Middle training methods aim to bridge the gap between the Masked Languag...
The MS MARCO-passage dataset has been the main large-scale dataset open ...
Sparse neural retrievers, such as DeepImpact, uniCOIL and SPLADE, have b...
This paper presents the AToMiC (Authoring Tools for Multimedia Content)
...
Parameter-Efficient transfer learning with Adapters have been studied in...
This paper describes our participation in the 2022 TREC NeuCLIR challeng...
This paper describes our participation to the 2022 TREC Deep Learning
ch...
Evaluation in Information Retrieval relies on post-hoc empirical procedu...
Neural retrieval models have acquired significant effectiveness gains ov...
Finetuning Pretrained Language Models (PLM) for IR has been de facto the...
Latency and efficiency issues are often overlooked when evaluating IR mo...
Neural retrievers based on dense representations combined with Approxima...
Recent IR approaches based on Pretrained Language Models (PLM) have now
...
We propose a Composite Code Sparse Autoencoder (CCSA) approach for
Appro...
Learning with noisy labels is an active research area for image
classifi...
The ColBERT model has recently been proposed as an effective BERT based
...
Neural Information Retrieval models hold the promise to replace lexical
...
In neural Information Retrieval (IR), ongoing research is directed towar...
Multilingual NMT has become an attractive solution for MT deployment in
...
Attacking Neural Machine Translation models is an inherently combinatori...
In neural Information Retrieval, ongoing research is directed towards
im...
Transformer-based models are nowadays state-of-the-art in ad-hoc Informa...
Exploiting large pretrained models for various NMT tasks have gained a l...
We present in this paper experiments on Table Recognition in hand-writte...