no code implementations • ECCV 2020 • Qing Liu, Orchid Majumder, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
This process enables incrementally improving the model by processing multiple learning episodes, each representing a different learning task, even with few training examples.
no code implementations • 27 Feb 2023 • Linhao Zhang, Li Jin, Xian Sun, Guangluan Xu, Zequn Zhang, Xiaoyu Li, Nayu Liu, Shiyao Yan, Qing Liu
Multimodal hate detection, which aims to identify harmful content online such as memes, is crucial for building a wholesome internet environment.
no code implementations • 21 Feb 2023 • Yunzhong He, Cong Zhang, Ruoyan Kong, Chaitanya Kulkarni, Qing Liu, Ashish Gandhe, Amit Nithianandan, Arul Prakash
Query categorization at customer-to-customer e-commerce platforms like Facebook Marketplace is challenging due to the vagueness of search intent, noise in real-world data, and imbalanced training data across languages.
no code implementations • 22 Dec 2022 • Srinivasan Iyer, Xi Victoria Lin, Ramakanth Pasunuru, Todor Mihaylov, Daniel Simig, Ping Yu, Kurt Shuster, Tianlu Wang, Qing Liu, Punit Singh Koura, Xian Li, Brian O'Horo, Gabriel Pereyra, Jeff Wang, Christopher Dewan, Asli Celikyilmaz, Luke Zettlemoyer, Ves Stoyanov
To this end, we create OPT-IML Bench: a large benchmark for Instruction Meta-Learning (IML) of 2000 NLP tasks consolidated into task categories from 8 existing benchmarks, and prepare an evaluation framework to measure three types of model generalizations: to tasks from fully held-out categories, to held-out tasks from seen categories, and to held-out instances from seen tasks.
Ranked #15 on Natural Language Inference on RTE
no code implementations • 13 Dec 2022 • Haitian Zheng, Zhe Lin, Jingwan Lu, Scott Cohen, Eli Shechtman, Connelly Barnes, Jianming Zhang, Qing Liu, Yuqian Zhou, Sohrab Amirghodsi, Jiebo Luo
Moreover, the object-level discriminators take aligned instances as inputs to enforce the realism of individual objects.
no code implementations • 21 Nov 2022 • Yu Zeng, Zhe Lin, Jianming Zhang, Qing Liu, John Collomosse, Jason Kuen, Vishal M. Patel
We propose a new framework for conditional image synthesis from semantic layouts of any precision levels, ranging from pure text to a 2D semantic canvas with precise shapes.
no code implementations • 19 Nov 2022 • Yi Yang, Zhong-Qiu Zhao, Quan Bai, Qing Liu, Weihua Li
Due to the dynamic nature, the proposed algorithms can also estimate true labels online without re-visiting historical data.
no code implementations • 7 Nov 2022 • Qing Liu, Wenli Yang, Shiqing Wu
Over the past two decades, PKAW has provided a forum for researchers and practitioners to discuss the state-of-the-arts in the area of knowledge acquisition and machine intelligence (MI, also Artificial Intelligence, AI).
1 code implementation • 11 Jul 2022 • Yixiong Liang, Shuo Feng, Qing Liu, Hulin Kuang, Jianfeng Liu, Liyan Liao, Yun Du, Jianxin Wang
To mimic these behaviors, we propose to explore contextual relationships to boost the performance of cervical abnormal cell detection.
no code implementations • 7 Jun 2022 • Jinkai Tian, Xiaoyu Sun, Yuxuan Du, Shanshan Zhao, Qing Liu, Kaining Zhang, Wei Yi, Wanrong Huang, Chaoyue Wang, Xingyao Wu, Min-Hsiu Hsieh, Tongliang Liu, Wenjing Yang, DaCheng Tao
Due to the intrinsic probabilistic nature of quantum mechanics, it is reasonable to postulate that quantum generative learning models (QGLMs) may surpass their classical counterparts.
1 code implementation • ACL 2022 • Yaojie Lu, Qing Liu, Dai Dai, Xinyan Xiao, Hongyu Lin, Xianpei Han, Le Sun, Hua Wu
Information extraction suffers from its varying targets, heterogeneous structures, and demand-specific schemas.
