Cover Image

Self-Refining Language Model Anonymizers via Adversarial Distillation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kim, Kyuyoung, Jeon, Hyunjun, Shin, Jinwoo
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

RedacBench: Can AI Erase Your Secrets?
by: Jeon, Hyunjun, et al.
Published: (2026)

Personalized Language Models via Privacy-Preserving Evolutionary Model Merging
by: Kim, Kyuyoung, et al.
Published: (2025)

ReVISE: Learning to Refine at Test-Time via Intrinsic Self-Verification
by: Lee, Hyunseok, et al.
Published: (2025)

Rebellious Student: Reversing Teacher Signals for Reasoning Exploration with Self-Distilled RLVR
by: Kim, Jeonghye, et al.
Published: (2026)

Adversarial Moment-Matching Distillation of Large Language Models
by: Jia, Chen
Published: (2024)

Why Does Self-Distillation (Sometimes) Degrade the Reasoning Capability of LLMs?
by: Kim, Jeonghye, et al.
Published: (2026)

Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models
by: Zhao, Siyan, et al.
Published: (2026)

Online Adaptation of Language Models with a Memory of Amortized Contexts
by: Tack, Jihoon, et al.
Published: (2024)

ReMoDetect: Reward Models Recognize Aligned LLM's Generations
by: Lee, Hyunseok, et al.
Published: (2024)

Self-Calibrating Language Models via Test-Time Discriminative Distillation
by: Hedna, Mohamed Rissal, et al.
Published: (2026)

Few-Step Diffusion Language Models via Trajectory Self-Distillation
by: Zhang, Tunyu, et al.
Published: (2026)

Beyond Correctness: Learning Robust Reasoning via Transfer
by: Lee, Hyunseok, et al.
Published: (2026)

Critique-Guided Distillation for Robust Reasoning via Refinement
by: Kapusuzoglu, Berkcan, et al.
Published: (2025)

Towards the Anonymization of the Language Modeling
by: Boutet, Antoine, et al.
Published: (2025)

Spread Preference Annotation: Direct Preference Judgment for Efficient LLM Alignment
by: Kim, Dongyoung, et al.
Published: (2024)

L4Q: Parameter Efficient Quantization-Aware Fine-Tuning on Large Language Models
by: Jeon, Hyesung, et al.
Published: (2024)

Self-Data Distillation for Recovering Quality in Pruned Large Language Models
by: Thangarasa, Vithursan, et al.
Published: (2024)

Margin Matching Preference Optimization: Enhanced Model Alignment with Granular Feedback
by: Kim, Kyuyoung, et al.
Published: (2024)

ROSD: Reflective On-Policy Self-Distillation for Language Model Reasoning across Domains
by: Zhao, Ziqi, et al.
Published: (2026)

Multi-Token Prediction via Self-Distillation
by: Kirchenbauer, John, et al.
Published: (2026)

RAD: Redundancy-Aware Distillation for Hybrid Models via Self-Speculative Decoding
by: Hoshino, Yuichiro, et al.
Published: (2025)

SSR: Socratic Self-Refine for Large Language Model Reasoning
by: Shi, Haizhou, et al.
Published: (2025)

ReGUIDE: Data Efficient GUI Grounding via Spatial Reasoning and Search
by: Lee, Hyunseok, et al.
Published: (2025)

Probing to Refine: Reinforcement Distillation of LLMs via Explanatory Inversion
by: Tan, Zhen, et al.
Published: (2026)

Efficient Knowledge Injection in LLMs via Self-Distillation
by: Kujanpää, Kalle, et al.
Published: (2024)

Pruning and Distilling Mixture-of-Experts into Dense Language Models
by: Kim, Junhyuck, et al.
Published: (2026)

Self-Verified Distillation: Your Language Model Is Secretly Its Own Synthetic Data Pipeline
by: Lee, Tony, et al.
Published: (2026)

Self-playing Adversarial Language Game Enhances LLM Reasoning
by: Cheng, Pengyu, et al.
Published: (2024)

Self-Refinement of Language Models from External Proxy Metrics Feedback
by: Ramji, Keshav, et al.
Published: (2024)

Self-Distilled RLVR
by: Yang, Chenxu, et al.
Published: (2026)

Optimized Feature Generation for Tabular Data via LLMs with Decision Tree Reasoning
by: Nam, Jaehyun, et al.
Published: (2024)

UniDetox: Universal Detoxification of Large Language Models via Dataset Distillation
by: Lu, Huimin, et al.
Published: (2025)

PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning
by: Kim, Gyeongman, et al.
Published: (2024)

Evolving LLMs' Self-Refinement Capability via Synergistic Training-Inference Optimization
by: Zeng, Yongcheng, et al.
Published: (2025)

AdaEDL: Early Draft Stopping for Speculative Decoding of Large Language Models via an Entropy-based Lower Bound on Token Acceptance Probability
by: Agrawal, Sudhanshu, et al.
Published: (2024)

DiLM: Distilling Dataset into Language Model for Text-level Dataset Distillation
by: Maekawa, Aru, et al.
Published: (2024)

Drifting Objectives for Refining Discrete Diffusion Language Models
by: Oba, Daisuke, et al.
Published: (2026)

Beyond Autoregression: Fast LLMs via Self-Distillation Through Time
by: Deschenaux, Justin, et al.
Published: (2024)

SDMPrune: Self-Distillation MLP Pruning for Efficient Large Language Models
by: Zhu, Hourun, et al.
Published: (2025)

On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes
by: Agarwal, Rishabh, et al.
Published: (2023)