Search Results for author: Bei Yu

Found 59 papers, 18 papers with code

Detecting Health Advice in Medical Research Literature

1 code implementation EMNLP 2021 Yingya Li, Jun Wang, Bei Yu

We also conducted a case study that applied this prediction model to retrieve specific health advice on COVID-19 treatments from LitCovid, a large COVID research literature portal, demonstrating the usefulness of retrieving health advice sentences as an advanced research literature navigation function for health researchers and the general public.

Retrieval Sentence

CAMO: Correlation-Aware Mask Optimization with Modulated Reinforcement Learning

no code implementations1 Apr 2024 Xiaoxiao Liang, HaoYu Yang, Kang Liu, Bei Yu, Yuzhe ma

Optical proximity correction (OPC) is a vital step to ensure printability in modern VLSI manufacturing.


ChatPattern: Layout Pattern Customization via Natural Language

no code implementations15 Mar 2024 Zixiao Wang, Yunheng Shen, Xufeng Yao, Wenqian Zhao, Yang Bai, Farzan Farnia, Bei Yu

Existing works focus on fixed-size layout pattern generation, while the more practical free-size pattern generation receives limited attention.

Language Modelling Large Language Model

Learning-driven Physically-aware Large-scale Circuit Gate Sizing

no code implementations13 Mar 2024 Yuyang Ye, Peng Xu, Lizheng Ren, Tinghuan Chen, Hao Yan, Bei Yu, Longxing Shi

Gate sizing plays an important role in timing optimization after physical design.

Classes Are Not Equal: An Empirical Study on Image Recognition Fairness

1 code implementation28 Feb 2024 Jiequan Cui, Beier Zhu, Xin Wen, Xiaojuan Qi, Bei Yu, Hanwang Zhang

Second, with the proposed concept of Model Prediction Bias, we investigate the origins of problematic representation during optimization.

Contrastive Learning Data Augmentation +3

SoLA: Solver-Layer Adaption of LLM for Better Logic Reasoning

no code implementations19 Feb 2024 Yu Zhang, Hui-Ling Zhen, Zehua Pei, Yingzhao Lian, Lihao Yin, Mingxuan Yuan, Bei Yu

In this paper, we propose a novel solver-layer adaptation (SoLA) method, where we introduce a solver as a new layer of the LLM to differentially guide solutions towards satisfiability.

Logical Reasoning

BetterV: Controlled Verilog Generation with Discriminative Guidance

no code implementations3 Feb 2024 Zehua Pei, Hui-Ling Zhen, Mingxuan Yuan, Yu Huang, Bei Yu

In this work, we propose a Verilog generation framework, BetterV, which fine-tunes the large language models (LLMs) on processed domain-specific datasets and incorporates generative discriminators for guidance on particular design demands.

Text Generation

Parameter-Efficient Sparsity Crafting from Dense to Mixture-of-Experts for Instruction Tuning on General Tasks

1 code implementation5 Jan 2024 Haoyuan Wu, Haisheng Zheng, Zhuolun He, Bei Yu

Instruction tuning, a successful paradigm, enhances the ability of LLMs to follow natural language instructions and exhibit robust generalization across a wide range of tasks.

Arithmetic Reasoning Code Generation +5

p-Laplacian Adaptation for Generative Pre-trained Vision-Language Models

1 code implementation17 Dec 2023 Haoyuan Wu, Xinyun Zhang, Peng Xu, Peiyu Liao, Xufeng Yao, Bei Yu

In this paper, we present a novel modeling framework that recasts adapter tuning after attention as a graph message passing process on attention graphs, where the projected query and value features and attention matrix constitute the node features and the graph adjacency matrix, respectively.

Image Captioning Question Answering +3

TinyFormer: Efficient Transformer Design and Deployment on Tiny Devices

no code implementations3 Nov 2023 Jianlei Yang, Jiacheng Liao, Fanding Lei, Meichen Liu, Junyi Chen, Lingkun Long, Han Wan, Bei Yu, Weisheng Zhao

To the best of our knowledge, SparseEngine is the first deployment framework capable of performing inference of sparse models with transformer on MCUs.

On the Evaluation of Generative Models in Distributed Learning Tasks

no code implementations18 Oct 2023 Zixiao Wang, Farzan Farnia, Zhenghao Lin, Yunheng Shen, Bei Yu

First, we focus on the Fr\'echet inception distance (FID) and consider the following FID-based aggregate scores over the clients: 1) FID-avg as the mean of clients' individual FID scores, 2) FID-all as the FID distance of the trained model to the collective dataset containing all clients' data.