1 code implementation • ACL 2022 • Jiawei Chen, Qing Liu, Hongyu Lin, Xianpei Han, Le Sun
In this paper, we propose a self-describing mechanism for few-shot NER, which can effectively leverage illustrative instances and precisely transfer knowledge from external resources by describing both entity types and mentions using a universal concept set.
no code implementations • 22 Jan 2022 • Jingwen Zhang, Qing Liu, Haorui Zhang, Michelle Dai, Qianqian Song, Defu Yang, Guorong Wu, Minghan Chen
Despite the striking efforts in investigating neurobiological factors behind the acquisition of beta-amyloid (A), protein tau (T), and neurodegeneration ([N]) biomarkers, the mechanistic pathways of how AT[N] biomarkers spread throughout the brain remain elusive.
no code implementations • 5 Dec 2021 • Qing Wang, Qing Liu, Zihao Zhang, HaoYu Fang, Xi Zheng
Artificial intelligence (AI) based device identification improves the security of the internet of things (IoT), and accelerates the authentication process.
1 code implementation • 30 Oct 2021 • Qing Liu, Haotian Liu, Wei Ke, Yixiong Liang
It reassembles features in a dimension-reduced feature space and simultaneously aggregates multiple features inside a large predefined region into multiple target features.
no code implementations • 26 Oct 2021 • Yixiao Zhang, Adam Kortylewski, Qing Liu, Seyoun Park, Benjamin Green, Elizabeth Engle, Guillermo Almodovar, Ryan Walk, Sigfredo Soto-Diaz, Janis Taube, Alex Szalay, Alan Yuille
It only requires annotations on isolated nucleus, rather than on all nuclei in the dataset.
no code implementations • 18 Oct 2021 • Yunjia Xi, Weiwen Liu, Xinyi Dai, Ruiming Tang, Weinan Zhang, Qing Liu, Xiuqiang He, Yong Yu
As a critical task for large-scale commercial recommender systems, reranking has shown the potential of improving recommendation results by uncovering mutual influence among items.
no code implementations • EMNLP 2021 • Qing Liu, Hongyu Lin, Xinyan Xiao, Xianpei Han, Le Sun, Hua Wu
Conventional entity typing approaches are based on independent classification paradigms, which make them difficult to recognize inter-dependent, long-tailed and fine-grained entity types.
Ranked #7 on Entity Typing on Open Entity
no code implementations • 23 Aug 2021 • Qing Liu, Longbing Cao
Different from existing COVID-19 models, SUDR characterizes the undocumented infections during unknown transmission processes.
no code implementations • 9 Jun 2021 • Xiangli Yang, Qing Liu, Rong Su, Ruiming Tang, Zhirong Liu, Xiuqiang He
The field-wise transfer policy decides how the pre-trained embedding representations are frozen or fine-tuned based on the given instance from the target domain.
no code implementations • 14 May 2021 • Nicholas Ichien, Qing Liu, Shuhao Fu, Keith J. Holyoak, Alan Yuille, Hongjing Lu
We compared human performance to that of two recent deep learning models (Siamese Network and Relation Network) directly trained to solve these analogy problems, as well as to that of a compositional model that assesses relational similarity between part-based representations.
no code implementations • NAACL 2021 • Anish Acharya, Suranjit Adhikari, Sanchit Agarwal, Vincent Auvray, Nehal Belgamwar, Arijit Biswas, Shubhra Chandra, Tagyoung Chung, Maryam Fazel-Zarandi, Raefer Gabriel, Shuyang Gao, Rahul Goel, Dilek Hakkani-Tur, Jan Jezabek, Abhay Jha, Jiun-Yu Kao, Prakash Krishnan, Peter Ku, Anuj Goyal, Chien-Wei Lin, Qing Liu, Arindam Mandal, Angeliki Metallinou, Vishal Naik, Yi Pan, Shachi Paul, Vittorio Perera, Abhishek Sethi, Minmin Shen, Nikko Strom, Eddie Wang
Finally, we evaluate our system using a typical movie ticket booking task and show that the dialogue simulator is an essential component of the system that leads to over $50\%$ improvement in turn-level action signature prediction accuracy.
no code implementations • 16 Apr 2021 • Longbing Cao, Qing Liu
The SARS-CoV-2 virus and COVID-19 disease have posed unprecedented and overwhelming demand, challenges and opportunities to domain, model and data driven modeling.
