Search Results for author: Yang Bai

Found 69 papers, 28 papers with code

HUB@DravidianLangTech-EACL2021: Identify and Classify Offensive Text in Multilingual Code Mixing in Social Media

no code implementations EACL (DravidianLangTech) 2021 Bo Huang, Yang Bai

Among the known tasks related to offensive speech detection, this is the first task to detect offensive comments posted in social media comments in the Dravidian language.

Classification Language Identification

Automatic Detecting for Health-related Twitter Data with BioBERT

no code implementations SMM4H (COLING) 2020 Yang Bai, Xiaobing Zhou

Social media used for health applications usually contains a large amount of data posted by users, which brings various challenges to NLP, such as spoken language, spelling errors, novel/creative phrases, etc.

Adversarial Robustness for Visual Grounding of Multimodal Large Language Models

no code implementations16 May 2024 Kuofeng Gao, Yang Bai, Jiawang Bai, Yong Yang, Shu-Tao Xia

Our methods not only provide a new perspective for designing novel attacks but also serve as a strong baseline for improving the adversarial robustness for visual grounding of MLLMs.

Adversarial Attack Adversarial Robustness +3

Special Characters Attack: Toward Scalable Training Data Extraction From Large Language Models

no code implementations9 May 2024 Yang Bai, Ge Pei, Jindong Gu, Yong Yang, Xingjun Ma

In this paper, we take a step further and show that certain special characters or their combinations with English letters are stronger memory triggers, leading to more severe data leakage.

Semi-supervised Text-based Person Search

no code implementations28 Apr 2024 Daming Gao, Yang Bai, Min Cao, Hao Dou, Mang Ye, Min Zhang

Text-based person search (TBPS) aims to retrieve images of a specific person from a large image gallery based on a natural language description.

Image Captioning Person Search +2

Energy-Latency Manipulation of Multi-modal Large Language Models via Verbose Samples

no code implementations25 Apr 2024 Kuofeng Gao, Jindong Gu, Yang Bai, Shu-Tao Xia, Philip Torr, Wei Liu, Zhifeng Li

For verbose videos, a frame feature diversity loss is proposed to increase the feature diversity among frames.

MedRG: Medical Report Grounding with Multi-modal Large Language Model

no code implementations10 Apr 2024 Ke Zou, Yang Bai, Zhihao Chen, Yang Zhou, Yidi Chen, Kai Ren, Meng Wang, Xuedong Yuan, Xiaojing Shen, Huazhu Fu

Medical Report Grounding is pivotal in identifying the most relevant regions in medical images based on a given phrase query, a critical aspect in medical image analysis and radiological diagnosis.

Decoder Language Modelling +3

M3: A Multi-Task Mixed-Objective Learning Framework for Open-Domain Multi-Hop Dense Sentence Retrieval

no code implementations21 Mar 2024 Yang Bai, Anthony Colas, Christan Grant, Daisy Zhe Wang

In recent research, contrastive learning has proven to be a highly effective method for representation learning and is widely used for dense retrieval.

Contrastive Learning Fact Verification +5

FMM-Attack: A Flow-based Multi-modal Adversarial Attack on Video-based LLMs

no code implementations20 Mar 2024 Jinmin Li, Kuofeng Gao, Yang Bai, Jingyun Zhang, Shu-Tao Xia, Yisen Wang

Despite the remarkable performance of video-based large language models (LLMs), their adversarial threat remains unexplored.

Adversarial Attack

Solving General Noisy Inverse Problem via Posterior Sampling: A Policy Gradient Viewpoint

no code implementations15 Mar 2024 Haoyue Tang, Tian Xie, Aosong Feng, Hanyu Wang, Chenyang Zhang, Yang Bai

Solving image inverse problems (e. g., super-resolution and inpainting) requires generating a high fidelity image that matches the given input (the low-resolution image or the masked image).

