Cover Image

Is Data Shapley Not Better than Random in Data Selection? Ask NASH

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Tian, Xiao, Fan, Jue, Sim, Rachael Hwee Ling, Wang, Zixuan, Chen, Nancy F., Low, Bryan Kian Hsiang
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

DeRDaVa: Deletion-Robust Data Valuation for Machine Learning
by: Tian, Xiao, et al.
Published: (2023)

INO-SGD: Addressing Utility Imbalance under Individualized Differential Privacy
by: Tian, Xiao, et al.
Published: (2026)

Incentivizing Truthfulness and Collaborative Fairness in Bayesian Learning
by: Sim, Rachael Hwee Ling, et al.
Published: (2026)

How Hard Can It Be? Hardness-Aware Multi-Objective Unlearning
by: Chen, Jiangwei, et al.
Published: (2026)

On Newton's Method to Unlearn Neural Networks
by: Bui, Nhung, et al.
Published: (2024)

DUPRE: Data Utility Prediction for Efficient Data Valuation
by: Pham, Kieu Thao Nguyen, et al.
Published: (2025)

Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions
by: Wang, Jingtan, et al.
Published: (2024)

Incentivizing Time-Aware Fairness in Data Sharing
by: Chen, Jiangwei, et al.
Published: (2025)

Data value estimation on private gradients
by: Zhou, Zijian, et al.
Published: (2024)

Provably Adaptive Linear Approximation for the Shapley Value and Beyond
by: Li, Weida, et al.
Published: (2026)

Incentives in Private Collaborative Machine Learning
by: Sim, Rachael Hwee Ling, et al.
Published: (2024)

DUET: Optimizing Training Data Mixtures via Feedback from Unseen Evaluation Tasks
by: Chen, Zhiliang, et al.
Published: (2025)

Self-Interested Agents in Collaborative Machine Learning: An Incentivized Adaptive Data-Centric Framework
by: Vijayan, Nithia, et al.
Published: (2024)

Broaden your SCOPE! Efficient Multi-turn Conversation Planning for LLMs with Semantic Space
by: Chen, Zhiliang, et al.
Published: (2025)

TETRIS: Optimal Draft Token Selection for Batch Speculative Decoding
by: Wu, Zhaoxuan, et al.
Published: (2025)

Keep Everyone Happy: Online Fair Division of Numerous Items with Few Copies
by: Verma, Arun, et al.
Published: (2024)

COBRA: Contextual Bandit Algorithm for Ensuring Truthful Strategic Agents
by: Verma, Arun, et al.
Published: (2025)

Source Attribution for Large Language Model-Generated Data
by: Wang, Jingtan, et al.
Published: (2023)

BoLT: A Benchmark to Democratize Black-box Optimization Research for Expensive LLM Tasks
by: Chew, Ruth Wan Theng, et al.
Published: (2026)

Dependency Structure Search Bayesian Optimization for Decision Making Models
by: Rajpal, Mohit, et al.
Published: (2023)

The Chicken and Egg Dilemma: Co-optimizing Data and Model Configurations for LLMs
by: Chen, Zhiliang, et al.
Published: (2026)

Paid with Models: Optimal Contract Design for Collaborative Machine Learning
by: Wang, Bingchen, et al.
Published: (2024)

WaterDrum: Watermarking for Data-centric Unlearning Metric
by: Lu, Xinyang, et al.
Published: (2025)

Neural Dueling Bandits: Preference-Based Optimization with Human Feedback
by: Verma, Arun, et al.
Published: (2024)

"Better Ask for Forgiveness than Permission": Practices and Policies of AI Disclosure in Freelance Work
by: Hwang, Angel Hsing-Chi, et al.
Published: (2026)

Understanding Domain Generalization: A Noise Robustness Perspective
by: Qiao, Rui, et al.
Published: (2024)

Decentralized Sum-of-Nonconvex Optimization
by: Liu, Zhuanghua, et al.
Published: (2024)

Fine-tuning Language Models with Generative Adversarial Reward Modelling
by: Yu, Zhang Ze, et al.
Published: (2023)

REFRAG: Rethinking RAG based Decoding
by: Lin, Xiaoqiang, et al.
Published: (2025)

BarrierSteer: LLM Safety via Learning Barrier Steering
by: Tran, Thanh Q., et al.
Published: (2026)

Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
by: Shu, Yao, et al.
Published: (2024)

Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions
by: Qiao, Rui, et al.
Published: (2025)

Prompt Optimization with EASE? Efficient Ordering-aware Automated Selection of Exemplars
by: Wu, Zhaoxuan, et al.
Published: (2024)

Data Distribution Valuation
by: Xu, Xinyi, et al.
Published: (2024)

DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning
by: Zhou, Zijian, et al.
Published: (2024)

PIED: Physics-Informed Experimental Design for Inverse Problems
by: Hemachandra, Apivich, et al.
Published: (2025)

PINNACLE: PINN Adaptive ColLocation and Experimental points selection
by: Lau, Gregory Kang Ruey, et al.
Published: (2024)

Federated Learning for Data Market: Shapley-UCB for Seller Selection and Incentives
by: Chen, Kongyang, et al.
Published: (2024)

Fast-DataShapley: Neural Modeling for Training Data Valuation
by: Sun, Haifeng, et al.
Published: (2025)

ActiveDPO: Active Direct Preference Optimization for Sample-Efficient Alignment
by: Lin, Xiaoqiang, et al.
Published: (2025)