Alibaba's Qwen releases a two-stage vision-language adaptation model with contrastive learning for Nepali meme classification, achieving 2nd place in hate speech detection and 4th place in sentiment analysis. This model addresses class imbalance and eliminates error propagation from separate OCR and translation pipelines. The approach has significant implications for low-resource South Asian languages.

Alibaba's Qwen team has unveiled a novel Reinforcement Learning (RL) approach, RLVR, designed to significantly enhance data-efficient code-switched Automatic Speech Recognition (ASR). This method uses verifiable rewards and a two-pass refinement process to adapt audio-language models, achieving state-of-the-art performance with just 10% of the data typically required.