Cover Image

Bounded Behavioral Indistinguishability for Black-Box LLM Distillation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Hasan, Munawar
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

SODA: Semi On-Policy Black-Box Distillation for Large Language Models
by: Chen, Xiwen, et al.
Published: (2026)

Beyond Indistinguishability: Measuring Extraction Risk in LLM APIs
by: Liu, Ruixuan, et al.
Published: (2026)

Deep Learning-based Method for Expressing Knowledge Boundary of Black-Box LLM
by: Sheng, Haotian, et al.
Published: (2026)

Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning Methods
by: Doshi, Jai, et al.
Published: (2024)

HYDRA: Model Factorization Framework for Black-Box LLM Personalization
by: Zhuang, Yuchen, et al.
Published: (2024)

Uncertainty Quantification for Language Models: A Suite of Black-Box, White-Box, LLM Judge, and Ensemble Scorers
by: Bouchard, Dylan, et al.
Published: (2025)

Does It Make Sense to Explain a Black Box With Another Black Box?
by: Delaunay, Julien, et al.
Published: (2024)

Unlocking the Black Box of Latent Reasoning: An Interpretability-Guided Approach to Intervention
by: Chang, Shuochen, et al.
Published: (2026)

PCS: Perceived Confidence Scoring of Black Box LLMs with Metamorphic Relations
by: Salimian, Sina, et al.
Published: (2025)

An Evaluation of Explanation Methods for Black-Box Detectors of Machine-Generated Text
by: Schoenegger, Loris, et al.
Published: (2024)

Hierarchical Text Classification Using Black Box Large Language Models
by: Yoshimura, Kosuke, et al.
Published: (2025)

SafePassage: High-Fidelity Information Extraction with Black Box LLMs
by: Barrow, Joe, et al.
Published: (2025)

Towards Universal and Black-Box Query-Response Only Attack on LLMs with QROA
by: Jawad, Hussein, et al.
Published: (2024)

Peering Inside the Black Box: Uncovering LLM Errors in Optimization Modelling through Component-Level Evaluation
by: Refai, Dania, et al.
Published: (2025)

A Watermark for Black-Box Language Models
by: Bahri, Dara, et al.
Published: (2024)

Strong Teacher Not Needed? On Distillation in LLM Pretraining
by: Lu, Taiming, et al.
Published: (2026)

Training Deliberative Monitors for Black-Box Scheming Detection
by: Sinha, Aditya, et al.
Published: (2026)

Collab-RAG: Boosting Retrieval-Augmented Generation for Complex Question Answering via White-Box and Black-Box LLM Collaboration
by: Xu, Ran, et al.
Published: (2025)

Topic Modelling Black Box Optimization
by: Akramov, Roman, et al.
Published: (2025)

Matryoshka Pilot: Learning to Drive Black-Box LLMs with LLMs
by: Li, Changhao, et al.
Published: (2024)

In-Context Explainers: Harnessing LLMs for Explaining Black Box Models
by: Kroeger, Nicholas, et al.
Published: (2023)

Reinforcement Learning-based Knowledge Distillation with LLM-as-a-Judge
by: Shen, Yiyang, et al.
Published: (2026)

Audit Me If You Can: Query-Efficient Active Fairness Auditing of Black-Box LLMs
by: Hartmann, David, et al.
Published: (2026)

Smoothing Out Hallucinations: Mitigating LLM Hallucination with Smoothed Knowledge Distillation
by: Nguyen, Hieu, et al.
Published: (2025)

Divide-or-Conquer? Which Part Should You Distill Your LLM?
by: Wu, Zhuofeng, et al.
Published: (2024)

BBox-Adapter: Lightweight Adapting for Black-Box Large Language Models
by: Sun, Haotian, et al.
Published: (2024)

Auto-Tuning Safety Guardrails for Black-Box Large Language Models
by: Abdulkadir, Perry
Published: (2025)

Large Language Model Confidence Estimation via Black-Box Access
by: Pedapati, Tejaswini, et al.
Published: (2024)

Mafin: Enhancing Black-Box Embeddings with Model Augmented Fine-Tuning
by: Zhang, Mingtian, et al.
Published: (2024)

Dialectical Behavior Therapy Approach to LLM Prompting
by: Vitman, Oxana, et al.
Published: (2024)

Kov: Transferable and Naturalistic Black-Box LLM Attacks using Markov Decision Processes and Tree Search
by: Moss, Robert J.
Published: (2024)

Group Fairness Meets the Black Box: Enabling Fair Algorithms on Closed LLMs via Post-Processing
by: Xian, Ruicheng, et al.
Published: (2025)

How to Train Your Advisor: Steering Black-Box LLMs with Advisor Models
by: Asawa, Parth, et al.
Published: (2025)

Bias Similarity Measurement: A Black-Box Audit of Fairness Across LLMs
by: Jeong, Hyejun, et al.
Published: (2024)

FactSelfCheck: Fact-Level Black-Box Hallucination Detection for LLMs
by: Sawczyn, Albert, et al.
Published: (2025)

ORPO-Distill: Mixed-Policy Preference Optimization for Cross-Architecture LLM Distillation
by: Singh, Aasheesh, et al.
Published: (2025)

Prompt Candidates, then Distill: A Teacher-Student Framework for LLM-driven Data Annotation
by: Xia, Mingxuan, et al.
Published: (2025)

TT-XAI: Trustworthy Clinical Text Explanations via Keyword Distillation and LLM Reasoning
by: Miok, Kristian, et al.
Published: (2025)

Knowledge Distillation in Automated Annotation: Supervised Text Classification with LLM-Generated Training Labels
by: Pangakis, Nicholas, et al.
Published: (2024)

LLM Pruning and Distillation in Practice: The Minitron Approach
by: Sreenivas, Sharath Turuvekere, et al.
Published: (2024)