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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 5851–5900 of 9051 papers

TitleStatusHype
Towards Iris Presentation Attack Detection with Foundation Models—0
Towards Large-Scale Exploratory Search over Heterogeneous Sources—0
Towards Large-Scale Simulations of Open-Ended Evolution in Continuous Cellular Automata—0
Towards Learned Clauses Database Reduction Strategies Based on Dominance Relationship—0
Towards Leveraging News Media to Support Impact Assessment of AI Technologies—0
Towards Markerless Grasp Capture—0
Towards Multi-Agent Reasoning Systems for Collaborative Expertise Delegation: An Exploratory Design Study—0
Towards Multimodal Response Generation with Exemplar Augmentation and Curriculum Optimization—0
Towards NeuroAI: Introducing Neuronal Diversity into Artificial Neural Networks—0
Towards Open Domain Text-Driven Synthesis of Multi-Person Motions—0
Towards Powerful Graph Neural Networks: Diversity Matters—0
Towards Precision Characterization of Communication Disorders using Models of Perceived Pragmatic Similarity—0
Towards Precision in Bolted Joint Design: A Preliminary Machine Learning-Based Parameter Prediction—0
Towards Pre-training an Effective Respiratory Audio Foundation Model—0
Towards Pretraining Robust ASR Foundation Model with Acoustic-Aware Data Augmentation—0
Towards Psychologically-Grounded Dynamic Preference Models—0
Towards QD-suite: developing a set of benchmarks for Quality-Diversity algorithms—0
Towards Quantifying The Privacy Of Redacted Text—0
Towards Radar Emitter Recognition in Changing Environments with Domain Generalization—0
Towards Realistic Emotional Voice Conversion using Controllable Emotional Intensity—0
Towards Reliable Neural Machine Translation with Consistency-Aware Meta-Learning—0
Generating Teammates for Training Robust Ad Hoc Teamwork Agents via Best-Response Diversity—0
Towards Robust Multimodal Prompting With Missing Modalities—0
Towards Robustness and Diversity: Continual Learning in Dialog Generation with Text-Mixup and Batch Nuclear-Norm Maximization—0
Towards Simple and Accurate Human Pose Estimation with Stair Network—0
Towards social pattern characterization in egocentric photo-streams—0
Towards Standard Criteria for human evaluation of Chatbots: A Survey—0
Towards Summarizing Healthcare Questions in Low-Resource Setting—0
Toward Stable World Models: Measuring and Addressing World Instability in Generative Environments—0
Towards Tailored Recovery of Lexical Diversity in Literary Machine Translation—0
Towards the Synthesis of Non-speech Vocalizations—0
Towards transparency in NLP shared tasks—0
Towards Universal Segmentations: UniSegments 1.0—0
Toward the Next Generation of News Recommender Systems—0
Toward Understanding the Impact of Staleness in Distributed Machine Learning—0
Toward Wireless Localization Using Multiple Reconfigurable Intelligent Surfaces—0
TPLogAD: Unsupervised Log Anomaly Detection Based on Event Templates and Key Parameters—0
TPPoet: Transformer-Based Persian Poem Generation using Minimal Data and Advanced Decoding Techniques—0
Tracking, exploring and analyzing recent developments in German-language online press in the face of the coronavirus crisis: cOWIDplus Analysis and cOWIDplus Viewer—0
Tracking of plus-ends reveals microtubule functional diversity in different cell types—0
Tracking Sports Players with Context-Conditioned Motion Models—0
Tractable Diversity: Scalable Multiperspective Ontology Management via Standpoint EL—0
Tradeoffs in Data Augmentation: An Empirical Study—0
Trading Off Diversity and Quality in Natural Language Generation—0
The Mapillary Traffic Sign Dataset for Detection and Classification on a Global Scale—0
A systematic approach to random data augmentation on graph neural networks—0
Training and Inference Methods for High-Coverage Neural Machine Translation—0
Training Diffusion Models Towards Diverse Image Generation with Reinforcement Learning—0
Training Diverse High-Dimensional Controllers by Scaling Covariance Matrix Adaptation MAP-Annealing—0
Training Group Orthogonal Neural Networks with Privileged Information—0
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