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Join me for my presentations at #SIGIR2024 M3.1 RAG session July 15 4pm 1. Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models 2. Optimization Methods for Personalizing Large Language Models through Retrieval Augmentation

(1/9) 🧠 Ever wondered if there's a unified framework for RAG? We've formalized the retrieval enhancement paradigm with consistent notations, synthesizing research across all ML domains. 🧵👇 w/ Alireza Salemi Andrew Drozdov Fernando Diaz Hamed Zamani arxiv.org/abs/2407.12982

🚨New Paper Alert🚨 Despite the long line of research in search and open-domain QA, it still feels like early days for RAG. In this paper we talk about the design patterns that are starting to emerge and future research opportunities for this space.

📢Happy to announce our tutorial acceptance at #SIGIRAP2024. We’ll be diving deep into "Retrieval-Enhanced Machine Learning" using our recent survey as core material. W/ Alireza Salemi Andrew Drozdov Fernando Diaz Hamed Zamani See you in Tokyo!! SIGIR-AP 2025 #SIGIR

Today we'll be presenting the Tutorial on Retrieval-Enhanced Machine Learning (REML). Come by to learn about the emerging design patterns in this space and see how retrieval can be used beyond RAG. In collaboration w/ the amazing Fernando Diaz Danny To Eun Kim (✈️SIGIR🇮🇹) Alireza Salemi Hamed Zamani

Do you want a way to evaluate both factuality and topical coverage in LLMs? 📢 Excited to share our new paper: "Beyond Factual Accuracy: Evaluating Coverage of Diverse Factual Information in Long-form Text Generation" Introducing ICAT - a new interpretable evaluation framework!

Generating accurate and factual (long-firm) responses has been a very active research area. But do you want to see if your LLM also generates *complete* responses? Read the ICAT paper! An easy-to-use python library will be released soon.

🇮🇹 We're presenting a tutorial on Retrieval-Enhanced Machine Learning (#REML) at #SIGIR2025! 🗓️Sunday July 13th | 9AM - 12:30PM 📌Donatello Floor 0 Details: retrieval-enhanced-ml.github.io/sigir-2025.html Fernando Diaz Andrew Drozdov Alireza Salemi Hamed Zamani SIGIR 2025