ProfessorsProfessors of Eberhard Karls Universität TübingenMadeeswaran Kannan

Madeeswaran Kannan

Eberhard Karls Universität Tübingen

H-index: 2

Europe-Germany

About Madeeswaran Kannan

Madeeswaran Kannan, With an exceptional h-index of 2 and a recent h-index of 2 (since 2020), a distinguished researcher at Eberhard Karls Universität Tübingen, specializes in the field of NLP, Computational Linguistics, Machine Learning, Information Retrieval.

His recent articles reflect a diverse array of research interests and contributions to the field:

Exploring neural question generation for formal pragmatics: Data set and model evaluation

Exploring input representation granularity for generating questions satisfying question-answer congruence

Advancing Neural Question Generation for Formal Pragmatics: Learning when to generate and when to copy

Towards automatically generating questions under discussion to link information and discourse structure

TüKaPo at SemEval-2020 Task 6: Def (n) tly Not BERT: Definition Extraction Using pre-BERT Methods in a post-BERT World

Madeeswaran Kannan Information

University	Eberhard Karls Universität Tübingen
Position	___
Citations(all)	35
Citations(since 2020)	21
Cited By	18
hIndex(all)	2
hIndex(since 2020)	2
i10Index(all)	2
i10Index(since 2020)	1
Email	Access Email
University Profile Page	Eberhard Karls Universität Tübingen
Google Scholar	View Google Scholar Profile

Madeeswaran Kannan Skills & Research Interests

NLP

Computational Linguistics

Machine Learning

Information Retrieval

Top articles of Madeeswaran Kannan

Title	Journal	Author(s)	Publication Date
Exploring neural question generation for formal pragmatics: Data set and model evaluation	Frontiers in Artificial Intelligence	Kordula De Kuthy Madeeswaran Kannan Haemanth Santhi Ponnusamy Detmar Meurers	2022/10/31
Exploring input representation granularity for generating questions satisfying question-answer congruence		Madeeswaran Kannan Haemanth Santhi Ponnusamy Kordula De Kuthy Lukas Stein Detmar Meurers	2021/8
Advancing Neural Question Generation for Formal Pragmatics: Learning when to generate and when to copy		Kordula De Kuthy Madeeswaran Kannan Haemanth Santhi Ponnusamy Detmar Meurers	2021/10
Towards automatically generating questions under discussion to link information and discourse structure		Kordula De Kuthy Madeeswaran Kannan Haemanth Santhi Ponnusamy Detmar Meurers	2020/12
TüKaPo at SemEval-2020 Task 6: Def (n) tly Not BERT: Definition Extraction Using pre-BERT Methods in a post-BERT World		Madeeswaran Kannan Haemanth Santhi Ponnusamy	2020/12