22 citations · 81 across the 31 of their papers we have counts for
35 papers
A Human-in-the-Loop Framework for Efficient Prompt Selection in Microscopy Vision-Language Models
Abhiram Kandiyana, Ankur Mali, Lawrence O. Hall +2
Deep-learning pipelines for microscopy image classification often require expensive, labor- and time-intensive expert annotation to produce high-quality ground truth for training.…
Curvature-Weighted Capacity Allocation: A Minimum Description Length Framework for Layer-Adaptive Large Language Model Optimization
Theophilus Amaefuna, Hitesh Vaidya, Anshuman Chhabra +1
Layer-wise capacity in large language models is highly non-uniform: some layers contribute disproportionately to loss reduction, whereas others are nearly redundant. Existing layer…
Tight Stability, Convergence, and Robustness Bounds for Predictive Coding Networks
Ankur Mali, Tommaso Salvatori, Alexander Ororbia
Energy-based learning algorithms, such as predictive coding (PC), have garnered significant attention in the machine learning community due to their theoretical properties, such as…
Precision, Stability, and Generalization: A Comprehensive Assessment of RNNs learnability capability for Classifying Counter and Dyck Languages
Neisarg Dave, Daniel Kifer, Lee Giles +1
This study investigates the learnability of Recurrent Neural Networks (RNNs) in classifying structured formal languages, focusing on counter and Dyck languages. Traditionally, both…
A Unified Framework for Continual Learning and Unlearning
Romit Chatterjee, Vikram Chundawat, Ayush Tarun +2
Continual learning and machine unlearning are crucial challenges in machine learning, typically addressed separately. Continual learning focuses on adapting to new knowledge while…
Investigating Symbolic Capabilities of Large Language Models
Neisarg Dave, Daniel Kifer, C. Lee Giles +1
Prompting techniques have significantly enhanced the capabilities of Large Language Models (LLMs) across various complex tasks, including reasoning, planning, and solving math word…