no code implementations • 13 Apr 2024 • Jiyang Li, Lechao Cheng, Zhangye Wang, Tingting Mu, Jingxuan He
In this paper, inspired by significant progress in the field of novel view synthesis (NVS) achieved by 3D Gaussian Splatting (3D-GS), we propose LoopGaussian to elevate cinemagraph from 2D image space to 3D space using 3D Gaussian modeling.
1 code implementation • 14 Feb 2024 • Jingxuan He, Mark Vero, Gabriela Krasnopolska, Martin Vechev
However, existing instruction tuning schemes overlook a crucial aspect: the security of generated code.
1 code implementation • 14 Dec 2023 • Jingxuan He, Lechao Cheng, Chaowei Fang, Zunlei Feng, Tingting Mu, Mingli Song
Building upon this, we introduce a complementary self-enhancement method that constrains the semantic consistency between these confident regions and an augmented image with the same class labels.
Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation
1 code implementation • 25 May 2023 • Niels Mündler, Jingxuan He, Slobodan Jenko, Martin Vechev
Large language models (large LMs) are susceptible to producing text that contains hallucinated content.
Hallucination Pair-wise Detection (1-ref) Informativeness +2
1 code implementation • 15 May 2023 • Fangwen Wu, Jingxuan He, Yufei Yin, Yanbin Hao, Gang Huang, Lechao Cheng
This study introduces an efficacious approach, Masked Collaborative Contrast (MCC), to highlight semantic regions in weakly supervised semantic segmentation.
Contrastive Learning Weakly supervised Semantic Segmentation +1
no code implementations • 4 May 2023 • Jingxuan He, Lechao Cheng, Chaowei Fang, Dingwen Zhang, Zhangye Wang, Wei Chen
A surge of interest has emerged in weakly supervised semantic segmentation due to its remarkable efficiency in recent years.
Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation
1 code implementation • 10 Feb 2023 • Jingxuan He, Martin Vechev
The task is parametric and takes as input a binary property to guide the LM to generate secure or unsafe code, while preserving the LM's capability of generating functionally correct code.
no code implementations • 15 Dec 2022 • Zerun Liu, Fan Zhang, Jingxuan He, Jin Wang, Zhangye Wang, Lechao Cheng
In the realm of multi-modality, text-guided image retouching techniques emerged with the advent of deep learning.
1 code implementation • 21 Apr 2022 • Jingxuan He, Luca Beurer-Kellner, Martin Vechev
To address this key challenge, we propose to train a bug detector in two phases, first on a synthetic bug distribution to adapt the model to the bug detection domain, and then on a real bug distribution to drive the model towards the real distribution.
1 code implementation • ICML 2021 • Berkay Berabi, Jingxuan He, Veselin Raychev, Martin Vechev
The problem of fixing errors in programs has attracted substantial interest over the years.
Ranked #1 on Program Repair on TFix's Code Patches Data