AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
This submission includes a curated corpus of gold-standard alignments for English-Spanish and English-German subtitles, along with their corresponding subtitle files, a novel annotation tool, and the full code to reproduce the method.
Surprisingly, later-stage supervised fine-tuning on short texts further improves alignment quality while retaining the long-context understanding acquired in earlier training, keeping the model robust on long-text word alignment.
CTFAlign is introduced, a lightweight, training-free approach for document-level word alignment that applies a coarse-to-fine refinement strategy that restricts the alignment search space to semantically similar regions and introduces MDPAlign, a simpler alternative that constrains alignments by position with a main di...
The results indicate that a moderately sized, shared self-attention architecture can deliver production-quality multilin-gual translation within the resource constraints of an academic de-ployment, while surfacing clear directions – low-resource language coverage, domain adaptation, and speech-based extension – for con...
Results from automatic and human evaluations show that fine-tuning on IMPaCTS improves performance both in terms of task completion and adherence to the targeted readability levels compared to few-shot baselines.
This paper proposes automated methods to construct high-quality WordNets using large language models (LLMs) to generate missing lemmas to address the synset shortfall in non-English and low-resource languages.
The results suggest that Portuguese-specialized encoder-decoder models are a promising direction for Gloss-to-Text translation in low-resource settings.
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