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Multi-source AI news clustered, deduplicated, and scored 0–100 across authority, cluster strength, headline signal, and time decay.

TOOL · Medium — fine-tuning tag English(EN) · 3d

How I Trained a Kannada-First 4B Language Model Using Gemma 3

An individual has fine-tuned Google's Gemma 3 model to create a 4-billion parameter language model specifically for the Kannada language. This effort aims to bridge the gap in large language model capabilities for Indian languages. The process involved adapting the existing Gemma 3 model to better understand and generate Kannada text. AI

IMPACT Enhances LLM capabilities for regional Indian languages, potentially improving accessibility and utility.
- Kannada
- Google
- Gemma 3
RESEARCH · arXiv cs.AI English(EN) · 1w · [2 sources]

SCRIBE: Diagnostic Evaluation and Rich Transcription Models for Indic ASR

Researchers have introduced SCRIBE, a new diagnostic framework designed to improve automatic speech recognition (ASR) for Indic languages. Unlike traditional metrics like Word Error Rate (WER), SCRIBE categorizes errors into lexical, punctuation, numeral, and domain-entity types, offering a more nuanced evaluation. The framework also incorporates sandhi-tolerant alignment and domain vocabulary injection to better handle agglutinative languages. Alongside SCRIBE, the team has released LLM curation pipelines, benchmarks, and open-weight rich transcription models for Hindi, Malayalam, and Kannada. AI

IMPACT Enhances ASR accuracy for under-resourced Indic languages, potentially improving accessibility and usability.