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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 1901–1950 of 9051 papers

TitleStatusHype
Assessing Social Determinants-Related Performance Bias of Machine Learning Models: A case of Hyperchloremia Prediction in ICU Population—0
Cosmic radiation drives quasi-periodic changes in the diversity of siliceous marine microplankton—0
Deformation Robust Text Spotting with Geometric Prior—0
Cost-Based Budget Active Learning for Deep Learning—0
Cost-Effective Cyber-Physical System Prototype for Precision Agriculture with a Focus on Crop Growth—0
Attribute analysis with synthetic dataset for person re-identification—0
Assessing Social Alignment: Do Personality-Prompted Large Language Models Behave Like Humans?—0
Counterfactual Data Augmentation improves Factuality of Abstractive Summarization—0
Considerations for Ethical Speech Recognition Datasets—0
Detecting patterns of species diversification in the presence of both rate shifts and mass extinctions—0
AI-based Reconstruction for Fast MRI -- A Systematic Review and Meta-analysis—0
Counting and optimising maximum phylogenetic diversity sets—0
DELIA: Diversity-Enhanced Learning for Instruction Adaptation in Large Language Models—0
CourseGPT-zh: an Educational Large Language Model Based on Knowledge Distillation Incorporating Prompt Optimization—0
Conservative Exploration using Interleaving—0
Consecutive Question Generation with Multitask Joint Reranking and Dynamic Rationale Search—0
Covariance Matrix Adaptation MAP-Annealing—0
Assessing Quality-Diversity Neuro-Evolution Algorithms Performance in Hard Exploration Problems—0
Connecting User and Item Perspectives in Popularity Debiasing for Collaborative Recommendation—0
Assessing Intra-class Diversity and Quality of Synthetically Generated Images in a Biomedical and Non-biomedical Setting—0
A Tutorial On Intersectionality in Fair Rankings—0
CPLM, a Parallel Corpus for Mexican Languages: Development and Interface—0
Crafting a Good Prompt or Providing Exemplary Dialogues? A Study of In-Context Learning for Persona-based Dialogue Generation—0
CrashAgent: Crash Scenario Generation via Multi-modal Reasoning—0
CRD-CGAN: Category-Consistent and Relativistic Constraints for Diverse Text-to-Image Generation—0
CREA: A Collaborative Multi-Agent Framework for Creative Content Generation with Diffusion Models—0
Creating a Basic Language Resource Kit for Faroese—0
Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue—0
Creating and Repairing Robot Programs in Open-World Domains—0
Creating Auxiliary Representations from Charge Definitions for Criminal Charge Prediction—0
AI and the EU Digital Markets Act: Addressing the Risks of Bigness in Generative AI—0
Alibaba Submission to the WMT20 Parallel Corpus Filtering Task—0
Creative Preference Optimization—0
Creativity Has Left the Chat: The Price of Debiasing Language Models—0
Active Learning for Point Cloud Semantic Segmentation via Spatial-Structural Diversity Reasoning—0
Deliberate Reasoning for LLMs as Structure-aware Planning with Accurate World Model—0
Conformity bias in the cultural transmission of music sampling traditions—0
Audio-Visual Segmentation via Unlabeled Frame Exploitation—0
Configuring Antenna System to Enhance the Downlink Performance of High Velocity Users in 5G MU-MIMO Networks—0
Cross-Cutting Political Awareness through Diverse News Recommendations—0
Cross-Dataset Generalization in Deep Learning—0
Assessing fish abundance from underwater video using deep neural networks—0
ConfigTron: Tackling network diversity with heterogeneous configurations—0
Cross-domain Adaptation with Discrepancy Minimization for Text-independent Forensic Speaker Verification—0
Assessing Distractors in Multiple-Choice Tests—0
Auditing Source Diversity Bias in Video Search Results Using Virtual Agents—0
A blindspot of AI ethics: anti-fragility in statistical prediction—0
Defining and Counting Phonological Classes in Cross-linguistic Segment Databases—0
AugDiff: Diffusion based Feature Augmentation for Multiple Instance Learning in Whole Slide Image—0
Confidence-Guided Semi-supervised Learning in Land Cover Classification—0
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