Avg Federated Learning

ChatEDA: A Large Language Model Powered Autonomous Agent for EDA

no code implementations20 Aug 2023 Zhuolun He, Haoyuan Wu, Xinyun Zhang, Xufeng Yao, Su Zheng, Haisheng Zheng, Bei Yu

The integration of a complex set of Electronic Design Automation (EDA) tools to enhance interoperability is a critical concern for circuit designers.

Language Modelling Large Language Model

Do Not Train It: A Linear Neural Architecture Search of Graph Neural Networks

1 code implementation23 May 2023 Peng Xu, Lin Zhang, Xuanzhou Liu, Jiaqi Sun, Yue Zhao, Haiqin Yang, Bei Yu

Neural architecture search (NAS) for Graph neural networks (GNNs), called NAS-GNNs, has achieved significant performance over manually designed GNN architectures.

Neural Architecture Search

Decoupled Kullback-Leibler Divergence Loss

4 code implementations23 May 2023 Jiequan Cui, Zhuotao Tian, Zhisheng Zhong, Xiaojuan Qi, Bei Yu, Hanwang Zhang

In this paper, we delve deeper into the Kullback-Leibler (KL) Divergence loss and observe that it is equivalent to the Doupled Kullback-Leibler (DKL) Divergence loss that consists of 1) a weighted Mean Square Error (wMSE) loss and 2) a Cross-Entropy loss incorporating soft labels.

Adversarial Defense Adversarial Robustness +1

Towards Versatile and Efficient Visual Knowledge Integration into Pre-trained Language Models with Cross-Modal Adapters

no code implementations12 May 2023 Xinyun Zhang, Haochen Tan, Han Wu, Bei Yu

To inject visual knowledge into PLMs, existing methods incorporate either the text or image encoder of vision-language models (VLMs) to encode the visual information and update all the original parameters of PLMs for knowledge fusion.

Natural Language Understanding

GPU-accelerated Matrix Cover Algorithm for Multiple Patterning Layout Decomposition

no code implementations25 Mar 2023 Guojin Chen, HaoYu Yang, Bei Yu

Multiple patterning lithography (MPL) is regarded as one of the most promising ways of overcoming the resolution limitations of conventional optical lithography due to the delay of next-generation lithography technology.

DiffPattern: Layout Pattern Generation via Discrete Diffusion

no code implementations23 Mar 2023 Zixiao Wang, Yunheng Shen, Wenqian Zhao, Yang Bai, Guojin Chen, Farzan Farnia, Bei Yu

Deep generative models dominate the existing literature in layout pattern generation.

DevelSet: Deep Neural Level Set for Instant Mask Optimization

no code implementations18 Mar 2023 Guojin Chen, Ziyang Yu, Hongduo Liu, Yuzhe ma, Bei Yu

To further enhance printability and fast iterative convergence, we propose a novel deep neural network delicately designed with level set intrinsic principles to facilitate the joint optimization of DNN and GPU accelerated level set optimizer.

AdaOPC: A Self-Adaptive Mask Optimization Framework For Real Design Patterns

no code implementations15 Mar 2023 Wenqian Zhao, Xufeng Yao, Ziyang Yu, Guojin Chen, Yuzhe ma, Bei Yu, Martin D. F. Wong

We inspect the pattern distribution on a design layer and find that different sub-regions have different pattern complexity.

Physics-Informed Optical Kernel Regression Using Complex-valued Neural Fields

no code implementations15 Mar 2023 Guojin Chen, Zehua Pei, HaoYu Yang, Yuzhe ma, Bei Yu, Martin D. F. Wong

Lithography is fundamental to integrated circuit fabrication, necessitating large computation overhead.


Efficient Deep Space Filling Curve

no code implementations ICCV 2023 Wanli Chen, Xufeng Yao, Xinyun Zhang, Bei Yu

By modeling the pixel grid as a graph, they first adopt GNN to predict the edge weights and then generate a minimum spanning tree (MST) based on the predictions, which is further used to construct the SFC.

Generalized Parametric Contrastive Learning

4 code implementations26 Sep 2022 Jiequan Cui, Zhisheng Zhong, Zhuotao Tian, Shu Liu, Bei Yu, Jiaya Jia

Based on theoretical analysis, we observe that supervised contrastive loss tends to bias high-frequency classes and thus increases the difficulty of imbalanced learning.

