Zobrazeno 1 - 10
of 17
pro vyhledávání: '"Lajewska, Weronika"'
Autor:
Łajewska, Weronika
While previous conversational information-seeking (CIS) research has focused on passage retrieval, reranking, and query rewriting, the challenge of synthesizing retrieved information into coherent responses remains. The proposed research delves into
Externí odkaz:
http://arxiv.org/abs/2406.19281
The increasing reliance on digital information necessitates advancements in conversational search systems, particularly in terms of information transparency. While prior research in conversational information-seeking has concentrated on improving ret
Externí odkaz:
http://arxiv.org/abs/2405.03303
Autor:
Bernard, Nolwenn, Kostric, Ivica, Łajewska, Weronika, Balog, Krisztian, Galuščáková, Petra, Setty, Vinay, Skjæveland, Martin G.
Personal knowledge graphs (PKGs) offer individuals a way to store and consolidate their fragmented personal data in a central place, improving service personalization while maintaining full user control. Despite their potential, practical PKG impleme
Externí odkaz:
http://arxiv.org/abs/2402.07540
While the body of research directed towards constructing and generating clarifying questions in mixed-initiative conversational search systems is vast, research aimed at processing and comprehending users' answers to such questions is scarce. To this
Externí odkaz:
http://arxiv.org/abs/2401.11463
Autor:
Łajewska, Weronika, Balog, Krisztian
Generative AI models face the challenge of hallucinations that can undermine users' trust in such systems. We approach the problem of conversational information seeking as a two-step process, where relevant passages in a corpus are identified first a
Externí odkaz:
http://arxiv.org/abs/2401.11452
Autor:
Łajewska, Weronika, Balog, Krisztian
Research on conversational search has so far mostly focused on query rewriting and multi-stage passage retrieval. However, synthesizing the top retrieved passages into a complete, relevant, and concise response is still an open challenge. Having snip
Externí odkaz:
http://arxiv.org/abs/2308.08911
Autor:
Skjæveland, Martin G., Balog, Krisztian, Bernard, Nolwenn, Łajewska, Weronika, Linjordet, Trond
Publikováno v:
An Ecosystem for Personal Knowledge Graphs: A Survey and Research Roadmap, M. G. Skj{\ae}veland, K. Balog, N. Bernard, W. {\L}ajewska, and T. Linjordet. In: AI Open, 5:55-69, 2024
This paper presents an ecosystem for personal knowledge graphs (PKGs), commonly defined as resources of structured information about entities related to an individual, their attributes, and the relations between them. PKGs are a key enabler of secure
Externí odkaz:
http://arxiv.org/abs/2304.09572
Autor:
Lajewska, Weronika, Balog, Krisztian
This paper reports on an effort of reproducing the organizers' baseline as well as the top performing participant submission at the 2021 edition of the TREC Conversational Assistance track. TREC systems are commonly regarded as reference points for e
Externí odkaz:
http://arxiv.org/abs/2301.10493
Autor:
Kostric, Ivica, Balog, Krisztian, Aresvik, Tølløv Alexander, Bernard, Nolwenn, Dørheim, Eyvinn Thu, Hantula, Pholit, Havn-Sørensen, Sander, Henriksen, Rune, Hosseini, Hengameh, Khlybova, Ekaterina, Lajewska, Weronika, Mosand, Sindre Ekrheim, Orujova, Narmin
DAGFiNN is a conversational conference assistant that can be made available for a given conference both as a chatbot on the website and as a Furhat robot physically exhibited at the conference venue. Conference participants can interact with the assi
Externí odkaz:
http://arxiv.org/abs/2211.16281
Autor:
Lajewska, Weronika, Wroblewska, Anna
Named entities recognition (NER) and disambiguation (NED) can add semantic context to the recognized named entities in texts. Named entity linkage in texts, regardless of a domain, provides links between the entities mentioned in unstructured texts a
Externí odkaz:
http://arxiv.org/abs/2203.06746