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#Natural Language Inference

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Stanford University

Improving Natural Language Understanding Through Adversarial Testing

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Explore adversarial testing in natural language understanding to challenge and improve AI systems. Learn to identify weaknesses and develop robust models for real-world applications.
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26 Lesons
59 minutes
On-Demand
Free-Video
Institute for Advanced Study

Tradeoffs Between Robustness and Accuracy - Percy Liang

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Explore tradeoffs between robustness and accuracy in machine learning, covering topics like spurious correlations, regularization, and model complexity with Percy Liang.
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21 Lesons
1 hour 3 minutes
On-Demand
Free-Video
Google Cloud Tech

Transformer Models and BERT Model: Overview

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Explore Transformer architecture and BERT model, understanding key components and applications in text classification, question answering, and natural language inference.
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1 Lesons
12 minutes
On-Demand
Free-Video
James Briggs

Today Unsupervised Sentence Transformers, Tomorrow Skynet - How TSDAE Works

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Explore unsupervised fine-tuning for sentence transformers using TSDAE. Learn to train models without labeled data, ideal for domains and languages with limited resources.
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13 Lesons
44 minutes
On-Demand
Free-Video
Center for Language & Speech Processing(CLSP), JHU

Towards Large-Scale Natural Language Inference with Distributional Semantics

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Explore natural language inference using distributional semantics, covering summarization, semantic models, and knowledge induction for advanced text analysis.
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23 Lesons
50 minutes
On-Demand
Free-Video
Discover AI

Knowledge-Adapted Fine-Tuning for Medical Vision Language Models

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Explore how Knowledge-Adapted Fine-Tuning (KnowAda) improves vision-language models in medical AI, reducing hallucinations while maintaining accurate image descriptions and diagnostic capabilities.
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10 Lesons
26 minutes
On-Demand
Free-Video