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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 4651–4675 of 9051 papers

TitleStatusHype
How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?Code0
Improving Response Diversity through Commonsense-Aware Empathetic Response Generation—0
Learning utterance-level representations through token-level acoustic latents prediction for Expressive Speech Synthesis—0
Lila: A Unified Benchmark for Mathematical ReasoningCode1
Evaluation of large-scale synthetic data for Grammar Error Correction—0
SSD-LM: Semi-autoregressive Simplex-based Diffusion Language Model for Text Generation and Modular ControlCode1
Tree Detection and Diameter Estimation Based on Deep LearningCode1
Space-time design for deep joint source channel coding of images Over MIMO channelsCode1
Towards Attribute-Entangled Controllable Text Generation: A Pilot Study of Blessing GenerationCode0
Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification AlgorithmsCode1
Track2Vec: fairness music recommendation with a GPU-free customizable-driven frameworkCode1
Period VITS: Variational Inference with Explicit Pitch Modeling for End-to-end Emotional Speech Synthesis—0
Latent Space is Feature Space: Regularization Term for GANs Training on Limited DatasetCode0
Few-shot Image Generation via Masked DiscriminationCode0
ScoreMix: A Scalable Augmentation Strategy for Training GANs with Limited Data—0
How well can Text-to-Image Generative Models understand Ethical Natural Language Interventions?Code1
Is Out-of-Distribution Detection Learnable?—0
Uncertainty Sentence Sampling by Virtual Adversarial Perturbation—0
Full-band General Audio Synthesis with Score-based Diffusion—0
DiffusionDB: A Large-scale Prompt Gallery Dataset for Text-to-Image Generative ModelsCode3
IFDID: Information Filter upon Diversity-Improved Decoding for Diversity-Faithfulness Tradeoff in NLG—0
Towards standardizing Korean Grammatical Error Correction: Datasets and AnnotationCode1
A single-cell gene expression language modelCode1
S3E: A Multi-Robot Multimodal Dataset for Collaborative SLAMCode1
Preference-Learning Emitters for Mixed-Initiative Quality-Diversity AlgorithmsCode1
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