Using LLMs in Information Retrieval (w/ Ronak Pradeep)

Neural Search Talks — Zeta Alpha

In this episode of Neural Search Talks, we're chatting with Ronak Pradeep, a PhD student from the University of Waterloo, about his experience using LLMs in Information Retrieval, both as a backbone of ranking systems and for their end-to-end evaluation. Ronak analyzes the impact of the advancements in language models on the way we think about IR systems and shares his insights on efficiently integrating them in production pipelines, with techniques such as knowledge distillation. Timestamps: 0:00 Introduction & the impact of the LLM day in SIGIR 2024 2:11 The perspective of the IR community on LLMs 6:10 Language models as backbones for Information Retrieval 13:49 The feasibility & tricks for using LLMs in production IR pipelines 20:11 Ronak's hidden gems from the SIGIR 2024 programme 21:36 Outro