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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 2226–2250 of 9051 papers

TitleStatusHype
Early Stopping Criteria for Training Generative Adversarial Networks in Biomedical Imaging—0
Learning Gaze-aware Compositional GANCode0
Sequence-Augmented SE(3)-Flow Matching For Conditional Protein Backbone GenerationCode3
Robo-Instruct: Simulator-Augmented Instruction Alignment For Finetuning Code LLMs—0
ROAST: Review-level Opinion Aspect Sentiment Target Joint Detection for ABSACode0
Quest: Query-centric Data Synthesis Approach for Long-context Scaling of Large Language ModelCode1
SemFlow: Binding Semantic Segmentation and Image Synthesis via Rectified FlowCode1
PostDoc: Generating Poster from a Long Multimodal Document Using Deep Submodular Optimization—0
Typography Leads Semantic Diversifying: Amplifying Adversarial Transferability across Multimodal Large Language Models—0
Improve Student's Reasoning Generalizability through Cascading Decomposed CoTs DistillationCode1
Adaptive In-conversation Team Building for Language Model AgentsCode7
GIST: Greedy Independent Set Thresholding for Diverse Data Summarization—0
AlchemistCoder: Harmonizing and Eliciting Code Capability by Hindsight Tuning on Multi-source DataCode1
EventZoom: A Progressive Approach to Event-Based Data Augmentation for Enhanced Neuromorphic Vision—0
PathReasoner: Modeling Reasoning Path with Equivalent Extension for Logical Question Answering—0
DiveR-CT: Diversity-enhanced Red Teaming Large Language Model Assistants with Relaxing ConstraintsCode1
Neutral phylogenetic models and their role in tree-based biodiversity measures—0
MM-Mixing: Multi-Modal Mixing Alignment for 3D Understanding—0
Learning diverse attacks on large language models for robust red-teaming and safety tuningCode1
Large Language Models as Partners in Student Essay Evaluation—0
DSDL: Data Set Description Language for Bridging Modalities and Tasks in AI DataCode1
PromptWizard: Task-Aware Prompt Optimization FrameworkCode7
Towards Open Domain Text-Driven Synthesis of Multi-Person Motions—0
Modeling Dynamic Topics in Chain-Free Fashion by Evolution-Tracking Contrastive Learning and Unassociated Word ExclusionCode1
Dataset GrowthCode1
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