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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 5301–5325 of 9051 papers

TitleStatusHype
Site Diversity in Downlink Optical Satellite Networks Through Ground Station Selection—0
Site-specific recombinatorics: in situ cellular barcoding with the Cre Lox system—0
Situation Monitor: Diversity-Driven Zero-Shot Out-of-Distribution Detection using Budding Ensemble Architecture for Object Detection—0
Situation-Specific Multimodal Feature Adaptation—0
SizeGAN: Improving Size Representation in Clothing Catalogs—0
SJTU-TMQA: A quality assessment database for static mesh with texture map—0
SKG: A Versatile Information Retrieval and Analysis Framework for Academic Papers with Semantic Knowledge Graphs—0
SkiLD: Unsupervised Skill Discovery Guided by Factor Interactions—0
Skill Discovery of Coordination in Multi-agent Reinforcement Learning—0
Skip-Layer Attention: Bridging Abstract and Detailed Dependencies in Transformers—0
SkyScenes: A Synthetic Dataset for Aerial Scene Understanding—0
Sliding Spectrum Decomposition for Diversified Recommendation—0
SLOGAN: Handwriting Style Synthesis for Arbitrary-Length and Out-of-Vocabulary Text—0
Slow and Fast Neurons Cooperate in Contextual Working Memory through Timescale Diversity—0
SLURG: Investigating the Feasibility of Generating Synthetic Online Fallacious Discourse—0
SM^3: Self-Supervised Multi-task Modeling with Multi-view 2D Images for Articulated Objects—0
Smaller, Weaker, Yet Better: Training LLM Reasoners via Compute-Optimal Sampling—0
Smartphone Multi-modal Biometric Authentication: Database and Evaluation—0
Smart Reply: Automated Response Suggestion for Email—0
SMART: Simultaneous Multi-Agent Recurrent Trajectory Prediction—0
Smirk: An Atomically Complete Tokenizer for Molecular Foundation Models—0
SMRT Chatbots: Improving Non-Task-Oriented Dialog with Simulated Multiple Reference Training—0
SMT(LIA) Sampling with High Diversity—0
Snapshot Difference Imaging using Time-of-Flight Sensors—0
SNIDA: Unlocking Few-Shot Object Detection with Non-linear Semantic Decoupling Augmentation—0
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