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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 3101–3125 of 9051 papers

TitleStatusHype
Is Functional Correctness Enough to Evaluate Code Language Models? Exploring Diversity of Generated CodesCode0
Transforming Location Retrieval at Airbnb: A Journey from Heuristics to Reinforcement Learning—0
MergeUp-augmented Semi-Weakly Supervised Learning for WSI Classification—0
Quality or Quantity? On Data Scale and Diversity in Adapting Large Language Models for Low-Resource Translation—0
SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Merging—0
Transformers are Minimax Optimal Nonparametric In-Context Learners—0
Multi-Task Curriculum Graph Contrastive Learning with Clustering Entropy Guidance—0
DLCRec: A Novel Approach for Managing Diversity in LLM-Based Recommender SystemsCode0
MakeupAttack: Feature Space Black-box Backdoor Attack on Face Recognition via Makeup TransferCode0
HiFAKES: High-frequency synthetic appliance signatures generator for non-intrusive load monitoring—0
Disentangled Structural and Featural Representation for Task-Agnostic Graph Valuation—0
LAHAJA: A Robust Multi-accent Benchmark for Evaluating Hindi ASR SystemsCode0
Lookism: The overlooked bias in computer vision—0
Cause-Aware Empathetic Response Generation via Chain-of-Thought Fine-Tuning—0
CARLA Drone: Monocular 3D Object Detection from a Different Perspective—0
SynPlay: Importing Real-world Diversity for a Synthetic Human Dataset—0
Compress Guidance in Conditional Diffusion Sampling—0
Mechanics promotes coherence in heterogeneous active media—0
MAPLE: Enhancing Review Generation with Multi-Aspect Prompt LEarning in Explainable Recommendation—0
Diversity and stylization of the contemporary user-generated visual arts in the complexity-entropy plane—0
GANPrompt: Enhancing Robustness in LLM-Based Recommendations with GAN-Enhanced Diversity Prompts—0
DELIA: Diversity-Enhanced Learning for Instruction Adaptation in Large Language Models—0
Debiased Contrastive Representation Learning for Mitigating Dual Biases in Recommender Systems—0
Generating Automatically Print/Scan Textures for Morphing Attack Detection ApplicationsCode0
AnomalyFactory: Regard Anomaly Generation as Unsupervised Anomaly Localization—0
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