Federated search techniques: an overview of the trends and state of the art

TL;DR: This collection fosters and supports the development and evaluation of new federated search methods, especially in the context of RAG pipelines, by comparing answers generated through the RAG pipeline through a qualitative side-by-side comparison.

TL;DR: A Cutting Plane Algorithm for training linear SVMs that provably has training time 0(s,n) for classification problems and o(sn log (n)) for ordinal regression problems and several orders of magnitude faster than decomposition methods like svm light for large datasets.

TL;DR: The experimental results show that metasearch algorithms based on the Borda and Bayesian models usually outperform the best input system and are competitive with, and often outperform, existing metAsearch strategies.

TL;DR: BrightPlanet's search technology automates the process of making dozens of direct queries simultaneously using multiple-thread technology and thus is the only search technology, so far, that is capable of identifying, retrieving, qualifying, classifying, and organizing both "deep" and "surface" content.

TL;DR: This work presents a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, and shows how to find the optimal linear combination for any two rankers, and uses this method to solve the line search problem exactly during boosting.