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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 5176–5200 of 9051 papers

TitleStatusHype
On Conditioning the Input Noise for Controlled Image Generation with Diffusion Models—0
Continual Object Detection via Prototypical Task Correlation Guided Gating MechanismCode1
Quantifying Synthesis and Fusion and their Impact on Machine Translation—0
Towards QD-suite: developing a set of benchmarks for Quality-Diversity algorithms—0
Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation—0
Reconfigurable Heterogeneous Parallel Island Models—0
Power Scaling Law for Optical IRSs and Comparison with Optical Relays—0
Phenomenology and dynamics of competitive ecosystems beyond the niche-neutral regimes—0
On the Diversity and Coded Modulation Design of Fluid Antenna Systems—0
Seed-Guided Topic Discovery with Out-of-Vocabulary SeedsCode1
Go Back in Time: Generating Flashbacks in Stories with Event Temporal PromptsCode0
An Analysis of Generative Methods for Multiple Image Inpainting—0
Diverse Image Captioning with Grounded StyleCode0
Improving In-Context Few-Shot Learning via Self-Supervised Training—0
Semantic Diversity in Dialogue with Natural Language Inference—0
RU-Net: Regularized Unrolling Network for Scene Graph GenerationCode1
Ensemble pruning via an integer programming approach with diversity constraints—0
Statistical Analysis of Received Signal Strength in Industrial IoT Distributed Massive MIMO Systems—0
Studying Retrievability of Publications and Datasets in an Integrated Retrieval System—0
Seeding Diversity into AI Art—0
DMix: Adaptive Distance-aware Interpolative MixupCode0
From text to talk: Harnessing conversational corpora for humane and diversity-aware language technology—0
A Natural Diet: Towards Improving Naturalness of Machine Translation Output—0
LeaningTower@LT-EDI-ACL2022: When Hope and Hate Collide—0
Using NLP to quantify the environmental cost and diversity benefits of in-person NLP conferencesCode0
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