activity
20172026
most citedApplying a Generic Sequence-to-Sequence Model for Simple and Effective Keyphrase Generation

12 citations · 26 across the 13 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

Agentic Control Center for Data Product Optimization

Priyadarshini Tamilselvan, Gregory Bramble, Sola Shirai +3

Data products enable end users to gain greater insights about their data by providing supporting assets, such as example question-SQL pairs which can be answered using the data or…

cs.AI2026

Automatic Prompt Engineering with No Task Cues and No Tuning

Faisal Chowdhury, Nandana Mihindukulasooriya, Niharika S D'Souza +4

This paper presents a system for automatic prompt engineering that is much simpler in both design and application and yet as effective as the existing approaches. It requires no tu…

cs.AI2025

Automatic Prompt Optimization for Knowledge Graph Construction: Insights from an Empirical Study

Nandana Mihindukulasooriya, Niharika S. D'Souza, Faisal Chowdhury +1

A KG represents a network of entities and illustrates relationships between them. KGs are used for various applications, including semantic search and discovery, reasoning, decisio…

cs.AI2022★ 1 cited

Knowledge Graph Induction enabling Recommending and Trend Analysis: A Corporate Research Community Use Case

Nandana Mihindukulasooriya, Mike Sava, Gaetano Rossiello +7

A research division plays an important role of driving innovation in an organization. Drawing insights, following trends, keeping abreast of new research, and formulating strategie…

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★ 8 cited

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…