This paper studies a category of visual question answering tasks, in whi...
Narrative-driven recommendation (NDR) presents an information access pro...
In this work, we explore a Multilingual Information Retrieval (MLIR) tas...
Dense retrieval models use bi-encoder network architectures for learning...
Developing a universal model that can efficiently and effectively respon...
Knowledge-Intensive Visual Question Answering (KI-VQA) refers to answeri...
This paper highlights the importance of personalization in the current s...
Neural ranking models (NRMs) have demonstrated effective performance in
...
Methods for making high-quality recommendations often rely on learning l...
Domain adaptation aims to transfer the knowledge acquired by models trai...
Retrieval-enhanced language models (LMs), which condition their predicti...
Retrieval-augmented generation models offer many benefits over standalon...
This paper studies multi-task training of retrieval-augmented generation...
Recently, several dense retrieval (DR) models have demonstrated competit...
Asking clarification questions is an active area of research; however,
r...
Although information access systems have long supported people in
accomp...
Recent work has shown that more effective dense retrieval models can be
...
Conversational information seeking (CIS) is concerned with a sequence of...
We present GenEx, a generative model to explain search results to users
...
At the foundation of scientific evaluation is the labor-intensive proces...
Information seeking conversations between users and Conversational Searc...
Podcasts are spoken documents across a wide-range of genres and styles, ...
An emerging recipe for achieving state-of-the-art effectiveness in neura...
In this work, we address multi-modal information needs that contain text...
The Transformer-Kernel (TK) model has demonstrated strong reranking
perf...
Query by Example is a well-known information retrieval task in which a
d...
While current information retrieval systems are effective for known-item...
Users install many apps on their smartphones, raising issues related to
...
We benchmark Conformer-Kernel models under the strict blind evaluation
s...
The Transformer-Kernel (TK) model has demonstrated strong reranking
perf...
Search clarification has recently attracted much attention due to its
ap...
Asking clarifying questions in response to ambiguous or faceted queries ...
Asking clarifying questions in response to search queries has been recog...
Neural networks, particularly Transformer-based architectures, have achi...
This paper discusses the potential for creating academic resources (tool...
Conversational information seeking (CIS) has been recognized as a major
...
Multi-hop question answering (QA) requires an information retrieval (IR)...
Fairness in recommender systems has been considered with respect to sens...
Users often fail to formulate their complex information needs in a singl...
Considering the widespread use of mobile and voice search, answer passag...
The bidirectional encoder representations from transformers (BERT) model...
Ranking models lie at the heart of research on information retrieval (IR...
The ACM Recommender Systems Challenge 2018 focused on the task of automa...
Despite the somewhat different techniques used in developing search engi...
Neural network approaches have recently shown to be effective in several...
With the recent growth of conversational systems and intelligent assista...
Deep neural networks have recently shown promise in the ad-hoc retrieval...
Music recommender systems (MRS) have experienced a boom in recent years,...
Learning a high-dimensional dense representation for vocabulary terms, a...
Despite the impressive improvements achieved by unsupervised deep neural...