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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 3576–3600 of 9051 papers

TitleStatusHype
Fairness and Diversity in the Recommendation and Ranking of Participatory Media Content—0
Consistent Multiple Sequence Decoding—0
Fairness on Synthetic Visual and Thermal Mask Images—0
FairRAG: Fair Human Generation via Fair Retrieval Augmentation—0
FairSkin: Fair Diffusion for Skin Disease Image Generation—0
Constrained Pseudo-market Equilibrium—0
Why Perturbing Symbolic Music is Necessary: Fitting the Distribution of Never-used Notes through a Joint Probabilistic Diffusion Model—0
GaitGCI: Generative Counterfactual Intervention for Gait Recognition—0
GameVibe: A Multimodal Affective Game Corpus—0
Garment Design with Generative Adversarial Networks—0
Diversified Ensemble of Independent Sub-Networks for Robust Self-Supervised Representation Learning—0
Boost Neural Networks by Checkpoints—0
Fantastic Style Channels and Where to Find Them: A Submodular Framework for Discovering Diverse Directions in GANs—0
Constructing Domain-Specific Evaluation Sets for LLM-as-a-judge—0
Farthest Greedy Path Sampling for Two-shot Recommender Search—0
FAS-assisted Wireless Powered Communication Systems—0
Fast ABC with joint generative modelling and subset simulation—0
Fast Adaptation in Generative Models with Generative Matching Networks—0
Construction and optimization of health behavior prediction model for the elderly in smart elderly care—0
Fast and High Quality Highlight Removal from A Single Image—0
Construction of Responsive Utterance Corpus for Attentive Listening Response Production—0
Fast and Robust: Task Sampling with Posterior and Diversity Synergies for Adaptive Decision-Makers in Randomized Environments—0
A novel multiobjective evolutionary algorithm based on decomposition and multi-reference points strategy—0
Fundamentals of Task-Agnostic Data Valuation—0
Diversidade linguística e inclusão digital: desafios para uma ia brasileira—0
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