AAAI
Collection
Accepted papers for AAAI (AAAI Conference on Artificial Intelligence), one dataset per year. • 10 items • Updated
paper_id string | title string | paper_url string | pdf_url string | authors list | abstract large_string | track string | primary_area string | doi string | volume string | issue string | pages string | abstract_source string | arxiv_id string | arxiv_id_source string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
10.1609/aaai.v38i7.28498 | Revisiting Open-Set Panoptic Segmentation | https://ojs.aaai.org/index.php/AAAI/article/view/28498 | https://ojs.aaai.org/index.php/AAAI/article/download/28498/28970 | [
"Yufei Yin",
"Hao Chen",
"Wengang Zhou",
"Jiajun Deng",
"Haiming Xu",
"Houqiang Li"
] | In this paper, we focus on the open-set panoptic segmentation (OPS) task to circumvent the data explosion problem. Different from the close-set setting, OPS targets to detect both known and unknown categories, where the latter is not annotated during training. Different from existing work that only selects a few common... | main | null | 10.1609/aaai.v38i7.28498 | 38 | 7 | 6747-6754 | official | null | null |
10.1609/aaai.v38i14.29498 | Semi-supervised Learning of Dynamical Systems with Neural Ordinary Differential Equations: A Teacher-Student Model Approach | https://ojs.aaai.org/index.php/AAAI/article/view/29498 | https://ojs.aaai.org/index.php/AAAI/article/download/29498/30823 | [
"Yu Wang",
"Yuxuan Yin",
"Karthik Somayaji NS",
"Ján Drgoňa",
"Malachi Schram",
"Mahantesh Halappanavar",
"Frank Liu",
"Peng Li"
] | Modeling dynamical systems is crucial for a wide range of tasks, but it remains challenging due to complex nonlinear dynamics, limited observations, or lack of prior knowledge. Recently, data-driven approaches such as Neural Ordinary Differential Equations (NODE) have shown promising results by leveraging the expressiv... | main | null | 10.1609/aaai.v38i14.29498 | 38 | 14 | 15698-15705 | official | 2310.13110 | title_snapshot |
10.1609/aaai.v38i18.30032 | Solving Satisfiability Modulo Counting for Symbolic and Statistical AI Integration with Provable Guarantees | https://ojs.aaai.org/index.php/AAAI/article/view/30032 | https://ojs.aaai.org/index.php/AAAI/article/download/30032/31816 | [
"Jinzhao Li",
"Nan Jiang",
"Yexiang Xue"
] | Satisfiability Modulo Counting (SMC) encompasses problems that require both symbolic decision-making and statistical reasoning. Its general formulation captures many real-world problems at the intersection of symbolic and statistical AI. SMC searches for policy interventions to control probabilistic outcomes. Solving S... | main | null | 10.1609/aaai.v38i18.30032 | 38 | 18 | 20481-20490 | official | 2309.08883 | title_snapshot |
10.1609/aaai.v38i10.28992 | Kernelized Normalizing Constant Estimation: Bridging Bayesian Quadrature and Bayesian Optimization | https://ojs.aaai.org/index.php/AAAI/article/view/28992 | https://ojs.aaai.org/index.php/AAAI/article/download/28992/29885 | [
"Xu Cai",
"Jonathan Scarlett"
] | In this paper, we study the problem of estimating the normalizing constant through queries to the black-box function f, which is the integration of the exponential function of f scaled by a problem parameter lambda. We assume f belongs to a reproducing kernel Hilbert space (RKHS), and show that to estimate the normaliz... | main | null | 10.1609/aaai.v38i10.28992 | 38 | 10 | 11150-11158 | official | 2401.05716 | title_snapshot |
10.1609/aaai.v38i11.29158 | Stochastic Bayesian Optimization with Unknown Continuous Context Distribution via Kernel Density Estimation | https://ojs.aaai.org/index.php/AAAI/article/view/29158 | https://ojs.aaai.org/index.php/AAAI/article/download/29158/30190 | [
"Xiaobin Huang",
"Lei Song",
"Ke Xue",
"Chao Qian"
