Self-Distillation Bridges Distribution Gap in Language Model Fine-Tuning
Fuente:
arXiv
Guardado en:
| Autores principales: | Yang, Zhaorui, Pang, Tianyu, Feng, Haozhe, Wang, Han, Chen, Wei, Zhu, Minfeng, Liu, Qian |
|---|---|
| Formato: | Preprint |
| Publicado: |
2024
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Multimodal DeepResearcher: Generating Text-Chart Interleaved Reports From Scratch with Agentic Framework
por: Yang, Zhaorui, et al.
Publicado: (2025)
por: Yang, Zhaorui, et al.
Publicado: (2025)
Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning
por: Pang, Jinlong, et al.
Publicado: (2025)
por: Pang, Jinlong, et al.
Publicado: (2025)
Phased Instruction Fine-Tuning for Large Language Models
por: Pang, Wei, et al.
Publicado: (2024)
por: Pang, Wei, et al.
Publicado: (2024)
Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
por: Zhao, Siyan, et al.
Publicado: (2026)
por: Zhao, Siyan, et al.
Publicado: (2026)
Efficiently Seeking Flat Minima for Better Generalization in Fine-Tuning Large Language Models and Beyond
por: Deng, Jiaxin, et al.
Publicado: (2025)
por: Deng, Jiaxin, et al.
Publicado: (2025)
Bridging the Visual Gap: Fine-Tuning Multimodal Models with Knowledge-Adapted Captions
por: Yanuka, Moran, et al.
Publicado: (2024)
por: Yanuka, Moran, et al.
Publicado: (2024)
GIFT: Guided Fine-Tuning and Transfer for Enhancing Instruction-Tuned Language Models
por: Ruan, Zhiwen, et al.
Publicado: (2026)
por: Ruan, Zhiwen, et al.
Publicado: (2026)
Parameter-Efficient Fine-Tuning With Adapters
por: Chen, Keyu, et al.
Publicado: (2024)
por: Chen, Keyu, et al.
Publicado: (2024)
Self-Distilled Trajectory-Aware Boltzmann Modeling: Bridging the Training-Inference Discrepancy in Diffusion Language Models
por: Chen, Kecheng, et al.
Publicado: (2026)
por: Chen, Kecheng, et al.
Publicado: (2026)
Enhancing Knowledge Distillation of Large Language Models through Efficient Multi-Modal Distribution Alignment
por: Peng, Tianyu, et al.
Publicado: (2024)
por: Peng, Tianyu, et al.
Publicado: (2024)
Fine-Tuning Language Models with Just Forward Passes
por: Malladi, Sadhika, et al.
Publicado: (2023)
por: Malladi, Sadhika, et al.
Publicado: (2023)
Geo-Expert: Towards Expert-Level Geological Reasoning via Parameter-Efficient Fine-Tuning
por: Guo, Chenyou, et al.
Publicado: (2026)
por: Guo, Chenyou, et al.
Publicado: (2026)
Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling
por: Xu, Wenda, et al.
Publicado: (2024)
por: Xu, Wenda, et al.
Publicado: (2024)
Enhancing Large Language Model Reasoning via Selective Critical Token Fine-Tuning
por: Ruan, Zhiwen, et al.
Publicado: (2025)
por: Ruan, Zhiwen, et al.
Publicado: (2025)
Optimizing Psychological Counseling with Instruction-Tuned Large Language Models
por: Li, Wenjie, et al.
Publicado: (2024)
por: Li, Wenjie, et al.
Publicado: (2024)
Dynamic Self-Distillation via Previous Mini-batches for Fine-tuning Small Language Models
por: Fu, Yao, et al.
Publicado: (2024)
por: Fu, Yao, et al.
Publicado: (2024)
Plug-in and Fine-tuning: Bridging the Gap between Small Language Models and Large Language Models
por: Kim, Kyeonghyun, et al.
Publicado: (2025)
por: Kim, Kyeonghyun, et al.
Publicado: (2025)
DEFT: Distribution-guided Efficient Fine-Tuning for Human Alignment
por: Zhu, Liang, et al.
Publicado: (2026)
por: Zhu, Liang, et al.
Publicado: (2026)
LegiLM: A Fine-Tuned Legal Language Model for Data Compliance
por: Zhu, Linkai, et al.
Publicado: (2024)
por: Zhu, Linkai, et al.
Publicado: (2024)
Skill-Aware Data Selection and Fine-Tuning for Data-Efficient Reasoning Distillation
por: Zhang, Lechen, et al.
Publicado: (2026)
por: Zhang, Lechen, et al.
Publicado: (2026)
Efficient Response Generation Strategy Selection for Fine-Tuning Large Language Models Through Self-Aligned Perplexity
por: Ren, Xuan, et al.
Publicado: (2025)
por: Ren, Xuan, et al.
