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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 7626–7650 of 9051 papers

TitleStatusHype
Parallel Structures in Pre-training Data Yield In-Context LearningCode0
Bipartite Graph Diffusion Model for Human Interaction GenerationCode0
Tackling Neural Architecture Search With Quality Diversity OptimizationCode0
Bioplastic Design using Multitask Deep Neural NetworksCode0
Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequencesCode0
In-distribution Public Data Synthesis with Diffusion Models for Differentially Private Image ClassificationCode0
BIISQ: Bayesian nonparametric discovery of Isoforms and Individual Specific QuantificationCode0
KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text GenerationCode0
Sebastian, Basti, Wastl?! Recognizing Named Entities in Bavarian Dialectal DataCode0
Indiscapes: Instance Segmentation Networks for Layout Parsing of Historical Indic ManuscriptsCode0
Paraphrase Detection: Human vs. Machine ContentCode0
Enhancing Diversity in Bayesian Deep Learning via Hyperspherical Energy Minimization of CKACode0
IndicEval-XL: Bridging Linguistic Diversity in Code Generation Across Indic LanguagesCode0
Finding Black Cat in a Coal Cellar -- Keyphrase Extraction & Keyphrase-Rubric Relationship Classification from Complex AssignmentsCode0
Indian Regional Movie Dataset for Recommender SystemsCode0
Custom Dual Transportation Mode Detection by Smartphone Devices Exploiting Sensor DiversityCode0
Paraphrase Types Elicit Prompt Engineering CapabilitiesCode0
Enhancing BERTopic with Intermediate Layer RepresentationsCode0
Incubating Text Classifiers Following User Instruction with Nothing but LLMCode0
Enhancing Assamese NLP Capabilities: Introducing a Centralized Dataset RepositoryCode0
Kinematic analysis of structural mechanics based on convolutional neural networkCode0
KL-Divergence Guided Temperature SamplingCode0
Increasing Entropy to Boost Policy Gradient Performance on Personalization TasksCode0
Using NLP to quantify the environmental cost and diversity benefits of in-person NLP conferencesCode0
BiERL: A Meta Evolutionary Reinforcement Learning Framework via Bilevel OptimizationCode0
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