SOTAVerified

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 4901–4925 of 9051 papers

TitleStatusHype
Recent Advances in Diversified Recommendation—0
Recent advances in text embedding: A Comprehensive Review of Top-Performing Methods on the MTEB Benchmark—0
Channel State Acquisition in Uplink NOMA for Cellular-Connected UAV: Exploitation of Doppler and Modulation Diversities—0
Recognising the importance of preference change: A call for a coordinated multidisciplinary research effort in the age of AI—0
Recognition-Guided Diffusion Model for Scene Text Image Super-Resolution—0
Recognition of non-domain phrases in automatically extracted lists of terms—0
Recognizing long-form speech using streaming end-to-end models—0
Recommendation Systems with Distribution-Free Reliability Guarantees—0
Recommenders with a mission: assessing diversity in newsrecommendations—0
Recommending Accurate and Diverse Items Using Bilateral Branch Network—0
Recommending on graphs: a comprehensive review from a data perspective—0
Reconciling Semantic Controllability and Diversity for Remote Sensing Image Synthesis with Hybrid Semantic Embedding—0
Reconciling the accuracy-diversity trade-off in recommendations—0
Reconfigurable Heterogeneous Parallel Island Models—0
Reconfigurable Holographic Surface-aided Distributed MIMO Radar Systems—0
Reconfigurable Holographic Surface: A New Paradigm to Implement Holographic Radio—0
Reconfigurable Intelligent Surface-Aided Grant-Free Access for Uplink URLLC—0
Reconfigurable Intelligent Surface Aided NOMA Networks—0
Reconfigurable Intelligent Surface-assisted Networks: Phase Alignment Categories—0
Reconfigurable Intelligent Surfaces and Machine Learning for Wireless Fingerprinting Localization—0
Reconstructing Objects in-the-wild for Realistic Sensor Simulation—0
Reconstructing seen images from human brain activity via guided stochastic search—0
Reconstructing Word Embeddings via Scattered k-Sub-Embedding—0
RECOST: External Knowledge Guided Data-efficient Instruction Tuning—0
Recoverability of Ancestral Recombination Graph Topologies—0
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