3 citations · 5 across the 10 of their papers we have counts for
11 papers
Population Fidelity: Evaluating Population Representativeness in LLMs
Neemias B. da Silva, Martin Lukk, Ali Sutani +5
Large language models (LLMs) show considerable potential in simulating human attitudes and preferences. Prior work finds that LLM-generated responses can compress the range of atti…
LiNC: Lightweight Noise Correction via Per-Sample Trust and Gaussian Mixture Modeling
Abhishek Moturu, Babak Taati, Anna Goldenberg
Label noise is common in medical imaging datasets due to factors such as inter-rater variability, annotation errors, and ambiguous cases. This can severely undermine the reliabilit…
Socially Grounded Agentic AI: Coordinating Plural Perspectives through Social Theory
Matt Ratto, Abhishek Moturu, Daniel Silver
As AI systems are deployed across increasingly diverse social contexts, alignment can no longer be framed as the optimization of a single, unified set of values. Instead, systems m…
LiBaGS: Lightweight Boundary Gap Synthesis for Targeted Synthetic Data Selection
Abhishek Moturu, Anna Goldenberg, Babak Taati
Synthetic data is useful only when the added samples fill missing parts of the training distribution that matter for the downstream task. We introduce LiBaGS, a lightweight, genera…
When Does RL Help Medical VLMs? Disentangling Vision, SFT, and RL Gains
Ahmadreza Jeddi, Kimia Shaban, Negin Baghbanzadeh +4
Reinforcement learning (RL) is increasingly used to post-train medical Vision-Language Models (VLMs), yet it remains unclear whether RL improves medical visual reasoning or mainly…
LiLAW: Lightweight Learnable Adaptive Weighting to Learn Sample Difficulty & Improve Noisy Training
Abhishek Moturu, Muhammad Muzammil, Anna Goldenberg +1
Training deep neural networks with noise and data heterogeneity is a major challenge. We introduce Lightweight Learnable Adaptive Weighting (LiLAW), a method that dynamically adjus…
Pain in 3D: Generating Controllable Synthetic Faces for Automated Pain Assessment
Xin Lei Lin, Soroush Mehraban, Abhishek Moturu +1
Automated pain assessment from facial expressions is crucial for non-communicative patient. Progress has been limited by two challenges: (i) existing datasets exhibit severe demogr…
SynPAIN: A Synthetic Dataset of Pain and Non-Pain Facial Expressions
Babak Taati, Muhammad Muzammil, Yasamin Zarghami +5
Accurate pain assessment in patients with limited ability to communicate, such as older adults with severe dementia, represents a critical healthcare challenge. Robust automated sy…
3D Reasoning for Unsupervised Anomaly Detection in Pediatric WbMRI
Alex Chang, Vinith Suriyakumar, Abhishek Moturu +5
Modern deep unsupervised learning methods have shown great promise for detecting diseases across a variety of medical imaging modalities. While previous generative modeling approac…
Unobtrusive Pain Monitoring in Older Adults with Dementia using Pairwise and Contrastive Training
Siavash Rezaei, Abhishek Moturu, Shun Zhao +3
Although pain is frequent in old age, older adults are often undertreated for pain. This is especially the case for long-term care residents with moderate to severe dementia who ca…
Using Generative Models for Pediatric wbMRI
Alex Chang, Vinith M. Suriyakumar, Abhishek Moturu +3
Early detection of cancer is key to a good prognosis and requires frequent testing, especially in pediatrics. Whole-body magnetic resonance imaging (wbMRI) is an essential part of…