no code implementations • ICML 2020 • Esteban Real, Chen Liang, David So, Quoc Le
However, this progress has largely focused on the architecture of neural networks, where it has relied on sophisticated expert-designed layers as building blocks---or similarly restrictive search spaces.
no code implementations • SemEval (NAACL) 2022 • Yangkun Lin, Chen Liang, Jing Xu, Chong Yang, Yongliang Wang
This paper presents our submission to task 10, Structured Sentiment Analysis of the SemEval 2022 competition.
no code implementations • 29 Nov 2023 • Zihao Tan, Qingliang Chen, Yongjian Huang, Chen Liang
Most of the existing attack methods focus on inserting manually predefined templates as triggers in the pre-training phase to train the victim model and utilize the same triggers in the downstream task to perform inference, which tends to ignore the transferability and stealthiness of the templates.
no code implementations • 16 Nov 2023 • Wei zhang, Dai Li, Chen Liang, Fang Zhou, Zhongke Zhang, Xuewei Wang, Ru Li, Yi Zhou, Yaning Huang, Dong Liang, Kai Wang, Zhangyuan Wang, Zhengxing Chen, Min Li, Fenggang Wu, Minghai Chen, Huayu Li, Yunnan Wu, Zhan Shu, Mindi Yuan, Sri Reddy
To address these challenges, we present Scaling User Modeling (SUM), a framework widely deployed in Meta's ads ranking system, designed to facilitate efficient and scalable sharing of online user representation across hundreds of ads models.
1 code implementation • 12 Oct 2023 • Yixiao Li, Yifan Yu, Chen Liang, Pengcheng He, Nikos Karampatziakis, Weizhu Chen, Tuo Zhao
Quantization is an indispensable technique for serving Large Language Models (LLMs) and has recently found its way into LoRA fine-tuning.
no code implementations • ICCV 2023 • Chen Liang, Wenguan Wang, Jiaxu Miao, Yi Yang
Recent advances in semi-supervised semantic segmentation have been heavily reliant on pseudo labeling to compensate for limited labeled data, disregarding the valuable relational knowledge among semantic concepts.
no code implementations • 21 Aug 2023 • Chen Liang
The development of ubiquitous computing and sensing devices has brought about novel interaction scenarios such as mixed reality and IoT (e. g., smart home), which pose new demands for the next generation of natural user interfaces (NUI).
no code implementations • 20 Jun 2023 • Yixiao Li, Yifan Yu, Qingru Zhang, Chen Liang, Pengcheng He, Weizhu Chen, Tuo Zhao
Pruning enhances the diversity of low-rank approximations, and low-rank approximation prevents pruning from losing too many expressive neurons.
1 code implementation • 30 May 2023 • Zhiyu Liang, Jianfeng Zhang, Chen Liang, Hongzhi Wang, Zheng Liang, Lujia Pan
Recent studies have shown great promise in unsupervised representation learning (URL) for multivariate time series, because URL has the capability in learning generalizable representation for many downstream tasks without using inaccessible labels.
no code implementations • 23 Apr 2023 • Xiaoming Wang, Chen Liang, Yulin Mei
In order to improve low-frequency characteristics of micro-perforated panel absorbers, sound absorption structures composed of micro-perforated panels and expansion chambers are design, and an optimization design method is constructed based on the transfer function model and the simulated annealing algorithm.
1 code implementation • 24 Mar 2023 • Zhiyu Liang, Chen Liang, Zheng Liang, Hongzhi Wang
Machine learning has emerged as a powerful tool for time series analysis.
no code implementations • 6 Mar 2023 • Bowen Wang, Chen Liang, Jiaze Wang, Furui Liu, Shaogang Hao, Dong Li, Jianye Hao, Guangyong Chen, Xiaolong Zou, Pheng-Ann Heng
Reversely, the model Reconstructs a more robust equilibrium state prediction by transforming edge-level predictions to node-level with a sphere-fitting algorithm.
