42 citations · 42 across the 6 of their papers we have counts for
10 papers
Scaling Therapy Supervision: Assessing Psychotherapy Fidelity Using Large Language Models
Arvind Pillai, Alexis Roach, Jason Holden +11
Psychotherapy fidelity assessment measures how faithfully a therapist adheres to a treatment protocol, a critical determinant of positive patient outcomes. However, fidelity assess…
MontageFlow: Physically Valid High Fidelity EEG Generation
Sudarshan Regmi, Nabaraj Subedi, Arvind Pillai +6
Generative modeling offers a promising solution to the scarcity of labeled clinical electroencephalography (EEG) data under strict privacy constraints. Although recent generative m…
Lapras: Latent Reasoning for Time Series Language Models
Yuliang Chen, Yu Yvonne Wu, Patrick Langer +11
Time Series Language Models (TSLMs) offer a promising path toward time series understanding by reasoning over temporal signals and producing natural language answers and explanatio…
TimeThink: Eliciting Compositional Reasoning in Timeseries Large Language Models
Sudarshan Regmi, Arvind Pillai, Yu Yvonne Wu +7
Timeseries multimodal large language models (TS-MLLMs) have recently begun leveraging the reasoning capabilities of large language models (LLMs) for question-answering tasks. Howev…
BALMS: Benchmarking Agentic LLMs for Longitudinal Mental Health Sensing
Yu Yvonne Wu, Arvind Pillai, Yuliang Chen +7
Mental health assessment relies on episodic self-report scales, which convert subjective states such as stress into numerical scores but provide only sparse snapshots of wellbeing.…
AdaSCALE: Adaptive Scaling for OOD Detection
Sudarshan Regmi
The ability of the deep learning model to recognize when a sample falls outside its learned distribution is critical for safe and reliable deployment. Recent state-of-the-art out-o…
Image-based Outlier Synthesis With Training Data
Sudarshan Regmi
Out-of-distribution (OOD) detection is critical to ensure the safe deployment of deep learning models in critical applications. Deep learning models can often misidentify OOD sampl…
Neural Network Pruning for Real-time Polyp Segmentation
Suman Sapkota, Pranav Poudel, Sudarshan Regmi +2
Computer-assisted treatment has emerged as a viable application of medical imaging, owing to the efficacy of deep learning models. Real-time inference speed remains a key requireme…
T2FNorm: Extremely Simple Scaled Train-time Feature Normalization for OOD Detection
Sudarshan Regmi, Bibek Panthi, Sakar Dotel +3
Neural networks are notorious for being overconfident predictors, posing a significant challenge to their safe deployment in real-world applications. While feature normalization ha…
CholecTriplet2022: Show me a tool and tell me the triplet -- an endoscopic vision challenge for surgical action triplet detection
Chinedu Innocent Nwoye, Tong Yu, Saurav Sharma +46
Formalizing surgical activities as triplets of the used instruments, actions performed, and target anatomies is becoming a gold standard approach for surgical activity modeling. Th…