Saved in:
| Main Authors: | Panda, Subhodip, S, Varun M, Jain, Shreyans, Maharana, Sarthak Kumar, P, Prathosh A. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.04058 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
FAST: Feature Aware Similarity Thresholding for Weak Unlearning in Black-Box Generative Models
by: Panda, Subhodip, et al.
Published: (2023)
by: Panda, Subhodip, et al.
Published: (2023)
Partially Blinded Unlearning: Class Unlearning for Deep Networks a Bayesian Perspective
by: Panda, Subhodip, et al.
Published: (2024)
by: Panda, Subhodip, et al.
Published: (2024)
Adapt then Unlearn: Exploring Parameter Space Semantics for Unlearning in Generative Adversarial Networks
by: Tiwary, Piyush, et al.
Published: (2023)
by: Tiwary, Piyush, et al.
Published: (2023)
f-INE: A Hypothesis Testing Framework for Estimating Influence under Training Randomness
by: Panda, Subhodip, et al.
Published: (2025)
by: Panda, Subhodip, et al.
Published: (2025)
Regret Tail Characterization of Optimal Bandit Algorithms with Generic Rewards
by: Panda, Subhodip, et al.
Published: (2026)
by: Panda, Subhodip, et al.
Published: (2026)
Not Just Change the Labels, Learn the Features: Watermarking Deep Neural Networks with Multi-View Data
by: Li, Yuxuan, et al.
Published: (2024)
by: Li, Yuxuan, et al.
Published: (2024)
Leveraging Data Symmetries to Select an Optimal Subset of Training Data under Label Noise
by: Shubham, Kumar, et al.
Published: (2026)
by: Shubham, Kumar, et al.
Published: (2026)
PALM: Pushing Adaptive Learning Rate Mechanisms for Continual Test-Time Adaptation
by: Maharana, Sarthak Kumar, et al.
Published: (2024)
by: Maharana, Sarthak Kumar, et al.
Published: (2024)
Acoustic-to-articulatory inversion for dysarthric speech: Are pre-trained self-supervised representations favorable?
by: Maharana, Sarthak Kumar, et al.
Published: (2023)
by: Maharana, Sarthak Kumar, et al.
Published: (2023)
Audio-Visual Continual Test-Time Adaptation without Forgetting
by: Maharana, Sarthak Kumar, et al.
Published: (2026)
by: Maharana, Sarthak Kumar, et al.
Published: (2026)
Sycophancy as compositions of Atomic Psychometric Traits
by: Jain, Shreyans, et al.
Published: (2025)
by: Jain, Shreyans, et al.
Published: (2025)
Spectral Discovery of Continuous Symmetries via Generalized Fourier Transforms
by: Karjol, Pavan, et al.
Published: (2026)
by: Karjol, Pavan, et al.
Published: (2026)
Data Unlearning in Diffusion Models
by: Alberti, Silas, et al.
Published: (2025)
by: Alberti, Silas, et al.
Published: (2025)
Bayesian Pseudo-Coresets via Contrastive Divergence
by: Tiwary, Piyush, et al.
Published: (2023)
by: Tiwary, Piyush, et al.
Published: (2023)
Beyond Linear Steering: Unified Multi-Attribute Control for Language Models
by: Oozeer, Narmeen, et al.
Published: (2025)
by: Oozeer, Narmeen, et al.
Published: (2025)
A Variational Approach to Bayesian Phylogenetic Inference
by: Zhang, Cheng, et al.
Published: (2022)
by: Zhang, Cheng, et al.
Published: (2022)
Adaptive LLM Routing under Budget Constraints
by: Panda, Pranoy, et al.
Published: (2025)
by: Panda, Pranoy, et al.
Published: (2025)
Latent Mamba Operator for Partial Differential Equations
by: Tiwari, Karn, et al.
Published: (2025)
by: Tiwari, Karn, et al.
Published: (2025)
Temporal Data Requirement for Predicting Unplanned Hospital Readmissions
by: Mohammadi, Ramin, et al.
Published: (2026)
by: Mohammadi, Ramin, et al.
Published: (2026)
Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning
by: Sula, Nexhi, et al.
Published: (2024)
by: Sula, Nexhi, et al.
Published: (2024)
Interleaved Gibbs Diffusion: Generating Discrete-Continuous Data with Implicit Constraints
by: Anil, Gautham Govind, et al.
Published: (2025)
by: Anil, Gautham Govind, et al.
Published: (2025)
Denoising Diffusion Variational Inference: Diffusion Models as Expressive Variational Posteriors
by: Piriyakulkij, Wasu Top, et al.
