Shima Imani
Orcid: 0000-0001-9616-3178
According to our database1,
Shima Imani authored at least 22 papers
between 2018 and 2026.
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Bibliography
2026
TRACE: A Framework for Analyzing and Enhancing Stepwise Reasoning in Vision-Language Models.
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026
SymPyBench: A Dynamic Benchmark for Scientific Reasoning with Executable Python Code.
Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics, 2026
2025
SymPyBench: A Dynamic Benchmark for Scientific Reasoning with Executable Python Code.
CoRR, December, 2025
PRiSM: An Agentic Multimodal Benchmark for Scientific Reasoning via Python-Grounded Evaluation.
CoRR, December, 2025
2024
Next-Token Prediction Task Assumes Optimal Data Ordering for LLM Training in Proof Generation.
CoRR, 2024
Learning How To Ask: Cycle-Consistency Refines Prompts in Multimodal Foundation Models.
CoRR, 2024
2023
CoRR, 2023
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 5: Industry Track), 2023
tGLAD: A Sparse Graph Recovery Based Approach for Multivariate Time Series Segmentation.
Proceedings of the Advanced Analytics and Learning on Temporal Data, 2023
2020
Data Min. Knowl. Discov., 2020
An ultra-fast time series distance measure to allow data mining in more complex real-world deployments.
Data Min. Knowl. Discov., 2020
Proceedings of the Companion of The 2020 Web Conference 2020, 2020
Fitbit for Chickens?: Time Series Data Mining Can Increase the Productivity of Poultry Farms.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
2019
Proceedings of the Companion of The 2019 World Wide Web Conference, 2019
Matrix Profile XIX: Time Series Semantic Motifs: A New Primitive for Finding Higher-Level Structure in Time Series.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019
Matrix Profile XX: Finding and Visualizing Time Series Motifs of All Lengths using the Matrix Profile.
Proceedings of the 2019 IEEE International Conference on Big Knowledge, 2019
2018
Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios.
Proceedings of the IEEE International Conference on Data Mining, 2018
Matrix Profile XIII: Time Series Snippets: A New Primitive for Time Series Data Mining.
Proceedings of the 2018 IEEE International Conference on Big Knowledge, 2018