Spectral Unforgetting: Post-Hoc Recovery of Damaged Capabilities Without Retraining
Fuente:
arXiv
Guardado en:
| Autores principales: | Abro, Aarash, Tahir, Muhammad |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Post Hoc Regression Refinement via Pairwise Rankings
por: Wijaya, Kevin Tirta, et al.
Publicado: (2025)
por: Wijaya, Kevin Tirta, et al.
Publicado: (2025)
Post-Hoc Reversal: Are We Selecting Models Prematurely?
por: Ranjan, Rishabh, et al.
Publicado: (2024)
por: Ranjan, Rishabh, et al.
Publicado: (2024)
Retrieval Augmented Anomaly Detection (RAAD): Nimble Model Adjustment Without Retraining
por: Pastoriza, Sam, et al.
Publicado: (2025)
por: Pastoriza, Sam, et al.
Publicado: (2025)
Sustainable Machine Learning Retraining: Optimizing Energy Efficiency Without Compromising Accuracy
por: Poenaru-Olaru, Lorena, et al.
Publicado: (2025)
por: Poenaru-Olaru, Lorena, et al.
Publicado: (2025)
Agent-Based Post-Hoc Correction of Agricultural Yield Forecasts
por: Beddows, Matthew, et al.
Publicado: (2026)
por: Beddows, Matthew, et al.
Publicado: (2026)
Smooth InfoMax -- Towards Easier Post-Hoc Interpretability
por: Denoodt, Fabian, et al.
Publicado: (2024)
por: Denoodt, Fabian, et al.
Publicado: (2024)
Informative Post-Hoc Explanations Only Exist for Simple Functions
por: Günther, Eric, et al.
Publicado: (2025)
por: Günther, Eric, et al.
Publicado: (2025)
CalArena: A Large-Scale Post-Hoc Calibration Benchmark
por: Berta, Eugène, et al.
Publicado: (2026)
por: Berta, Eugène, et al.
Publicado: (2026)
Operationalizing Fairness: Post-Hoc Threshold Optimization Under Hard Resource Limits
por: Singh, Moirangthem Tiken, et al.
Publicado: (2026)
por: Singh, Moirangthem Tiken, et al.
Publicado: (2026)
Principled Input-Output-Conditioned Post-Hoc Uncertainty Estimation for Regression Networks
por: Bramlage, Lennart, et al.
Publicado: (2025)
por: Bramlage, Lennart, et al.
Publicado: (2025)
Are We Merely Justifying Results ex Post Facto? Quantifying Explanatory Inversion in Post-Hoc Model Explanations
por: Tan, Zhen, et al.
Publicado: (2025)
por: Tan, Zhen, et al.
Publicado: (2025)
When Policies Cannot Be Retrained: A Unified Closed-Form View of Post-Training Steering in Offline Reinforcement Learning
por: Hossain, Elias, et al.
Publicado: (2026)
por: Hossain, Elias, et al.
Publicado: (2026)
ShapeX: Shapelet-Driven Post Hoc Explanations for Time Series Classification Models
por: Huang, Bosong, et al.
Publicado: (2025)
por: Huang, Bosong, et al.
Publicado: (2025)
Improving Policy Optimization via $\varepsilon$-Retrain
por: Marzari, Luca, et al.
Publicado: (2024)
por: Marzari, Luca, et al.
Publicado: (2024)
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery
por: Liu, Renpu, et al.
Publicado: (2024)
por: Liu, Renpu, et al.
Publicado: (2024)
PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs
por: Zimmer, Max, et al.
Publicado: (2023)
por: Zimmer, Max, et al.
Publicado: (2023)
Comparing Post-Hoc Explainable AI Methods for Interpreting Black-Box EEG Models in Depression Detection
por: Šarčević, Antonia, et al.
Publicado: (2026)
por: Šarčević, Antonia, et al.
Publicado: (2026)
TaylorPODA: A Taylor Expansion-Based Method to Improve Post-Hoc Attributions for Opaque Models
por: Tang, Yuchi, et al.
Publicado: (2025)
por: Tang, Yuchi, et al.
Publicado: (2025)
ChaosMining: A Benchmark to Evaluate Post-Hoc Local Attribution Methods in Low SNR Environments
por: Shi, Ge, et al.
Publicado: (2024)
por: Shi, Ge, et al.
Publicado: (2024)
Assessing Per-Sample Membership Inference Vulnerability without Retraining
por: Dorseuil, Valentin, et al.
Publicado: (2026)
por: Dorseuil, Valentin, et al.
Publicado: (2026)
Evaluating LLMs Capabilities Towards Understanding Social Dynamics
por: Tahir, Anique, et al.
Publicado: (2024)
por: Tahir, Anique, et al.
Publicado: (2024)
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems
por: Xia, Yifan, et al.
Publicado: (2024)
por: Xia, Yifan, et al.