Image Restoration Super-Resolution

What Makes Good Collaborative Views? Contrastive Mutual Information Maximization for Multi-Agent Perception

1 code implementation15 Mar 2024 Wanfang Su, Lixing Chen, Yang Bai, Xi Lin, Gaolei Li, Zhe Qu, Pan Zhou

The core philosophy of CMiMC is to preserve discriminative information of individual views in the collaborative view by maximizing mutual information between pre- and post-collaboration features while enhancing the efficacy of collaborative views by minimizing the loss function of downstream tasks.

Contrastive Learning Philosophy

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

IMUOptimize: A Data-Driven Approach to Optimal IMU Placement for Human Pose Estimation with Transformer Architecture

no code implementations14 Feb 2024 Varun Ramani, Hossein Khayami, Yang Bai, Nakul Garg, Nirupam Roy

This paper presents a novel approach for predicting human poses using IMU data, diverging from previous studies such as DIP-IMU, IMUPoser, and TransPose, which use up to 6 IMUs in conjunction with bidirectional RNNs.

Pose Estimation Time Series +1

ConRF: Zero-shot Stylization of 3D Scenes with Conditioned Radiation Fields

1 code implementation2 Feb 2024 Xingyu Miao, Yang Bai, Haoran Duan, Fan Wan, Yawen Huang, Yang Long, Yefeng Zheng

Most of the existing works on arbitrary 3D NeRF style transfer required retraining on each single style condition.

Style Transfer

Cheating Suffix: Targeted Attack to Text-To-Image Diffusion Models with Multi-Modal Priors

1 code implementation2 Feb 2024 Dingcheng Yang, Yang Bai, Xiaojun Jia, Yang Liu, Xiaochun Cao, Wenjian Yu

The MMP-Attack shows a notable advantage over existing works with superior universality and transferability, which can effectively attack commercial text-to-image (T2I) models such as DALL-E 3.

Image Generation

Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images

1 code implementation20 Jan 2024 Kuofeng Gao, Yang Bai, Jindong Gu, Shu-Tao Xia, Philip Torr, Zhifeng Li, Wei Liu

Once attackers maliciously induce high energy consumption and latency time (energy-latency cost) during inference of VLMs, it will exhaust computational resources.

CTNeRF: Cross-Time Transformer for Dynamic Neural Radiance Field from Monocular Video

no code implementations10 Jan 2024 Xingyu Miao, Yang Bai, Haoran Duan, Yawen Huang, Fan Wan, Yang Long, Yefeng Zheng

The goal of our work is to generate high-quality novel views from monocular videos of complex and dynamic scenes.

VQA4CIR: Boosting Composed Image Retrieval with Visual Question Answering

1 code implementation19 Dec 2023 Chun-Mei Feng, Yang Bai, Tao Luo, Zhen Li, Salman Khan, WangMeng Zuo, Xinxing Xu, Rick Siow Mong Goh, Yong liu

By feeding the retrieved image and question to the VQA model, one can find the images inconsistent with relative caption when the answer by VQA is inconsistent with the answer in the QA pair.

Image Retrieval Question Answering +2

OT-Attack: Enhancing Adversarial Transferability of Vision-Language Models via Optimal Transport Optimization

no code implementations7 Dec 2023 Dongchen Han, Xiaojun Jia, Yang Bai, Jindong Gu, Yang Liu, Xiaochun Cao

Investigating the generation of high-transferability adversarial examples is crucial for uncovering VLP models' vulnerabilities in practical scenarios.

Adversarial Attack Data Augmentation +2

Fast Propagation is Better: Accelerating Single-Step Adversarial Training via Sampling Subnetworks

1 code implementation24 Oct 2023 Xiaojun Jia, Jianshu Li, Jindong Gu, Yang Bai, Xiaochun Cao

Besides, we provide theoretical analysis to show the model robustness can be improved by the single-step adversarial training with sampled subnetworks.

ASBART:Accelerated Soft Bayes Additive Regression Trees

1 code implementation21 Oct 2023 Hao Ran, Yang Bai

Bayes additive regression trees(BART) is a nonparametric regression model which has gained wide-spread popularity in recent years due to its flexibility and high accuracy of estimation.

regression

Sentence-level Prompts Benefit Composed Image Retrieval

1 code implementation9 Oct 2023 Yang Bai, Xinxing Xu, Yong liu, Salman Khan, Fahad Khan, WangMeng Zuo, Rick Siow Mong Goh, Chun-Mei Feng

Composed image retrieval (CIR) is the task of retrieving specific images by using a query that involves both a reference image and a relative caption.

