Cover Image

Q-SFT: Q-Learning for Language Models via Supervised Fine-Tuning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Hong, Joey, Dragan, Anca, Levine, Sergey
Format:	Preprint
Published:	2024
Subjects:	Machine Learning Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Interactive Dialogue Agents via Reinforcement Learning on Hindsight Regenerations
by: Hong, Joey, et al.
Published: (2024)

Planning without Search: Refining Frontier LLMs with Offline Goal-Conditioned RL
by: Hong, Joey, et al.
Published: (2025)

Learning to Model the World with Language
by: Lin, Jessy, et al.
Published: (2023)

Supervised Fine-Tuning as Inverse Reinforcement Learning
by: Sun, Hao
Published: (2024)

Fine-Tuning Large Vision-Language Models as Decision-Making Agents via Reinforcement Learning
by: Zhai, Yuexiang, et al.
Published: (2024)

Zero-Overhead Introspection for Adaptive Test-Time Compute
by: Manvi, Rohin, et al.
Published: (2025)

Proximal Supervised Fine-Tuning
by: Zhu, Wenhong, et al.
Published: (2025)

Flow Q-Learning
by: Park, Seohong, et al.
Published: (2025)

Fine-Tuning Language Models with Reward Learning on Policy
by: Lang, Hao, et al.
Published: (2024)

DynamixSFT: Dynamic Mixture Optimization of Instruction Tuning Collections
by: Shin, Haebin, et al.
Published: (2025)

SFT-GO: Supervised Fine-Tuning with Group Optimization for Large Language Models
by: Kim, Gyuhak, et al.
Published: (2025)

Aligning Large Language Models via Fine-grained Supervision
by: Xu, Dehong, et al.
Published: (2024)

Stabilizing LLM Supervised Fine-Tuning via Explicit Distributional Control
by: Wang, Xinyu, et al.
Published: (2026)

Learning to Assist Humans without Inferring Rewards
by: Myers, Vivek, et al.
Published: (2024)

ArCHer: Training Language Model Agents via Hierarchical Multi-Turn RL
by: Zhou, Yifei, et al.
Published: (2024)

Embedding Enhancement via Fine-Tuned Language Models for Learner-Item Cognitive Modeling
by: Liu, Yuanhao, et al.
Published: (2026)

Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling
by: Huang, Zeyu, et al.
Published: (2025)

Enhancing Trust in Large Language Models via Uncertainty-Calibrated Fine-Tuning
by: Krishnan, Ranganath, et al.
Published: (2024)

Linear Chain Transformation: Expanding Optimization Dynamics for Fine-Tuning Large Language Models
by: Wang, Yulong, et al.
Published: (2024)

Supervised Fine-Tuning Needs to Unlock the Potential of Token Priority
by: Shen, Zhanming, et al.
Published: (2026)

Scaling Sparse Fine-Tuning to Large Language Models
by: Ansell, Alan, et al.
Published: (2024)

Boosting Large Language Models with Mask Fine-Tuning
by: Zhang, Mingyuan, et al.
Published: (2025)

Fine-Tuning Improves Information Conveyance in Language Models
by: Cheng, Yuwei, et al.
Published: (2026)

Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
by: Myers, Vivek, et al.
Published: (2024)

Q-learning with Adjoint Matching
by: Li, Qiyang, et al.
Published: (2026)

Unfamiliar Finetuning Examples Control How Language Models Hallucinate
by: Kang, Katie, et al.
Published: (2024)

Q-PEFT: Query-dependent Parameter Efficient Fine-tuning for Text Reranking with Large Language Models
by: Peng, Zhiyuan, et al.
Published: (2024)

Nested-ReFT: Efficient Reinforcement Learning for Large Language Model Fine-Tuning via Off-Policy Rollouts
by: Heuillet, Maxime, et al.
Published: (2025)

Fine-Tuning LLMs for Report Summarization: Analysis on Supervised and Unsupervised Data
by: Rallapalli, Swati, et al.
Published: (2025)

IA2: Alignment with ICL Activations Improves Supervised Fine-Tuning
by: Mishra, Aayush, et al.
Published: (2025)

Crafting Efficient Fine-Tuning Strategies for Large Language Models
by: Oliver, Michael, et al.
Published: (2024)

Improving Large Language Models with Concept-Aware Fine-Tuning
by: Chen, Michael K., et al.
Published: (2025)

Unintended Memorization of Sensitive Information in Fine-Tuned Language Models
by: Szep, Marton, et al.
Published: (2026)

G-Loss: Graph-Guided Fine-Tuning of Language Models
by: Sharma, Aditya, et al.
Published: (2026)

BASE-Q: Bias and Asymmetric Scaling Enhanced Rotational Quantization for Large Language Models
by: He, Liulu, et al.
Published: (2025)

FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain
by: Deb, Rohan, et al.
Published: (2025)

Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
by: Chen, Zixiang, et al.
Published: (2024)

Continual SFT Matches Multimodal RLHF with Negative Supervision
by: Zhu, Ke, et al.
Published: (2024)

Quagmires in SFT-RL Post-Training: When High SFT Scores Mislead and What to Use Instead
by: Kang, Feiyang, et al.
Published: (2025)

Children's English Reading Story Generation via Supervised Fine-Tuning of Compact LLMs with Controllable Difficulty and Safety
by: Shen, Qian, et al.
Published: (2026)