Implicit Reward as the Bridge: A Unified View of SFT and DPO Connections
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Bo, Cheng, Qinyuan, Peng, Runyu, Bao, Rong, Li, Peiji, Guo, Qipeng, Li, Linyang, Zeng, Zhiyuan, Zhou, Yunhua, Qiu, Xipeng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
How Attention Sinks Emerge in Large Language Models: An Interpretability Perspective
by: Peng, Runyu, et al.
Published: (2026)
by: Peng, Runyu, et al.
Published: (2026)
Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective
by: Zeng, Zhiyuan, et al.
Published: (2024)
by: Zeng, Zhiyuan, et al.
Published: (2024)
Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?
by: Zeng, Zhiyuan, et al.
Published: (2025)
by: Zeng, Zhiyuan, et al.
Published: (2025)
Explicit Multi-head Attention for Inter-head Interaction in Large Language Models
by: Peng, Runyu, et al.
Published: (2026)
by: Peng, Runyu, et al.
Published: (2026)
UnitCoder: Scalable Iterative Code Synthesis with Unit Test Guidance
by: Ma, Yichuan, et al.
Published: (2025)
by: Ma, Yichuan, et al.
Published: (2025)
FastMCTS: A Simple Sampling Strategy for Data Synthesis
by: Li, Peiji, et al.
Published: (2025)
by: Li, Peiji, et al.
Published: (2025)
Data-free Weight Compress and Denoise for Large Language Models
by: Peng, Runyu, et al.
Published: (2024)
by: Peng, Runyu, et al.
Published: (2024)
Dynamic and Generalizable Process Reward Modeling
by: Yin, Zhangyue, et al.
Published: (2025)
by: Yin, Zhangyue, et al.
Published: (2025)
UFT: Unifying Fine-Tuning of SFT and RLHF/DPO/UNA through a Generalized Implicit Reward Function
by: Wang, Zhichao, et al.
Published: (2024)
by: Wang, Zhichao, et al.
Published: (2024)
Turn Waste into Worth: Rectifying Top-$k$ Router of MoE
by: Zeng, Zhiyuan, et al.
Published: (2024)
by: Zeng, Zhiyuan, et al.
Published: (2024)
Case2Code: Scalable Synthetic Data for Code Generation
by: Shao, Yunfan, et al.
Published: (2024)
by: Shao, Yunfan, et al.
Published: (2024)
How to Set the Learning Rate for Large-Scale Pre-training?
by: Zhou, Yunhua, et al.
Published: (2026)
by: Zhou, Yunhua, et al.
Published: (2026)
How to Mitigate Overfitting in Weak-to-strong Generalization?
by: Shi, Junhao, et al.
Published: (2025)
by: Shi, Junhao, et al.
Published: (2025)
Unearthing Large Scale Domain-Specific Knowledge from Public Corpora
by: Fei, Zhaoye, et al.
Published: (2024)
by: Fei, Zhaoye, et al.
Published: (2024)
Unified Active Retrieval for Retrieval Augmented Generation
by: Cheng, Qinyuan, et al.
Published: (2024)
by: Cheng, Qinyuan, et al.
Published: (2024)
How to Set the Batch Size for Large-Scale Pre-training?
by: Zhou, Yunhua, et al.
Published: (2026)
by: Zhou, Yunhua, et al.
Published: (2026)
Bridging SFT and DPO for Diffusion Model Alignment with Self-Sampling Preference Optimization
by: Zhang, Daoan, et al.
Published: (2024)
by: Zhang, Daoan, et al.
Published: (2024)
Timely Machine: Awareness of Time Makes Test-Time Scaling Agentic
by: Ma, Yichuan, et al.
Published: (2026)
by: Ma, Yichuan, et al.
Published: (2026)
Agent Alignment in Evolving Social Norms
by: Li, Shimin, et al.
Published: (2024)
by: Li, Shimin, et al.
Published: (2024)
Mixing Expert Knowledge: Bring Human Thoughts Back To the Game of Go
by: Ma, Yichuan, et al.
Published: (2026)
by: Ma, Yichuan, et al.
Published: (2026)
ARISE: An Adaptive Resolution-Aware Metric for Test-Time Scaling Evaluation in Large Reasoning Models
by: Yin, Zhangyue, et al.
Published: (2025)
by: Yin, Zhangyue, et al.
Published: (2025)
Synthetic Pre-Pre-Training Improves Language Model Robustness to Noisy Pre-Training Data
by: Guo, Xu, et al.
