Search papers, labs, and topics across Lattice.
3
0
6
Contemporary frontier speech models still catastrophically fail on living Arabic dialects, with top systems like GPT-4o achieving an error rate no better than 35.0% WER across 17 regional vernaculars.
State-of-the-art Vision-Language Models may excel in understanding but falter dramatically in creative tasks and factual recall, revealing hidden cognitive weaknesses.
Resource-constrained Arabic AI development can compete with systems built at far greater scale, as demonstrated by Fanar 2.0's performance gains using 8x fewer pre-training tokens than its predecessor.
