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20172024
most citedBenchmarking Natural Language Understanding Services for building Conversational Agents

89 citations · 108 across the 8 of their papers we have counts for

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13 papers · 1 filter

cs.CL2024

Reasoning or a Semblance of it? A Diagnostic Study of Transitive Reasoning in LLMs

Houman Mehrafarin, Arash Eshghi, Ioannis Konstas

Evaluating Large Language Models (LLMs) on reasoning benchmarks demonstrates their ability to solve compositional questions. However, little is known of whether these models engage…

cs.CL2024

Repairs in a Block World: A New Benchmark for Handling User Corrections with Multi-Modal Language Models

Javier Chiyah-Garcia, Alessandro Suglia, Arash Eshghi

In dialogue, the addressee may initially misunderstand the speaker and respond erroneously, often prompting the speaker to correct the misunderstanding in the next turn with a Thir…

cs.CL2021

A Study of Automatic Metrics for the Evaluation of Natural Language Explanations

Miruna Clinciu, Arash Eshghi, Helen Hastie

As transparency becomes key for robotics and AI, it will be necessary to evaluate the methods through which transparency is provided, including automatically generated natural lang…

cs.CL2019

Data-Efficient Goal-Oriented Conversation with Dialogue Knowledge Transfer Networks

Igor Shalyminov, Sungjin Lee, Arash Eshghi +1

Goal-oriented dialogue systems are now being widely adopted in industry where it is of key importance to maintain a rapid prototyping cycle for new products and domains. Data-drive…

cs.CL2019

Current Challenges in Spoken Dialogue Systems and Why They Are Critical for Those Living with Dementia

Angus Addlesee, Arash Eshghi, Ioannis Konstas

Dialogue technologies such as Amazon's Alexa have the potential to transform the healthcare industry. However, current systems are not yet naturally interactive: they are often tur…

cs.CL2019

Few-Shot Dialogue Generation Without Annotated Data: A Transfer Learning Approach

Igor Shalyminov, Sungjin Lee, Arash Eshghi +1

Learning with minimal data is one of the key challenges in the development of practical, production-ready goal-oriented dialogue systems. In a real-world enterprise setting where d…