Savitha Sam Abraham

Dr Savitha Sam Abraham

Postdoctoral Researcher

Australian Institute for Machine Learning - Projects

Faculty of Sciences, Engineering and Technology


I currently work as a postdoctoral researcher at AIML, focusing my research on the convergence of Natural Language Processing (NLP), logical reasoning, and their practical applications, particularly in the field of robotics.

I currently work as a postdoctoral researcher at AIML, focusing my research on the convergence of Natural Language Processing (NLP), logical reasoning, and their practical applications, particularly in the field of robotics.

  • Journals

    Year Citation
    2024 Sundaram, S. S., Gurajada, S., Padmanabhan, D., Abraham, S. S., & Fisichella, M. (2024). Does a language model “understand” high school math? A survey of deep learning based word problem solvers. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 14(4).
    DOI Scopus2
    2024 Kadan, A., Deepak, P., Gangan, M. P., Abraham, S. S., & Lajish, V. L. (2024). REDAffectiveLM: leveraging affect enriched embedding and transformer-based neural language model for readers’ emotion detection. Knowledge and Information Systems, 66(12), 7495-7525.
    DOI
    2022 Anoop, K., Deepak, P., Sam Abraham, S., Lajish, V. L., & Gangan, M. P. (2022). Readers’ affect: predicting and understanding readers’ emotions with deep learning. Journal of Big Data, 9(1), 31 pages.
    DOI Scopus8 WoS3
    2021 Deepak, P., & Abraham, S. S. (2021). FairLOF: Fairness in Outlier Detection. Data Science and Engineering, 6(4), 485-499.
    DOI Scopus12 WoS5
    2020 Deepak, P., & Abraham, S. S. (2020). Correction to: Chapter “Fair Outlier Detection” in: Z. Huang et al. (Eds.): Web Information Systems Engineering – WISE 2020, (LNCS 12343 (10.1007/978-3-030-62008-0_31)). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12343 LNCS, C1.
    DOI
    2019 Abraham, S. S., & Sundaram, S. S. (2019). An Ontology-Based Kinematics Problem Solver Using Qualitative and Quantitative Knowledge. New Generation Computing, 37(4), 551-584.
    DOI Scopus3 WoS1
    2019 Sundaram, S. S., & Abraham, S. S. (2019). Semantic Representation for Age Word Problems with Schemas. New Generation Computing, 37(4), 429-452.
    DOI Scopus3 WoS1
  • Conference Papers

    Year Citation
    2025 Abraham, S. S., Garg, S., & Dayoub, F. (2025). To Ask or Not to Ask? Detecting Absence of Information in Vision and Language Navigation. In Proceedings - 2025 IEEE Winter Conference on Applications of Computer Vision, WACV 2025 (pp. 7480-7489). Tucson, AZ, USA Funding Agency: Authors Savitha Sam Abraham Australian Institute for Machine Learning, The University of Adelaide, Australia Sourav Garg Australian Institute for Machine Learning, The University of Adelaide, Australia Feras Dayoub Australian Institute for Machine Learning, The University of Adelaide, Australia Figures References Keywords Metrics Contact IEEE to Subscribe: IEEE.
    DOI
    2024 Abraham, S. S., Alirezaie, M., & De Raedt, L. (2024). CLEVR-POC: Reasoning-Intensive Visual Question Answering in Partially Observable Environments. In 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC-COLING 2024 - Main Conference Proceedings (pp. 3297-3313). Online: European Language Resources Association (ELRA).
    2024 Aregbede, V., Abraham, S. S., Persson, A., Langkvist, M., & Loutfi, A. (2024). Affordance-Based Goal Imagination for Embodied AI Agents. In IEEE International Conference on Development and Learning, ICDL 2024 (pp. 1-6). Austin Texas: IEEE.
    DOI
    2023 Abraham, S. S., P, D., & Sundaram, S. S. (2023). Span Detection for Kinematics Word Problems. In Communications in Computer and Information Science Vol. 1793 CCIS (pp. 276-288). Online: Springer Nature Singapore.
    DOI
    2022 Lindström, A. D., & Abraham, S. S. (2022). CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoning. In CEUR Workshop Proceedings Vol. 3212 (pp. 1-17). Cumberland Lodge, Windsor, UK: CEUR Workshop Proceedings.
    Scopus3
    2022 Lindstrom, A. D., & Abraham, S. S. (2022). CLEVR-Math: A Dataset for Compositional Language, Visual and Mathematical Reasoning. In A. D. Garcez, & E. Jimenez-Ruiz (Eds.), NEURAL-SYMBOLIC LEARNING AND REASONING, NESY 2022 (pp. 155-170). ENGLAND, Windsor: RWTH AACHEN.
    2020 Deepak, P., & Abraham, S. S. (2020). Representativity Fairness in Clustering. In WebSci 2020 - Proceedings of the 12th ACM Conference on Web Science (pp. 202-211). Southampton: ACM.
    DOI Scopus9
    2020 Abraham, S. S., Deepak, P., & Sundaram, S. S. (2020). Fairness in clustering with multiple sensitive attributes. In Advances in Database Technology - EDBT Vol. 2020-March (pp. 287-298). Copenhagen: OpenProceedings.org.
    DOI Scopus25
    2020 Deepak, P., & Sam Abraham, S. (2020). Fair Outlier Detection. In Z. Huang, W. Beek, H. Wang, R. Zhou, & Y. Zhang (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 12343 LNCS (pp. 447-462). Amsterdam: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus11 WoS7
    2020 Sundaram, S. S., Deepak, P., & Abraham, S. S. (2020). Distributed representations for arithmeticword problems. In AAAI 2020 - 34th AAAI Conference on Artificial Intelligence Vol. 34 (pp. 9000-9007). NY, New York: ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE.
    Scopus1
    2018 Abraham, S. S., & Sundaram, S. S. (2018). Combining qualitative and quantitative reasoning for solving kinematics word problems. In Proceedings of the 31st International Florida Artificial Intelligence Research Society Conference, FLAIRS 2018 (pp. 164-167).
    Scopus1
    2018 Sundaram, S. S., & Abraham, S. S. (2018). Solving simple arithmetic word problems precisely with schemas. In M. Mouhoub, S. Sadaoui, O. A. Mohamed, & M. Ali (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 10868 LNAI (pp. 542-547). CANADA, Montreal: SPRINGER INTERNATIONAL PUBLISHING AG.
    DOI Scopus1 WoS1
    2016 Abraham, S. S., & Khemani, D. (2016). Hybrid of qualitative and quantitative knowledge models for solving physics word problems. In Proceedings of the 29th International Florida Artificial Intelligence Research Society Conference, FLAIRS 2016 (pp. 510-515).
    Scopus2
    2012 Abraham, S. S., & Idicula, S. M. (2012). Comparison of statistical and semantic similarity techniques for paraphrase identification. In Proceedings - 2012 International Conference on Data Science and Engineering, ICDSE 2012 (pp. 209-213). IEEE.
    DOI Scopus3
  • Preprint

    Year Citation
    2024 Abraham, S. S., Garg, S., & Dayoub, F. (2024). To Ask or Not to Ask? Detecting Absence of Information in Vision and
    Language Navigation.
  • Position: Postdoctoral Researcher
  • Email: savitha.samabraham@adelaide.edu.au
  • Campus: North Terrace
  • Building: Australian Institute for Machine Learning, floor LG
  • Org Unit: Australian Institute for Machine Learning - Projects

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