241 citations · 686 across the 25 of their papers we have counts for
5 papers · 1 filter
Language Models As or For Knowledge Bases
Simon Razniewski, Andrew Yates, Nora Kassner +1
Pre-trained language models (LMs) have recently gained attention for their potential as an alternative to (or proxy for) explicit knowledge bases (KBs). In this position paper, we…
You Get What You Chat: Using Conversations to Personalize Search-based Recommendations
Ghazaleh Haratinezhad Torbati, Andrew Yates, Gerhard Weikum
Prior work on personalized recommendations has focused on exploiting explicit signals from user-specific queries, clicks, likes, and ratings. This paper investigates tapping into a…
Personalized Entity Search by Sparse and Scrutable User Profiles
Ghazaleh Haratinezhad Torbati, Andrew Yates, Gerhard Weikum
Prior work on personalizing web search results has focused on considering query-and-click logs to capture users individual interests. For product search, extensive user histories a…
How Deep is your Learning: the DL-HARD Annotated Deep Learning Dataset
Iain Mackie, Jeffery Dalton, Andrew Yates
Deep Learning Hard (DL-HARD) is a new annotated dataset designed to more effectively evaluate neural ranking models on complex topics. It builds on TREC Deep Learning (DL) topics b…
Simplified Data Wrangling with ir_datasets
Sean MacAvaney, Andrew Yates, Sergey Feldman +3
Managing the data for Information Retrieval (IR) experiments can be challenging. Dataset documentation is scattered across the Internet and once one obtains a copy of the data, the…