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Diversity

Diversity in data sampling is crucial across various use cases, including search, recommendation systems, and more. Ensuring diverse samples means capturing a wide range of variations and perspectives, which leads to more robust, unbiased, and comprehensive models. In search use cases, for instance, diversity helps avoid redundancy, ensuring that users are exposed to a broader set of relevant information rather than repeated similar results.

Papers

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Showing 601–650 of 9051 papers

TitleStatusHype
DUAL: Diversity and Uncertainty Active Learning for Text SummarizationCode0
How Diversely Can Language Models Solve Problems? Exploring the Algorithmic Diversity of Model-Generated Code—0
AILS-NTUA at SemEval-2025 Task 8: Language-to-Code prompting and Error Fixing for Tabular Question AnsweringCode0
Jointly Understand Your Command and Intention:Reciprocal Co-Evolution between Scene-Aware 3D Human Motion Synthesis and Analysis—0
Embracing Diversity: A Multi-Perspective Approach with Soft Labels—0
Autoencoder-Based Framework to Capture Vocabulary Quality in NLP—0
Supporting the development of Machine Learning for fundamental science in a federated Cloud with the AI_INFN platform—0
Innovation-exnovation dynamics on trees and trusses—0
Modeling cell differentiation in neuroblastoma: insights into development, malignancy, and treatment relapse—0
ADAGE: Active Defenses Against GNN Extraction—0
LIVS: A Pluralistic Alignment Dataset for Inclusive Public Spaces—0
Identifiable Multi-View Causal Discovery Without Non-Gaussianity—0
RURANET++: An Unsupervised Learning Method for Diabetic Macular Edema Based on SCSE Attention Mechanisms and Dynamic Multi-Projection Head Clustering—0
UIFace: Unleashing Inherent Model Capabilities to Enhance Intra-Class Diversity in Synthetic Face Recognition—0
DiffCSS: Diverse and Expressive Conversational Speech Synthesis with Diffusion Models—0
Recent Advances on Generalizable Diffusion-generated Image DetectionCode1
Revisiting Self-Consistency from Dynamic Distributional Alignment Perspective on Answer Aggregation—0
Where Are We? Evaluating LLM Performance on African Languages—0
IndicEval-XL: Bridging Linguistic Diversity in Code Generation Across Indic LanguagesCode0
Low-Confidence Gold: Refining Low-Confidence Samples for Efficient Instruction Tuning—0
Distill Any Depth: Distillation Creates a Stronger Monocular Depth EstimatorCode4
EnDive: A Cross-Dialect Benchmark for Fairness and Performance in Large Language Models—0
Effect of Gender Fair Job Description on Generative AI Images—0
SMT(LIA) Sampling with High Diversity—0
MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment—0
olmOCR: Unlocking Trillions of Tokens in PDFs with Vision Language ModelsCode11
Inverse Materials Design by Large Language Model-Assisted Generative FrameworkCode1
AIRIS2 : a Smart Gateway Diversity Algorithm for Very High-Throughput Satellite Systems—0
Can Score-Based Generative Modeling Effectively Handle Medical Image Classification?Code0
CLEP-GAN: An Innovative Approach to Subject-Independent ECG Reconstruction from PPG Signals—0
Bridging Information Gaps with Comprehensive Answers: Improving the Diversity and Informativeness of Follow-Up QuestionsCode0
Delta Decompression for MoE-based LLMs CompressionCode2
HIPPO: Enhancing the Table Understanding Capability of Large Language Models through Hybrid-Modal Preference OptimizationCode1
Low-Rank and Sparse Model Merging for Multi-Lingual Speech Recognition and Translation—0
HybridLinker: Topology-Guided Posterior Sampling for Enhanced Diversity and Validity in 3D Molecular Linker Generation—0
Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable MetricCode1
UrduLLaMA 1.0: Dataset Curation, Preprocessing, and Evaluation in Low-Resource Settings—0
Improving the Transferability of Adversarial Examples by Inverse Knowledge Distillation—0
Entailment-Preserving First-order Logic Representations in Natural Language Entailment—0
SFLD: Reducing the content bias for AI-generated Image Detection—0
Auxiliary Discrminator Sequence Generative Adversarial Networks (ADSeqGAN) for Few Sample Molecule GenerationCode0
The Hidden Strength of Disagreement: Unraveling the Consensus-Diversity Tradeoff in Adaptive Multi-Agent SystemsCode0
Multi-objective Cat Swarm Optimization Algorithm based on a Grid System—0
Be a Multitude to Itself: A Prompt Evolution Framework for Red Teaming—0
ESANS: Effective and Semantic-Aware Negative Sampling for Large-Scale Retrieval Systems—0
CoT-ICL Lab: A Petri Dish for Studying Chain-of-Thought Learning from In-Context DemonstrationsCode1
Unveiling Attractor Cycles in Large Language Models: A Dynamical Systems View of Successive Paraphrasing—0
Chitrarth: Bridging Vision and Language for a Billion People—0
Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence—0
MMRAG: Multi-Mode Retrieval-Augmented Generation with Large Language Models for Biomedical In-Context Learning—0
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