Publicado: (2024)
SHapley Estimated Explanation (SHEP): A Fast Post-Hoc Attribution Method for Interpreting Intelligent Fault Diagnosis
por: Chen, Qian, et al.
Publicado: (2025)
por: Chen, Qian, et al.
Publicado: (2025)
Inner Loop Inference for Pretrained Transformers: Unlocking Latent Capabilities Without Training
por: Lys, Jonathan, et al.
Publicado: (2026)
por: Lys, Jonathan, et al.
Publicado: (2026)
A Free Lunch in LLM Compression: Revisiting Retraining after Pruning
por: Wagner, Moritz, et al.
Publicado: (2025)
por: Wagner, Moritz, et al.
Publicado: (2025)
xai_evals : A Framework for Evaluating Post-Hoc Local Explanation Methods
por: Seth, Pratinav, et al.
Publicado: (2025)
por: Seth, Pratinav, et al.
Publicado: (2025)
AI Scientists Fail Without Strong Implementation Capability
por: Zhu, Minjun, et al.
Publicado: (2025)
por: Zhu, Minjun, et al.
Publicado: (2025)
Is Retraining-Free Enough? The Necessity of Router Calibration for Efficient MoE Compression
por: Hyeon, Sieun, et al.
Publicado: (2026)
por: Hyeon, Sieun, et al.
Publicado: (2026)
Estimating the Effects of Sample Training Orders for Large Language Models without Retraining
por: Yang, Hao, et al.
Publicado: (2025)
por: Yang, Hao, et al.
Publicado: (2025)
EvalxNLP: A Framework for Benchmarking Post-Hoc Explainability Methods on NLP Models
por: Dhaini, Mahdi, et al.
Publicado: (2025)
por: Dhaini, Mahdi, et al.
Publicado: (2025)
Safe Fairness Guarantees Without Demographics in Classification: Spectral Uncertainty Set Perspective
por: Barrainkua, Ainhize, et al.
Publicado: (2026)
por: Barrainkua, Ainhize, et al.
Publicado: (2026)
Don't Retrain, Align: Adapting Autoregressive LMs to Diffusion LMs via Representation Alignment
por: Peng, Fred Zhangzhi, et al.
Publicado: (2026)
por: Peng, Fred Zhangzhi, et al.
Publicado: (2026)
Post-Pruning Accuracy Recovery via Data-Free Knowledge Distillation
por: Tripurwar, Chinmay, et al.
Publicado: (2025)
por: Tripurwar, Chinmay, et al.
Publicado: (2025)
Symmetry-Breaking Augmentations for Ad Hoc Teamwork
por: Hammond, Ravi, et al.
Publicado: (2024)
por: Hammond, Ravi, et al.
Publicado: (2024)
Pruning Foundation Models for High Accuracy without Retraining
por: Zhao, Pu, et al.
Publicado: (2024)
por: Zhao, Pu, et al.
Publicado: (2024)
Multi-Level Safety Continual Projection for Fine-Tuned Large Language Models without Retraining
por: Han, Bing, et al.
Publicado: (2025)
por: Han, Bing, et al.
Publicado: (2025)
Feature Attribution Stability Suite: How Stable Are Post-Hoc Attributions?
por: Subramaniakuppusamy, Kamalasankari, et al.
Publicado: (2026)
por: Subramaniakuppusamy, Kamalasankari, et al.
Publicado: (2026)
Post-Hoc Concept Disentanglement: From Correlated to Isolated Concept Representations
por: Erogullari, Eren, et al.
Publicado: (2025)
por: Erogullari, Eren, et al.
Publicado: (2025)
On Background Bias of Post-Hoc Concept Embeddings in Computer Vision DNNs
por: Schwalbe, Gesina, et al.
Publicado: (2025)
por: Schwalbe, Gesina, et al.
Publicado: (2025)
GPS-SSL: Guided Positive Sampling to Inject Prior Into Self-Supervised Learning
por: Feizi, Aarash, et al.
Publicado: (2024)
por: Feizi, Aarash, et al.
Publicado: (2024)
Ejemplares similares
-
Post Hoc Regression Refinement via Pairwise Rankings
por: Wijaya, Kevin Tirta, et al.
Publicado: (2025) -
Post-Hoc Reversal: Are We Selecting Models Prematurely?
por: Ranjan, Rishabh, et al.
Publicado: (2024) -
Retrieval Augmented Anomaly Detection (RAAD): Nimble Model Adjustment Without Retraining
por: Pastoriza, Sam, et al.
Publicado: (2025) -
Sustainable Machine Learning Retraining: Optimizing Energy Efficiency Without Compromising Accuracy
por: Poenaru-Olaru, Lorena, et al.
Publicado: (2025) -
Agent-Based Post-Hoc Correction of Agricultural Yield Forecasts
por: Beddows, Matthew, et al.
Publicado: (2026)