Initial Structure to Relaxed Energy (IS2RE), Direct
Property Prediction
no code implementations • 19 Feb 2023 • Chen Liang, Haoming Jiang, Zheng Li, Xianfeng Tang, Bin Yin, Tuo Zhao
Since the teacher model has a significantly larger capacity and stronger representation power than the student model, it is very difficult for the student to produce predictions that match the teacher's over a massive amount of open-domain training data.
1 code implementation • 10 Feb 2023 • Ryan Gillard, Stephen Jonany, Yingjie Miao, Michael Munn, Connal de Souza, Jonathan Dungay, Chen Liang, David R. So, Quoc V. Le, Esteban Real
In this paper, we show that large efficiency gains can be obtained by employing a fast unified functional hash, especially through the functional equivalence caching technique, which we also present.
2 code implementations • 5 Oct 2022 • Chen Liang, Wenguan Wang, Jiaxu Miao, Yi Yang
Going beyond this, we propose GMMSeg, a new family of segmentation models that rely on a dense generative classifier for the joint distribution p(pixel feature, class).
1 code implementation • 4 Oct 2022 • Chen Liang, Simiao Zuo, Qingru Zhang, Pengcheng He, Weizhu Chen, Tuo Zhao
As such, TED reduces the knowledge gap between the two models and helps the student to fit better on the target task.
no code implementations • 15 Sep 2022 • Chen Liang, Bowen Wang, Shaogang Hao, Guangyong Chen, Pheng-Ann Heng, Xiaolong Zou
Graph neural networks (GNNs) have drawn more and more attention from material scientists and demonstrated a high capacity to establish connections between the structure and properties.
1 code implementation • 25 Jun 2022 • Qingru Zhang, Simiao Zuo, Chen Liang, Alexander Bukharin, Pengcheng He, Weizhu Chen, Tuo Zhao
Large Transformer-based models have exhibited superior performance in various natural language processing and computer vision tasks.
no code implementations • 12 May 2022 • Chen Liang, Alessandro Zocca, Steven H. Low, Adam Wierman
Transmission power systems usually consist of interconnected sub-grids that are operated relatively independently.
1 code implementation • NAACL 2022 • Simiao Zuo, Qingru Zhang, Chen Liang, Pengcheng He, Tuo Zhao, Weizhu Chen
We propose MoEBERT, which uses a Mixture-of-Experts structure to increase model capacity and inference speed.
1 code implementation • ACL 2022 • Chen Liang, Pengcheng He, Yelong Shen, Weizhu Chen, Tuo Zhao
To retain ensemble benefits while maintaining a low memory cost, we propose a consistency-regularized ensemble learning approach based on perturbed models, named CAMERO.
no code implementations • 11 Apr 2022 • David Patterson, Joseph Gonzalez, Urs Hölzle, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David So, Maud Texier, Jeff Dean
Four best practices can reduce ML training energy by up to 100x and CO2 emissions up to 1000x.
1 code implementation • CVPR 2022 • Chen Liang, Wenguan Wang, Tianfei Zhou, Yi Yang
In this paper, we propose a new task and dataset, Visual Abductive Reasoning (VAR), for examining abductive reasoning ability of machine intelligence in everyday visual situations.
1 code implementation • 18 Mar 2022 • Chen Liang, Wenguan Wang, Tianfei Zhou, Jiaxu Miao, Yawei Luo, Yi Yang
In light of this, we present Locater (local-global context aware Transformer), which augments the Transformer architecture with a finite memory so as to query the entire video with the language expression in an efficient manner.
Ranked #7 on
Referring Expression Segmentation
on A2D Sentences
Referring Expression Segmentation
Referring Video Object Segmentation
+5
1 code implementation • 18 Feb 2022 • Yuyang Wang, Rishikesh Magar, Chen Liang, Amir Barati Farimani
On most benchmarks, the generic GNN pre-trained by iMolCLR rivals or even surpasses supervised learning models with sophisticated architecture designs and engineered features.
