Saved in:
| Main Authors: | Garg, Arpit, Saratchandran, Hemanth, Garg, Ravi, Lucey, Simon |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2509.24166 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
SineProject: Machine Unlearning for Stable Vision Language Alignment
by: Garg, Arpit, et al.
Published: (2025)
by: Garg, Arpit, et al.
Published: (2025)
Mask the Target: A Plug-and-Play Regularizer Against LoRA Forgetting
by: Xu, Runze, et al.
Published: (2026)
by: Xu, Runze, et al.
Published: (2026)
SineLoRA$Δ$: Sine-Activated Delta Compression
by: Gordon, Cameron, et al.
Published: (2025)
by: Gordon, Cameron, et al.
Published: (2025)
Spectral Conditioning of Attention Improves Transformer Performance
by: Saratchandran, Hemanth, et al.
Published: (2026)
by: Saratchandran, Hemanth, et al.
Published: (2026)
The Inlet Rank Collapse in Implicit Neural Representations: Diagnosis and Unified Remedy
by: Zheng, Jianqiao, et al.
Published: (2026)
by: Zheng, Jianqiao, et al.
Published: (2026)
Leaner Transformers: More Heads, Less Depth
by: Saratchandran, Hemanth, et al.
Published: (2025)
by: Saratchandran, Hemanth, et al.
Published: (2025)
From Activation to Initialization: Scaling Insights for Optimizing Neural Fields
by: Saratchandran, Hemanth, et al.
Published: (2024)
by: Saratchandran, Hemanth, et al.
Published: (2024)
Analyzing the Neural Tangent Kernel of Periodically Activated Coordinate Networks
by: Saratchandran, Hemanth, et al.
Published: (2024)
by: Saratchandran, Hemanth, et al.
Published: (2024)
Architectural Strategies for the optimization of Physics-Informed Neural Networks
by: Saratchandran, Hemanth, et al.
Published: (2024)
by: Saratchandran, Hemanth, et al.
Published: (2024)
Preconditioners for the Stochastic Training of Neural Fields
by: Chng, Shin-Fang, et al.
Published: (2024)
by: Chng, Shin-Fang, et al.
Published: (2024)
Invertible Neural Warp for NeRF
by: Chng, Shin-Fang, et al.
Published: (2024)
by: Chng, Shin-Fang, et al.
Published: (2024)
Always Skip Attention
by: Ji, Yiping, et al.
Published: (2025)
by: Ji, Yiping, et al.
Published: (2025)
Efficient Learning With Sine-Activated Low-rank Matrices
by: Ji, Yiping, et al.
Published: (2024)
by: Ji, Yiping, et al.
Published: (2024)
A Sampling Theory Perspective on Activations for Implicit Neural Representations
by: Saratchandran, Hemanth, et al.
Published: (2024)
by: Saratchandran, Hemanth, et al.
Published: (2024)
The Quantization Benefits of Residual-Free Transformers
by: Ji, Yiping, et al.
Published: (2026)
by: Ji, Yiping, et al.
Published: (2026)
3D-LFM: Lifting Foundation Model
by: Dabhi, Mosam, et al.
Published: (2023)
by: Dabhi, Mosam, et al.
Published: (2023)
Preconditioned Attention: Enhancing Efficiency in Transformers
by: Saratchandran, Hemanth
Published: (2026)
by: Saratchandran, Hemanth
Published: (2026)
A Methodology-Oriented Study of Catastrophic Forgetting in Incremental Deep Neural Networks
by: Kumar, Ashutosh, et al.
Published: (2024)
by: Kumar, Ashutosh, et al.
Published: (2024)
From Tables to Signals: Revealing Spectral Adaptivity in TabPFN
by: Zheng, Jianqiao, et al.
Published: (2025)
by: Zheng, Jianqiao, et al.
Published: (2025)
Rethinking Attention: Polynomial Alternatives to Softmax in Transformers
by: Saratchandran, Hemanth, et al.
Published: (2024)
by: Saratchandran, Hemanth, et al.
Published: (2024)
D'OH: Decoder-Only Random Hypernetworks for Implicit Neural Representations
by: Gordon, Cameron, et al.
Published: (2024)
by: Gordon, Cameron, et al.
Published: (2024)
Unified Parameter-Efficient Unlearning for LLMs
by: Ding, Chenlu, et al.
