38 citations · 247 across the 108 of their papers we have counts for
7 papers · 1 filter
Thinking While Listening: Simple Test Time Scaling For Audio Classification
Prateek Verma, Mert Pilanci
We propose a framework that enables neural models to "think while listening" to everyday sounds, thereby enhancing audio classification performance. Motivated by recent advances in…
A Recovery Guarantee for Sparse Neural Networks
Sara Fridovich-Keil, Mert Pilanci
We prove the first guarantees of sparse recovery for ReLU neural networks, where the sparse network weights constitute the signal to be recovered. Specifically, we study structural…
DRIVE: Dynamic Rule Inference and Verified Evaluation for Constraint-Aware Autonomous Driving
Longling Geng, Huangxing Li, Viktor Lado Naess +1
Understanding and adhering to soft constraints is essential for safe and socially compliant autonomous driving. However, such constraints are often implicit, context-dependent, and…
MatRL: Provably Generalizable Iterative Algorithm Discovery via Monte-Carlo Tree Search
Sungyoon Kim, Rajat Vadiraj Dwaraknath, Longling geng +1
Iterative methods for computing matrix functions have been extensively studied and their convergence speed can be significantly improved with the right tuning of parameters and by…
Large Language Models Implicitly Learn to See and Hear Just By Reading
Prateek Verma, Mert Pilanci
This paper presents a fascinating find: By training an auto-regressive LLM model on text tokens, the text model inherently develops internally an ability to understand images and a…
Spectral-Aware Low-Rank Adaptation for Speaker Verification
Zhe Li, Man-wai Mak, Mert Pilanci +2
Previous research has shown that the principal singular vectors of a pre-trained model's weight matrices capture critical knowledge. In contrast, those associated with small singul…
LLM-Lasso: A Robust Framework for Domain-Informed Feature Selection and Regularization
Erica Zhang, Ryunosuke Goto, Naomi Sagan +7
We introduce LLM-Lasso, a novel framework that leverages large language models (LLMs) to guide feature selection in Lasso regression. Unlike traditional methods that rely…