58 citations · 96 across the 13 of their papers we have counts for
5 papers · 1 filter
ShapeFlow: Dynamic Shape Interpreter for TensorFlow
Sahil Verma, Zhendong Su
We present ShapeFlow, a dynamic abstract interpreter for TensorFlow which quickly catches tensor shape incompatibility errors, one of the most common bugs in deep learning code. Sh…
Debug-Localize-Repair: A Symbiotic Construction for Heap Manipulations
Sahil Verma, Subhajit Roy
We present Wolverine2, an integrated Debug-Localize-Repair environment for heap manipulating programs. Wolverine2 provides an interactive debugging environment: while concretely ex…
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review
Sahil Verma, Varich Boonsanong, Minh Hoang +3
Machine learning plays a role in many deployed decision systems, often in ways that are difficult or impossible to understand by human stakeholders. Explaining, in a human-understa…
Facets of Fairness in Search and Recommendation
Sahil Verma, Ruoyuan Gao, Chirag Shah
Several recent works have highlighted how search and recommender systems exhibit bias along different dimensions. Counteracting this bias and bringing a certain amount of fairness…
Benchmarking Symbolic Execution Using Constraint Problems -- Initial Results
Sahil Verma, Roland H. C. Yap
Symbolic execution is a powerful technique for bug finding and program testing. It is successful in finding bugs in real-world code. The core reasoning techniques use constraint so…