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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 376–400 of 9051 papers

TitleStatusHype
Uncertainty-Aware Trajectory Prediction via Rule-Regularized Heteroscedastic Deep ClassificationCode0
Real-World Depth Recovery via Structure Uncertainty Modeling and Inaccurate GT Depth Fitting—0
Bridging the Semantic Gaps: Improving Medical VQA Consistency with LLM-Augmented Question Sets—0
Evaluating the Diversity and Quality of LLM Generated Content—0
Rethinking LLM-Based Recommendations: A Query Generation-Based, Training-Free Approach—0
SLURG: Investigating the Feasibility of Generating Synthetic Online Fallacious Discourse—0
FedEPA: Enhancing Personalization and Modality Alignment in Multimodal Federated Learning—0
How Do I Do That? Synthesizing 3D Hand Motion and Contacts for Everyday Interactions—0
Unravelling Technical debt topics through Time, Programming Languages and Repository—0
Voice Conversion with Diverse Intonation using Conditional Variational Auto-Encoder—0
X-Teaming: Multi-Turn Jailbreaks and Defenses with Adaptive Multi-Agents—0
Multi-Agent Reinforcement Learning for Decentralized Reservoir Management via Murmuration Intelligence—0
Large Language Model-Informed Feature Discovery Improves Prediction and Interpretation of Credibility Perceptions of Visual Content—0
Diversity-Driven Learning: Tackling Spurious Correlations and Data Heterogeneity in Federated Models—0
Elucidating the Design Space of Multimodal Protein Language ModelsCode3
Using LLMs as prompt modifier to avoid biases in AI image generators—0
Controllable Expressive 3D Facial Animation via Diffusion in a Unified Multimodal Space—0
TAMP: Token-Adaptive Layerwise Pruning in Multimodal Large Language ModelsCode1
Relation-Rich Visual Document Generator for Visual Information ExtractionCode0
The Impact of Model Zoo Size and Composition on Weight Space LearningCode0
Accelerating Differentially Private Federated Learning via Adaptive Extrapolation—0
Can genomic analysis actually estimate past population size?—0
Weight Ensembling Improves Reasoning in Language Models—0
Diversity Analysis for Indoor Terahertz Communication Systems under Small-Scale Fading—0
Diversity-Fair Online Selection—0
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