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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 6901–6925 of 9051 papers

TitleStatusHype
MotionScript: Natural Language Descriptions for Expressive 3D Human Motions—0
MotorFactory: A Blender Add-on for Large Dataset Generation of Small Electric Motors—0
Moving Beyond LDA: A Comparison of Unsupervised Topic Modelling Techniques for Qualitative Data Analysis of Online Communities—0
MPO: An Efficient Post-Processing Framework for Mixing Diverse Preference Alignment—0
MrTrack: Register Mamba for Needle Tracking with Rapid Reciprocating Motion during Ultrasound-Guided Aspiration Biopsy—0
MsDC-DEQ-Net: Deep Equilibrium Model (DEQ) with Multi-scale Dilated Convolution for Image Compressive Sensing (CS)—0
MSLIQA: Enhancing Learning Representations for Image Quality Assessment through Multi-Scale Learning—0
MUCIC@LT-EDI-ACL2022: Hope Speech Detection using Data Re-Sampling and 1D Conv-LSTM—0
MUCS@LT-EDI-EACL2021:CoHope-Hope Speech Detection for Equality, Diversity, and Inclusion in Code-Mixed Texts—0
MulDA: A Multilingual Data Augmentation Framework for Low-Resource Cross-Lingual NER—0
MULDEF: Multi-model-based Defense Against Adversarial Examples for Neural Networks—0
Multi-Agent Diagnostics for Robustness via Illuminated Diversity—0
Multi-agent query reformulation: Challenges and the role of diversity—0
Multi-Agent Reinforcement Learning for Decentralized Reservoir Management via Murmuration Intelligence—0
Multi-Agent Reinforcement Learning for Graph Discovery in D2D-Enabled Federated Learning—0
Multi-Attributed and Structured Text-to-Face Synthesis—0
Multichannel Generative Language Model: Learning All Possible Factorizations Within and Across Channels—0
Multi-Classification of Brain Tumor Images Using Transfer Learning Based Deep Neural Network—0
Multiclass non-Adversarial Image Synthesis, with Application to Classification from Very Small Sample—0
Multi-class Road Defect Detection and Segmentation using Spatial and Channel-wise Attention for Autonomous Road Repairing—0
Multi-Cohort Framework with Cohort-Aware Attention and Adversarial Mutual-Information Minimization for Whole Slide Image Classification—0
Multi-dimensional data refining strategy for effective fine-tuning LLMs—0
Multidimensional Fairness in Paper Recommendation—0
Multi-Domain Goal-Oriented Dialogues (MultiDoGO): Strategies toward Curating and Annotating Large Scale Dialogue Data—0
Multi-Domain Image-to-Image Translation with Adaptive Inference Graph—0
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