Saved in:
| Main Authors: | Pareek, Divyansh, Oh, Sewoong, Du, Simon S. |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2512.14230 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Understanding the Gains from Repeated Self-Distillation
by: Pareek, Divyansh, et al.
Published: (2024)
by: Pareek, Divyansh, et al.
Published: (2024)
Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data?
by: Hayase, Jonathan, et al.
Published: (2024)
by: Hayase, Jonathan, et al.
Published: (2024)
PLeaS -- Merging Models with Permutations and Least Squares
by: Nasery, Anshul, et al.
Published: (2024)
by: Nasery, Anshul, et al.
Published: (2024)
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning
by: Wang, Yiping, et al.
Published: (2024)
by: Wang, Yiping, et al.
Published: (2024)
Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning
by: Wang, Yiping, et al.
Published: (2024)
by: Wang, Yiping, et al.
Published: (2024)
Training AI to be Loyal
by: Oh, Sewoong, et al.
Published: (2025)
by: Oh, Sewoong, et al.
Published: (2025)
DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning
by: Hebbar, S Ashwin, et al.
Published: (2024)
by: Hebbar, S Ashwin, et al.
Published: (2024)
Randomization Techniques to Mitigate the Risk of Copyright Infringement
by: Chen, Wei-Ning, et al.
Published: (2024)
by: Chen, Wei-Ning, et al.
Published: (2024)
Characterizing the Training Dynamics of Private Fine-tuning with Langevin diffusion
by: Ke, Shuqi, et al.
Published: (2024)
by: Ke, Shuqi, et al.
Published: (2024)
Sampling from Your Language Model One Byte at a Time
by: Hayase, Jonathan, et al.
Published: (2025)
by: Hayase, Jonathan, et al.
Published: (2025)
Hierarchical Contrastive Learning for Multimodal Data
by: Li, Huichao, et al.
Published: (2026)
by: Li, Huichao, et al.
Published: (2026)
Do Vision--Language Models Understand 3D Scenes or Just Catalogue Objects?
by: Maheshwari, Animesh, et al.
Published: (2026)
by: Maheshwari, Animesh, et al.
Published: (2026)
CUBE: Contrastive Understanding by Balanced Experiments
by: Kim, Dongseok, et al.
Published: (2025)
by: Kim, Dongseok, et al.
Published: (2025)
Cross-Contrastive Clustering for Multimodal Attributed Graphs with Dual Graph Filtering
by: Zheng, Haoran, et al.
Published: (2025)
by: Zheng, Haoran, et al.
Published: (2025)
Are Robust LLM Fingerprints Adversarially Robust?
by: Nasery, Anshul, et al.
Published: (2025)
by: Nasery, Anshul, et al.
Published: (2025)
One-shot Empirical Privacy Estimation for Federated Learning
by: Andrew, Galen, et al.
Published: (2023)
by: Andrew, Galen, et al.
Published: (2023)
Decoupled-Value Attention for Prior-Data Fitted Networks: GP Inference for Physical Equations
by: Sharma, Kaustubh, et al.
Published: (2025)
by: Sharma, Kaustubh, et al.
Published: (2025)
Recycling the Web: A Method to Enhance Pre-training Data Quality and Quantity for Language Models
by: Nguyen, Thao, et al.
Published: (2025)
by: Nguyen, Thao, et al.
Published: (2025)
Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning
by: Wen, Xiaoyu, et al.
Published: (2024)
by: Wen, Xiaoyu, et al.
Published: (2024)
Generative Pre-Training of Time-Series Data for Unsupervised Fault Detection in Semiconductor Manufacturing
by: Lee, Sewoong, et al.
Published: (2023)
by: Lee, Sewoong, et al.
Published: (2023)
Understanding Language Prior of LVLMs by Contrasting Chain-of-Embedding
by: Long, Lin, et al.
Published: (2025)
by: Long, Lin, et al.
Published: (2025)
Understanding Multimodal LLMs Under Distribution Shifts: An Information-Theoretic Approach
by: Oh, Changdae, et al.
Published: (2025)
by: Oh, Changdae, et al.
