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Welcome to Bytez.

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Here's what's trending today

 * MINERS: Multilingual Language Models as Semantic Retrievers
   * The results show that these models perform well, even without fine-tuning.
     The research aims to improve how computers understand and use language in
     various languages.
 * Dynamical Mean-Field Theory of Self-Attention Neural Networks
   * This research paper explores how transformer models work by comparing them
     to Hopfield networks from physics. By using special mathematical
     techniques, the study uncovers different dynamic behaviors in transformers,
     such as memory effects beyond the context window and phase transitions.
 * CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
   * It includes questions in 26 languages from 28 countries, challenging
     current AI models. When tested, most models struggle with questions in
     non-English languages, highlighting the need for more diverse training
     data.

1MINERS: Multilingual Language Models as Semantic Retrievers
2Dynamical Mean-Field Theory of Self-Attention Neural Networks
3CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark

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papers
MINERS: Multilingual Language Models as Semantic Retrievers
vor 2 Tagen·arXiv

Dynamical Mean-Field Theory of Self-Attention Neural Networks
vor 2 Tagen·arXiv

CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark
vor 4 Tagen·arXiv

Contrastive learning of T cell receptor representations
vor 3 Tagen·arXiv

Compute Better Spent: Replacing Dense Layers with Structured Matrices
vor 3 Tagen·arXiv

Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in
State-Of-the-Art Large Language Models
vor 1 Woche·arXiv

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