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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 1026–1050 of 9051 papers

TitleStatusHype
Diversity Drives Fairness: Ensemble of Higher Order Mutants for Intersectional Fairness of Machine Learning Software—0
RoomTour3D: Geometry-Aware Video-Instruction Tuning for Embodied Navigation—0
Multi-perspective Alignment for Increasing Naturalness in Neural Machine Translation—0
Competition and Diversity in Generative AICode0
Surveying Facial Recognition Models for Diverse Indian Demographics: A Comparative Analysis on LFW and Custom Dataset—0
Towards Precision in Bolted Joint Design: A Preliminary Machine Learning-Based Parameter Prediction—0
AmCLR: Unified Augmented Learning for Cross-Modal RepresentationsCode0
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets—0
LOGen: Toward Lidar Object Generation by Point Diffusion—0
OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive AnnotationsCode5
A Dynamical Systems-Inspired Pruning Strategy for Addressing Oversmoothing in Graph Neural Networks—0
CADSpotting: Robust Panoptic Symbol Spotting on Large-Scale CAD Drawings—0
MIT-10M: A Large Scale Parallel Corpus of Multilingual Image Translation—0
Reconfigurable Holographic Surface-aided Distributed MIMO Radar Systems—0
AIDE: Task-Specific Fine Tuning with Attribute Guided Multi-Hop Data Expansion—0
Diffusing Differentiable Representations—0
Data Quality Enhancement on the Basis of Diversity with Large Language Models for Text Classification: Uncovered, Difficult, and Noisy—0
Learnable Evolutionary Multi-Objective Combinatorial Optimization via Sequence-to-Sequence ModelCode0
CONDEN-FI: Consistency and Diversity Learning-based Multi-View Unsupervised Feature and In-stance Co-Selection—0
Diverse Score Distillation—0
VariFace: Fair and Diverse Synthetic Dataset Generation for Face Recognition—0
Exploring Critical Testing Scenarios for Decision-Making Policies: An LLM Approach—0
PPT: Pretraining with Pseudo-Labeled Trajectories for Motion Forecasting—0
Does RLHF Scale? Exploring the Impacts From Data, Model, and Method—0
Measuring Grammatical Diversity from Small Corpora: Derivational Entropy Rates, Mean Length of Utterances, and Annotation Invariance—0
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