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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 2551–2575 of 9051 papers

TitleStatusHype
A Comprehensive Review of Data-Driven Co-Speech Gesture Generation—0
Cause-Aware Empathetic Response Generation via Chain-of-Thought Fine-Tuning—0
Causal Learning for Heterogeneous Subgroups Based on Nonlinear Causal Kernel Clustering—0
Antithetic Noise in Diffusion Models—0
Causality-based Dual-Contrastive Learning Framework for Domain Generalization—0
Adversarial Learning of Semantic Relevance in Text to Image Synthesis—0
DOZE: A Dataset for Open-Vocabulary Zero-Shot Object Navigation in Dynamic Environments—0
D-PAGE: Diverse Paraphrase Generation—0
Causal Effect of Group Diversity on Redundancy and Coverage in Peer-Reviewing—0
CausalDyna: Improving Generalization of Dyna-style Reinforcement Learning via Counterfactual-Based Data Augmentation—0
AntiBARTy Diffusion for Property Guided Antibody Design—0
Causal Conceptions of Fairness and their Consequences—0
5G Simulation-Based Experimentation Framework for Vertical Performance Assessment—0
Do you MIND? Reflections on the MIND dataset for research on diversity in news recommendations—0
CausalAF: Causal Autoregressive Flow for Safety-Critical Driving Scenario Generation—0
Downlink and Uplink Intelligent Reflecting Surface Aided Networks: NOMA and OMA—0
Antenna Array Calibration Via Gaussian Process Models—0
Do ``Undocumented Workers'' == ``Illegal Aliens''? Differentiating Denotation and Connotation in Vector Spaces—0
Downstream-Pretext Domain Knowledge Traceback for Active Learning—0
Do You See What I See? Coordinating Multiple Aerial Cameras for Robot Cinematography—0
DPE-Net: Dual-Parallel Encoder Based Network for Semantic Segmentation of Polyps—0
DPPNet: Approximating Determinantal Point Processes with Deep Networks—0
An Overview of Open-Ended Evolution: Editorial Introduction to the Open-Ended Evolution II Special Issue—0
An Overview of the Research on Texture Based Plant Leaf Classification—0
Don't Throw Away Data: Better Sequence Knowledge Distillation—0
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