Md. Faisal Mahbub Chowdhury — accepted AI-conference papers

2023

KnowGL: Knowledge Generation and Linking from Text

Gaetano Rossiello, Md. Faisal Mahbub Chowdhury, Nandana Mihindukulasooriya, Owen Cornec, Alfio Massimiliano Gliozzo

AAAI 2023technical

We propose KnowGL, a tool that allows converting text into structured relational data represented as a set of ABox assertions compliant with the TBox of a given Knowledge Graph (KG), such as Wikidata. We address this problem as a sequence generation task by leveraging pre-trained sequence-to-sequen…

Cited by 30 Source ↗PDF ↗Scholar ↗

2022

Re2G: Retrieve, Rerank, Generate

Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, Ankita Naik, Pengshan Cai, Alfio Gliozzo

NAACL 2022long

As demonstrated by GPT-3 and T5, transformers grow in capability as parameter spaces become larger and larger. However, for tasks that require a large amount of knowledge, non-parametric memory allows models to grow dramatically with a sub-linear increase in computational cost and GPU memory require…

Cited by 145 Source ↗PDF ↗code ↗Scholar ↗

2021

Robust Retrieval Augmented Generation for Zero-shot Slot Filling

Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury, Alfio Gliozzo

EMNLP 2021main

Automatically inducing high quality knowledge graphs from a given collection of documents still remains a challenging problem in AI. One way to make headway for this problem is through advancements in a related task known as slot filling. In this task, given an entity query in form of [Entity, Slot,…

Cited by 39 Source ↗PDF ↗code ↗Scholar ↗