1 code implementation • ICLR 2022 • Chen Liang, Haoming Jiang, Simiao Zuo, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao
Analysis shows that the proposed schedule indeed reduces the redundancy and improves generalization performance.
no code implementations • 9 Jan 2022 • Chunnan Wang, Chen Liang, Xiang Chen, Hongzhi Wang
They are lack of self-evaluation ability, that is, to examine the rationality of their prediction results, thus failing to guide users to identify high-quality ones from their candidate results.
no code implementations • 30 Dec 2021 • Chenlin Shen, Guangda Huzhang, YuHang Zhou, Chen Liang, Qing Da
Our algorithm can straightforwardly optimize the linear programming in the prime space, and its solution can be simply applied by a stochastic strategy to fulfill the optimized objective and the constraints in expectation.
no code implementations • 23 Dec 2021 • Chen Liang, Chong Yang, Jing Xu, Juyang Huang, Yongliang Wang, Yang Dong
Emotion recognition in conversation (ERC) has attracted much attention in recent years for its necessity in widespread applications.
Ranked #1 on
Emotion Recognition in Conversation
on DailyDialog
1 code implementation • 30 Nov 2021 • Rishikesh Magar, Yuyang Wang, Cooper Lorsung, Chen Liang, Hariharan Ramasubramanian, Peiyuan Li, Amir Barati Farimani
Inspired by the success of data augmentations in computer vision and natural language processing, we developed AugLiChem: the data augmentation library for chemical structures.
no code implementations • 29 Sep 2021 • Chen Liang, Yawei Luo, Yu Wu, Yi Yang
We focus on the problem of segmenting a certain object referred by a natural language sentence in video content, at the core of formulating a pinpoint vision-language relation.
no code implementations • Findings (NAACL) 2022 • Simiao Zuo, Yue Yu, Chen Liang, Haoming Jiang, Siawpeng Er, Chao Zhang, Tuo Zhao, Hongyuan Zha
In self-training, the student contributes to the prediction performance, and the teacher controls the training process by generating pseudo-labels.
1 code implementation • Findings (EMNLP) 2021 • Simiao Zuo, Chen Liang, Haoming Jiang, Pengcheng He, Xiaodong Liu, Jianfeng Gao, Weizhu Chen, Tuo Zhao
Adversarial regularization can improve model generalization in many natural language processing tasks.
no code implementations • CVPR 2021 • Jiaxu Miao, Yunchao Wei, Yu Wu, Chen Liang, Guangrui Li, Yi Yang
To the best of our knowledge, our VSPW is the first attempt to tackle the challenging video scene parsing task in the wild by considering diverse scenarios.
no code implementations • 2 Jun 2021 • Chen Liang, Yu Wu, Tianfei Zhou, Wenguan Wang, Zongxin Yang, Yunchao Wei, Yi Yang
Referring video object segmentation (RVOS) aims to segment video objects with the guidance of natural language reference.
One-shot visual object segmentation
Referring Video Object Segmentation
+2
1 code implementation • ACL 2021 • Chen Liang, Simiao Zuo, Minshuo Chen, Haoming Jiang, Xiaodong Liu, Pengcheng He, Tuo Zhao, Weizhu Chen
The Lottery Ticket Hypothesis suggests that an over-parametrized network consists of ``lottery tickets'', and training a certain collection of them (i. e., a subnetwork) can match the performance of the full model.
no code implementations • 21 Apr 2021 • David Patterson, Joseph Gonzalez, Quoc Le, Chen Liang, Lluis-Miquel Munguia, Daniel Rothchild, David So, Maud Texier, Jeff Dean
To help reduce the carbon footprint of ML, we believe energy usage and CO2e should be a key metric in evaluating models, and we are collaborating with MLPerf developers to include energy usage during training and inference in this industry standard benchmark.
1 code implementation • EMNLP 2021 • Simiao Zuo, Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Jianfeng Gao, Weizhu Chen, Tuo Zhao
Adversarial regularization has been shown to improve the generalization performance of deep learning models in various natural language processing tasks.
no code implementations • Findings (EMNLP) 2021 • Chen Liang, Haoming Jiang, Xiaodong Liu, Pengcheng He, Weizhu Chen, Jianfeng Gao, Tuo Zhao
Existing curriculum learning approaches to Neural Machine Translation (NMT) require sampling sufficient amounts of "easy" samples from training data at the early training stage.
no code implementations • 19 Mar 2021 • Chen Liang, Yu Wu, Yawei Luo, Yi Yang
Text-based video segmentation is a challenging task that segments out the natural language referred objects in videos.