Contrastive Learning Domain Generalization +3

Rethinking Graph Neural Networks for the Graph Coloring Problem

no code implementations15 Aug 2022 Wei Li, Ruxuan Li, Yuzhe ma, Siu On Chan, David Pan, Bei Yu

Graph coloring, a classical and critical NP-hard problem, is the problem of assigning connected nodes as different colors as possible.

Towards Real-World Video Denosing: A Practical Video Denosing Dataset and Network

no code implementations4 Jul 2022 Xiaogang Xu, Yitong Yu, Nianjuan Jiang, Jiangbo Lu, Bei Yu, Jiaya Jia

Moreover, we also propose a new video denoising framework, called Recurrent Video Denoising Transformer (RVDT), which can achieve SOTA performance on PVDD and other current video denoising benchmarks.

Denoising Video Denoising

DSGN++: Exploiting Visual-Spatial Relation for Stereo-based 3D Detectors

1 code implementation6 Apr 2022 Yilun Chen, Shijia Huang, Shu Liu, Bei Yu, Jiaya Jia

First, to effectively lift the 2D information to stereo volume, we propose depth-wise plane sweeping (DPS) that allows denser connections and extracts depth-guided features.

3D Object Detection From Stereo Images Relation

Eventor: An Efficient Event-Based Monocular Multi-View Stereo Accelerator on FPGA Platform

no code implementations29 Mar 2022 Mingjun Li, Jianlei Yang, Yingjie Qi, Meng Dong, Yuhao Yang, Runze Liu, Weitao Pan, Bei Yu, Weisheng Zhao

In this paper, Eventor is proposed as a fast and efficient EMVS accelerator by realizing the most critical and time-consuming stages including event back-projection and volumetric ray-counting on FPGA.


PCL: Proxy-Based Contrastive Learning for Domain Generalization

1 code implementation CVPR 2022 Xufeng Yao, Yang Bai, Xinyun Zhang, Yuechen Zhang, Qi Sun, Ran Chen, Ruiyu Li, Bei Yu

Domain generalization refers to the problem of training a model from a collection of different source domains that can directly generalize to the unseen target domains.

Contrastive Learning Domain Generalization

Conditional Temporal Variational AutoEncoder for Action Video Prediction

no code implementations12 Aug 2021 Xiaogang Xu, Yi Wang, LiWei Wang, Bei Yu, Jiaya Jia

To synthesize a realistic action sequence based on a single human image, it is crucial to model both motion patterns and diversity in the action video.

motion prediction Video Prediction

Linking Health News to Research Literature

1 code implementation14 Jul 2021 Jun Wang, Bei Yu

Accurately linking news articles to scientific research works is a critical component in a number of applications, such as measuring the social impact of a research work and detecting inaccuracies or distortions in science news.

named-entity-recognition Named Entity Recognition +1

Self Promotion in US Congressional Tweets

1 code implementation NAACL 2021 Jun Wang, Kelly Cui, Bei Yu

Prior studies have found that women self-promote less than men due to gender stereotypes.

Routing Towards Discriminative Power of Class Capsules

no code implementations7 Mar 2021 HaoYu Yang, Shuhe Li, Bei Yu

The activation of lower layer capsules affects the behavior of the following capsules via routing links that are constructed during training via certain routing algorithms.

Rethinking Graph Neural Networks for Graph Coloring

no code implementations1 Jan 2021 Wei Li, Ruxuan Li, Yuzhe ma, Siu On Chan, Bei Yu

To characterize the power of GNNs for the graph coloring problem, we first formalize the discrimination power of GNNs as the capability to assign nodes different colors.

Measuring Correlation-to-Causation Exaggeration in Press Releases

1 code implementation COLING 2020 Bei Yu, Jun Wang, Lu Guo, Yingya Li

By comparing the claims made in a press release with the corresponding claims in the original research paper, we found that 22{\%} of press releases made exaggerated causal claims from correlational findings in observational studies.

Tensor Low-Rank Reconstruction for Semantic Segmentation

no code implementations ECCV 2020 Wanli Chen, Xinge Zhu, Ruoqi Sun, Junjun He, Ruiyu Li, Xiaoyong Shen, Bei Yu

Then we use these rank-1 tensors to recover the high-rank context features through our proposed tensor reconstruction module (TRM).

