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Found 11 papers, 8 papers with code
Benchmarking Language Models for Code Syntax Understanding
Our key observation is that existing language models pretrained on code still lack the understanding of code syntax.
PALT: Parameter-Lite Transfer of Language Models for Knowledge Graph Completion
For instance, we outperform the fully finetuning approaches on a KG completion benchmark by tuning only 1% of the parameters.
Ranked #5 on
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on UMLS
LGV: Boosting Adversarial Example Transferability from Large Geometric Vicinity
We propose transferability from Large Geometric Vicinity (LGV), a new technique to increase the transferability of black-box adversarial attacks.
Efficient and Transferable Adversarial Examples from Bayesian Neural Networks
An established way to improve the transferability of black-box evasion attacks is to craft the adversarial examples on an ensemble-based surrogate to increase diversity.
Ansor : Generating High-Performance Tensor Programs for Deep Learning
Ansor can find high-performance programs that are outside the search space of existing state-of-the-art approaches.
QFAST: Quantum Synthesis Using a Hierarchical Continuous Circuit Space
We present QFAST, a quantum synthesis tool designed to produce short circuits and to scale well in practice.
Quantum Physics
When Deep Learning Met Code Search
Our evaluation shows that: 1. adding supervision to an existing unsupervised technique can improve performance, though not necessarily by much; 2. simple networks for supervision can be more effective that more sophisticated sequence-based networks for code search; 3. while it is common to use docstrings to carry out supervision, there is a sizeable gap between the effectiveness of docstrings and a more query-appropriate supervision corpus.
Aroma: Code Recommendation via Structural Code Search
Such a tool could help programmers to extend partially written code snippets to completely implement necessary functionality, help to discover extensions to the partial code which are commonly done by other programmers, help to cross-check against similar code written by other programmers, or help to add extra code which would avoid common mistakes and errors.
Software Engineering
Context2Name: A Deep Learning-Based Approach to Infer Natural Variable Names from Usage Contexts
Most of the JavaScript code deployed in the wild has been minified, a process in which identifier names are replaced with short, arbitrary and meaningless names.
DeepBugs: A Learning Approach to Name-based Bug Detection
We formulate bug detection as a binary classification problem and train a classifier that distinguishes correct from incorrect code.
Software Engineering Programming Languages
FairFuzz: Targeting Rare Branches to Rapidly Increase Greybox Fuzz Testing Coverage
However, AFL remains limited in the depth of program coverage it achieves, in particular because it does not consider which parts of program inputs should not be mutated in order to maintain deep program coverage.
Software Engineering Cryptography and Security
