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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 1526–1550 of 9051 papers

TitleStatusHype
Leveraging Long-Context Large Language Models for Multi-Document Understanding and Summarization in Enterprise Applications—0
Flat'n'Fold: A Diverse Multi-Modal Dataset for Garment Perception and Manipulation—0
Enriched Functional Tree-Based Classifiers: A Novel Approach Leveraging Derivatives and Geometric Features—0
Diversity-Driven Synthesis: Enhancing Dataset Distillation through Directed Weight AdjustmentCode0
ID^3: Identity-Preserving-yet-Diversified Diffusion Models for Synthetic Face Recognition—0
Text Image Generation for Low-Resource Languages with Dual Translation Learning—0
EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generation—0
Open-World Evaluation for Retrieving Diverse Perspectives—0
The Impact of Designated Market Makers on Market Liquidity and Competition: A Simulation Approach—0
Results of the Big ANN: NeurIPS'23 competitionCode3
A Character-Centric Creative Story Generation via Imagination—0
Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions—0
DALDA: Data Augmentation Leveraging Diffusion Model and LLM with Adaptive Guidance ScalingCode1
Harnessing Diversity for Important Data Selection in Pretraining Large Language Models—0
Holistic Automated Red Teaming for Large Language Models through Top-Down Test Case Generation and Multi-turn InteractionCode1
Qualitative Insights Tool (QualIT): LLM Enhanced Topic Modeling—0
Long-horizon Embodied Planning with Implicit Logical Inference and Hallucination Mitigation—0
Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary SegmentationCode2
Automated test generation to evaluate tool-augmented LLMs as conversational AI agents—0
The Impact of Generative Artificial Intelligence on Ideation and the performance of Innovation Teams (Preprint)—0
LDPC Codes in Cooperative Communication—0
MODEL&CO: Exoplanet detection in angular differential imaging by learning across multiple observations—0
Style Outweighs Substance: Failure Modes of LLM Judges in Alignment BenchmarkingCode0
Research on Dynamic Data Flow Anomaly Detection based on Machine Learning—0
Orthogonal Finetuning for Direct Preference Optimization—0
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