Published: (2026)
by: Guo, Xu, et al.
Published: (2026)
Bootstrapping Language Models with DPO Implicit Rewards
by: Chen, Changyu, et al.
Published: (2024)
by: Chen, Changyu, et al.
Published: (2024)
What and When to Distill: Selective Hindsight Distillation for Multi-Turn Agents
by: Li, Xiaozhe, et al.
Published: (2026)
by: Li, Xiaozhe, et al.
Published: (2026)
Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer Selection in Large Language Models
by: Yin, Zhangyue, et al.
Published: (2024)
by: Yin, Zhangyue, et al.
Published: (2024)
F-Eval: Assessing Fundamental Abilities with Refined Evaluation Methods
by: Sun, Yu, et al.
Published: (2024)
by: Sun, Yu, et al.
Published: (2024)
VisuoThink: Empowering LVLM Reasoning with Multimodal Tree Search
by: Wang, Yikun, et al.
Published: (2025)
by: Wang, Yikun, et al.
Published: (2025)
DuoDecoding: Hardware-aware Heterogeneous Speculative Decoding with Dynamic Multi-Sequence Drafting
by: Lv, Kai, et al.
Published: (2025)
by: Lv, Kai, et al.
Published: (2025)
AutoLogi: Automated Generation of Logic Puzzles for Evaluating Reasoning Abilities of Large Language Models
by: Zhu, Qin, et al.
Published: (2025)
by: Zhu, Qin, et al.
Published: (2025)
Getting More Juice Out of the SFT Data: Reward Learning from Human Demonstration Improves SFT for LLM Alignment
by: Li, Jiaxiang, et al.
Published: (2024)
by: Li, Jiaxiang, et al.
Published: (2024)
Can AI Assistants Know What They Don't Know?
by: Cheng, Qinyuan, et al.
Published: (2024)
by: Cheng, Qinyuan, et al.
Published: (2024)
Mousse: Rectifying the Geometry of Muon with Curvature-Aware Preconditioning
by: Zhang, Yechen, et al.
Published: (2026)
by: Zhang, Yechen, et al.
Published: (2026)
Difficulty-Based Preference Data Selection by DPO Implicit Reward Gap
by: Qi, Xuan, et al.
Published: (2025)
by: Qi, Xuan, et al.
Published: (2025)
Reg-DPO: SFT-Regularized Direct Preference Optimization with GT-Pair for Improving Video Generation
by: Du, Jie, et al.
Published: (2025)
by: Du, Jie, et al.
Published: (2025)
Scaling Laws for Fact Memorization of Large Language Models
by: Lu, Xingyu, et al.
Published: (2024)
by: Lu, Xingyu, et al.
Published: (2024)
TL-GRPO: Turn-Level RL for Reasoning-Guided Iterative Optimization
by: Li, Peiji, et al.
Published: (2026)
by: Li, Peiji, et al.
Published: (2026)
An Empirical Study of SFT-DPO Interaction and Parameterization in Small Language Models
by: Feng, Yuming, et al.
Published: (2026)
by: Feng, Yuming, et al.
Published: (2026)
The Past Is Not Past: Memory-Enhanced Dynamic Reward Shaping
by: Liu, Yang, et al.
Published: (2026)
by: Liu, Yang, et al.
Published: (2026)
LLatrieval: LLM-Verified Retrieval for Verifiable Generation
by: Li, Xiaonan, et al.
Published: (2023)
by: Li, Xiaonan, et al.
Published: (2023)
Inference-Time Decontamination: Reusing Leaked Benchmarks for Large Language Model Evaluation
by: Zhu, Qin, et al.
Published: (2024)
by: Zhu, Qin, et al.
Published: (2024)
Similar Items
-
How Attention Sinks Emerge in Large Language Models: An Interpretability Perspective
by: Peng, Runyu, et al.
Published: (2026) -
Scaling of Search and Learning: A Roadmap to Reproduce o1 from Reinforcement Learning Perspective
by: Zeng, Zhiyuan, et al.
Published: (2024) -
Revisiting the Test-Time Scaling of o1-like Models: Do they Truly Possess Test-Time Scaling Capabilities?
by: Zeng, Zhiyuan, et al.
Published: (2025) -
Explicit Multi-head Attention for Inter-head Interaction in Large Language Models
by: Peng, Runyu, et al.
Published: (2026) -
UnitCoder: Scalable Iterative Code Synthesis with Unit Test Guidance
by: Ma, Yichuan, et al.
Published: (2025)