Attribute Composed Image Retrieval (CoIR) +2

An Empirical Study of CLIP for Text-based Person Search

1 code implementation19 Aug 2023 Min Cao, Yang Bai, Ziyin Zeng, Mang Ye, Min Zhang

TPBS, as a fine-grained cross-modal retrieval task, is also facing the rise of research on the CLIP-based TBPS.

Cross-Modal Retrieval Data Augmentation +5

DS-Depth: Dynamic and Static Depth Estimation via a Fusion Cost Volume

1 code implementation14 Aug 2023 Xingyu Miao, Yang Bai, Haoran Duan, Yawen Huang, Fan Wan, Xinxing Xu, Yang Long, Yefeng Zheng

Nevertheless, the dynamic cost volume inevitably generates extra occlusions and noise, thus we alleviate this by designing a fusion module that makes static and dynamic cost volumes compensate for each other.

Monocular Depth Estimation Optical Flow Estimation +1

Can Knowledge Graphs Simplify Text?

1 code implementation14 Aug 2023 Anthony Colas, Haodi Ma, Xuanli He, Yang Bai, Daisy Zhe Wang

Knowledge Graph (KG)-to-Text Generation has seen recent improvements in generating fluent and informative sentences which describe a given KG.

Descriptive KG-to-Text Generation +3

MythQA: Query-Based Large-Scale Check-Worthy Claim Detection through Multi-Answer Open-Domain Question Answering

1 code implementation21 Jul 2023 Yang Bai, Anthony Colas, Daisy Zhe Wang

The idea behind this is that contradictory claims are a strong indicator of misinformation that merits scrutiny by the appropriate authorities.

Fact Checking Misinformation +1

RaSa: Relation and Sensitivity Aware Representation Learning for Text-based Person Search

1 code implementation23 May 2023 Yang Bai, Min Cao, Daming Gao, Ziqiang Cao, Chen Chen, Zhenfeng Fan, Liqiang Nie, Min Zhang

RA offsets the overfitting risk by introducing a novel positive relation detection task (i. e., learning to distinguish strong and weak positive pairs).

Person Search Relation +2

Text-based Person Search without Parallel Image-Text Data

no code implementations22 May 2023 Yang Bai, Jingyao Wang, Min Cao, Chen Chen, Ziqiang Cao, Liqiang Nie, Min Zhang

Text-based person search (TBPS) aims to retrieve the images of the target person from a large image gallery based on a given natural language description.

Image Captioning Language Modelling +4

Learning Procedure-aware Video Representation from Instructional Videos and Their Narrations

1 code implementation CVPR 2023 Yiwu Zhong, Licheng Yu, Yang Bai, Shangwen Li, Xueting Yan, Yin Li

In this work, we propose to learn video representation that encodes both action steps and their temporal ordering, based on a large-scale dataset of web instructional videos and their narrations, without using human annotations.

Backdoor Defense via Adaptively Splitting Poisoned Dataset

1 code implementation CVPR 2023 Kuofeng Gao, Yang Bai, Jindong Gu, Yong Yang, Shu-Tao Xia

With the split clean data pool and polluted data pool, ASD successfully defends against backdoor attacks during training.

backdoor defense

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.

Efficient Image-Text Retrieval via Keyword-Guided Pre-Screening

no code implementations14 Mar 2023 Min Cao, Yang Bai, Jingyao Wang, Ziqiang Cao, Liqiang Nie, Min Zhang

The proposed framework equipped with only two embedding layers achieves $O(1)$ querying time complexity, while improving the retrieval efficiency and keeping its performance, when applied prior to the common image-text retrieval methods.

Multi-Label Classification Multi-Task Learning +2

Temporal Segment Transformer for Action Segmentation

no code implementations25 Feb 2023 Zhichao Liu, Leshan Wang, Desen Zhou, Jian Wang, Songyang Zhang, Yang Bai, Errui Ding, Rui Fan

To deal with these issues, we propose an attention based approach which we call \textit{temporal segment transformer}, for joint segment relation modeling and denoising.

