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tech-srl

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code2vec

TensorFlow code for the neural network presented in the paper: "code2vec: Learning Distributed Representations of Code"

code2seq

Code for the model presented in the paper: "code2seq: Generating Sequences from Structured Representations of Code"

how_attentive_are_gats

Code for the paper "How Attentive are Graph Attention Networks?" (ICLR'2022)

RASP

An interpreter for RASP as described in the ICML 2021 paper "Thinking Like Transformers"

Nero

Code and resources for the paper: "Neural Reverse Engineering of Stripped Binaries using Augmented Control Flow Graphs"

bottleneck

Code for the paper: "On the Bottleneck of Graph Neural Networks and Its Practical Implications"

slm-code-generation

TensorFlow code for the neural network presented in the paper: "Structural Language Models of Code" (ICML'2020)

esh

statistical similarity of binaries (Esh)

lstar_extraction

implementation of ICML 2018 paper, Extracting Automata from Recurrent Neural Networks Using Queries and Counterexamples

Jupyter Notebook

layer_norm_expressivity_role

Code for the paper "On the Expressivity Role of LayerNorm in Transformers' Attention" (Findings of ACL'2023)

c3po

Code for the paper "A Structural Model for Contextual Code Changes"

adversarial-examples

Code for the paper: "Adversarial Examples for Models of Code"

weighted_lstar

implementation for "learning weighted deterministic automata from queries and counterexamples", neurips 2019

RASP-exps

Code for running the transformers in the ICML 2021 paper "Thinking Like Transformers"

prime

safe

SAFE static analysis tools

differential

counting_dimensions

demonstration for our ACL 2018 paper, "On the Practical Computational Power of Finite Precision RNNs for Language Recognition"

Jupyter Notebook

id2vec

RNN_to_PRS_CFG

Implementation of TACAS 2021 paper, "Extrapolating CFGs from RNNs"

atam

Example programs for ATAM