Copertina

A Mechanistic Investigation of Supervised Fine Tuning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autore principale:	Chopra, Ruhaan
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Hecto: Modular Sparse Experts for Adaptive and Interpretable Reasoning
di: Pandey, Sanskar, et al.
Pubblicazione: (2025)

Beacon: Single-Turn Diagnosis and Mitigation of Latent Sycophancy in Large Language Models
di: Pandey, Sanskar, et al.
Pubblicazione: (2025)

On-Policy Supervised Fine-Tuning for Efficient Reasoning
di: Zhao, Anhao, et al.
Pubblicazione: (2026)

Rotation-Preserving Supervised Fine-Tuning
di: Jin, Hangzhan, et al.
Pubblicazione: (2026)

Proximal Supervised Fine-Tuning
di: Zhu, Wenhong, et al.
Pubblicazione: (2025)

A Layer-wise Analysis of Supervised Fine-Tuning
di: Zhao, Qinghua, et al.
Pubblicazione: (2026)

Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods
di: Hao, Yifan, et al.
Pubblicazione: (2025)

Data Mixing Optimization for Supervised Fine-Tuning of Large Language Models
di: Li, Yuan, et al.
Pubblicazione: (2025)

Goal-Conditioned Supervised Learning for LLM Fine-Tuning
di: Li, Shijun, et al.
Pubblicazione: (2026)

Token Cleaning: Fine-Grained Data Selection for LLM Supervised Fine-Tuning
di: Pang, Jinlong, et al.
Pubblicazione: (2025)

Supervised Fine-Tuning as Inverse Reinforcement Learning
di: Sun, Hao
Pubblicazione: (2024)

Teaching AI to Handle Exceptions: Supervised Fine-Tuning with Human-Aligned Judgment
di: DiSorbo, Matthew DosSantos, et al.
Pubblicazione: (2025)

Preserving Diversity in Supervised Fine-Tuning of Large Language Models
di: Li, Ziniu, et al.
Pubblicazione: (2024)

ASFT: Aligned Supervised Fine-Tuning through Absolute Likelihood
di: Wang, Ruoyu, et al.
Pubblicazione: (2024)

Directional Gradient Projection for Robust Fine-Tuning of Foundation Models
di: Huang, Chengyue, et al.
Pubblicazione: (2025)

Beyond Perplexity: A Lightweight Benchmark for Knowledge Retention in Supervised Fine-Tuning
di: Shabgahi, Soheil Zibakhsh, et al.
Pubblicazione: (2026)

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

Supervised Fine-Tuning or In-Context Learning? Evaluating LLMs for Clinical NER
di: Baroian, Andrei
Pubblicazione: (2025)

Supervised Fine Tuning on Curated Data is Reinforcement Learning (and can be improved)
di: Qin, Chongli, et al.
Pubblicazione: (2025)

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

LIA: Supervised Fine-Tuning of Large Language Models for Automatic Issue Assignment
di: Khosravani, Arsham, et al.
Pubblicazione: (2026)

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

Improved Supervised Fine-Tuning for Large Language Models to Mitigate Catastrophic Forgetting
di: Ding, Fei, et al.
Pubblicazione: (2025)

FRAMES-VQA: Benchmarking Fine-Tuning Robustness across Multi-Modal Shifts in Visual Question Answering
di: Huang, Chengyue, et al.
Pubblicazione: (2025)

GeoLocSFT: Efficient Visual Geolocation via Supervised Fine-Tuning of Multimodal Foundation Models
di: Yi, Qiang, et al.
Pubblicazione: (2025)

Simulation as Supervision: Mechanistic Pretraining for Scientific Discovery
di: Dudley, Carson, et al.
Pubblicazione: (2025)

A Self-Supervised Reinforcement Learning Approach for Fine-Tuning Large Language Models Using Cross-Attention Signals
di: Kiruluta, Andrew, et al.
Pubblicazione: (2025)

SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning
di: Fu, Yuqian, et al.
Pubblicazione: (2025)

Analyzing the Effects of Supervised Fine-Tuning on Model Knowledge from Token and Parameter Levels
di: Ye, Junjie, et al.
Pubblicazione: (2025)

The Effectiveness of Approximate Regularized Replay for Efficient Supervised Fine-Tuning of Large Language Models
di: Riemer, Matthew, et al.
Pubblicazione: (2025)

Rethinking Supervised Fine-Tuning: Emphasizing Key Answer Tokens for Improved LLM Accuracy
di: Shi, Xiaofeng, et al.
Pubblicazione: (2025)

Semantic Loss Guided Data Efficient Supervised Fine Tuning for Safe Responses in LLMs
di: Lu, Yuxiao, et al.
Pubblicazione: (2024)

Mechanistic Interpretability of Fine-Tuned Vision Transformers on Distorted Images: Decoding Attention Head Behavior for Transparent and Trustworthy AI
di: Bahador, Nooshin
Pubblicazione: (2025)

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

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

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

RoSTE: An Efficient Quantization-Aware Supervised Fine-Tuning Approach for Large Language Models
di: Wei, Quan, et al.
Pubblicazione: (2025)

GraphGen: Enhancing Supervised Fine-Tuning for LLMs with Knowledge-Driven Synthetic Data Generation
di: Chen, Zihong, et al.
Pubblicazione: (2025)

Mechanistic Fine-tuning for In-context Learning
di: Cho, Hakaze, et al.
Pubblicazione: (2025)

Beyond Generation: Unlocking Universal Editing via Self-Supervised Fine-Tuning
di: Chen, Harold Haodong, et al.
Pubblicazione: (2024)