Action Segmentation Denoising +1

BackdoorBox: A Python Toolbox for Backdoor Learning

1 code implementation1 Feb 2023 Yiming Li, Mengxi Ya, Yang Bai, Yong Jiang, Shu-Tao Xia

Third-party resources ($e. g.$, samples, backbones, and pre-trained models) are usually involved in the training of deep neural networks (DNNs), which brings backdoor attacks as a new training-phase threat.

150 Years of Return Predictability Around the World: A Holistic View

no code implementations31 Aug 2022 Yang Bai

The predictive regressions based on the VAR analysis by Cochrane (2008, 2011) suggest that 14 (5) countries have predictable payout growth in the equity (housing) markets, ex., the dividend price predicts the dividend growth in the US.

MOVE: Effective and Harmless Ownership Verification via Embedded External Features

1 code implementation4 Aug 2022 Yiming Li, Linghui Zhu, Xiaojun Jia, Yang Bai, Yong Jiang, Shu-Tao Xia, Xiaochun Cao

In general, we conduct the ownership verification by verifying whether a suspicious model contains the knowledge of defender-specified external features.

Style Transfer

Action Quality Assessment with Temporal Parsing Transformer

1 code implementation19 Jul 2022 Yang Bai, Desen Zhou, Songyang Zhang, Jian Wang, Errui Ding, Yu Guan, Yang Long, Jingdong Wang

Action Quality Assessment(AQA) is important for action understanding and resolving the task poses unique challenges due to subtle visual differences.

Action Quality Assessment Action Understanding +2

Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal

1 code implementation17 Jul 2022 Xinwei Liu, Jian Liu, Yang Bai, Jindong Gu, Tao Chen, Xiaojun Jia, Xiaochun Cao

Inspired by the vulnerability of DNNs on adversarial perturbations, we propose a novel defence mechanism by adversarial machine learning for good.

Residual Local Feature Network for Efficient Super-Resolution

2 code implementations16 May 2022 Fangyuan Kong, Mingxi Li, Songwei Liu, Ding Liu, Jingwen He, Yang Bai, Fangmin Chen, Lean Fu

Moreover, we revisit the popular contrastive loss and observe that the selection of intermediate features of its feature extractor has great influence on the performance.

Image Super-Resolution SSIM

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

Automated Customization of On-Thing Inference for Quality-of-Experience Enhancement

no code implementations11 Dec 2021 Yang Bai, Lixing Chen, Shaolei Ren, Jie Xu

The core of our method is a DNN selection module that learns user QoE patterns on-the-fly and identifies the best-fit DNN for on-thing inference with the learned knowledge.

Transfer Learning

Clustering Effect of (Linearized) Adversarial Robust Models

1 code implementation25 Nov 2021 Yang Bai, Xin Yan, Yong Jiang, Shu-Tao Xia, Yisen Wang

Adversarial robustness has received increasing attention along with the study of adversarial examples.

Adversarial Robustness Clustering +1

More Than Reading Comprehension: A Survey on Datasets and Metrics of Textual Question Answering

no code implementations25 Sep 2021 Yang Bai, Daisy Zhe Wang

Textual Question Answering (QA) aims to provide precise answers to user's questions in natural language using unstructured data.

Machine Reading Comprehension Question Answering

Discriminative Latent Semantic Graph for Video Captioning

1 code implementation8 Aug 2021 Yang Bai, Junyan Wang, Yang Long, Bingzhang Hu, Yang song, Maurice Pagnucco, Yu Guan

Video captioning aims to automatically generate natural language sentences that can describe the visual contents of a given video.

Decoder Object +3

hub at SemEval-2021 Task 2: Word Meaning Similarity Prediction Model Based on RoBERTa and Word Frequency

no code implementations SEMEVAL 2021 Bo Huang, Yang Bai, Xiaobing Zhou

What we need to do is to use our method to determine as accurately as possible the meaning of the words in a sentence pair are the same or different.

