We present a study of Tip-of-the-tongue (ToT) retrieval for music, where...
The creation of relevance assessments by human assessors (often nowadays...
When asked, current large language models (LLMs) like ChatGPT claim that...
A number of learned sparse and dense retrieval approaches have recently ...
The Search Engine Results Page (SERP) has evolved significantly over the...
When training neural rankers using Large Language Models, it's expected ...
Ranking responses for a given dialogue context is a popular benchmark in...
Complex search tasks - such as those from the Search as Learning (SAL) d...
Word embeddings, made widely popular in 2013 with the release of word2ve...
Search engines are considered the primary tool to assist and empower lea...
Heavily pre-trained transformers for language modelling, such as BERT, h...
According to the Probability Ranking Principle (PRP), ranking documents ...
We study Label Smoothing (LS), a widely used regularization technique, i...
Understanding when and why neural ranking models fail for an IR task via...
Heavily pre-trained transformer models such as BERT have recently shown ...
Neural ranking models are traditionally trained on a series of random
ba...
Conversational search is an approach to information retrieval (IR), wher...
With the growing popularity of Social Web applications, more and more us...