4 citations · 9 across the 16 of their papers we have counts for
6 papers · 1 filter
Lumos: Let there be Language Model System Certification
Isha Chaudhary, Vedaant Jain, Prineet Parhar +4
We introduce the first principled framework, Lumos, for specifying and formally certifying Language Model System (LMS) behaviors. Lumos is an imperative probabilistic programming D…
GnnXemplar: Exemplars to Explanations -- Natural Language Rules for Global GNN Interpretability
Burouj Armgaan, Eshan Jain, Harsh Pandey +2
Graph Neural Networks (GNNs) are widely used for node classification, yet their opaque decision-making limits trust and adoption. While local explanations offer insights into indiv…
Panorama: Fast-Track Nearest Neighbors
Vansh Ramani, Alexis Schlomer, Akash Nayar +3
Approximate Nearest-Neighbor Search (ANNS) pipelines for high-dimensional neural embeddings spend the bulk of their query time in candidate verification, making it the primary bott…
UniFFBench: Evaluating Universal Machine Learning Force Fields Against Experimental Measurements
Sajid Mannan, Vaibhav Bihani, Carmelo Gonzales +5
Universal machine learning force fields (UMLFFs) promise to revolutionize materials science by enabling rapid atomistic simulations across the periodic table. However, their evalua…
GRAIL: Graph Edit Distance and Node Alignment Using LLM-Generated Code
Samidha Verma, Arushi Goyal, Ananya Mathur +2
Graph Edit Distance (GED) is a widely used metric for measuring similarity between two graphs. Computing the optimal GED is NP-hard, leading to the development of various neural an…
GNNMerge: Merging of GNN Models Without Accessing Training Data
Vipul Garg, Ishita Thakre, Sayan Ranu
Model merging has gained prominence in machine learning as a method to integrate multiple trained models into a single model without accessing the original training data. While exi…