AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces Santham, a curated Sanskrit-Tamil parallel dataset comprising over 90,000 pairs drawn from classical texts such as the Mahābhārata, Rāmāyaṇa, and Bhagavad Gīta, and utilizes anvaya (prose-order reordering) to mitigate the structural complexity of poetic verses.
SurakshaEval is introduced, a novel safety benchmark composed of human-written prompts spanning real-world scenarios, explicitly designed for ten major Indian languages - Assamese, Bengali, Gujarati, Hindi, Kannada, Malayalam, Marathi, Punjabi, Tamil, and Telugu - along with English.
This work analyzes what tokens are learned when tokenization is jointly optimized with language modeling, and finds tokenizer-free approaches optimize for contextual and computational efficiency rather than strict morphological structure, resulting in fundamentally different yet effective vocabularies for downstream NL...
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