Binary Classification Sentence +1

hub at SemEval-2021 Task 1: Fusion of Sentence and Word Frequency to Predict Lexical Complexity

no code implementations SEMEVAL 2021 Bo Huang, Yang Bai, Xiaobing Zhou

Use Inception block as a shared layer to learn sentence and word frequency information We described the implementation of our best system and discussed our methods and experiments in the task.

Lexical Complexity Prediction Sentence

hub at SemEval-2021 Task 7: Fusion of ALBERT and Word Frequency Information Detecting and Rating Humor and Offense

no code implementations SEMEVAL 2021 Bo Huang, Yang Bai

The final scores of the prediction results of the two subtask test sets submitted by our team are task1a 0. 921 (F1), task1a 0. 9364 (Accuracy), task1b 0. 6288 (RMSE), task1c 0. 5333 (F1), task1c 0. 0. 5591 (Accuracy), and task2 0. 5027 (RMSE) respectively.

Humor Detection regression +3

hub at SemEval-2021 Task 5: Toxic Span Detection Based on Word-Level Classification

no code implementations SEMEVAL 2021 Bo Huang, Yang Bai, Xiaobing Zhou

This article introduces the system description of the hub team, which explains the related work and experimental results of our team{'}s participation in SemEval 2021 Task 5: Toxic Spans Detection.

Toxic Spans Detection

Improving Adversarial Robustness via Channel-wise Activation Suppressing

1 code implementation ICLR 2021 Yang Bai, Yuyuan Zeng, Yong Jiang, Shu-Tao Xia, Xingjun Ma, Yisen Wang

The study of adversarial examples and their activation has attracted significant attention for secure and robust learning with deep neural networks (DNNs).

Adversarial Robustness

BYteam at SemEval-2020 Task 5: Detecting Counterfactual Statements with BERT and Ensembles

no code implementations SEMEVAL 2020 Yang Bai, Xiaobing Zhou

We participate in the classification tasks of SemEval-2020 Task: Subtask1: Detecting counterfactual statements of semeval-2020 task5(Detecting Counterfactuals).

Classification counterfactual

Bridge the Gap: High-level Semantic Planning for Image Captioning

no code implementations COLING 2020 Chenxi Yuan, Yang Bai, Chun Yuan

To bridge the gaps we propose a high-level semantic planning (HSP) mechanism that incorporates both a semantic reconstruction and an explicit order planning.

Image Captioning Vocal Bursts Intensity Prediction

SparTerm: Learning Term-based Sparse Representation for Fast Text Retrieval

no code implementations2 Oct 2020 Yang Bai, Xiaoguang Li, Gang Wang, Chaoliang Zhang, Lifeng Shang, Jun Xu, Zhaowei Wang, Fangshan Wang, Qun Liu

Term-based sparse representations dominate the first-stage text retrieval in industrial applications, due to its advantage in efficiency, interpretability, and exact term matching.

Language Modelling Retrieval +1

Improving Query Efficiency of Black-box Adversarial Attack

1 code implementation ECCV 2020 Yang Bai, Yuyuan Zeng, Yong Jiang, Yisen Wang, Shu-Tao Xia, Weiwei Guo

Deep neural networks (DNNs) have demonstrated excellent performance on various tasks, however they are under the risk of adversarial examples that can be easily generated when the target model is accessible to an attacker (white-box setting).

Adversarial Attack

Query Twice: Dual Mixture Attention Meta Learning for Video Summarization

no code implementations19 Aug 2020 Junyan Wang, Yang Bai, Yang Long, Bingzhang Hu, Zhenhua Chai, Yu Guan, Xiaolin Wei

Video summarization aims to select representative frames to retain high-level information, which is usually solved by predicting the segment-wise importance score via a softmax function.

Meta-Learning Video Summarization

Fatigue Assessment using ECG and Actigraphy Sensors

1 code implementation6 Aug 2020 Yang Bai, Yu Guan, Wan-Fai Ng

For deep learning solution, we used state-of-the-art self-attention model, based on which we further proposed a consistency self-attention (CSA) mechanism for fatigue assessment.