] | Bayesian optimization (BO) is a sample-efficient method and has been widely used for optimizing expensive black-box functions. Recently, there has been a considerable interest in BO literature in optimizing functions that are affected by context variable in the environment, which is uncontrollable by decision makers. I... | main | null | 10.1609/aaai.v38i11.29158 | 38 | 11 | 12635-12643 | official | 2312.10423 | title_snapshot |
10.1609/aaai.v38i8.28662 | Large-Scale Non-convex Stochastic Constrained Distributionally Robust Optimization | https://ojs.aaai.org/index.php/AAAI/article/view/28662 | https://ojs.aaai.org/index.php/AAAI/article/download/28662/29286 | [
"Qi Zhang",
"Yi Zhou",
"Ashley Prater-Bennette",
"Lixin Shen",
"Shaofeng Zou"
] | Distributionally robust optimization (DRO) is a powerful framework for training robust models against data distribution shifts. This paper focuses on constrained DRO, which has an explicit characterization of the robustness level. Existing studies on constrained DRO mostly focus on convex loss function, and exclude the... | main | null | 10.1609/aaai.v38i8.28662 | 38 | 8 | 8217-8225 | official | 2404.01200 | title_snapshot |
10.1609/aaai.v38i10.28984 | MEPSI: An MDL-Based Ensemble Pruning Approach with Structural Information | https://ojs.aaai.org/index.php/AAAI/article/view/28984 | https://ojs.aaai.org/index.php/AAAI/article/download/28984/29870 | [
"Xiao-Dong Bi",
"Shao-Qun Zhang",
"Yuan Jiang"
] | Ensemble pruning that combines a subset of individual learners generated in parallel to make predictions is an important topic in ensemble learning. Past decades have developed a lot of pruning algorithms that focus on the external behavior of learners on samples, which may lead to over-fitting. In this paper, we conje... | main | null | 10.1609/aaai.v38i10.28984 | 38 | 10 | 11078-11086 | official | null | null |
10.1609/aaai.v38i8.28675 | Modeling Knowledge Graphs with Composite Reasoning | https://ojs.aaai.org/index.php/AAAI/article/view/28675 | https://ojs.aaai.org/index.php/AAAI/article/download/28675/29311 | [
"Wanyun Cui",
"Linqiu Zhang"
] | The ability to combine multiple pieces of existing knowledge to infer new knowledge is both crucial and challenging. In this paper, we explore how facts of various entities are combined in the context of knowledge graph completion (KGC). We use composite reasoning to unify the views from different KGC models, including... | main | null | 10.1609/aaai.v38i8.28675 | 38 | 8 | 8338-8345 | official | null | null |
10.1609/aaai.v38i14.29516 | Robust Loss Functions for Training Decision Trees with Noisy Labels | https://ojs.aaai.org/index.php/AAAI/article/view/29516 | https://ojs.aaai.org/index.php/AAAI/article/download/29516/30856 | [
"Jonathan Wilton",
"Nan Ye"
] | We consider training decision trees using noisily labeled data, focusing on loss functions that can lead to robust learning algorithms. Our contributions are threefold. First, we offer novel theoretical insights on the robustness of many existing loss functions in the context of decision tree learning. We show that som... | main | null | 10.1609/aaai.v38i14.29516 | 38 | 14 | 15859-15867 | official | 2312.12937 | title_snapshot |
10.1609/aaai.v38i18.30072 | Inertial Algorithm with Dry Fraction and Convolutional Sparse Coding for 3D Localization with Light Field Microscopy | https://ojs.aaai.org/index.php/AAAI/article/view/30072 | https://ojs.aaai.org/index.php/AAAI/article/download/30072/31887 | [
"Xiaofan Wang",
"Zhiyuan Deng",
"Changle Wang",
"Jinjia Wang"
] | Light field microscopy is a high-speed 3D imaging technique that records the light field from multiple angles by the microlens array(MLA), thus allowing us to obtain information about the light source from a single image only. For the fundamental problem of neuron localization, we improve the method of combining depth-... | main | null | 10.1609/aaai.v38i18.30072 | 38 | 18 | 20830-20837 | official | null | null |