Published: (2024)
by: Ding, Chenlu, et al.
Published: (2024)
Forgetting is Competition: Rethinking Unlearning as Representation Interference in Diffusion Models
by: Ranjan, Ashutosh, et al.
Published: (2026)
by: Ranjan, Ashutosh, et al.
Published: (2026)
Enhancing Transformers Through Conditioned Embedded Tokens
by: Saratchandran, Hemanth, et al.
Published: (2025)
by: Saratchandran, Hemanth, et al.
Published: (2025)
Forget and Explain: Transparent Verification of GNN Unlearning
by: Ahsan, Imran, et al.
Published: (2025)
by: Ahsan, Imran, et al.
Published: (2025)
Graph Transformers without Positional Encodings
by: Garg, Ayush
Published: (2024)
by: Garg, Ayush
Published: (2024)
ACU: Analytic Continual Unlearning for Efficient and Exact Forgetting with Privacy Preservation
by: Tang, Jianheng, et al.
Published: (2025)
by: Tang, Jianheng, et al.
Published: (2025)
Module-Aware Parameter-Efficient Machine Unlearning on Transformers
by: Bao, Wenjie, et al.
Published: (2025)
by: Bao, Wenjie, et al.
Published: (2025)
Don't Forget It! Conditional Sparse Autoencoder Clamping Works for Unlearning
by: Khoriaty, Matthew, et al.
Published: (2025)
by: Khoriaty, Matthew, et al.
Published: (2025)
Distill, Forget, Repeat: A Framework for Continual Unlearning in Text-to-Image Diffusion Models
by: George, Naveen, et al.
Published: (2025)
by: George, Naveen, et al.
Published: (2025)
Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills
by: Wang, Changsheng, et al.
Published: (2025)
by: Wang, Changsheng, et al.
Published: (2025)
Analyzing and Reducing Catastrophic Forgetting in Parameter Efficient Tuning
by: Ren, Weijieying, et al.
Published: (2024)
by: Ren, Weijieying, et al.
Published: (2024)
BLUR: A Benchmark for LLM Unlearning Robust to Forget-Retain Overlap
by: Hu, Shengyuan, et al.
Published: (2025)
by: Hu, Shengyuan, et al.
Published: (2025)
OPC: One-Point-Contraction Unlearning Toward Deep Feature Forgetting
by: Jung, Jaeheun, et al.
Published: (2025)
by: Jung, Jaeheun, et al.
Published: (2025)
Correlated Errors in Large Language Models
by: Kim, Elliot, et al.
Published: (2025)
by: Kim, Elliot, et al.
Published: (2025)
Deep Unlearning: Fast and Efficient Gradient-free Approach to Class Forgetting
by: Kodge, Sangamesh, et al.
Published: (2023)
by: Kodge, Sangamesh, et al.
Published: (2023)
Margin-calibrated Classifier Guidance for Property-driven Synthesis Planning
by: Laabid, Najwa, et al.
Published: (2026)
by: Laabid, Najwa, et al.
Published: (2026)
Machine Unlearning using Forgetting Neural Networks
by: Hatua, Amartya, et al.
Published: (2024)
by: Hatua, Amartya, et al.
Published: (2024)
Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning
by: Fan, Chongyu, et al.
Published: (2024)
by: Fan, Chongyu, et al.
Published: (2024)
Parameter-Efficient Token Embedding Editing for Clinical Class-Level Unlearning
by: Hou, Iyad Ait, et al.
Published: (2026)
by: Hou, Iyad Ait, et al.
Published: (2026)
Similar Items
-
SineProject: Machine Unlearning for Stable Vision Language Alignment
by: Garg, Arpit, et al.
Published: (2025) -
Mask the Target: A Plug-and-Play Regularizer Against LoRA Forgetting
by: Xu, Runze, et al.
Published: (2026) -
SineLoRA$Δ$: Sine-Activated Delta Compression
by: Gordon, Cameron, et al.
Published: (2025) -
Spectral Conditioning of Attention Improves Transformer Performance
by: Saratchandran, Hemanth, et al.
Published: (2026) -
The Inlet Rank Collapse in Implicit Neural Representations: Diagnosis and Unified Remedy
by: Zheng, Jianqiao, et al.
Published: (2026)