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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 2976–3000 of 9051 papers

TitleStatusHype
EAG: Extract and Generate Multi-way Aligned Corpus for Complete Multi-lingual Neural Machine Translation—0
Characterization of phase transitions in a model ecosystem of sessile species—0
Early Exiting with Ensemble Internal Classifiers—0
Broad Twitter Corpus: A Diverse Named Entity Recognition Resource—0
EarthSynth: Generating Informative Earth Observation with Diffusion Models—0
Characterizing Halloumi cheese bacterial communities through metagenomic analysis—0
Bringing Diversity from Diffusion Models to Semantic-Guided Face Asset Generation—0
Diversity-aware Event Prediction based on a Conditional Variational Autoencoder with Reconstruction—0
Eccentric Regularization: Minimizing Hyperspherical Energy without explicit projection—0
ECGAN: Self-supervised generative adversarial network for electrocardiography—0
Echo-chambers and Idea Labs: Communication Styles on Twitter—0
Echo Chambers in Collaborative Filtering Based Recommendation Systems—0
Echoes in AI: Quantifying Lack of Plot Diversity in LLM Outputs—0
Characterizing the Social Interactions in the Artificial Bee Colony Algorithm—0
Ecological communities from random generalised Lotka-Volterra dynamics with non-linear feedback—0
Annotating Cognates and Etymological Origin in Turkic Languages—0
3D-Prover: Diversity Driven Theorem Proving With Determinantal Point Processes—0
EcoSafeRAG: Efficient Security through Context Analysis in Retrieval-Augmented Generation—0
EDCompress: Energy-Aware Model Compression for Dataflows—0
Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting—0
Edge AI Inference in Heterogeneous Constrained Computing: Feasibility and Opportunities—0
Edge computing service deployment and task offloading based on multi-task high-dimensional multi-objective optimization—0
Edge Conditional Node Update Graph Neural Network for Multi-variate Time Series Anomaly Detection—0
Diversity-aware Dual-promotion Poisoning Attack on Sequential Recommendation—0
Bridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets—0
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