2 citations · 2 across the 3 of their papers we have counts for
4 papers
Interpreting Reasoning of Large Language Models via Partial Information Decomposition
Barproda Halder, Qiuyi Zhang, Sanghamitra Dutta
Large reasoning models (LRMs) have achieved substantial improvements in solving complex mathematical problems, but often produce lengthy, repetitive, or erroneous reasoning traject…
Learning Invariant Graph Representations Through Redundant Information
Barproda Halder, Pasan Dissanayake, Sanghamitra Dutta
Learning invariant graph representations for out-of-distribution (OOD) generalization remains challenging because the learned representations often retain spurious components. To a…
VISION: Robust and Interpretable Code Vulnerability Detection Leveraging Counterfactual Augmentation
David Egea, Barproda Halder, Sanghamitra Dutta
Automated detection of vulnerabilities in source code is an essential cybersecurity challenge, underpinning trust in digital systems and services. Graph Neural Networks (GNNs) have…
Demystifying the Accuracy-Interpretability Trade-Off: A Case Study of Inferring Ratings from Reviews
Pranjal Atrey, Michael P. Brundage, Min Wu +1
Interpretable machine learning models offer understandable reasoning behind their decision-making process, though they may not always match the performance of their black-box count…