Despite the remarkable ability of large language models (LMs) to compreh...
While dense retrieval has been shown effective and efficient across task...
Systems for knowledge-intensive tasks such as open-domain question answe...
ClueWeb22, the newest iteration of the ClueWeb line of datasets, provide...
Large language models (LLMs) have recently demonstrated an impressive ab...
Long document re-ranking has been a challenging problem for neural re-ra...
Recent rapid advancements in deep pre-trained language models and the
in...
Dense retrieval systems conduct first-stage retrieval using embedded
rep...
Recent research demonstrates the effectiveness of using fine-tuned langu...
Pre-trained language models (LM) have become go-to text representation
e...
Classical information retrieval systems such as BM25 rely on exact lexic...
Pre-trained deep language models (LM) have advanced the state-of-the-art...
Our work aimed at experimentally assessing the benefits of model ensembl...
Most research on pseudo relevance feedback (PRF) has been done in vector...
Category systems are central components of knowledge bases, as they prov...
Deep language models such as BERT pre-trained on large corpus have given...
Tabular data provide answers to a significant portion of search queries....
Information retrieval traditionally has relied on lexical matching signa...
Recent innovations in Transformer-based ranking models have advanced the...
The Conversational Assistance Track (CAsT) is a new track for TREC 2019 ...
Term frequency is a common method for identifying the importance of a te...
Neural networks provide new possibilities to automatically learn complex...
Newsworthy events are broadcast through multiple mediums and prompt the
...
In microblog retrieval, query expansion can be essential to obtain good
...
Text mining and analytics software has become popular, but little attent...
This paper studies the consistency of the kernel-based neural ranking mo...
This paper presents a Kernel Entity Salience Model (KESM) that improves ...
Existing techniques for efficiently crawling social media sites rely on ...
This paper presents a word-entity duet framework for utilizing knowledge...
This paper proposes K-NRM, a kernel based neural model for document rank...