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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 4776–4800 of 9051 papers

TitleStatusHype
Promoting the linguistic diversity of TEI in the Maghreb and the Arab region—0
Prompt as Free Lunch: Enhancing Diversity in Source-Free Cross-domain Few-shot Learning through Semantic-Guided Prompting—0
PromptEVC: Controllable Emotional Voice Conversion with Natural Language Prompts—0
Prompting a Large Language Model to Generate Diverse Motivational Messages: A Comparison with Human-Written Messages—0
Prompting and Fine-Tuning of Small LLMs for Length-Controllable Telephone Call Summarization—0
Prompting Audios Using Acoustic Properties For Emotion Representation—0
Prompting Diverse Ideas: Increasing AI Idea Variance—0
Prompting for a conversation: How to control a dialog model?—0
Prompting Towards Alleviating Code-Switched Data Scarcity in Under-Resourced Languages with GPT as a Pivot—0
PromptRefine: Enhancing Few-Shot Performance on Low-Resource Indic Languages with Example Selection from Related Example Banks—0
Prompt Selection and Augmentation for Few Examples Code Generation in Large Language Model and its Application in Robotics Control—0
Proof of Efficient Liquidity: A Staking Mechanism for Capital Efficient Liquidity—0
Proportional Allocation: Simple, Distributed, and Diverse Matching with High Entropy—0
Proportional Selection in Networks—0
Prosody-controllable spontaneous TTS with neural HMMs—0
ProTA: Probabilistic Token Aggregation for Text-Video Retrieval—0
Protected group bias and stereotypes in Large Language Models—0
Protein residue networks from a local search perspective—0
ProteinZero: Self-Improving Protein Generation via Online Reinforcement Learning—0
Prototype Discovery using Quality-Diversity—0
Prototype Fission: Closing Set for Robust Open-set Semi-supervised Learning—0
Provable Hierarchy-Based Meta-Reinforcement Learning—0
Provably Neural Active Learning Succeeds via Prioritizing Perplexing Samples—0
Provenance-Based Assessment of Plans in Context—0
Provenance-Based Interpretation of Multi-Agent Information Analysis—0
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