no code implementations • 22 Nov 2023 • Nan Jiang, Chengxiao Wang, Kevin Liu, Xiangzhe Xu, Lin Tan, Xiangyu Zhang
We build Nova$^+$ to further boost Nova using two new pre-training tasks, i. e., optimization generation and optimization level prediction, which are designed to learn binary optimization and align equivalent binaries.
1 code implementation • 29 May 2023 • Yi Wu, Nan Jiang, Hung Viet Pham, Thibaud Lutellier, Jordan Davis, Lin Tan, Petr Babkin, Sameena Shah
The results call for innovations to enhance automated Java vulnerability repair such as creating larger vulnerability repair training data, tuning LLMs with such data, and applying code simplification transformation to facilitate vulnerability repair.
1 code implementation • 3 Feb 2023 • Nan Jiang, Thibaud Lutellier, Yiling Lou, Lin Tan, Dan Goldwasser, Xiangyu Zhang
KNOD has two major novelties, including (1) a novel three-stage tree decoder, which directly generates Abstract Syntax Trees of patched code according to the inherent tree structure, and (2) a novel domain-rule distillation, which leverages syntactic and semantic rules and teacher-student distributions to explicitly inject the domain knowledge into the decoding procedure during both the training and inference phases.
2 code implementations • 24 Nov 2022 • Pengfei Li, Gang Liu, Lin Tan, Jinying Liao, Shenjun Zhong
Medical image visual question answering (VQA) is a task to answer clinical questions, given a radiographic image, which is a challenging problem that requires a model to integrate both vision and language information.
Ranked #1 on Medical Visual Question Answering on SLAKE-English
no code implementations • NeurIPS 2021 • Shangshu Qian, Hung Pham, Thibaud Lutellier, Zeou Hu, Jungwon Kim, Lin Tan, YaoLiang Yu, Jiahao Chen, Sameena Shah
Our study of 22 mitigation techniques and five baselines reveals up to 12. 6% fairness variance across identical training runs with identical seeds.
1 code implementation • 26 Feb 2021 • Nan Jiang, Thibaud Lutellier, Lin Tan
Finally, CURE uses a subword tokenization technique to generate a smaller search space that contains more correct fixes.
1 code implementation • 18 Jul 2020 • Thibaud Lutellier, Hung Viet Pham, Lawrence Pang, Yitong Li, Moshi Wei, Lin Tan
To address these challenges, we propose a new G&V technique—CoCoNuT, which uses ensemble learning on the combination of convolutional neural networks (CNNs) and a new context-aware neural machine translation (NMT) architecture to automatically fix bugs in multiple programming languages.
no code implementations • 20 Jun 2019 • Thibaud Lutellier, Lawrence Pang, Viet Hung Pham, Moshi Wei, Lin Tan
We propose ENCORE, a new G&V technique, which uses ensemble learning on convolutional neural machine translation (NMT) models to automatically fix bugs in multiple programming languages.