Tag
LatentMT applies latent-reasoning looped language models to machine translation, achieving performance comparable to models three to five times larger while requiring lower compute, and sets state-of-the-art on mid- and low-resource languages.
KaLM-Reranker-V1 is a fast reranker that decouples query and passage computation using an encoder-decoder architecture with Matryoshka embedding pooling and cross-attention, achieving state-of-the-art reranking performance on BEIR and competitive results on multilingual benchmarks.