Cover Image

Coresets from Trajectories: Selecting Data via Correlation of Loss Differences

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nagaraj, Manish, Ravikumar, Deepak, Roy, Kaushik
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Finding the Muses: Identifying Coresets through Loss Trajectories
by: Nagaraj, Manish, et al.
Published: (2025)

TRIM: Token-wise Attention-Derived Saliency for Data-Efficient Instruction Tuning
by: Nagaraj, Manish, et al.
Published: (2025)

The Easy Path to Robustness: Coreset Selection using Sample Hardness
by: Ramesh, Pranav, et al.
Published: (2025)

Loss Knows Best: Detecting Annotation Errors in Videos via Loss Trajectories
by: Alwis, Praditha, et al.
Published: (2026)

Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature
by: Ravikumar, Deepak, et al.
Published: (2024)

TOFU: Towards Obfuscated Federated Updates by Encoding Weight Updates into Gradients from Proxy Data
by: Garg, Isha, et al.
Published: (2022)

TopoPrune: Robust Data Pruning via Unified Latent Space Topology
by: Roy, Arjun, et al.
Published: (2026)

TraceNAS: Zero-shot LLM Pruning via Gradient Trace Correlation
by: Malettira, Prajna G., et al.
Published: (2026)

GradientSpace: Unsupervised Data Clustering for Improved Instruction Tuning
by: Sridharan, Shrihari, et al.
Published: (2025)

Advancing Compressed Video Action Recognition through Progressive Knowledge Distillation
by: Soufleri, Efstathia, et al.
Published: (2024)

SAP: Corrective Machine Unlearning with Scaled Activation Projection for Label Noise Robustness
by: Kodge, Sangamesh, et al.
Published: (2024)

Homogenizing Non-IID datasets via In-Distribution Knowledge Distillation for Decentralized Learning
by: Ravikumar, Deepak, et al.
Published: (2023)

Unveiling Privacy, Memorization, and Input Curvature Links
by: Ravikumar, Deepak, et al.
Published: (2024)

The Impact of Coreset Selection on Spurious Correlations and Group Robustness
by: Dharmasiri, Amaya, et al.
Published: (2025)

Coreset Selection via LLM-based Concept Bottlenecks
by: Mehra, Akshay, et al.
Published: (2025)

FEDORA: Flying Event Dataset fOr Reactive behAvior
by: Joshi, Amogh, et al.
Published: (2023)

The Power of Few: Accelerating and Enhancing Data Reweighting with Coreset Selection
by: Jafari, Mohammad, et al.
Published: (2024)

A Coreset Selection of Coreset Selection Literature: Introduction and Recent Advances
by: Moser, Brian B., et al.
Published: (2025)

Class-Proportional Coreset Selection for Difficulty-Separable Data
by: Tsai, Elisa, et al.
Published: (2025)

Stable Coresets via Posterior Sampling: Aligning Induced and Full Loss Landscapes
by: Chang, Wei-Kai, et al.
Published: (2025)

Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints
by: Xia, Xiaobo, et al.
Published: (2023)

TOFFE -- Temporally-binned Object Flow from Events for High-speed and Energy-Efficient Object Detection and Tracking
by: Kosta, Adarsh Kumar, et al.
Published: (2025)

Coreset Selection for Object Detection
by: Lee, Hojun, et al.
Published: (2024)

PDAC: Efficient Coreset Selection for Continual Learning via Probability Density Awareness
by: Gao, Junqi, et al.
Published: (2025)

Distributionally Robust Coreset Selection under Covariate Shift
by: Tanaka, Tomonari, et al.
Published: (2025)

Challenges of Multi-Modal Coreset Selection for Depth Prediction
by: Moskvoretskii, Viktor, et al.
Published: (2025)

PICore: Physics-Informed Unsupervised Coreset Selection for Data Efficient Neural Operator Training
by: Satheesh, Anirudh, et al.
Published: (2025)

HyperCore: Coreset Selection under Noise via Hypersphere Models
by: Moser, Brian B., et al.
Published: (2025)

MODE: Multi-Objective Adaptive Coreset Selection
by: Mukherjee, Tanmoy, et al.
Published: (2025)

Contributing Dimension Structure of Deep Feature for Coreset Selection
by: Wan, Zhijing, et al.
Published: (2024)

Speculative Coreset Selection for Task-Specific Fine-tuning
by: Zhang, Xiaoyu, et al.
Published: (2024)

Predictive Coresets
by: Flores, Bernardo
Published: (2025)

TAGCOS: Task-agnostic Gradient Clustered Coreset Selection for Instruction Tuning Data
by: Zhang, Jipeng, et al.
Published: (2024)

Efficient Content-based Recommendation Model Training via Noise-aware Coreset Selection
by: Tran, Hung Vinh, et al.
Published: (2026)

THEMIS: Unlocking Pretrained Knowledge with Foundation Model Embeddings for Anomaly Detection in Time Series
by: Lorik, Yadav Mahesh, et al.
Published: (2025)

UPCORE: Utility-Preserving Coreset Selection for Balanced Unlearning
by: Patil, Vaidehi, et al.
Published: (2025)

Variational Bayesian Pseudo-Coreset
by: Lee, Hyungi, et al.
Published: (2025)

Gradient Coreset for Federated Learning
by: Sivasubramanian, Durga, et al.
Published: (2024)

Bayesian Pseudo-Coresets via Contrastive Divergence
by: Tiwary, Piyush, et al.
Published: (2023)

Efficient and Robust Quantization-aware Training via Adaptive Coreset Selection
by: Huang, Xijie, et al.
Published: (2023)