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Accepted into Journal of Special Topics in Signal Processing (JSTSP). Paper on utilizing a Switch Network to alleviate catastrophic forgetting in LLMs
Recommended citation: Wu, X., Hartman, M.*, Jayaraman, V. A.*, & Varshney, L. R. (2024, July 16). SwitchCIT: Switching for continual instruction tuning of large language models. arXiv.org. https://arxiv.org/abs/2407.11780
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Not yet published, undergoing internal review. Improves existing methods for Reliability Growth Planning and system reliability estimation. Manuscript available upon request
Recommended citation: Bernstein, H. C., Bindel, S. R., McKibben, M. A., & Jayaraman, V. A. (2024). Planning Model based on Projection Methodology Bayesian Discrete Extended (PM2-BDE)
Under Review for ICML 2026. Paper presents a unified framework for analyzing model efficiency improvement methods such as token pruning and layer skipping. We then use this framework and do a case-study on layer-skipping, theoretically grounding its results.
Recommended citation: Hartman, M.*, Jayaraman V.A.*, Choraria, M., Bhimaraju, A., & Varshney, L.R. (2025). Skip-It? Theoretical Conditions for Layer Skipping in Vision-Language Models. Preprint https://www.arxiv.org/abs/2509.25584
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Presented at the eXCV Workshop at ICCV 2025. Interpretability work on determining how vision is transformed in the early layers in VLMs.
Recommended citation: Hartman, M.*, Jayaraman, V.A.*, Choraria, M., Bhimaraju, A., & Varshney, L. R. (2025). Unmasking the functionality of early layers in VLMs
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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