10.1609/aaai.v38i12.29258 | EMGAN: Early-Mix-GAN on Extracting Server-Side Model in Split Federated Learning | https://ojs.aaai.org/index.php/AAAI/article/view/29258 | https://ojs.aaai.org/index.php/AAAI/article/download/29258/30374 | [
"Jingtao Li",
"Xing Chen",
"Li Yang",
"Adnan Siraj Rakin",
"Deliang Fan",
"Chaitali Chakrabarti"
] | Split Federated Learning (SFL) is an emerging edge-friendly version of Federated Learning (FL), where clients process a small portion of the entire model. While SFL was considered to be resistant to Model Extraction Attack (MEA) by design, a recent work shows it is not necessarily the case. In general, gradient-based M... | main | null | 10.1609/aaai.v38i12.29258 | 38 | 12 | 13545-13553 | official | null | null |
10.1609/aaai.v38i8.28780 | Parallel Ranking of Ads and Creatives in Real-Time Advertising Systems | https://ojs.aaai.org/index.php/AAAI/article/view/28780 | https://ojs.aaai.org/index.php/AAAI/article/download/28780/29495 | [
"Zhiguang Yang",
"Liufang Sang",
"Haoran Wang",
"Wenlong Chen",
"Lu Wang",
"Jie He",
"Changping Peng",
"Zhangang Lin",
"Chun Gan",
"Jingping Shao"
] | Creativity is the heart and soul of advertising services. Effective creatives can create a win-win scenario: advertisers each target users and achieve marketing objectives more effectively, users more quickly find products of interest, and platforms generate more advertising revenue. With the advent of AI-Generated Con... | main | null | 10.1609/aaai.v38i8.28780 | 38 | 8 | 9278-9286 | official | 2312.12750 | title_snapshot |
10.1609/aaai.v38i9.28801 | Fair Lotteries for Participatory Budgeting | https://ojs.aaai.org/index.php/AAAI/article/view/28801 | https://ojs.aaai.org/index.php/AAAI/article/download/28801/29533 | [
"Haris Aziz",
"Xinhang Lu",
"Mashbat Suzuki",
"Jeremy Vollen",
"Toby Walsh"
] | In pursuit of participatory budgeting (PB) outcomes with broader fairness guarantees, we initiate the study of lotteries over discrete PB outcomes. As the projects have heterogeneous costs, the amount spent may not be equal ex ante and ex post. To address this, we develop a technique to bound the amount by which the ex... | main | null | 10.1609/aaai.v38i9.28801 | 38 | 9 | 9469-9476 | official | 2404.05198 | title_snapshot |
10.1609/aaai.v38i14.29463 | Weisfeiler and Lehman Go Paths: Learning Topological Features via Path Complexes | https://ojs.aaai.org/index.php/AAAI/article/view/29463 | https://ojs.aaai.org/index.php/AAAI/article/download/29463/30758 | [
"Quang Truong",
"Peter Chin"
] | Graph Neural Networks (GNNs), despite achieving remarkable performance across different tasks, are theoretically bounded by the 1-Weisfeiler-Lehman test, resulting in limitations in terms of graph expressivity. Even though prior works on topological higher-order GNNs overcome that boundary, these models often depend on... | main | null | 10.1609/aaai.v38i14.29463 | 38 | 14 | 15382-15391 | official | 2308.06838 | title_snapshot |
10.1609/aaai.v38i2.27869 | Null Space Matters: Range-Null Decomposition for Consistent Multi-Contrast MRI Reconstruction | https://ojs.aaai.org/index.php/AAAI/article/view/27869 | https://ojs.aaai.org/index.php/AAAI/article/download/27869/27763 | [
"Jiacheng Chen",
"Jiawei Jiang",
"Fei Wu",
"Jianwei Zheng"
] | Consistency and interpretability have long been the critical issues in MRI reconstruction. While interpretability has been dramatically improved with the employment of deep unfolding networks (DUNs), current methods still suffer from inconsistencies and generate inferior anatomical structure. Especially in multi-contra... | main | null | 10.1609/aaai.v38i2.27869 | 38 | 2 | 1081-1090 | official | null | null |
