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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

Showing 451475 of 9051 papers

TitleStatusHype
Adaptive Contrastive Search: Uncertainty-Guided Decoding for Open-Ended Text GenerationCode1
Self-Supervision Improves Diffusion Models for Tabular Data ImputationCode1
Take a Step and Reconsider: Sequence Decoding for Self-Improved Neural Combinatorial OptimizationCode1
A Quantum Leaky Integrate-and-Fire Spiking Neuron and NetworkCode1
Annealed Multiple Choice Learning: Overcoming limitations of Winner-takes-all with annealingCode1
Diffusion for Out-of-Distribution Detection on Road Scenes and BeyondCode1
Semantic Diversity-aware Prototype-based Learning for Unbiased Scene Graph GenerationCode1
DriveDiTFit: Fine-tuning Diffusion Transformers for Autonomous DrivingCode1
Personalized Privacy Protection Mask Against Unauthorized Facial RecognitionCode1
Are Large Language Models Capable of Generating Human-Level Narratives?Code1
Learning Semantic Latent Directions for Accurate and Controllable Human Motion PredictionCode1
DiffStega: Towards Universal Training-Free Coverless Image Steganography with Diffusion ModelsCode1
Visual Prompt Selection for In-Context Learning SegmentationCode1
FedMedICL: Towards Holistic Evaluation of Distribution Shifts in Federated Medical ImagingCode1
Dual-stage Hyperspectral Image Classification Model with Spectral SupertokenCode1
Secondary Structure-Guided Novel Protein Sequence Generation with Latent Graph DiffusionCode1
Virtual Personas for Language Models via an Anthology of BackstoriesCode1
Remastering Divide and Remaster: A Cinematic Audio Source Separation Dataset with Multilingual SupportCode1
General and Task-Oriented Video SegmentationCode1
3D Vision and Language Pretraining with Large-Scale Synthetic DataCode1
FDS: Feedback-guided Domain Synthesis with Multi-Source Conditional Diffusion Models for Domain GeneralizationCode1
Emotion and Intent Joint Understanding in Multimodal Conversation: A Benchmarking DatasetCode1
RobocupGym: A challenging continuous control benchmark in RobocupCode1
Fibottention: Inceptive Visual Representation Learning with Diverse Attention Across HeadsCode1
RuBLiMP: Russian Benchmark of Linguistic Minimal PairsCode1
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