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 Scopus7 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 Scopus2 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
    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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