Published: (2025)
Improved Communication-Privacy Trade-offs in $L_2$ Mean Estimation under Streaming Differential Privacy
by: Chen, Wei-Ning, et al.
Published: (2024)
by: Chen, Wei-Ning, et al.
Published: (2024)
When Incentives Backfire, Data Stops Being Human
by: Santy, Sebastin, et al.
Published: (2025)
by: Santy, Sebastin, et al.
Published: (2025)
Advancing Drug Discovery with Enhanced Chemical Understanding via Asymmetric Contrastive Multimodal Learning
by: Wang, Yifei, et al.
Published: (2023)
by: Wang, Yifei, et al.
Published: (2023)
DPZero: Private Fine-Tuning of Language Models without Backpropagation
by: Zhang, Liang, et al.
Published: (2023)
by: Zhang, Liang, et al.
Published: (2023)
Group Contrastive Learning for Weakly Paired Multimodal Data
by: Gorla, Aditya, et al.
Published: (2026)
by: Gorla, Aditya, et al.
Published: (2026)
S4S: Solving for a Diffusion Model Solver
by: Frankel, Eric, et al.
Published: (2025)
by: Frankel, Eric, et al.
Published: (2025)
Continual Multimodal Contrastive Learning
by: Liu, Xiaohao, et al.
Published: (2025)
by: Liu, Xiaohao, et al.
Published: (2025)
Data-Efficient Strategies for Probabilistic Voltage Envelopes under Network Contingencies
by: Pareek, Parikshit, et al.
Published: (2023)
by: Pareek, Parikshit, et al.
Published: (2023)
Mechanistic Evidence for Spectral Structures in Prior-Data Fitted Networks
by: Sharma, Kaustubh, et al.
Published: (2026)
by: Sharma, Kaustubh, et al.
Published: (2026)
SuperBPE: Space Travel for Language Models
by: Liu, Alisa, et al.
Published: (2025)
by: Liu, Alisa, et al.
Published: (2025)
A Multi-Component AI Framework for Computational Psychology: From Robust Predictive Modeling to Deployed Generative Dialogue
by: Pareek, Anant
Published: (2025)
by: Pareek, Anant
Published: (2025)
Can Public Large Language Models Help Private Cross-device Federated Learning?
by: Wang, Boxin, et al.
Published: (2023)
by: Wang, Boxin, et al.
Published: (2023)
Structure-aware Contrastive Learning for Diagram Understanding of Multimodal Models
by: Sasaki, Hiroshi
Published: (2025)
by: Sasaki, Hiroshi
Published: (2025)
Zeroth-Order Optimization at the Edge of Stability
by: Song, Minhak, et al.
Published: (2026)
by: Song, Minhak, et al.
Published: (2026)
Graph Contrastive Learning under Heterophily via Graph Filters
by: Yang, Wenhan, et al.
Published: (2023)
by: Yang, Wenhan, et al.
Published: (2023)
Canonicalizing Multimodal Contrastive Representation Learning
by: Gupta, Sharut, et al.
Published: (2026)
by: Gupta, Sharut, et al.
Published: (2026)
Learning Power Flow with Confidence: A Probabilistic Guarantee Framework for Voltage Risk
by: Pareek, Parikshit, et al.
Published: (2023)
by: Pareek, Parikshit, et al.
Published: (2023)
Neuronal Fluctuations: Learning Rates vs Participating Neurons
by: Pareek, Darsh, et al.
Published: (2025)
by: Pareek, Darsh, et al.
Published: (2025)
Similar Items
-
Understanding the Gains from Repeated Self-Distillation
by: Pareek, Divyansh, et al.
Published: (2024) -
Data Mixture Inference: What do BPE Tokenizers Reveal about their Training Data?
by: Hayase, Jonathan, et al.
Published: (2024) -
PLeaS -- Merging Models with Permutations and Least Squares
by: Nasery, Anshul, et al.
Published: (2024) -
CLIPLoss and Norm-Based Data Selection Methods for Multimodal Contrastive Learning
by: Wang, Yiping, et al.
Published: (2024) -
Variance Alignment Score: A Simple But Tough-to-Beat Data Selection Method for Multimodal Contrastive Learning
by: Wang, Yiping, et al.
Published: (2024)