Imagen de Portada

Rethinking Representativeness and Diversity in Dynamic Data Selection

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Zhou, Yuzhe, Hua, Zhenglin, Guo, Haiyun, Jia, Yuheng
Formato:	Preprint
Publicado:	2026
Materias:	Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Steering LVLMs via Sparse Autoencoder for Hallucination Mitigation
por: Hua, Zhenglin, et al.
Publicado: (2025)

MLLM-CTBench: A Benchmark for Continual Instruction Tuning with Reasoning Process Diagnosis
por: Guo, Haiyun, et al.
Publicado: (2025)

Time-Annealed Perturbation Sampling: Diverse Generation for Diffusion Language Models
por: Wu, Jingxuan, et al.
Publicado: (2026)

Letting Trajectories Spread: Quality-Preserving Control for Diverse Flow Matching
por: Wu, Jingxuan, et al.
Publicado: (2025)

Finding the Correct Visual Evidence Without Forgetting: Mitigating Hallucination in LVLMs via Inter-Layer Visual Attention Discrepancy
por: Xie, Yutong, et al.
Publicado: (2026)

Learning from the Best, Differently: A Diversity-Driven Rethinking on Data Selection
por: He, Hongyi, et al.
Publicado: (2025)

Imitation from Diverse Behaviors: Wasserstein Quality Diversity Imitation Learning with Single-Step Archive Exploration
por: Yu, Xingrui, et al.
Publicado: (2024)

Dynamic Mixture of Experts: An Auto-Tuning Approach for Efficient Transformer Models
por: Guo, Yongxin, et al.
Publicado: (2024)

Prompt Optimization Across Multiple Agents for Representing Diverse Human Populations
por: Nguyen, Manh Hung, et al.
Publicado: (2025)

G$^2$RPO-A: Guided Group Relative Policy Optimization with Adaptive Guidance
por: Guo, Yongxin, et al.
Publicado: (2025)

BERnaT: Basque Encoders for Representing Natural Textual Diversity
por: Azurmendi, Ekhi, et al.
Publicado: (2025)

Rethinking Data Selection at Scale: Random Selection is Almost All You Need
por: Xia, Tingyu, et al.
Publicado: (2024)

Parallel Thinking, Sequential Answering: Bridging NAR and AR for Efficient Reasoning
por: Ai, Qihang, et al.
Publicado: (2025)

Concentration Distribution Learning from Label Distributions
por: Tang, Jiawei, et al.
Publicado: (2025)

Stable LLM Ensemble: Interaction between Example Representativeness and Diversity
por: Niimi, Junichiro
Publicado: (2025)

Harnessing Diversity for Important Data Selection in Pretraining Large Language Models
por: Zhang, Chi, et al.
Publicado: (2024)

Rethinking Diversity in Deep Neural Network Testing
por: Wang, Zi, et al.
Publicado: (2023)

FedDiverse: Tackling Data Heterogeneity in Federated Learning with Diversity-Driven Client Selection
por: Németh, Gergely D., et al.
Publicado: (2025)

BrainBench: Exposing the Commonsense Reasoning Gap in Large Language Models
por: Tang, Yuzhe
Publicado: (2026)

PASA: A Principled Embedding-Space Watermarking Approach for LLM-Generated Text under Semantic-Invariant Attacks
por: Ai, Zhenxin, et al.
Publicado: (2026)

Knowledge Authoring with Factual English, Rules, and Actions
por: Wang, Yuheng
Publicado: (2024)

Diversify and Conquer: Diversity-Centric Data Selection with Iterative Refinement
por: Yu, Simon, et al.
Publicado: (2024)

LoReC: Rethinking Large Language Models for Graph Data Analysis
por: Zhan, Hongyu, et al.
Publicado: (2026)

Enabling Small Models for Zero-Shot Selection and Reuse through Model Label Learning
por: Zhang, Jia, et al.
Publicado: (2024)

Rethinking Supervised Fine-Tuning: Emphasizing Key Answer Tokens for Improved LLM Accuracy
por: Shi, Xiaofeng, et al.
Publicado: (2025)

Rethinking Inverse Reinforcement Learning: from Data Alignment to Task Alignment
por: Zhou, Weichao, et al.
Publicado: (2024)

Label Distribution Learning from Logical Label
por: Jia, Yuheng, et al.
Publicado: (2023)

Collaborative LLM Numerical Reasoning with Local Data Protection
por: Zhang, Min, et al.
Publicado: (2025)

Incrementally Learning Multiple Diverse Data Domains via Multi-Source Dynamic Expansion Model
por: Wu, Runqing, et al.
Publicado: (2025)

REPrune: Channel Pruning via Kernel Representative Selection
por: Park, Mincheol, et al.
Publicado: (2024)

Rethinking Toxicity Evaluation in Large Language Models: A Multi-Label Perspective
por: Kou, Zhiqiang, et al.
Publicado: (2025)

Empowering Users in Digital Privacy Management through Interactive LLM-Based Agents
por: Sun, Bolun, et al.
Publicado: (2024)

Rethinking Importance Sampling in LLM Policy Optimization: A Cumulative Token Perspective
por: Zhang, Yuheng, et al.
Publicado: (2026)

Rethink Deep Learning with Invariance in Data Representation
por: Qi, Shuren, et al.
Publicado: (2024)

HLogformer: A Hierarchical Transformer for Representing Log Data
por: Hou, Zhichao, et al.
Publicado: (2024)

When Dynamic Data Selection Meets Data Augmentation
por: Yang, Suorong, et al.
Publicado: (2025)

Inflated Excellence or True Performance? Rethinking Medical Diagnostic Benchmarks with Dynamic Evaluation
por: Zhang, Xiangxu, et al.
Publicado: (2025)

LLM Data Selection and Utilization via Dynamic Bi-level Optimization
por: Yu, Yang, et al.
Publicado: (2025)

Rethinking Diverse Human Preference Learning through Principal Component Analysis
por: Luo, Feng, et al.
Publicado: (2025)

Rethinking Independent Cross-Entropy Loss For Graph-Structured Data
por: Miao, Rui, et al.
Publicado: (2024)