Decision Making Feature Engineering +1

Reinterpretation of LHC Results for New Physics: Status and Recommendations after Run 2

no code implementations17 Mar 2020 Waleed Abdallah, Shehu AbdusSalam, Azar Ahmadov, Amine Ahriche, Gaël Alguero, Benjamin C. Allanach, Jack Y. Araz, Alexandre Arbey, Chiara Arina, Peter Athron, Emanuele Bagnaschi, Yang Bai, Michael J. Baker, Csaba Balazs, Daniele Barducci, Philip Bechtle, Aoife Bharucha, Andy Buckley, Jonathan Butterworth, Haiying Cai, Claudio Campagnari, Cari Cesarotti, Marcin Chrzaszcz, Andrea Coccaro, Eric Conte, Jonathan M. Cornell, Louie Dartmoor Corpe, Matthias Danninger, Luc Darmé, Aldo Deandrea, Nishita Desai, Barry Dillon, Caterina Doglioni, Juhi Dutta, John R. Ellis, Sebastian Ellis, Farida Fassi, Matthew Feickert, Nicolas Fernandez, Sylvain Fichet, Jernej F. Kamenik, Thomas Flacke, Benjamin Fuks, Achim Geiser, Marie-Hélène Genest, Akshay Ghalsasi, Tomas Gonzalo, Mark Goodsell, Stefania Gori, Philippe Gras, Admir Greljo, Diego Guadagnoli, Sven Heinemeyer, Lukas A. Heinrich, Jan Heisig, Deog Ki Hong, Tetiana Hryn'ova, Katri Huitu, Philip Ilten, Ahmed Ismail, Adil Jueid, Felix Kahlhoefer, Jan Kalinowski, Deepak Kar, Yevgeny Kats, Charanjit K. Khosa, Valeri Khoze, Tobias Klingl, Pyungwon Ko, Kyoungchul Kong, Wojciech Kotlarski, Michael Krämer, Sabine Kraml, Suchita Kulkarni, Anders Kvellestad, Clemens Lange, Kati Lassila-Perini, Seung J. Lee, Andre Lessa, Zhen Liu, Lara Lloret Iglesias, Jeanette M. Lorenz, Danika MacDonell, Farvah Mahmoudi, Judita Mamuzic, Andrea C. Marini, Pete Markowitz, Pablo Martinez Ruiz del Arbol, David Miller, Vasiliki Mitsou, Stefano Moretti, Marco Nardecchia, Siavash Neshatpour, Dao Thi Nhung, Per Osland, Patrick H. Owen, Orlando Panella, Alexander Pankov, Myeonghun Park, Werner Porod, Darren Price, Harrison Prosper, Are Raklev, Jürgen Reuter, Humberto Reyes-González, Thomas Rizzo, Tania Robens, Juan Rojo, Janusz A. Rosiek, Oleg Ruchayskiy, Veronica Sanz, Kai Schmidt-Hoberg, Pat Scott, Sezen Sekmen, Dipan Sengupta, Elizabeth Sexton-Kennedy, Hua-Sheng Shao, Seodong Shin, Luca Silvestrini, Ritesh Singh, Sukanya Sinha, Jory Sonneveld, Yotam Soreq, Giordon H. Stark, Tim Stefaniak, Jesse Thaler, Riccardo Torre, Emilio Torrente-Lujan, Gokhan Unel, Natascia Vignaroli, Wolfgang Waltenberger, Nicholas Wardle, Graeme Watt, Georg Weiglein, Martin J. White, Sophie L. Williamson, Jonas Wittbrodt, Lei Wu, Stefan Wunsch, Tevong You, Yang Zhang, José Zurita

We report on the status of efforts to improve the reinterpretation of searches and measurements at the LHC in terms of models for new physics, in the context of the LHC Reinterpretation Forum.

High Energy Physics - Phenomenology High Energy Physics - Experiment

Hilbert-Based Generative Defense for Adversarial Examples

no code implementations ICCV 2019 Yang Bai, Yan Feng, Yisen Wang, Tao Dai, Shu-Tao Xia, Yong Jiang

Adversarial perturbations of clean images are usually imperceptible for human eyes, but can confidently fool deep neural networks (DNNs) to make incorrect predictions.