1 code implementation • CVPR 2022 • Qing Liu, Adam Kortylewski, Zhishuai Zhang, Zizhang Li, Mengqi Guo, Qihao Liu, Xiaoding Yuan, Jiteng Mu, Weichao Qiu, Alan Yuille
We believe our dataset provides a rich testbed to study UDA for part segmentation and will help to significantly push forward research in this area.
no code implementations • CVPR 2021 • Qing Liu, Vignesh Ramanathan, Dhruv Mahajan, Alan Yuille, Zhenheng Yang
However, existing approaches which rely only on image-level class labels predominantly suffer from errors due to (a) partial segmentation of objects and (b) missing object predictions.
no code implementations • 7 Mar 2021 • Qing Liu, Defu Yang, Jingwen Zhang, Ziming Wei, Guorong Wu, Minghan Chen
Three major biomarkers: beta-amyloid (A), pathologic tau (T), and neurodegeneration (N), are recognized as valid proxies for neuropathologic changes of Alzheimer's disease.
no code implementations • 26 Feb 2021 • Cheng Xie, Ting Zeng, Hongxin Xiang, Keqin Li, Yun Yang, Qing Liu
The approach also applies a semi-supervised learning process to re-train knowledge-to-visual model.
no code implementations • 25 Jan 2021 • Cheng Xie, Hongxin Xiang, Ting Zeng, Yun Yang, Beibei Yu, Qing Liu
CKL enables more relevant semantic features to be trained for semantic-to-visual feature embedding in ZSL, while Taxonomy Regularization (TR) significantly improves the intersections with unseen images with more generalized visual features generated from generative network.
no code implementations • 31 Dec 2020 • Ziwen Xu, Beiji Zou, Qing Liu
Dual-branch SalStructIQA contains two CNN branches and one is guided by large-size salient structures while the other is guided by tiny-size salient structures.
no code implementations • 3 Dec 2020 • Qing Liu, Haotian Liu, Yixiong Liang
In detail, for the first branch, we use a uniform sampler to sample pixels from predicted segmentation mask for Dice loss calculation, which leads to this branch naturally be biased in favour of large hard exudates as Dice loss generates larger cost on misidentification of large hard exudates than small hard exudates.
no code implementations • 1 Nov 2020 • Xinyi Dai, Jiawei Hou, Qing Liu, Yunjia Xi, Ruiming Tang, Weinan Zhang, Xiuqiang He, Jun Wang, Yong Yu
To this end, we propose a novel ranking framework called U-rank that directly optimizes the expected utility of the ranking list.
no code implementations • 26 Oct 2020 • Ziwen Xu, Beiji Zou, Qing Liu
Retinal image quality assessment is an essential task in the diagnosis of retinal diseases.
no code implementations • 28 Jun 2020 • Adam Kortylewski, Qing Liu, Angtian Wang, Yihong Sun, Alan Yuille
The structure of the compositional model enables CompositionalNets to decompose images into objects and context, as well as to further decompose object representations in terms of individual parts and the objects' pose.
1 code implementation • CVPR 2020 • Adam Kortylewski, Ju He, Qing Liu, Alan Yuille
Inspired by the success of compositional models at classifying partially occluded objects, we propose to integrate compositional models and DCNNs into a unified deep model with innate robustness to partial occlusion.
no code implementations • 11 Feb 2020 • Qing Liu, Orchid Majumder, Alessandro Achille, Avinash Ravichandran, Rahul Bhotika, Stefano Soatto
Majority of the modern meta-learning methods for few-shot classification tasks operate in two phases: a meta-training phase where the meta-learner learns a generic representation by solving multiple few-shot tasks sampled from a large dataset and a testing phase, where the meta-learner leverages its learnt internal representation for a specific few-shot task involving classes which were not seen during the meta-training phase.
