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20162026
most citedOptimization and Abstraction: A Synergistic Approach for Analyzing Neural Network Robustness

84 citations · 356 across the 59 of their papers we have counts for

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Showing 2021Show all

6 papers · 1 filter

cs.SE2021

Counterfactual Explanations for Models of Code

Jürgen Cito, Isil Dillig, Vijayaraghavan Murali +1

Machine learning (ML) models play an increasingly prevalent role in many software engineering tasks. However, because most models are now powered by opaque deep neural networks, it…

cs.DB2021

Making Table Understanding Work in Practice

Madelon Hulsebos, Sneha Gathani, James Gale +3

Understanding the semantics of tables at scale is crucial for tasks like data integration, preparation, and search. Table understanding methods aim at detecting a table's topic, se…

cs.PL2021

Bottom-up Synthesis of Recursive Functional Programs using Angelic Execution

Anders Miltner, Adrian Trejo Nuñez, Ana Brendel +2

We present a novel bottom-up method for the synthesis of functional recursive programs. While bottom-up synthesis techniques can work better than top-down methods in certain settin…

cs.PL2021★ 1 cited

Web Question Answering with Neurosymbolic Program Synthesis

Qiaochu Chen, Aaron Lamoreaux, Xinyu Wang +3

In this paper, we propose a new technique based on program synthesis for extracting information from webpages. Given a natural language query and a few labeled webpages, our method…

cs.RO2021

OneVision: Centralized to Distributed Controller Synthesis with Delay Compensation

Jiayi Wei, Tongrui Li, Swarat Chaudhuri +2

We propose a new algorithm to simplify the controller development for distributed robotic systems subject to external observations, disturbances, and communication delays. Unlike p…

cs.HC2021★ 34 cited

Falx: Synthesis-Powered Visualization Authoring

Chenglong Wang, Yu Feng, Rastislav Bodik +3

Modern visualization tools aim to allow data analysts to easily create exploratory visualizations. When the input data layout conforms to the visualization design, users can easily…