10.1609/aaai.v38i15.29579 | Progressively Knowledge Distillation via Re-parameterizing Diffusion Reverse Process | https://ojs.aaai.org/index.php/AAAI/article/view/29579 | https://ojs.aaai.org/index.php/AAAI/article/download/29579/30973 | [
"Xufeng Yao",
"Fanbin Lu",
"Yuechen Zhang",
"Xinyun Zhang",
"Wenqian Zhao",
"Bei Yu"
] | Knowledge distillation aims at transferring knowledge from the teacher model to the student one by aligning their distributions. Feature-level distillation often uses L2 distance or its variants as the loss function, based on the assumption that outputs follow normal distributions. This poses a significant challenge wh... | main | null | 10.1609/aaai.v38i15.29579 | 38 | 15 | 16425-16432 | official | null | null |
10.1609/aaai.v38i17.29934 | LLMEval: A Preliminary Study on How to Evaluate Large Language Models | https://ojs.aaai.org/index.php/AAAI/article/view/29934 | https://ojs.aaai.org/index.php/AAAI/article/download/29934/31632 | [
"Yue Zhang",
"Ming Zhang",
"Haipeng Yuan",
"Shichun Liu",
"Yongyao Shi",
"Tao Gui",
"Qi Zhang",
"Xuanjing Huang"
] | Recently, the evaluation of Large Language Models has emerged as a popular area of research. The three crucial questions for LLM evaluation are ``what, where, and how to evaluate''. However, the existing research mainly focuses on the first two questions, which are basically what tasks to give the LLM during testing an... | main | null | 10.1609/aaai.v38i17.29934 | 38 | 17 | 19615-19622 | official | 2312.07398 | title_snapshot |
10.1609/aaai.v38i11.29076 | PAC-Bayes Generalisation Bounds for Dynamical Systems including Stable RNNs | https://ojs.aaai.org/index.php/AAAI/article/view/29076 | https://ojs.aaai.org/index.php/AAAI/article/download/29076/30037 | [
"Deividas Eringis",
"John Leth",
"Zheng-Hua Tan",
"Rafael Wisniewski",
"Mihály Petreczky"
] | In this paper, we derive a PAC-Bayes bound on the generalisation gap, in a supervised time-series setting for a special class of discrete-time non-linear dynamical systems. This class includes stable recurrent neural networks (RNN), and the motivation for this work was its application to RNNs. In order to achieve the r... | main | null | 10.1609/aaai.v38i11.29076 | 38 | 11 | 11901-11909 | official | 2312.09793 | title_snapshot |
10.1609/aaai.v38i7.28624 | Enhancing Neural Radiance Fields with Adaptive Multi-Exposure Fusion: A Bilevel Optimization Approach for Novel View Synthesis | https://ojs.aaai.org/index.php/AAAI/article/view/28624 | https://ojs.aaai.org/index.php/AAAI/article/download/28624/29212 | [
"Yang Zou",
"Xingyuan Li",
"Zhiying Jiang",
"Jinyuan Liu"
] | Neural Radiance Fields (NeRF) have made significant strides in the modeling and rendering of 3D scenes. However, due to the complexity of luminance information, existing NeRF methods often struggle to produce satisfactory renderings when dealing with high and low exposure images. To address this issue, we propose an in... | main | null | 10.1609/aaai.v38i7.28624 | 38 | 7 | 7882-7890 | official | null | null |
10.1609/aaai.v38i3.27995 | Learning Explicit Contact for Implicit Reconstruction of Hand-Held Objects from Monocular Images | https://ojs.aaai.org/index.php/AAAI/article/view/27995 | https://ojs.aaai.org/index.php/AAAI/article/download/27995/28007 | [
"Junxing Hu",
"Hongwen Zhang",
"Zerui Chen",
"Mengcheng Li",
"Yunlong Wang",
"Yebin Liu",
"Zhenan Sun"
] | Reconstructing hand-held objects from monocular RGB images is an appealing yet challenging task. In this task, contacts between hands and objects provide important cues for recovering the 3D geometry of the hand-held objects. Though recent works have employed implicit functions to achieve impressive progress, they igno... | main | null | 10.1609/aaai.v38i3.27995 | 38 | 3 | 2220-2228 | official | 2305.20089 | title_snapshot |
