activity
20182022
most citedRewarding Smatch: Transition-Based AMR Parsing with Reinforcement Learning

13 citations · 14 across the 2 of their papers we have counts for

collaborators

8 papers

cs.CR20221 cited

Effective Seed Scheduling for Fuzzing with Graph Centrality Analysis

Dongdong She, Abhishek Shah, Suman Jana

Seed scheduling, the order in which seeds are selected, can greatly affect the performance of a fuzzer. Existing approaches schedule seeds based on their historical mutation data,…

cs.CL2020

Benchmarking Commercial Intent Detection Services with Practice-Driven Evaluations

Haode Qi, Lin Pan, Atin Sood +4

Intent detection is a key component of modern goal-oriented dialog systems that accomplish a user task by predicting the intent of users' text input. There are three primary challe…

cs.CL2020

Multilingual BERT Post-Pretraining Alignment

Lin Pan, Chung-Wei Hang, Haode Qi +3

We propose a simple method to align multilingual contextual embeddings as a post-pretraining step for improved zero-shot cross-lingual transferability of the pretrained models. Usi…

cs.LG2020

Iterative Data Programming for Expanding Text Classification Corpora

Neil Mallinar, Abhishek Shah, Tin Kam Ho +2

Real-world text classification tasks often require many labeled training examples that are expensive to obtain. Recent advancements in machine teaching, specifically the data progr…

cs.CR2019

Fine Grained Dataflow Tracking with Proximal Gradients

Gabriel Ryan, Abhishek Shah, Dongdong She +2

Dataflow tracking with Dynamic Taint Analysis (DTA) is an important method in systems security with many applications, including exploit analysis, guided fuzzing, and side-channel…

cs.CR2019

Neutaint: Efficient Dynamic Taint Analysis with Neural Networks

Dongdong She, Yizheng Chen, Abhishek Shah +2

Dynamic taint analysis (DTA) is widely used by various applications to track information flow during runtime execution. Existing DTA techniques use rule-based taint-propagation, wh…