Search Results for author:
Found 13 papers, 7 papers with code
Weakly-supervised Contextualization of Knowledge Graph Facts
KG fact contextualization is the task of augmenting a given KG fact with additional and useful KG facts.
Query Resolution for Conversational Search with Limited Supervision
Context from the conversational history can be used to arrive at a better expression of the current turn query, defined as the task of query resolution.
Knowledge Graph Simple Question Answering for Unseen Domains
Knowledge graph simple question answering (KGSQA), in its standard form, does not take into account that human-curated question answering training data only cover a small subset of the relations that exist in a Knowledge Graph (KG), or even worse, that new domains covering unseen and rather different to existing domains relations are added to the KG.
A Comparison of Supervised Learning to Match Methods for Product Search
As recent learning to match methods have made important advances in bridging the vocabulary gap for these traditional IR areas, we investigate their potential in the context of product search.
Analysing the Effect of Clarifying Questions on Document Ranking in Conversational Search
Recent research on conversational search highlights the importance of mixed-initiative in conversations.
A Comparison of Question Rewriting Methods for Conversational Passage Retrieval
Conversational passage retrieval relies on question rewriting to modify the original question so that it no longer depends on the conversation history.
MICROS: Mixed-Initiative ConveRsatiOnal Systems Workshop
The 1st edition of the workshop on Mixed-Initiative ConveRsatiOnal Systems (MICROS@ECIR2021) aims at investigating and collecting novel ideas and contributions in the field of conversational systems.
Supporting search engines with knowledge and context
In the final part of this thesis, we focus on search engine support for professional writers in the news domain.
Leveraging Query Resolution and Reading Comprehension for Conversational Passage Retrieval
This paper describes the participation of UvA. ILPS group at the TREC CAsT 2020 track.
Combining Lexical and Dense Retrieval for Computationally Efficient Multi-hop Question Answering
In simple open-domain question answering (QA), dense retrieval has become one of the standard approaches for retrieving the relevant passages to infer an answer.
Multi-hop Question Answering
Open-Domain Question Answering
+2
News Article Retrieval in Context for Event-centric Narrative Creation
Given an incomplete narrative that specifies a main event and a context, we aim to retrieve news articles that discuss relevant events that would enable the continuation of the narrative.
Performance-Efficiency Trade-Offs in Adapting Language Models to Text Classification Tasks
Interestingly, we find that prompting combined with KD can reduce compute and data cost at the same time.
