Zobrazeno 1 - 10
of 450
pro vyhledávání: '"Vries, Arjen"'
In question answering (QA), different questions can be effectively addressed with different answering strategies. Some require a simple lookup, while others need complex, multi-step reasoning to be answered adequately. This observation motivates the
Externí odkaz:
http://arxiv.org/abs/2409.13447
Entity linking (EL) in conversations faces notable challenges in practical applications, primarily due to the scarcity of entity-annotated conversational datasets and sparse knowledge bases (KB) containing domain-specific, long-tail entities. We desi
Externí odkaz:
http://arxiv.org/abs/2409.01152
Autor:
Joko, Hideaki, Chatterjee, Shubham, Ramsay, Andrew, de Vries, Arjen P., Dalton, Jeff, Hasibi, Faegheh
The future of conversational agents will provide users with personalized information responses. However, a significant challenge in developing models is the lack of large-scale dialogue datasets that span multiple sessions and reflect real-world user
Externí odkaz:
http://arxiv.org/abs/2405.03480
This paper illustrates some challenges of common ranking evaluation methods for legal information retrieval (IR). We show these challenges with log data from a live legal search system and two user studies. We provide an overview of aspects of legal
Externí odkaz:
http://arxiv.org/abs/2403.18962
MMEAD, or MS MARCO Entity Annotations and Disambiguations, is a resource for entity links for the MS MARCO datasets. We specify a format to store and share links for both document and passage collections of MS MARCO. Following this specification, we
Externí odkaz:
http://arxiv.org/abs/2309.07574
User intent classification is an important task in information retrieval. In this work, we introduce a revised taxonomy of user intent. We take the widely used differentiation between navigational, transactional and informational queries as a startin
Externí odkaz:
http://arxiv.org/abs/2205.00926
Pre-trained language models such as BERT have been a key ingredient to achieve state-of-the-art results on a variety of tasks in natural language processing and, more recently, also in information retrieval.Recent research even claims that BERT is ab
Externí odkaz:
http://arxiv.org/abs/2205.00820
Machine understanding of user utterances in conversational systems is of utmost importance for enabling engaging and meaningful conversations with users. Entity Linking (EL) is one of the means of text understanding, with proven efficacy for various
Externí odkaz:
http://arxiv.org/abs/2105.04903
Autor:
Schoegje, Thomas, Kamphuis, Chris, Dercksen, Koen, Hiemstra, Djoerd, Pieters, Toine, de Vries, Arjen
We explore how to generate effective queries based on search tasks. Our approach has three main steps: 1) identify search tasks based on research goals, 2) manually classify search queries according to those tasks, and 3) compare three methods to imp
Externí odkaz:
http://arxiv.org/abs/2010.12674
Conversational AI systems are being used in personal devices, providing users with highly personalized content. Personalized knowledge graphs (PKGs) are one of the recently proposed methods to store users' information in a structured form and tailor
Externí odkaz:
http://arxiv.org/abs/2010.10409