Saved in:
| Main Authors: | Damirchi, Hamed, Abbasnejad, Ehsan, Zhang, Zhen, Shi, Javen |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.22511 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
The Quest for Winning Tickets in Low-Rank Adapters
by: Damirchi, Hamed, et al.
Published: (2025)
by: Damirchi, Hamed, et al.
Published: (2025)
Truth as a Trajectory: What Internal Representations Reveal About Large Language Model Reasoning
by: Damirchi, Hamed, et al.
Published: (2026)
by: Damirchi, Hamed, et al.
Published: (2026)
Learning Latent Dynamical Causal Processes for Single-Cell Perturbation Prediction
by: Jiang, Wenkang, et al.
Published: (2026)
by: Jiang, Wenkang, et al.
Published: (2026)
Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling
by: Rodriguez-Opazo, Cristian, et al.
Published: (2024)
by: Rodriguez-Opazo, Cristian, et al.
Published: (2024)
What Makes a Representation Good for Single-Cell Perturbation Prediction?
by: Jiang, Wenkang, et al.
Published: (2026)
by: Jiang, Wenkang, et al.
Published: (2026)
Knowledge Composition using Task Vectors with Learned Anisotropic Scaling
by: Zhang, Frederic Z., et al.
Published: (2024)
by: Zhang, Frederic Z., et al.
Published: (2024)
Rethinking State Disentanglement in Causal Reinforcement Learning
by: Cao, Haiyao, et al.
Published: (2024)
by: Cao, Haiyao, et al.
Published: (2024)
BruSLeAttack: A Query-Efficient Score-Based Black-Box Sparse Adversarial Attack
by: Vo, Viet Quoc, et al.
Published: (2024)
by: Vo, Viet Quoc, et al.
Published: (2024)
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild
by: Teney, Damien, et al.
Published: (2025)
by: Teney, Damien, et al.
Published: (2025)
Beyond Imitation: Recovering Dense Rewards from Demonstrations
by: Li, Jiangnan, et al.
Published: (2025)
by: Li, Jiangnan, et al.
Published: (2025)
Do Deep Neural Network Solutions Form a Star Domain?
by: Sonthalia, Ankit, et al.
Published: (2024)
by: Sonthalia, Ankit, et al.
Published: (2024)
Highway Graph to Accelerate Reinforcement Learning
by: Yin, Zidu, et al.
Published: (2024)
by: Yin, Zidu, et al.
Published: (2024)
Decomposing and Editing Predictions by Modeling Model Computation
by: Shah, Harshay, et al.
Published: (2024)
by: Shah, Harshay, et al.
Published: (2024)
Neural Redshift: Random Networks are not Random Functions
by: Teney, Damien, et al.
Published: (2024)
by: Teney, Damien, et al.
Published: (2024)
Exploring Context Window of Large Language Models via Decomposed Positional Vectors
by: Dong, Zican, et al.
Published: (2024)
by: Dong, Zican, et al.
Published: (2024)
A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations
by: Cheng, Hongrong, et al.
Published: (2023)
by: Cheng, Hongrong, et al.
Published: (2023)
When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers
by: Li, Hongkang, et al.
Published: (2025)
by: Li, Hongkang, et al.
Published: (2025)
ETAGE: Enhanced Test Time Adaptation with Integrated Entropy and Gradient Norms for Robust Model Performance
by: Shamsi, Afshar, et al.
Published: (2024)
by: Shamsi, Afshar, et al.
Published: (2024)
Premonition: Using Generative Models to Preempt Future Data Changes in Continual Learning
by: McDonnell, Mark D., et al.
Published: (2024)
by: McDonnell, Mark D., et al.
Published: (2024)
Variational Task Vector Composition
by: Zhang, Boyuan, et al.
Published: (2025)
by: Zhang, Boyuan, et al.
Published: (2025)
Identifying Weight-Variant Latent Causal Models
by: Liu, Yuhang, et al.
Published: (2022)
by: Liu, Yuhang, et al.
Published: (2022)
Identifiable Latent Polynomial Causal Models Through the Lens of Change
by: Liu, Yuhang, et al.
Published: (2023)
by: Liu, Yuhang, et al.
Published: (2023)
RanPAC: Random Projections and Pre-trained Models for Continual Learning
by: McDonnell, Mark D., et al.
