Tag: transformer models

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Sequential KV Cache Compression Beyond Shannon Limit

Discover advanced sequential KV cache compression using probabilistic tries, surpassing the per-vector Shannon limit for transformer models.

Zero-Shot Learning for Sentiment Analysis in Software Engineering

Explore how zero-shot learning tackles sentiment analysis challenges in software engineering without relying on annotated datasets.

Unified Conditional Flow for AI Motion Generation & Editing

Explore a unified conditional flow framework for AI-driven motion generation, editing, and intra-structural retargeting with improved accuracy and consiste...

Quantifying Numerical Instability in Large Language Models

Explore how numerical instability causes unpredictability in large language models and learn methods to improve their reliability and performance.

Principled Inductive Bias for Advanced Document Recognition

Enhance document recognition with structure-specific inductive biases and transformer models for complex documents like engineering drawings and sheet musi...

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