Dark Matter Benchmark Models for Early LHC Run-2 Searches: Report of the ATLAS/CMS Dark Matter Forum

1 code implementation3 Jul 2015 Daniel Abercrombie, Nural Akchurin, Ece Akilli, Juan Alcaraz Maestre, Brandon Allen, Barbara Alvarez Gonzalez, Jeremy Andrea, Alexandre Arbey, Georges Azuelos, Patrizia Azzi, Mihailo Backović, Yang Bai, Swagato Banerjee, James Beacham, Alexander Belyaev, Antonio Boveia, Amelia Jean Brennan, Oliver Buchmueller, Matthew R. Buckley, Giorgio Busoni, Michael Buttignol, Giacomo Cacciapaglia, Regina Caputo, Linda Carpenter, Nuno Filipe Castro, Guillelmo Gomez Ceballos, Yangyang Cheng, John Paul Chou, Arely Cortes Gonzalez, Chris Cowden, Francesco D'Eramo, Annapaola De Cosa, Michele De Gruttola, Albert De Roeck, Andrea De Simone, Aldo Deandrea, Zeynep Demiragli, Anthony DiFranzo, Caterina Doglioni, Tristan du Pree, Robin Erbacher, Johannes Erdmann, Cora Fischer, Henning Flaecher, Patrick J. Fox, Benjamin Fuks, Marie-Helene Genest, Bhawna Gomber, Andreas Goudelis, Johanna Gramling, John Gunion, Kristian Hahn, Ulrich Haisch, Roni Harnik, Philip C. Harris, Kerstin Hoepfner, Siew Yan Hoh, Dylan George Hsu, Shih-Chieh Hsu, Yutaro Iiyama, Valerio Ippolito, Thomas Jacques, Xiangyang Ju, Felix Kahlhoefer, Alexis Kalogeropoulos, Laser Seymour Kaplan, Lashkar Kashif, Valentin V. Khoze, Raman Khurana, Khristian Kotov, Dmytro Kovalskyi, Suchita Kulkarni, Shuichi Kunori, Viktor Kutzner, Hyun Min Lee, Sung-Won Lee, Seng Pei Liew, Tongyan Lin, Steven Lowette, Romain Madar, Sarah Malik, Fabio Maltoni, Mario Martinez Perez, Olivier Mattelaer, Kentarou Mawatari, Christopher McCabe, Théo Megy, Enrico Morgante, Stephen Mrenna, Siddharth M. Narayanan, Andy Nelson, Sérgio F. Novaes, Klaas Ole Padeken, Priscilla Pani, Michele Papucci, Manfred Paulini, Christoph Paus, Jacopo Pazzini, Björn Penning, Michael E. Peskin, Deborah Pinna, Massimiliano Procura, Shamona F. Qazi, Davide Racco, Emanuele Re, Antonio Riotto, Thomas G. Rizzo, Rainer Roehrig, David Salek, Arturo Sanchez Pineda, Subir Sarkar, Alexander Schmidt, Steven Randolph Schramm, William Shepherd, Gurpreet Singh, Livia Soffi, Norraphat Srimanobhas, Kevin Sung, Tim M. P. Tait, Timothee Theveneaux-Pelzer, Marc Thomas, Mia Tosi, Daniele Trocino, Sonaina Undleeb, Alessandro Vichi, Fuquan Wang, Lian-Tao Wang, Ren-Jie Wang, Nikola Whallon, Steven Worm, Mengqing Wu, Sau Lan Wu, Hongtao Yang, Yong Yang, Shin-Shan Yu, Bryan Zaldivar, Marco Zanetti, Zhiqing Zhang, Alberto Zucchetta

This document is the final report of the ATLAS-CMS Dark Matter Forum, a forum organized by the ATLAS and CMS collaborations with the participation of experts on theories of Dark Matter, to select a minimal basis set of dark matter simplified models that should support the design of the early LHC Run-2 searches.

High Energy Physics - Experiment High Energy Physics - Phenomenology

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