Published: (2023)
by: McDonnell, Mark D., et al.
Published: (2023)
The Geometric Mechanics of Contrastive Representation Learning: Alignment Potentials, Entropic Dispersion, and Cross-modal Divergence
by: Cai, Yichao, et al.
Published: (2026)
by: Cai, Yichao, et al.
Published: (2026)
Chem4DLLM: 4D Multimodal LLMs for Chemical Dynamics Understanding
by: Li, Xinyu, et al.
Published: (2026)
by: Li, Xinyu, et al.
Published: (2026)
CEDL: Centre-Enhanced Discriminative Learning for Anomaly Detection
by: Darban, Zahra Zamanzadeh, et al.
Published: (2025)
by: Darban, Zahra Zamanzadeh, et al.
Published: (2025)
Towards Identifiable Latent Additive Noise Models
by: Liu, Yuhang, et al.
Published: (2024)
by: Liu, Yuhang, et al.
Published: (2024)
Towards Higher Effective Rank in Parameter-efficient Fine-tuning using Khatri--Rao Product
by: Albert, Paul, et al.
Published: (2025)
by: Albert, Paul, et al.
Published: (2025)
Latent Covariate Shift: Unlocking Partial Identifiability for Multi-Source Domain Adaptation
by: Liu, Yuhang, et al.
Published: (2022)
by: Liu, Yuhang, et al.
Published: (2022)
InvariantStock: Learning Invariant Features for Mastering the Shifting Market
by: Cao, Haiyao, et al.
Published: (2024)
by: Cao, Haiyao, et al.
Published: (2024)
Analytic DAG Constraints for Differentiable DAG Learning
by: Zhang, Zhen, et al.
Published: (2025)
by: Zhang, Zhen, et al.
Published: (2025)
Beyond DAGs: A Latent Partial Causal Model for Multimodal Learning
by: Liu, Yuhang, et al.
Published: (2024)
by: Liu, Yuhang, et al.
Published: (2024)
Learning to Reason and Navigate: Parameter Efficient Action Planning with Large Language Models
by: Mohammadi, Bahram, et al.
Published: (2025)
by: Mohammadi, Bahram, et al.
Published: (2025)
On the Value of Cross-Modal Misalignment in Multimodal Representation Learning
by: Cai, Yichao, et al.
Published: (2025)
by: Cai, Yichao, et al.
Published: (2025)
Concept Component Analysis: A Principled Approach for Concept Extraction in LLMs
by: Liu, Yuhang, et al.
Published: (2026)
by: Liu, Yuhang, et al.
Published: (2026)
VectorEdits: A Dataset and Benchmark for Instruction-Based Editing of Vector Graphics
by: Kuchař, Josef, et al.
Published: (2025)
by: Kuchař, Josef, et al.
Published: (2025)
Certified but Fooled! Breaking Certified Defences with Ghost Certificates
by: Vo, Quoc Viet, et al.
Published: (2025)
by: Vo, Quoc Viet, et al.
Published: (2025)
The Character Error Vector: Decomposable errors for page-level OCR evaluation
by: Bourne, Jonathan, et al.
Published: (2026)
by: Bourne, Jonathan, et al.
Published: (2026)
On Fairness of Task Arithmetic: The Role of Task Vectors
by: Naganuma, Hiroki, et al.
Published: (2025)
by: Naganuma, Hiroki, et al.
Published: (2025)
Task Vector Quantization for Memory-Efficient Model Merging
by: Kim, Youngeun, et al.
Published: (2025)
by: Kim, Youngeun, et al.
Published: (2025)
Similar Items
-
The Quest for Winning Tickets in Low-Rank Adapters
by: Damirchi, Hamed, et al.
Published: (2025) -
Truth as a Trajectory: What Internal Representations Reveal About Large Language Model Reasoning
by: Damirchi, Hamed, et al.
Published: (2026) -
Learning Latent Dynamical Causal Processes for Single-Cell Perturbation Prediction
by: Jiang, Wenkang, et al.
Published: (2026) -
Synergy and Diversity in CLIP: Enhancing Performance Through Adaptive Backbone Ensembling
by: Rodriguez-Opazo, Cristian, et al.
Published: (2024) -
What Makes a Representation Good for Single-Cell Perturbation Prediction?
by: Jiang, Wenkang, et al.
Published: (2026)