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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 2201–2225 of 9051 papers

TitleStatusHype
FuncGenFoil: Airfoil Generation and Editing Model in Function SpaceCode0
To Bin or not to Bin: Alternative Representations of Mass Spectra—0
VarGes: Improving Variation in Co-Speech 3D Gesture Generation via StyleCLIPSCode0
The Vendiscope: An Algorithmic Microscope For Data Collections—0
Is Depth All You Need? An Exploration of Iterative Reasoning in LLMsCode0
Direct Preference Optimization-Enhanced Multi-Guided Diffusion Model for Traffic Scenario Generation—0
Enhancing Age-Related Robustness in Children Speaker Verification—0
Expert-Agnostic Learning to Defer—0
Diversity Enhances an LLM's Performance in RAG and Long-context Task—0
Inverse problems with experiment-guided AlphaFold—0
When and How Does CLIP Enable Domain and Compositional Generalization?—0
Communication is All You Need: Persuasion Dataset Construction via Multi-LLM Communication—0
Matina: A Large-Scale 73B Token Persian Text Corpus—0
GenIAS: Generator for Instantiating Anomalies in time Series—0
The Paradox of Stochasticity: Limited Creativity and Computational Decoupling in Temperature-Varied LLM Outputs of Structured Fictional Data—0
Faithful, Unfaithful or Ambiguous? Multi-Agent Debate with Initial Stance for Summary EvaluationCode0
RenderBox: Expressive Performance Rendering with Text Control—0
Classifier-Free Guidance: From High-Dimensional Analysis to Generalized Guidance Forms—0
On properties driving diversity index selection—0
Scaling Pre-training to One Hundred Billion Data for Vision Language Models—0
Bridging the Evaluation Gap: Leveraging Large Language Models for Topic Model EvaluationCode0
exHarmony: Authorship and Citations for Benchmarking the Reviewer Assignment ProblemCode0
Unsupervised Translation of Emergent Communication—0
We Can't Understand AI Using our Existing Vocabulary—0
Select before Act: Spatially Decoupled Action Repetition for Continuous Control—0
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