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#Fine-tuning — 2 articles ✕

Voice AI· Important· 🧪 Worth Testing

NVIDIA Publishes Fine-Tuning Recipe for Dialect-Specific Speech Recognition with Nemotron

NVIDIA released a detailed workflow for fine-tuning its Nemotron 3.5 ASR multilingual streaming model on Saudi Arabic dialects (Najdi and Hijazi). Using minimal data curation, replay mixing with FLEURS data, duration-based bucketing, and partial encoder unfreezing, they reduced word error rate on the target dialects from 55.05% to 29.96% while also slightly improving English and other Arabic performance. The post also covers decoding tweaks and speaker diarization extensions for multi-speaker transcription.

NVIDIA Developer
Models

Ai2 Open-Sources AstaBrief, a Fast 8B Model for Scientific Report Generation

Allen Institute for AI (Ai2) has open-sourced AstaBrief 8B, a model built on Qwen3-8B that turns research questions and retrieved literature excerpts into cited scientific reports. It's now live in Ai2's Asta platform as a 'Fast mode' alongside a Claude-powered 'Thinking mode', generating reports in about 51.1 seconds on average compared to 178.5 seconds for the Claude pipeline — roughly 3.5x faster. Ai2 trained the model using supervised fine-tuning on 47K examples (from 90K filtered real research queries) followed by DPO on about 6K preference pairs, and found that filtering training data for citation density was the single most effective lever for improving grounding quality.

Hugging Face