[Answer.AI] Small but Mighty: Introducing answerai-colbert-small
Say hello to answerai-colbert-small-v1, a tiny ColBERT model that punches well above its weight.
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[Answer.AI] JaColBERTv2.5🇯🇵: Optimising Retrieval Training for Lower-Resources Languages
Introducing JaColBERTv2.5🇯🇵, the new best Japanese retrieval model. Through this release, we present a thorough analysis to better understand what helps in training a good multi-vector retrieval model.
[Answer.AI] A little pooling goes a long way for multi-vector representations
Blog post offering a quick overview of ColBERT and how it works, and introducing an efficient pooling trick to alleviate the issues it faces.
Questions & Answer(s): thoughts and joining Answer.AI
If you’re old school, you can find a raw HTML version of this post here This is a fairly long, stream-of-thought post about how I currently (Sunday Feb 4, 2024) feel about the broader ML/NLP/IR ecosystem and its future. Everything here’s on-the-fly opinion and can & will change. In summary: I think ML developments are incredibly exciting, and we need to continue to work on bridging the gap between ML-as-a-commodity-for-ML-practitioners to ML-as-a-commodity-for-everyone....