[Curator's note: there are numerous other technical challenges addressed with alternative prescriptions throughout the paper. These highlights are narrative-centric, and I invite you to review the paper if you are a keen technologist looking for answers to the following:- Zero- and Few-Shot Learning - Response Generation- Arith... See more
This represents a fundamentally different way of thinking about IR systems. Within the index-retrieve-then-rank paradigm, modeling work (e.g., query understanding, document understanding, retrieval, ranking, etc.) is done on top of the index itself. This results in modern IR systems being comprised of a disparate mix of heterogeneous models (e.g., ... See more
We envision using the same corpus model as a multi-task learner for multiple IR tasks. To this end, once a corpus model has been trained, it can of course be used for the most classical of all IR tasks – document retrieval. However, by leveraging recent advances in multi-task learning, such a model can very likely be applied to a diverse range of t... See more
Pre-trained language models (LM), by contrast, are capable of directly generating prose that may be responsive to an information need, but at present they are *dilettantes* rather than domain experts – they do not have a true understanding of the world, they are prone to hallucinating, and crucially they are incapable of justifying their utterances... See more
When experiencing an information need, users want to engage with a domain expert, but often turn to an information retrieval (IR) system, such as a search engine, instead. Classical information retrieval systems do not answer information needs directly, but instead provide references to (hopefully authoritative) answers.
- The problem is one of content. The misconception is that without deep content, design is reduced to pure style, a bag of dubious tricks. In graphic-design circles, form-follows-function is reconfigured as form-follows-content. If content is the source of form, always preceding it and imbuing it with meaning, form without content (as if that were ... See more