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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 4976–5000 of 9051 papers

TitleStatusHype
REMoH: A Reflective Evolution of Multi-objective Heuristics approach via Large Language Models—0
RenderBox: Expressive Performance Rendering with Text Control—0
GlyphDiffusion: Text Generation as Image Generation—0
R\'enyi entropy, abundance distribution and the equivalence of ensembles—0
RePaint-NeRF: NeRF Editting via Semantic Masks and Diffusion Models—0
repgenHMM: a dynamic programming tool to infer the rules of immune receptor generation from sequence data—0
Replica Exchange using q-Gaussian Swarm Quantum Particle Intelligence Method—0
Replicate immunosequencing as a robust probe of B cell repertoire diversity—0
Representational Ethical Model Calibration—0
Representation Heterogeneity—0
Representation Learning Beyond Linear Prediction Functions—0
Representation Online Matters: Practical End-to-End Diversification in Search and Recommender Systems—0
Representing Interlingual Meaning in Lexical Databases—0
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference—0
Repurformer: Transformers for Repurposing-Aware Molecule Generation—0
Requirements for efficient cell-type proportioning: regulatory timescales, stochasticity and lateral inhibition—0
Requirements for Open-Ended Evolution in Natural and Artificial Systems—0
Re-ranking Based Diversification: A Unifying View—0
Re-ranking With Constraints on Diversified Exposures for Homepage Recommender System—0
ResBench: Benchmarking LLM-Generated FPGA Designs with Resource Awareness—0
Research Experience of an Undergraduate Student in Computer Vision and Robotics—0
Research on Dynamic Data Flow Anomaly Detection based on Machine Learning—0
Resolving Multi-path Interference in Time-of-Flight Imaging via Modulation Frequency Diversity and Sparse Regularization—0
Adaptive pruning-based Newton's method for distributed learning—0
Resource Allocation in 6G Optical Wireless Systems—0
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