no code implementations • 18 Nov 2019 • Adam Kortylewski, Qing Liu, Huiyu Wang, Zhishuai Zhang, Alan Yuille
Our experimental results demonstrate that the proposed extensions increase the model's performance at localizing occluders as well as at classifying partially occluded objects.
no code implementations • 5 Nov 2019 • Qing Liu, Beiji Zou, Yang Zhao, Yixiong Liang
To build connections among prediction branches, this paper introduces gradient boosting framework to deep classification model and proposes a gradient boosting network called BoostNet.
no code implementations • 11 Sep 2019 • Yukun Zhou, Zailiang Chen, Hailan Shen, Qing Liu, Rongchang Zhao, Yixiong Liang
In each branch, the input feature map is deduced into an enhancement map and a mask map, thereby highlighting the most discriminative parts or hiding them.
no code implementations • 28 May 2019 • Adam Kortylewski, Qing Liu, Huiyu Wang, Zhishuai Zhang, Alan Yuille
In this work, we combine DCNNs and compositional object models to retain the best of both approaches: a discriminative model that is robust to partial occlusion and mask attacks.
no code implementations • 18 Apr 2019 • Qing Liu, Xiaopeng Hong, Wei Ke, Zailiang Chen, Beiji Zou
In this paper, we propose a novel segmentation approach, named Cartesian-polar dual-domain network (DDNet), which for the first time considers the complementary of the Cartesian domain and the polar domain.
1 code implementation • ICCV 2019 • Qing Liu, Lingxi Xie, Huiyu Wang, Alan Yuille
Sketch-based image retrieval (SBIR) is widely recognized as an important vision problem which implies a wide range of real-world applications.
no code implementations • 27 Dec 2018 • Chandra Khatri, Behnam Hedayatnia, Anu Venkatesh, Jeff Nunn, Yi Pan, Qing Liu, Han Song, Anna Gottardi, Sanjeev Kwatra, Sanju Pancholi, Ming Cheng, Qinglang Chen, Lauren Stubel, Karthik Gopalakrishnan, Kate Bland, Raefer Gabriel, Arindam Mandal, Dilek Hakkani-Tur, Gene Hwang, Nate Michel, Eric King, Rohit Prasad
In the second iteration of the competition in 2018, university teams advanced the state of the art by using context in dialog models, leveraging knowledge graphs for language understanding, handling complex utterances, building statistical and hierarchical dialog managers, and leveraging model-driven signals from user responses.
1 code implementation • ICCV 2019 • Yutong Bai, Qing Liu, Lingxi Xie, Weichao Qiu, Yan Zheng, Alan Yuille
In particular, this enables images in the training dataset to be matched to a virtual 3D model of the object (for simplicity, we assume that the object viewpoint can be estimated by standard techniques).
1 code implementation • 14 Oct 2018 • Yixiong Liang, Zhihong Tang, Meng Yan, Jialin Chen, Qing Liu, Yao Xiang
In this paper we propose an efficient CNN-based object detection methods for cervical cancer cells/clumps detection.
no code implementations • 11 Jan 2018 • Ashwin Ram, Rohit Prasad, Chandra Khatri, Anu Venkatesh, Raefer Gabriel, Qing Liu, Jeff Nunn, Behnam Hedayatnia, Ming Cheng, Ashish Nagar, Eric King, Kate Bland, Amanda Wartick, Yi Pan, Han Song, Sk Jayadevan, Gene Hwang, Art Pettigrue
This paper outlines the advances created by the university teams as well as the Alexa Prize team to achieve the common goal of solving the problem of Conversational
no code implementations • ICLR 2018 • Boyang Deng, Qing Liu, Siyuan Qiao, Alan Yuille
Our models are based on the idea of encoding objects in terms of visual concepts, which are interpretable visual cues represented by the feature vectors within CNNs.
no code implementations • 22 Nov 2017 • Boyang Deng, Qing Liu, Siyuan Qiao, Alan Yuille
In this work, we address these limitations of CNNs by developing novel, flexible, and interpretable models for few-shot learning.