Ranked #4 on
Referring Expression Segmentation
on J-HMDB
(Precision@0.9 metric)
no code implementations • 3 Feb 2021 • Tianchi Cai, Daxi Cheng, Chen Liang, Ziqi Liu, Lihong Gu, Huizhi Xie, Zhiqiang Zhang, Xiaodong Zeng, Jinjie Gu
In this paper, we analyze the network A/B testing problem under a real-world online marketing campaign, describe our proposed LinkLouvain method, and evaluate it on real-world data.
no code implementations • NeurIPS 2020 • Daiyi Peng, Xuanyi Dong, Esteban Real, Mingxing Tan, Yifeng Lu, Hanxiao Liu, Gabriel Bender, Adam Kraft, Chen Liang, Quoc V. Le
As a result, AutoML can be reformulated as an automated process of symbolic manipulation.
no code implementations • NeurIPS 2020 • Xinyun Chen, Chen Liang, Adams Wei Yu, Dawn Song, Denny Zhou
Despite achieving tremendous success, existing deep learning models have exposed limitations in compositional generalization, the capability to learn compositional rules and apply them to unseen cases in a systematic manner.
1 code implementation • 28 Jun 2020 • Chen Liang, Yue Yu, Haoming Jiang, Siawpeng Er, Ruijia Wang, Tuo Zhao, Chao Zhang
We study the open-domain named entity recognition (NER) problem under distant supervision.
no code implementations • 22 May 2020 • Linqi Guo, Chen Liang, Alessandro Zocca, Steven H. Low, Adam Wierman
Transmission line failure in power systems prop-agate non-locally, making the control of the resulting outages extremely difficult.
no code implementations • 22 May 2020 • Chen Liang, Linqi Guo, Alessandro Zocca, Steven H. Low, Adam Wierman
Transmission line failures in power systems propagate and cascade non-locally.
no code implementations • 20 May 2020 • Linqi Guo, Chen Liang, Alessandro Zocca, Steven H. Low, Adam Wierman
Transmission line failures in power systems propagate non-locally, making the control of the resulting outages extremely difficult.
no code implementations • ICLR 2020 • Xinyun Chen, Chen Liang, Adams Wei Yu, Denny Zhou, Dawn Song, Quoc V. Le
Integrating distributed representations with symbolic operations is essential for reading comprehension requiring complex reasoning, such as counting, sorting and arithmetics, but most existing approaches are hard to scale to more domains or more complex reasoning.
Ranked #5 on
Question Answering
on DROP Test
2 code implementations • 6 Mar 2020 • Esteban Real, Chen Liang, David R. So, Quoc V. Le
However, this progress has largely focused on the architecture of neural networks, where it has relied on sophisticated expert-designed layers as building blocks---or similarly restrictive search spaces.
no code implementations • 5 Mar 2020 • Cen Chen, Chen Liang, Jianbin Lin, Li Wang, Ziqi Liu, Xinxing Yang, Xiukun Wang, Jun Zhou, Yang Shuang, Yuan Qi
The insurance industry has been creating innovative products around the emerging online shopping activities.
no code implementations • 27 Feb 2020 • Chen Liang, Ziqi Liu, Bin Liu, Jun Zhou, Xiaolong Li, Shuang Yang, Yuan Qi
In order to detect and prevent fraudulent insurance claims, we developed a novel data-driven procedure to identify groups of organized fraudsters, one of the major contributions to financial losses, by learning network information.
1 code implementation • ACL 2020 • Haoming Jiang, Chen Liang, Chong Wang, Tuo Zhao
To overcome this limitation, we propose a novel multi-domain NMT model using individual modules for each domain, on which we apply word-level, adaptive and layer-wise domain mixing.
no code implementations • 15 Apr 2019 • Chen Liang, Weihong Wang, Zhenghua Liu, Chao Lai, Benchun Zhou
However the traditional MPPI framework assumes the actual environment similar to the training dataset for the deep neural network which is impractical in practice with different maneuvering of target, other perturbations and actuator failures.
