activity
20172022
most citedApplying a Generic Sequence-to-Sequence Model for Simple and Effective Keyphrase Generation

12 citations · 15 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CL202212 cited

Applying a Generic Sequence-to-Sequence Model for Simple and Effective Keyphrase Generation

Md Faisal Mahbub Chowdhury, Gaetano Rossiello, Michael Glass +2

In recent years, a number of keyphrase generation (KPG) approaches were proposed consisting of complex model architectures, dedicated training paradigms and decoding strategies. In…

cs.CL2021

Robust Retrieval Augmented Generation for Zero-shot Slot Filling

Michael Glass, Gaetano Rossiello, Md Faisal Mahbub Chowdhury +1

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 thr…

cs.AI2020

Template Controllable keywords-to-text Generation

Abhijit Mishra, Md Faisal Mahbub Chowdhury, Sagar Manohar +2

This paper proposes a novel neural model for the understudied task of generating text from keywords. The model takes as input a set of un-ordered keywords, and part-of-speech (POS)…

cs.AI2019

Hypernym Detection Using Strict Partial Order Networks

Sarthak Dash, Md Faisal Mahbub Chowdhury, Alfio Gliozzo +2

This paper introduces Strict Partial Order Networks (SPON), a novel neural network architecture designed to enforce asymmetry and transitive properties as soft constraints. We appl…

cs.DS20192 cited

An Efficient Approach for Super and Nested Term Indexing and Retrieval

Md Faisal Mahbub Chowdhury, Robert Farrell

This paper describes a new approach, called Terminological Bucket Indexing (TBI), for efficient indexing and retrieval of both nested and super terms using a single method. We prop…

cs.CL2018

A Study on Passage Re-ranking in Embedding based Unsupervised Semantic Search

Md Faisal Mahbub Chowdhury, Vijil Chenthamarakshan, Rishav Chakravarti +1

State of the art approaches for (embedding based) unsupervised semantic search exploits either compositional similarity (of a query and a passage) or pair-wise word (or term) simil…