World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
9848
World Ranking
7481
National Ranking
370

Overview

Milica Gasic is affiliated with Heinrich Heine University Düsseldorf in Germany. Their research is primarily situated within the broad field of Computer Science, with a particular concentration on Artificial Intelligence. Other subfields of study include Experimental and Cognitive Psychology, Computational Theory and Mathematics, Social Psychology, and Computer Vision and Pattern Recognition.

The scientist's work extensively explores several main topics, such as:

  • Topic Modeling
  • Speech and dialogue systems
  • Natural Language Processing Techniques
  • AI in Service Interactions
  • Emotion and Mood Recognition
  • Intelligent Tutoring Systems and Adaptive Learning
  • Sentiment Analysis and Opinion Mining

Milica Gasic has contributed to numerous research papers published in various venues. Recent publications include:

  • "Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges," 2022, arXiv (Cornell University)
  • "TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking," 2020, arXiv (Cornell University)
  • "Robust Dialogue State Tracking with Weak Supervision and Sparse Data," 2022, Transactions of the Association for Computational Linguistics
  • "EmoWOZ: A Large-Scale Corpus and Labelling Scheme for Emotion Recognition in Task-Oriented Dialogue Systems," 2022, arXiv (Cornell University)
  • "Dynamic Dialogue Policy for Continual Reinforcement Learning," 2022, arXiv (Cornell University)

The frequent co-authors collaborating with Milica Gasic include:

  • Michael Heck
  • Carel van Niekerk
  • Nurul Lubis
  • Hsien-chin Lin
  • Christian Geishauser

Publications appear most often in the following venues:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • AI Magazine

Best Publications

  • Semantically Conditioned LSTM-based Natural Language Generation for Spoken Dialogue Systems

    Tsung-Hsien Wen;Milica Gasic;Nikola Mrkšić;Pei-Hao Su

  • MultiWOZ - A Large-Scale Multi-Domain Wizard-of-Oz Dataset for Task-Oriented Dialogue Modelling

    Paweł Budzianowski;Tsung-Hsien Wen;Bo-Hsiang Tseng;Iñigo Casanueva

  • POMDP-Based Statistical Spoken Dialog Systems: A Review

    S. Young;M. Gasic;B. Thomson;J. D. Williams

  • A Network-based End-to-End Trainable Task-oriented Dialogue System

    Tsung-Hsien Wen;David Vandyke;Nikola Mrksic;Milica Gasic

  • The Hidden Information State model: A practical framework for POMDP-based spoken dialogue management

    Steve Young;Milica Gašić;Simon Keizer;François Mairesse

  • Counter-fitting word vectors to linguistic constraints

    Nikola Mrksic;Diarmuid Ó Séaghdha;Blaise Thomson;Milica Gasic

  • Semantic Specialization of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints

    Nikola Mrksic;Nikola Mrksic;Ivan Vulic;Diarmuid Ó Séaghdha;Ira Leviant

  • Multi-domain Neural Network Language Generation for Spoken Dialogue Systems

    Tsung-Hsien Wen;Milica Gasic;Nikola Mrksic;Lina Maria Rojas-Barahona

  • Multi-domain Dialog State Tracking using Recurrent Neural Networks

    Nikola Mrkšić;Diarmuid Ó Séaghdha;Blaise Thomson;Milica Gasic

  • TripPy: A Triple Copy Strategy for Value Independent Neural Dialog State Tracking

    Michael Heck;Carel van Niekerk;Nurul Lubis;Christian Geishauser

  • Gaussian Processes for POMDP-Based Dialogue Manager Optimization

    Milica Gasic;Steve Young

  • PyDial: A Multi-domain Statistical Dialogue System Toolkit

    Stefan Ultes;Lina Maria Rojas-Barahona;Pei-Hao Su;David Vandyke

  • Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking

    Tsung-Hsien Wen;Milica Gasic;Dongho Kim;Nikola Mrksic

  • Phrase-Based Statistical Language Generation Using Graphical Models and Active Learning

    Francois Mairesse;Milica Gasic;Filip Jurcicek;Simon Keizer

  • Large-Scale Multi-Domain Belief Tracking with Knowledge Sharing

    Osman Ramadan;Paweł Budzianowski;Milica Gašić

  • A Network-based End-to-End Trainable Task-oriented Dialogue System

    Tsung-Hsien Wen;David Vandyke;Nikola Mrksic;Milica Gasic

  • On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems

    Pei-Hao Su;Milica Gasic;Nikola Mrksic;Lina Maria Rojas-Barahona

  • Continuously Learning Neural Dialogue Management.

    Pei-Hao Su;Milica Gasic;Nikola Mrksic;Lina Maria Rojas-Barahona

  • Sample-efficient Actor-Critic Reinforcement Learning with Supervised Data for Dialogue Management

    Pei-Hao Su;Pawel Budzianowski;Stefan Ultes;Milica Gasic

  • Discriminative spoken language understanding using word confusion networks

    Matthew Henderson;Milica Gasic;Blaise Thomson;Pirros Tsiakoulis

  • Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints

    Nikola Mrkšić;Ivan Vulić;Diarmuid Ó Séaghdha;Ira Leviant

  • POMDP-Based Statistical Spoken Dialog Systems: A Review This paper presents the theory and practice of belief tracking, policy optimization, parameter estimation, and fast learning.

    Steve Young;Milica Gasic;Blaise Thomson;Jason D. Williams

Frequent Co-Authors

Steve Young
Steve Young University of Cambridge
Nikola Mrksic
Nikola Mrksic PolyAI Limited
Kai Yu
Kai Yu Shanghai Jiao Tong University
Peter Mika
Peter Mika Yahoo (United Kingdom)
Verena Rieser
Verena Rieser Heriot-Watt University
Oliver Lemon
Oliver Lemon Heriot-Watt University
Roi Reichart
Roi Reichart Technion – Israel Institute of Technology
Jason D. Williams
Jason D. Williams Apple (United States)
Anna Korhonen
Anna Korhonen University of Cambridge
Ivan Vulić
Ivan Vulić University of Cambridge

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