Robotics Systems and Control
no code implementations • ICLR Workshop drlStructPred 2019 • Jacob Biloki, Chen Liang, Ni Lao
We consider the problem of weakly supervised structured prediction (SP) with reinforcement learning (RL) – for example, given a database table and a question, perform a sequence of computation actions on the table, which generates a response and receives a binary success-failure reward.
1 code implementation • 19 Feb 2019 • Rishabh Agarwal, Chen Liang, Dale Schuurmans, Mohammad Norouzi
The parameters of the auxiliary reward function are optimized with respect to the validation performance of a trained policy.
3 code implementations • 30 Jan 2019 • David R. So, Chen Liang, Quoc V. Le
Recent works have highlighted the strength of the Transformer architecture on sequence tasks while, at the same time, neural architecture search (NAS) has begun to outperform human-designed models.
Ranked #1 on
Machine Translation
on WMT2014 English-Czech
1 code implementation • 6 Nov 2018 • Jiaxin Shi, Chen Liang, Lei Hou, Juanzi Li, Zhiyuan Liu, Hanwang Zhang
We propose DeepChannel, a robust, data-efficient, and interpretable neural model for extractive document summarization.
4 code implementations • NeurIPS 2018 • Chen Liang, Mohammad Norouzi, Jonathan Berant, Quoc Le, Ni Lao
We present Memory Augmented Policy Optimization (MAPO), a simple and novel way to leverage a memory buffer of promising trajectories to reduce the variance of policy gradient estimate.
1 code implementation • WS 2018 • Chen Liang, Xiao Yang, Neisarg Dave, Drew Wham, Bart Pursel, C. Lee Giles
We investigate how machine learning models, specifically ranking models, can be used to select useful distractors for multiple choice questions.
no code implementations • 19 Jan 2018 • Chen Liang, Jianbo Ye, Han Zhao, Bart Pursel, C. Lee Giles
Strict partial order is a mathematical structure commonly seen in relational data.
no code implementations • 10 Nov 2017 • Junting Zhang, Chen Liang, C. -C. Jay Kuo
We evaluate the proposed network on large-scale domain adaptation experiments using both synthetic (GTA) and real (Cityscapes) images.
no code implementations • 11 Sep 2017 • Liang Tingting, He Lifang, Lu Chun-Ta, Chen Liang, Yu Philip S., Wu Jian
With the rapid development of mobile apps, the availability of a large number of mobile apps in application stores brings challenge to locate appropriate apps for users.
no code implementations • CVPR 2017 • Dafang He, Xiao Yang, Chen Liang, Zihan Zhou, Alexander G. Ororbi II, Daniel Kifer, C. Lee Giles
Scene text detection has attracted great attention these years.
no code implementations • 4 Dec 2016 • Chen Liang, Jonathan Berant, Quoc Le, Kenneth D. Forbus, Ni Lao
In this work, we propose the Manager-Programmer-Computer framework, which integrates neural networks with non-differentiable memory to support abstract, scalable and precise operations through a friendly neural computer interface.
2 code implementations • 1 Dec 2016 • Thanapon Noraset, Chen Liang, Larry Birnbaum, Doug Downey
Distributed representations of words have been shown to capture lexical semantics, as demonstrated by their effectiveness in word similarity and analogical relation tasks.
2 code implementations • ACL 2017 • Chen Liang, Jonathan Berant, Quoc Le, Kenneth D. Forbus, Ni Lao
Harnessing the statistical power of neural networks to perform language understanding and symbolic reasoning is difficult, when it requires executing efficient discrete operations against a large knowledge-base.
no code implementations • AAAI 2015 • Wenyi Huang, Zhaohui Wu, Chen Liang, Prasenjit Mitra, C. Lee Giles
It is not always easy for knowledgeable researchers to give an accurate citation context for a cited paper or to find the right paper to cite given context.