15 citations · 43 across the 7 of their papers we have counts for
7 papers
The Role of Complex NLP in Transformers for Text Ranking?
David Rau, Jaap Kamps
Even though term-based methods such as BM25 provide strong baselines in ranking, under certain conditions they are dominated by large pre-trained masked language models (MLMs) such…
How Different are Pre-trained Transformers for Text Ranking?
David Rau, Jaap Kamps
In recent years, large pre-trained transformers have led to substantial gains in performance over traditional retrieval models and feedback approaches. However, these results are p…
Words are Malleable: Computing Semantic Shifts in Political and Media Discourse
Hosein Azarbonyad, Mostafa Dehghani, Kaspar Beelen +3
Recently, researchers started to pay attention to the detection of temporal shifts in the meaning of words. However, most (if not all) of these approaches restricted their efforts…
Hierarchical Re-estimation of Topic Models for Measuring Topical Diversity
Hosein Azarbonyad, Mostafa Dehghani, Tom Kenter +3
A high degree of topical diversity is often considered to be an important characteristic of interesting text documents. A recent proposal for measuring topical diversity identifies…
Generalized Group Profiling for Content Customization
Mostafa Dehghani, Hosein Azarbonyad, Jaap Kamps +1
There is an ongoing debate on personalization, adapting results to the unique user exploiting a user's personal history, versus customization, adapting results to a group profile s…
Topical Generalization for Presentation of User Profiles
Alex Olieman, Jaap Kamps, Gleb Satyukov +1
Fine-grained user profile generation approaches have made it increasingly feasible to display on a profile page in which topics a user has expertise or interest. Earlier work on to…