Published: (2024)
by: Piriyakulkij, Wasu Top, et al.
Published: (2024)
Knockoffs Inference under Privacy Constraints
by: Cai, Zhanrui, et al.
Published: (2025)
by: Cai, Zhanrui, et al.
Published: (2025)
Class Machine Unlearning for Complex Data via Concepts Inference and Data Poisoning
by: Chang, Wenhan, et al.
Published: (2024)
by: Chang, Wenhan, et al.
Published: (2024)
Verifiable and Provably Secure Machine Unlearning
by: Eisenhofer, Thorsten, et al.
Published: (2022)
by: Eisenhofer, Thorsten, et al.
Published: (2022)
From Instructions to Constraints: Language Model Alignment with Automatic Constraint Verification
by: Wang, Fei, et al.
Published: (2024)
by: Wang, Fei, et al.
Published: (2024)
Interpretable Discovery of One-parameter Subgroups: A Modular Framework for Elliptical, Hyperbolic, and Parabolic Symmetries
by: Karjol, Pavan, et al.
Published: (2025)
by: Karjol, Pavan, et al.
Published: (2025)
Unlearning or Concealment? A Critical Analysis and Evaluation Metrics for Unlearning in Diffusion Models
by: Sharma, Aakash Sen, et al.
Published: (2024)
by: Sharma, Aakash Sen, et al.
Published: (2024)
Discovering mesoscopic descriptions of collective movement with neural stochastic modelling
by: Pratiush, Utkarsh, et al.
Published: (2023)
by: Pratiush, Utkarsh, et al.
Published: (2023)
LoMOE: Localized Multi-Object Editing via Multi-Diffusion
by: Chakrabarty, Goirik, et al.
Published: (2024)
by: Chakrabarty, Goirik, et al.
Published: (2024)
Accelerated Smoothing: A Scalable Approach to Randomized Smoothing
by: Bhardwaj, Devansh, et al.
Published: (2024)
by: Bhardwaj, Devansh, et al.
Published: (2024)
Earthquake Damage Grades Prediction using An Ensemble Approach Integrating Advanced Machine and Deep Learning Models
by: Panda, Anurag, et al.
Published: (2025)
by: Panda, Anurag, et al.
Published: (2025)
A Kernel Approach for Semi-implicit Variational Inference
by: Yu, Longlin, et al.
Published: (2026)
by: Yu, Longlin, et al.
Published: (2026)
The Sample Complexity of Distributed Simple Binary Hypothesis Testing under Information Constraints
by: Kazemi, Hadi, et al.
Published: (2025)
by: Kazemi, Hadi, et al.
Published: (2025)
CoNOAir: A Neural Operator for Forecasting Carbon Monoxide Evolution in Cities
by: Bedi, Sanchit, et al.
Published: (2025)
by: Bedi, Sanchit, et al.
Published: (2025)
HiRE: High Recall Approximate Top-$k$ Estimation for Efficient LLM Inference
by: L, Yashas Samaga B, et al.
Published: (2024)
by: L, Yashas Samaga B, et al.
Published: (2024)
Learning Equivariant Functions via Quadratic Forms
by: Karjol, Pavan, et al.
Published: (2025)
by: Karjol, Pavan, et al.
Published: (2025)
Diffusion Bridge Variational Inference for Deep Gaussian Processes
by: Xu, Jian, et al.
Published: (2025)
by: Xu, Jian, et al.
Published: (2025)
Contrastive Unlearning: A Contrastive Approach to Machine Unlearning
by: Lee, Hong kyu, et al.
Published: (2024)
by: Lee, Hong kyu, et al.
Published: (2024)
AdaKD: Dynamic Knowledge Distillation of ASR models using Adaptive Loss Weighting
by: Ganguly, Shreyan, et al.
Published: (2024)
by: Ganguly, Shreyan, et al.
Published: (2024)
Similar Items
-
FAST: Feature Aware Similarity Thresholding for Weak Unlearning in Black-Box Generative Models
by: Panda, Subhodip, et al.
Published: (2023) -
Partially Blinded Unlearning: Class Unlearning for Deep Networks a Bayesian Perspective
by: Panda, Subhodip, et al.
Published: (2024) -
Adapt then Unlearn: Exploring Parameter Space Semantics for Unlearning in Generative Adversarial Networks
by: Tiwary, Piyush, et al.
Published: (2023) -
f-INE: A Hypothesis Testing Framework for Estimating Influence under Training Randomness
by: Panda, Subhodip, et al.
Published: (2025) -
Regret Tail Characterization of Optimal Bandit Algorithms with Generic Rewards
by: Panda, Subhodip, et al.
Published: (2026)