most citedEnhancing Text-based Reinforcement Learning Agents with Commonsense Knowledge

17 citations · 25 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG2021

SQALER: Scaling Question Answering by Decoupling Multi-Hop and Logical Reasoning

Mattia Atzeni, Jasmina Bogojeska, Andreas Loukas

State-of-the-art approaches to reasoning and question answering over knowledge graphs (KGs) usually scale with the number of edges and can only be applied effectively on small inst…

cs.AI2021

Business Entity Matching with Siamese Graph Convolutional Networks

Evgeny Krivosheev, Mattia Atzeni, Katsiaryna Mirylenka +3

Data integration has been studied extensively for decades and approached from different angles. However, this domain still remains largely rule-driven and lacks universal automatio…

cs.AI2020

Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines

Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi +6

Text-based games have emerged as an important test-bed for Reinforcement Learning (RL) research, requiring RL agents to combine grounded language understanding with sequential deci…

cs.AI202017 cited

Enhancing Text-based Reinforcement Learning Agents with Commonsense Knowledge

Keerthiram Murugesan, Mattia Atzeni, Pushkar Shukla +3

In this paper, we consider the recent trend of evaluating progress on reinforcement learning technology by using text-based environments and games as evaluation environments. This…

cs.DB20208 cited

Siamese Graph Neural Networks for Data Integration

Evgeny Krivosheev, Mattia Atzeni, Katsiaryna Mirylenka +2

Data integration has been studied extensively for decades and approached from different angles. However, this domain still remains largely rule-driven and lacks universal automatio…