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Vinitra Swamy
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2020 – today
- 2024
- [c14]Isadora Salles
, Paola Mejia-Domenzain
Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection. AIED Companion (1) 2024: 382-390 - [c13]Tanya Nazaretsky
AI or Human? Evaluating Student Feedback Perceptions in Higher Education. EC-TEL (1) 2024: 284-298 - [c12]Elena Grazia Gado, Tommaso Martorella, Luca Zunino, Paola Mejia-Domenzain, Vinitra Swamy, Jibril Frej, Tanja Käser:
Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning. EDM 2024 - [c11]Juan Pinto, Luc Paquette, Vinitra Swamy, Tanja Käser, Qianhui Liu, Lea Cohausz:
Human-Centric eXplainable AI in Education (HEXED) Workshop. EDM 2024 - [c10]Juan Pinto, Luc Paquette, Vinitra Swamy, Tanja Käser, Qianhui Liu, Lea Cohausz:
Preface. HEXED/L3MNGET@EDM 2024 - [e1]Juan D. Pinto, Eamon Worden, Anthony Botelho, Lea Cohausz, Clayton Cohn, Mingyu Feng, Neil T. Heffernan, Arto Hellas, Lan Jiang, David Joyner, Tanja Käser, Juho Kim, Andrew Lan, Chenglu Li, Joshua Littenberg-Tobias, Qianhui Liu, Christopher MacLellan, Steven Moore, Maciej Pankiewicz, Luc Paquette, Zach A. Pardos, Anna N. Rafferty, Adish Singla, Shashank Sonkar, Vinitra Swamy, Rose E. Wang, Candace Walkington:
Joint Proceedings of the Human-Centric eXplainable AI in Education and the Leveraging Large Language Models for Next Generation Educational Technologies Workshops (HEXED-L3MNGET 2024) co-located with 17th International Conference on Educational Data Mining (EDM 2024), Atlanta, Georgia, USA, July 14, 2024. CEUR Workshop Proceedings 3840, CEUR-WS.org 2024 [contents] - [i14]Vinitra Swamy
InterpretCC: Conditional Computation for Inherently Interpretable Neural Networks. CoRR abs/2402.02933 (2024) - [i13]Elena Grazia Gado, Tommaso Martorella, Luca Zunino, Paola Mejia-Domenzain, Vinitra Swamy, Jibril Frej, Tanja Käser:
Student Answer Forecasting: Transformer-Driven Answer Choice Prediction for Language Learning. CoRR abs/2405.20079 (2024) - [i12]Isadora Salles, Paola Mejia-Domenzain, Vinitra Swamy, Julian Blackwell, Tanja Käser:
Interpret3C: Interpretable Student Clustering Through Individualized Feature Selection. CoRR abs/2407.11979 (2024) - [i11]Vinitra Swamy, Davide Romano, Bhargav Srinivasa Desikan, Oana-Maria Camburu, Tanja Käser:
From Explanations to Action: A Zero-Shot, Theory-Driven LLM Framework for Student Performance Feedback. CoRR abs/2409.08027 (2024) - 2023
- [c9]Mohammad Asadi, Vinitra Swamy, Jibril Frej, Julien Tuan Tu Vignoud, Mirko Marras, Tanja Käser:
Ripple: Concept-Based Interpretation for Raw Time Series Models in Education. AAAI 2023: 15903-15911 - [c8]Thiemo Wambsganss, Xiaotian Su, Vinitra Swamy, Seyed Parsa Neshaei, Roman Rietsche, Tanja Käser:
Unraveling Downstream Gender Bias from Large Language Models: A Study on AI Educational Writing Assistance. EMNLP (Findings) 2023: 10275-10288 - [c7]Vinitra Swamy
Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design. LAK 2023: 345-356 - [c6]Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser, Mary-Anne Hartley:
MultiMoDN - Multimodal, Multi-Task, Interpretable Modular Networks. NeurIPS 2023 - [i10]Vinitra Swamy, Jibril Frej, Tanja Käser:
The future of human-centric eXplainable Artificial Intelligence (XAI) is not post-hoc explanations. CoRR abs/2307.00364 (2023) - [i9]Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser
MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks. CoRR abs/2309.14118 (2023) - [i8]Thiemo Wambsganss, Xiaotian Su, Vinitra Swamy
Unraveling Downstream Gender Bias from Large Language Models: A Study on AI Educational Writing Assistance. CoRR abs/2311.03311 (2023) - [i7]Zeming Chen
MEDITRON-70B: Scaling Medical Pretraining for Large Language Models. CoRR abs/2311.16079 (2023) - 2022
- [c5]Thiemo Wambsganss
Bias at a Second Glance: A Deep Dive into Bias for German Educational Peer-Review Data Modeling. COLING 2022: 1344-1356 - [c4]Collin F. Lynch, Mirko Marras, Mykola Pechenizkiy, Anna N. Rafferty, Steven Ritter, Vinitra Swamy, Renzhe Yu:
FATED 2022: Fairness, Accountability, and Transparency in Educational Data. EDM 2022 - [c3]Vinitra Swamy, Bahar Radmehr, Natasa Krco, Mirko Marras, Tanja Käser:
Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs. EDM 2022 - [c2]Vinitra Swamy
Meta Transfer Learning for Early Success Prediction in MOOCs. L@S 2022: 121-132 - [i6]Vinitra Swamy
Meta Transfer Learning for Early Success Prediction in MOOCs. CoRR abs/2205.01064 (2022) - [i5]Vinitra Swamy
Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs. CoRR abs/2207.00551 (2022) - [i4]Thiemo Wambsganss
Bias at a Second Glance: A Deep Dive into Bias for German Educational Peer-Review Data Modeling. CoRR abs/2209.10335 (2022) - [i3]Mohammad Asadi, Vinitra Swamy
Ripple: Concept-Based Interpretation for Raw Time Series Models in Education. CoRR abs/2212.01133 (2022) - [i2]Vinitra Swamy
Trusting the Explainers: Teacher Validation of Explainable Artificial Intelligence for Course Design. CoRR abs/2212.08955 (2022) - 2021
- [i1]Vinitra Swamy, Angelika Romanou, Martin Jaggi:
Interpreting Language Models Through Knowledge Graph Extraction. CoRR abs/2111.08546 (2021)
2010 – 2019
- 2018
- [c1]Vinitra Swamy
Deep Knowledge Tracing for Free-Form Student Code Progression. AIED (2) 2018: 348-352
Coauthor Index
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