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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 7901–7950 of 9051 papers

TitleStatusHype
Cultural Evaluations of Vision-Language Models Have a Lot to Learn from Cultural Theory—0
Subset Selection for Fine-Tuning: A Utility-Diversity Balanced Approach for Mathematical Domain Adaptation—0
Cultural Incongruencies in Artificial Intelligence—0
Subspace Representation Learning for Few-shot Image Classification—0
CURAJ_IIITDWD@LT-EDI-ACL 2022: Hope Speech Detection in English YouTube Comments using Deep Learning Techniques—0
Curating Grounded Synthetic Data with Global Perspectives for Equitable AI—0
Curatr: A Platform for Semantic Analysis and Curation of Historical Literary Texts—0
Subword Regularization: An Analysis of Scalability and Generalization for End-to-End Automatic Speech Recognition—0
Curiosity creates Diversity in Policy Search—0
Visual Place Recognition for Large-Scale UAV Applications—0
Cost-Based Budget Active Learning for Deep Learning—0
Suction Grasp Region Prediction using Self-supervised Learning for Object Picking in Dense Clutter—0
Sudden Death: A New Way to Compare Recommendation Diversification—0
Current and future directions in network biology—0
Current State-of-the-Art of Bias Detection and Mitigation in Machine Translation for African and European Languages: a Review—0
Current Status and Performance Analysis of Table Recognition in Document Images with Deep Neural Networks—0
COSMOS: Experimental and Comparative Studies of Concept Representations in Schoolchildren—0
Curriculum Learning with Diversity for Supervised Computer Vision Tasks—0
Curse of "Low" Dimensionality in Recommender Systems—0
Cosmic radiation drives quasi-periodic changes in the diversity of siliceous marine microplankton—0
HelpSteer3-Preference: Open Human-Annotated Preference Data across Diverse Tasks and Languages—0
Customized Image Narrative Generation via Interactive Visual Question Generation and Answering—0
Customized Video QoE Estimation with Algorithm-Agnostic Transfer Learning—0
Customizing an Adversarial Example Generator with Class-Conditional GANs—0
CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark—0
Cycle3D: High-quality and Consistent Image-to-3D Generation via Generation-Reconstruction Cycle—0
Cycle-Consistent Inverse GAN for Text-to-Image Synthesis—0
Cyclic Delay-Doppler Shift: A Simple Transmit Diversity Technique for Delay-Doppler Waveforms in Doubly Selective Channels—0
Summarization Evaluation in the Absence of Human Model Summaries Using the Compositionality of Word Embeddings—0
Cyclic Prefix (CP) Jamming Against Eavesdropping Relays in OFDM Systems—0
Cytology Image Analysis Techniques Towards Automation: Systematically Revisited—0
D2AF: A Dual-Driven Annotation and Filtering Framework for Visual Grounding—0
D^2-City: A Large-Scale Dashcam Video Dataset of Diverse Traffic Scenarios—0
Cosine Similarity of Multimodal Content Vectors for TV Programmes—0
D2RLIR : an improved and diversified ranking function in interactive recommendation systems based on deep reinforcement learning—0
Adversarial Training: embedding adversarial perturbations into the parameter space of a neural network to build a robust system—0
D3: Diversity, Difficulty, and Dependability-Aware Data Selection for Sample-Efficient LLM Instruction Tuning—0
D4: Text-guided diffusion model-based domain adaptive data augmentation for vineyard shoot detection—0
DAAI at CASE 2021 Task 1: Transformer-based Multilingual Socio-political and Crisis Event Detection—0
CorrSynth -- A Correlated Sampling Method for Diverse Dataset Generation from LLMs—0
DACSR: Decoupled-Aggregated End-to-End Calibrated Sequential Recommendation—0
Correlated Errors in Large Language Models—0
DAEBAK!: Peripheral Diversity for Multilingual Word Sense Disambiguation—0
DAFA: Diversity-Aware Feature Aggregation for Attention-Based Video Object Detection—0
Corpus Development of Kiswahili Speech Recognition Test and Evaluation sets, Preemptively Mitigating Demographic Bias Through Collaboration with Linguists—0
Corpus COFLA: A research corpus for the Computational study of Flamenco Music—0
DAL: Dual Adversarial Learning for Dialogue Generation—0
Daleel: Simplifying Cloud Instance Selection Using Machine Learning—0
Corpus-based Content Construction—0
SummScore: A Comprehensive Evaluation Metric for Summary Quality Based on Cross-Encoder—0
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