1 code implementation • EMNLP (ClinicalNLP) 2020 • Zixu Wang, Julia Ive, Sinead Moylett, Christoph Mueller, Rudolf Cardinal, Sumithra Velupillai, John O’Brien, Robert Stewart
To the best of our knowledge, this is the first attempt to distinguish DLB from AD using mental health records, and to improve the reliability of DLB predictions.
no code implementations • 30 Apr 2024 • Zhigang Sun, Zixu Wang, Lavdim Halilaj, Juergen Luettin
Trajectory prediction in autonomous driving relies on accurate representation of all relevant contexts of the driving scene including traffic participants, road topology, traffic signs as well as their semantic relations to each other.
1 code implementation • 20 Mar 2024 • Peng Zhou, Jianmin Wang, Chunyan Li, Zixu Wang, Yiping Liu, Siqi Sun, Jianxin Lin, Longyue Wang, Xiangxiang Zeng
While various models and computational tools have been proposed for structure and property analysis of molecules, generating molecules that conform to all desired structures and properties remains a challenge.
no code implementations • 8 Feb 2024 • Farnaz Niknia, Ping Wang, Zixu Wang, Aakash Agarwal, Adib S. Rezaei
This paper addresses the escalating challenge of redundant data transmission in networks.
1 code implementation • 15 Dec 2023 • Leon Mlodzian, Zhigang Sun, Hendrik Berkemeyer, Sebastian Monka, Zixu Wang, Stefan Dietze, Lavdim Halilaj, Juergen Luettin
Further, we present nuScenes Knowledge Graph (nSKG), a knowledge graph for the nuScenes dataset, that models explicitly all scene participants and road elements, as well as their semantic and spatial relationships.
no code implementations • 22 Jan 2023 • Md Abdullah-Al Kaiser, Gourav Datta, Zixu Wang, Ajey P. Jacob, Peter A. Beerel, Akhilesh R. Jaiswal
Edge devices equipped with computer vision must deal with vast amounts of sensory data with limited computing resources.
no code implementations • 19 Oct 2022 • Joshua Cesare Placidi, Yishu Miao, Zixu Wang, Lucia Specia
Scene Text Recognition (STR) models have achieved high performance in recent years on benchmark datasets where text images are presented with minimal noise.
no code implementations • 10 Oct 2022 • Zixu Wang, Yujie Zhong, Yishu Miao, Lin Ma, Lucia Specia
However, even in paired video-text segments, only a subset of the frames are semantically relevant to the corresponding text, with the remainder representing noise; where the ratio of noisy frames is higher for longer videos.
no code implementations • 28 May 2022 • Gourav Datta, Souvik Kundu, Zihan Yin, Joe Mathai, Zeyu Liu, Zixu Wang, Mulin Tian, Shunlin Lu, Ravi T. Lakkireddy, Andrew Schmidt, Wael Abd-Almageed, Ajey P. Jacob, Akhilesh R. Jaiswal, Peter A. Beerel
The designs also reduce the sensor and total energy (obtained from in-house circuit simulations at Globalfoundries 22nm technology node) per frame by 5. 7x and 1. 14x, respectively.
no code implementations • NAACL 2022 • Nihir Vedd, Zixu Wang, Marek Rei, Yishu Miao, Lucia Specia
In traditional Visual Question Generation (VQG), most images have multiple concepts (e. g. objects and categories) for which a question could be generated, but models are trained to mimic an arbitrary choice of concept as given in their training data.
no code implementations • 11 May 2021 • Zixu Wang, Yishu Miao, Lucia Specia
Experiments on Visual Question Answering as downstream task demonstrate the effectiveness of the proposed generative model, which is able to improve strong UpDn-based models to achieve state-of-the-art performance.
1 code implementation • EACL 2021 • Julia Ive, Zixu Wang, Marina Fomicheva, Lucia Specia
Reinforcement Learning (RL) is a powerful framework to address the discrepancy between loss functions used during training and the final evaluation metrics to be used at test time.
no code implementations • 16 Jan 2021 • Zixu Wang, Yishu Miao, Lucia Specia
Current work on Visual Question Answering (VQA) explore deterministic approaches conditioned on various types of image and question features.
2 code implementations • ECCV 2020 • Yixuan Li, Zixu Wang, Li-Min Wang, Gangshan Wu
The existing action tubelet detectors often depend on heuristic anchor design and placement, which might be computationally expensive and sub-optimal for precise localization.
Ranked #5 on Action Detection on UCF101-24
no code implementations • WS 2019 • Zixu Wang, Julia Ive, Sumithra Velupillai, Lucia Specia
A major obstacle to the development of Natural Language Processing (NLP) methods in the biomedical domain is data accessibility.