1 citations · 2 across the 6 of their papers we have counts for
5 papers · 1 filter
Change of Thought: Adaptive Test-Time Computation
Mrinal Mathur, Mike Doan, Barak Pearlmutter +1
Transformers evaluated in a single, fixed-depth pass are provably limited in expressive power to the constant-depth circuit class TC0. Running a Transformer autoregressively remove…
How Overconfidence in Initial Choices and Underconfidence Under Criticism Modulate Change of Mind in Large Language Models
Dharshan Kumaran, Stephen M Fleming, Larisa Markeeva +8
Large language models (LLMs) exhibit strikingly conflicting behaviors: they can appear steadfastly overconfident in their initial answers whilst at the same time being prone to exc…
DynaLay: An Introspective Approach to Dynamic Layer Selection for Deep Networks
Mrinal Mathur, Sergey Plis
Deep learning models have become increasingly computationally intensive, requiring extensive computational resources and time for both training and inference. A significant contrib…
Pipeline-Invariant Representation Learning for Neuroimaging
Xinhui Li, Alex Fedorov, Mrinal Mathur +4
Deep learning has been widely applied in neuroimaging, including predicting brain-phenotype relationships from magnetic resonance imaging (MRI) volumes. MRI data usually requires e…
Routing and Placement of Macros using Deep Reinforcement Learning
Mrinal Mathur
Chip placement has been one of the most time consuming task in any semi conductor area, Due to this negligence, many projects are pushed and chips availability in real markets get…