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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 726–750 of 9051 papers

TitleStatusHype
SeDi-Instruct: Enhancing Alignment of Language Models through Self-Directed Instruction Generation—0
Hummingbird: High Fidelity Image Generation via Multimodal Context Alignment—0
PoI: Pixel of Interest for Novel View Synthesis Assisted Scene Coordinate Regression—0
Seasonal Station-Keeping of Short Duration High Altitude Balloons using Deep Reinforcement Learning—0
Affine Frequency Division Multiplexing: Extending OFDM for Scenario-Flexibility and Resilience—0
Leveraging Hypernetworks and Learnable Kernels for Consumer Energy Forecasting Across Diverse Consumer Types—0
CCS: Controllable and Constrained Sampling with Diffusion Models via Initial Noise Perturbation—0
Leveraging band diversity for feature selection in EO data—0
When One LLM Drools, Multi-LLM Collaboration Rules—0
Multi-Agent Reinforcement Learning with Focal Diversity OptimizationCode0
TriNER: A Series of Named Entity Recognition Models For Hindi, Bengali & Marathi—0
Single-Domain Generalized Object Detection by Balancing Domain Diversity and Invariance—0
UniForm: A Unified Multi-Task Diffusion Transformer for Audio-Video Generation—0
Augmented Conditioning Is Enough For Effective Training Image Generation—0
Pre-Optimized Irregular Arrays versus Moveable Antennas in Multi-User MIMO Systems—0
DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation—0
From Features to Transformers: Redefining Ranking for Scalable Impact—0
MaxInfo: A Training-Free Key-Frame Selection Method Using Maximum Volume for Enhanced Video Understanding—0
KDA: A Knowledge-Distilled Attacker for Generating Diverse Prompts to Jailbreak LLMs—0
Proportional Selection in Networks—0
Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data—0
Controllable Satellite-to-Street-View Synthesis with Precise Pose Alignment and Zero-Shot Environmental Control—0
How Inclusively do LMs Perceive Social and Moral Norms?Code0
Position Paper: Building Trust in Synthetic Data for Clinical AI—0
Topic Modeling in Marathi—0
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