8 citations · 49 across the 40 of their papers we have counts for
7 papers · 1 filter
Numerical reasoning in machine reading comprehension tasks: are we there yet?
Hadeel Al-Negheimish, Pranava Madhyastha, Alessandra Russo
Numerical reasoning based machine reading comprehension is a task that involves reading comprehension along with using arithmetic operations such as addition, subtraction, sorting,…
BERTGEN: Multi-task Generation through BERT
Faidon Mitzalis, Ozan Caglayan, Pranava Madhyastha +1
We present BERTGEN, a novel generative, decoder-only model which extends BERT by fusing multimodal and multilingual pretrained models VL-BERT and M-BERT, respectively. BERTGEN is a…
A call for better unit testing for invariant risk minimisation
Chunyang Xiao, Pranava Madhyastha
In this paper we present a controlled study on the linearized IRM framework (IRMv1) introduced in Arjovsky et al. (2020). We show that IRMv1 (and its variants) framework can be pot…
Discrete Reasoning Templates for Natural Language Understanding
Hadeel Al-Negheimish, Pranava Madhyastha, Alessandra Russo
Reasoning about information from multiple parts of a passage to derive an answer is an open challenge for reading-comprehension models. In this paper, we present an approach that r…
MultiSubs: A Large-scale Multimodal and Multilingual Dataset
Josiah Wang, Pranava Madhyastha, Josiel Figueiredo +2
This paper introduces a large-scale multimodal and multilingual dataset that aims to facilitate research on grounding words to images in their contextual usage in language. The dat…
Exploiting Multimodal Reinforcement Learning for Simultaneous Machine Translation
Julia Ive, Andy Mingren Li, Yishu Miao +3
This paper addresses the problem of simultaneous machine translation (SiMT) by exploring two main concepts: (a) adaptive policies to learn a good trade-off between high translation…
Cross-lingual Visual Pre-training for Multimodal Machine Translation
Ozan Caglayan, Menekse Kuyu, Mustafa Sercan Amac +4
Pre-trained language models have been shown to improve performance in many natural language tasks substantially. Although the early focus of such models was single language pre-tra…