding Multi-Step Reasoning in Large Language Models
por: Park, Jinyoung, et al.
Publicado: (2023)

High-Order Matching for One-Step Shortcut Diffusion Models
por: Chen, Bo, et al.
Publicado: (2025)

WFR-MFM: One-Step Inference for Dynamic Unbalanced Optimal Transport
por: Wang, Xinyu, et al.
Publicado: (2026)

Putting the Value Back in RL: Better Test-Time Scaling by Unifying LLM Reasoners With Verifiers
por: Sareen, Kusha, et al.
Publicado: (2025)

Envisioning the Future, One Step at a Time
por: Baumann, Stefan Andreas, et al.
Publicado: (2026)