Semantic Segmentation

Dive Deeper Into Box for Object Detection

no code implementations ECCV 2020 Ran Chen, Yong liu, Mengdan Zhang, Shu Liu, Bei Yu, Yu-Wing Tai

Anchor free methods have defined the new frontier in state-of-the-art object detection researches where accurate bounding box estimation is the key to the success of these methods.

Object object-detection +1

Attacking Split Manufacturing from a Deep Learning Perspective

no code implementations8 Jul 2020 Haocheng Li, Satwik Patnaik, Abhrajit Sengupta, Hao-Yu Yang, Johann Knechtel, Bei Yu, Evangeline F. Y. Young, Ozgur Sinanoglu

The notion of integrated circuit split manufacturing which delegates the front-end-of-line (FEOL) and back-end-of-line (BEOL) parts to different foundries, is to prevent overproduction, piracy of the intellectual property (IP), or targeted insertion of hardware Trojans by adversaries in the FEOL facility.

VLSI Mask Optimization: From Shallow To Deep Learning

no code implementations16 Dec 2019 Haoyu Yang, Wei Zhong, Yuzhe ma, Hao Geng, Ran Chen, Wanli Chen, Bei Yu

VLSI mask optimization is one of the most critical stages in manufacturability aware design, which is costly due to the complicated mask optimization and lithography simulation.

BIG-bench Machine Learning

Detecting Causal Language Use in Science Findings

no code implementations IJCNLP 2019 Bei Yu, Yingya Li, Jun Wang

We then applied the prediction model to measure the causal language use in the research conclusions of about 38, 000 observational studies in PubMed.


Are Adversarial Perturbations a Showstopper for ML-Based CAD? A Case Study on CNN-Based Lithographic Hotspot Detection

no code implementations25 Jun 2019 Kang Liu, Hao-Yu Yang, Yuzhe ma, Benjamin Tan, Bei Yu, Evangeline F. Y. Young, Ramesh Karri, Siddharth Garg

There is substantial interest in the use of machine learning (ML) based techniques throughout the electronic computer-aided design (CAD) flow, particularly those based on deep learning.

DeepBillboard: Systematic Physical-World Testing of Autonomous Driving Systems

no code implementations27 Dec 2018 Husheng Zhou, Wei Li, Yuankun Zhu, Yuqun Zhang, Bei Yu, Lingming Zhang, Cong Liu

Furthermore, DeepBillboard is sufficiently robust and resilient for generating physical-world adversarial billboard tests for real-world driving under various weather conditions.

Autonomous Driving DNN Testing

An Evaluation of Information Extraction Tools for Identifying Health Claims in News Headlines

no code implementations COLING 2018 Shi Yuan, Bei Yu

This study evaluates the performance of four information extraction tools (extractors) on identifying health claims in health news headlines.

Relation Relation Extraction

A Unified Approximation Framework for Compressing and Accelerating Deep Neural Networks

no code implementations26 Jul 2018 Yuzhe Ma, Ran Chen, Wei Li, Fanhua Shang, Wenjian Yu, Minsik Cho, Bei Yu

To address this issue, various approximation techniques have been investigated, which seek for a light weighted network with little performance degradation in exchange of smaller model size or faster inference.

General Classification Image Classification +1

Recent Advances in Convolutional Neural Network Acceleration

no code implementations23 Jul 2018 Qianru Zhang, Meng Zhang, Tinghuan Chen, Zhifei Sun, Yuzhe ma, Bei Yu

We propose a taxonomy in terms of three levels, i. e.~structure level, algorithm level, and implementation level, for acceleration methods.

Image Classification

Cross-layer Optimization for High Speed Adders: A Pareto Driven Machine Learning Approach

1 code implementation18 Jul 2018 Yuzhe Ma, Subhendu Roy, Jin Miao, Jiamin Chen, Bei Yu

In spite of maturity to the modern electronic design automation (EDA) tools, optimized designs at architectural stage may become sub-optimal after going through physical design flow.

Active Learning BIG-bench Machine Learning

An NLP Analysis of Exaggerated Claims in Science News

no code implementations WS 2017 Yingya Li, Jieke Zhang, Bei Yu

The discrepancy between science and media has been affecting the effectiveness of science communication.

Misinformation Text Classification

Cannot find the paper you are looking for? You can Submit a new open access paper.