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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 6151–6200 of 9051 papers

TitleStatusHype
Voice of a Continent: Mapping Africa's Speech Technology Frontier—0
VOLTA: Improving Generative Diversity by Variational Mutual Information Maximizing Autoencoder—0
vONTSS: vMF based semi-supervised neural topic modeling with optimal transport—0
VoxArabica: A Robust Dialect-Aware Arabic Speech Recognition System—0
VoxVietnam: a Large-Scale Multi-Genre Dataset for Vietnamese Speaker Recognition—0
VR.net: A Real-world Dataset for Virtual Reality Motion Sickness Research—0
VRSD: Rethinking Similarity and Diversity for Retrieval in Large Language Models—0
V-VIPE: Variational View Invariant Pose Embedding—0
Wafer Map Defect Classification Using Autoencoder-Based Data Augmentation and Convolutional Neural Network—0
WakaVT: A Sequential Variational Transformer for Waka Generation—0
WaLRUS: Wavelets for Long-range Representation Using SSMs—0
WangLab at MEDIQA-CORR 2024: Optimized LLM-based Programs for Medical Error Detection and Correction—0
WarriorCoder: Learning from Expert Battles to Augment Code Large Language Models—0
Wasserstein Distance Maximizing Intrinsic Control—0
Wasserstein Diversity-Enriched Regularizer for Hierarchical Reinforcement Learning—0
Watch and Learn: Semi-Supervised Learning for Object Detectors From Video—0
Watch and Learn: Semi-Supervised Learning of Object Detectors from Videos—0
River Surface Patch-wise Detector Using Mixture Augmentation for Scum-cover-index—0
Watertox: The Art of Simplicity in Universal Attacks A Cross-Model Framework for Robust Adversarial Generation—0
Wavelet Classification for Over-the-Air Non-Orthogonal Waveforms—0
WaveMo: Learning Wavefront Modulations to See Through Scattering—0
WavFusion: Towards wav2vec 2.0 Multimodal Speech Emotion Recognition—0
Weakly-supervised Pre-training for 3D Human Pose Estimation via Perspective Knowledge—0
We Are Depleting Our Research Subject as We Are Investigating It: In Language Technology, more Replication and Diversity Are Needed—0
WebSeg: Learning Semantic Segmentation from Web Searches—0
We Can't Understand AI Using our Existing Vocabulary—0
WEDGE: Web-Image Assisted Domain Generalization for Semantic Segmentation—0
Federated Learning Model Aggregation in Heterogenous Aerial and Space Networks—0
Weighted Diversified Sampling for Efficient Data-Driven Single-Cell Gene-Gene Interaction Discovery—0
Weighted Ensemble Self-Supervised Learning—0
Weighted Spectral Cluster Ensemble—0
Weighted Theta Functions and Embeddings with Applications to Max-Cut, Clustering and Summarization—0
Weight Ensembling Improves Reasoning in Language Models—0
Weighting and Pruning based Ensemble Deep Random Vector Functional Link Network for Tabular Data Classification—0
WellFactor: Patient Profiling using Integrative Embedding of Healthcare Data—0
Well-temperate phage: optimal bet-hedging against local environmental collapses—0
We Need to Measure Data Diversity in NLP -- Better and Broader—0
We Need to Talk About Classification Evaluation Metrics in NLP—0
"What are my options?": Explaining RL Agents with Diverse Near-Optimal Alternatives (Extended)—0
What are Public Concerns about ChatGPT? A Novel Self-Supervised Neural Topic Model Tells You—0
What Are We Optimizing For? A Human-centric Evaluation of Deep Learning-based Movie Recommenders—0
What are you optimizing for? Aligning Recommender Systems with Human Values—0
What Large Language Models Do Not Talk About: An Empirical Study of Moderation and Censorship Practices—0
What leads to generalization of object proposals?—0
What Makes for Good Representations for Contrastive Learning—0
What Makes it Ok to Set a Fire? Iterative Self-distillation of Contexts and Rationales for Disambiguating Defeasible Social and Moral Situations—0
What Matters in Learning from Large-Scale Datasets for Robot Manipulation—0
What Matters in LLM-generated Data: Diversity and Its Effect on Model Fine-Tuning—0
"What's in the box?!": Deflecting Adversarial Attacks by Randomly Deploying Adversarially-Disjoint Models—0
What the %PCSA? Addressing Diversity in Lower-Limb Musculoskeletal Models: Age- and Sex-related Differences in PCSA and Muscle Mass—0
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