no code implementations • 25 Apr 2024 • Yu Jiang, Jie Liang, Fuchen Ma, Yuanliang Chen, Chijin Zhou, Yuheng Shen, Zhiyong Wu, Jingzhou Fu, Mingzhe Wang, Shanshan Li, Quan Zhang
Fuzzing, a widely-used technique for bug detection, has seen advancements through Large Language Models (LLMs).
1 code implementation • CVPR 2023 • Alexander Raistrick, Lahav Lipson, Zeyu Ma, Lingjie Mei, Mingzhe Wang, Yiming Zuo, Karhan Kayan, Hongyu Wen, Beining Han, Yihan Wang, Alejandro Newell, Hei Law, Ankit Goyal, Kaiyu Yang, Jia Deng
We introduce Infinigen, a procedural generator of photorealistic 3D scenes of the natural world.
no code implementations • 16 Nov 2022 • Jiaqi Cao, Shengli Zhang, Qingxia Chen, Houtian Wang, Mingzhe Wang, Naijin Liu
To address the network-wide offloading problem, we propose a metagraph-based computation and transmission fusion offloading scheme for multi-tier networks.
no code implementations • 16 Nov 2022 • Jiaqi Cao, Shengli Zhang, Mingzhe Wang, Qingxia Chen, Houtian Wang, Naijin Liu
However, the overall delay is determined by both computation and transmission costs.
1 code implementation • ECCV 2020 • Lanlan Liu, Mingzhe Wang, Jia Deng
We introduce UniLoss, a unified framework to generate surrogate losses for training deep networks with gradient descent, reducing the amount of manual design of task-specific surrogate losses.
2 code implementations • NeurIPS 2020 • Mingzhe Wang, Jia Deng
We consider the task of automated theorem proving, a key AI task.
Ranked #2 on Automated Theorem Proving on Metamath set.mm
no code implementations • NAACL 2018 • Mahmoud Azab, Mingzhe Wang, Max Smith, Noriyuki Kojima, Jia Deng, Rada Mihalcea
We propose a new model for speaker naming in movies that leverages visual, textual, and acoustic modalities in an unified optimization framework.
no code implementations • 30 Jun 2018 • Yuanliang Chen, Yu Jiang, Jie Liang, Mingzhe Wang, Xun Jiao
For evaluation, we implement EnFuzz , a prototype basing on four strong open-source fuzzers (AFL, AFLFast, AFLGo, FairFuzz), and test them on Google's fuzzing test suite, which consists of widely used real-world applications.
Software Engineering
1 code implementation • NeurIPS 2017 • Mingzhe Wang, Yihe Tang, Jian Wang, Jia Deng
We propose a deep learning-based approach to the problem of premise selection: selecting mathematical statements relevant for proving a given conjecture.
Ranked #1 on Automated Theorem Proving on HolStep (Unconditional)
8 code implementations • 12 Mar 2015 • Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, Qiaozhu Mei
This paper studies the problem of embedding very large information networks into low-dimensional vector spaces, which is useful in many tasks such as visualization, node classification, and link prediction.
Ranked #5 on Node Classification on Wikipedia