Publicado: (2025)
TRACE: Discovering Task-Specific Parameter via Adaptation-Aware Probing for Continual Fine-Tuning
por: Han, Xiaosong, et al.
Publicado: (2026)
por: Han, Xiaosong, et al.
Publicado: (2026)
Distribution Corrected Offline Data Distillation for Large Language Models
por: Zhang, Yumeng, et al.
Publicado: (2026)
por: Zhang, Yumeng, et al.
Publicado: (2026)
JailbreakLens: Visual Analysis of Jailbreak Attacks Against Large Language Models
por: Feng, Yingchaojie, et al.
Publicado: (2024)
por: Feng, Yingchaojie, et al.
Publicado: (2024)
DLoRA: Distributed Parameter-Efficient Fine-Tuning Solution for Large Language Model
por: Gao, Chao, et al.
Publicado: (2024)
por: Gao, Chao, et al.
Publicado: (2024)
SelfIE: Self-Interpretation of Large Language Model Embeddings
por: Chen, Haozhe, et al.
Publicado: (2024)
por: Chen, Haozhe, et al.
Publicado: (2024)
Selective Self-to-Supervised Fine-Tuning for Generalization in Large Language Models
por: Gupta, Sonam, et al.
Publicado: (2025)
por: Gupta, Sonam, et al.
Publicado: (2025)
Hyperbolic Fine-Tuning for Large Language Models
por: Yang, Menglin, et al.
Publicado: (2024)
por: Yang, Menglin, et al.
Publicado: (2024)
SPFT-SQL: Enhancing Large Language Model for Text-to-SQL Parsing by Self-Play Fine-Tuning
por: Zhang, Yuhao, et al.
Publicado: (2025)
por: Zhang, Yuhao, et al.
Publicado: (2025)
Warmup-Distill: Bridge the Distribution Mismatch between Teacher and Student before Knowledge Distillation
por: Sun, Zengkui, et al.
Publicado: (2025)
por: Sun, Zengkui, et al.
Publicado: (2025)
Bridging the Capability Gap: Joint Alignment Tuning for Harmonizing LLM-based Multi-Agent Systems
por: Zhu, Minghang, et al.
Publicado: (2025)
por: Zhu, Minghang, et al.
Publicado: (2025)
Natural Language Fine-Tuning
por: Liu, Jia, et al.
Publicado: (2024)
por: Liu, Jia, et al.
Publicado: (2024)
In-Context Learning Distillation for Efficient Few-Shot Fine-Tuning
por: Duan, Yifei, et al.
Publicado: (2024)
por: Duan, Yifei, et al.
Publicado: (2024)
Learning While Staying Curious: Entropy-Preserving Supervised Fine-Tuning via Adaptive Self-Distillation for Large Reasoning Models
por: Wang, Hao, et al.
Publicado: (2026)
por: Wang, Hao, et al.
Publicado: (2026)
State-of-the-Art Arabic Language Modeling with Sparse MoE Fine-Tuning and Chain-of-Thought Distillation
por: Singh, Navan Preet, et al.
Publicado: (2026)
por: Singh, Navan Preet, et al.
Publicado: (2026)
Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models
por: Chen, Zixiang, et al.
Publicado: (2024)
por: Chen, Zixiang, et al.
Publicado: (2024)
Graph-Based Spectral Decomposition for Parameter Coordination in Language Model Fine-Tuning
por: Zhang, Hanlu, et al.
Publicado: (2025)
por: Zhang, Hanlu, et al.
Publicado: (2025)
Enhancing Multilingual Capabilities of Large Language Models through Self-Distillation from Resource-Rich Languages
por: Zhang, Yuanchi, et al.
Publicado: (2024)
por: Zhang, Yuanchi, et al.
Publicado: (2024)
Bridging the Gap Between Preference Alignment and Machine Unlearning
por: Feng, Xiaohua, et al.
Publicado: (2025)
por: Feng, Xiaohua, et al.
Publicado: (2025)
Survey on Knowledge Distillation for Large Language Models: Methods, Evaluation, and Application
por: Yang, Chuanpeng, et al.
Publicado: (2024)
por: Yang, Chuanpeng, et al.
Publicado: (2024)
Ejemplares similares
-
Multimodal DeepResearcher: Generating Text-Chart Interleaved Reports From Scratch with Agentic Framework
por: Yang, Zhaorui, et al.
Publicado: (2025) -
Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning
por: Pang, Jinlong, et al.
Publicado: (2025) -
Phased Instruction Fine-Tuning for Large Language Models
por: Pang, Wei, et al.
Publicado: (2024) -
Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
por: Zhao, Siyan, et al.
Publicado: (2026) -
Efficiently Seeking Flat Minima for Better Generalization in Fine-Tuning Large Language Models and Beyond
por: Deng, Jiaxin, et al.
Publicado: (2025)