84 citations · 128 across the 9 of their papers we have counts for
5 papers · 1 filter
3D-RETR: End-to-End Single and Multi-View 3D Reconstruction with Transformers
Zai Shi, Zhao Meng, Yiran Xing +2
3D reconstruction aims to reconstruct 3D objects from 2D views. Previous works for 3D reconstruction mainly focus on feature matching between views or using CNNs as backbones. Rece…
BERT is Robust! A Case Against Synonym-Based Adversarial Examples in Text Classification
Jens Hauser, Zhao Meng, Damián Pascual +1
Deep Neural Networks have taken Natural Language Processing by storm. While this led to incredible improvements across many tasks, it also initiated a new research field, questioni…
Self-Supervised Contrastive Learning with Adversarial Perturbations for Defending Word Substitution-based Attacks
Zhao Meng, Yihan Dong, Mrinmaya Sachan +1
In this paper, we present an approach to improve the robustness of BERT language models against word substitution-based adversarial attacks by leveraging adversarial perturbations…
Towards Robust Graph Contrastive Learning
Nikola Jovanović, Zhao Meng, Lukas Faber +1
We study the problem of adversarially robust self-supervised learning on graphs. In the contrastive learning framework, we introduce a new method that increases the adversarial rob…
KM-BART: Knowledge Enhanced Multimodal BART for Visual Commonsense Generation
Yiran Xing, Zai Shi, Zhao Meng +3
We present Knowledge Enhanced Multimodal BART (KM-BART), which is a Transformer-based sequence-to-sequence model capable of reasoning about commonsense knowledge from multimodal in…