activity
20172023
most citedPlato Dialogue System: A Flexible Conversational AI Research Platform

15 citations · 51 across the 20 of their papers we have counts for

collaborators
Showing 2020Show all

7 papers · 1 filter

cs.CL2020★ 6 cited

Can You be More Social? Injecting Politeness and Positivity into Task-Oriented Conversational Agents

Yi-Chia Wang, Alexandros Papangelis, Runze Wang +3

Goal-oriented conversational agents are becoming prevalent in our daily lives. For these systems to engage users and achieve their goals, they need to exhibit appropriate social be…

cs.CL2020

Language Model is All You Need: Natural Language Understanding as Question Answering

Mahdi Namazifar, Alexandros Papangelis, Gokhan Tur +1

Different flavors of transfer learning have shown tremendous impact in advancing research and applications of machine learning. In this work we study the use of a specific family o…

cs.CL2020

Controllable Text Generation with Focused Variation

Lei Shu, Alexandros Papangelis, Yi-Chia Wang +5

This work introduces Focused-Variation Network (FVN), a novel model to control language generation. The main problems in previous controlled language generation models range from t…

cs.HC2020

Towards meaningful, grounded conversations with intelligent agents

Alexandros Papangelis, Stefan Ultes

As conversational agents become integral parts of many aspects of our lives, current approaches are reaching bottlenecks of performance that require increasing amounts of data or i…

cs.CL2020★ 2 cited

Joint Contextual Modeling for ASR Correction and Language Understanding

Yue Weng, Sai Sumanth Miryala, Chandra Khatri +8

The quality of automatic speech recognition (ASR) is critical to Dialogue Systems as ASR errors propagate to and directly impact downstream tasks such as language understanding (LU…

cs.HC2020★ 15 cited

Plato Dialogue System: A Flexible Conversational AI Research Platform

Alexandros Papangelis, Mahdi Namazifar, Chandra Khatri +3

As the field of Spoken Dialogue Systems and Conversational AI grows, so does the need for tools and environments that abstract away implementation details in order to expedite the…

cs.CL2020

Exploration Based Language Learning for Text-Based Games

Andrea Madotto, Mahdi Namazifar, Joost Huizinga +7

This work presents an exploration and imitation-learning-based agent capable of state-of-the-art performance in playing text-based computer games. Text-based computer games describ…