10.1609/aaai.v38i5.28307 | RL-SeqISP: Reinforcement Learning-Based Sequential Optimization for Image Signal Processing | https://ojs.aaai.org/index.php/AAAI/article/view/28307 | https://ojs.aaai.org/index.php/AAAI/article/download/28307/28603 | [
"Xinyu Sun",
"Zhikun Zhao",
"Lili Wei",
"Congyan Lang",
"Mingxuan Cai",
"Longfei Han",
"Juan Wang",
"Bing Li",
"Yuxuan Guo"
] | Hardware image signal processing (ISP), aiming at converting RAW inputs to RGB images, consists of a series of processing blocks, each with multiple parameters. Traditionally, ISP parameters are manually tuned in isolation by imaging experts according to application-specific quality and performance metrics, which is ti... | main | null | 10.1609/aaai.v38i5.28307 | 38 | 5 | 5025-5033 | official | null | null |
10.1609/aaai.v38i14.29445 | Cross-Gate MLP with Protein Complex Invariant Embedding Is a One-Shot Antibody Designer | https://ojs.aaai.org/index.php/AAAI/article/view/29445 | https://ojs.aaai.org/index.php/AAAI/article/download/29445/30725 | [
"Cheng Tan",
"Zhangyang Gao",
"Lirong Wu",
"Jun Xia",
"Jiangbin Zheng",
"Xihong Yang",
"Yue Liu",
"Bozhen Hu",
"Stan Z. Li"
] | Antibodies are crucial proteins produced by the immune system in response to foreign substances or antigens. The specificity of an antibody is determined by its complementarity-determining regions (CDRs), which are located in the variable domains of the antibody chains and form the antigen-binding site. Previous studie... | main | null | 10.1609/aaai.v38i14.29445 | 38 | 14 | 15222-15230 | official | 2305.09480 | title_snapshot |
10.1609/aaai.v38i4.28165 | Differentiable Auxiliary Learning for Sketch Re-Identification | https://ojs.aaai.org/index.php/AAAI/article/view/28165 | https://ojs.aaai.org/index.php/AAAI/article/download/28165/28329 | [
"Xingyu Liu",
"Xu Cheng",
"Haoyu Chen",
"Hao Yu",
"Guoying Zhao"
] | Sketch re-identification (Re-ID) seeks to match pedestrians' photos from surveillance videos with corresponding sketches. However, we observe that existing works still have two critical limitations: (i) cross- and intra-modality discrepancies hinder the extraction of modality-shared features, (ii) standard triplet loss... | main | null | 10.1609/aaai.v38i4.28165 | 38 | 4 | 3747-3755 | official | null | null |
10.1609/aaai.v38i9.28907 | Learning from Ambiguous Demonstrations with Self-Explanation Guided Reinforcement Learning | https://ojs.aaai.org/index.php/AAAI/article/view/28907 | https://ojs.aaai.org/index.php/AAAI/article/download/28907/29726 | [
"Yantian Zha",
"Lin Guan",
"Subbarao Kambhampati"
] | Our work aims at efficiently leveraging ambiguous demonstrations for the training of a reinforcement learning (RL) agent. An ambiguous demonstration can usually be interpreted in multiple ways, which severely hinders the RL agent from learning stably and efficiently. Since an optimal demonstration may also suffer from ... | main | null | 10.1609/aaai.v38i9.28907 | 38 | 9 | 10395-10403 | official | 2110.05286 | title_snapshot |
10.1609/aaai.v38i9.28805 | Principal-Agent Reward Shaping in MDPs | https://ojs.aaai.org/index.php/AAAI/article/view/28805 | https://ojs.aaai.org/index.php/AAAI/article/download/28805/29540 | [
"Omer Ben-Porat",
"Yishay Mansour",
"Michal Moshkovitz",
"Boaz Taitler"
] | Principal-agent problems arise when one party acts on behalf of another, leading to conflicts of interest. The economic literature has extensively studied principal-agent problems, and recent work has extended this to more complex scenarios such as Markov Decision Processes (MDPs). In this paper, we further explore thi... | main | null | 10.1609/aaai.v38i9.28805 | 38 | 9 | 9502-9510 | official | 2401.00298 | title_snapshot |
10.1609/aaai.v38i11.29126 | Improving Distinguishability of Class for Graph Neural Networks | https://ojs.aaai.org/index.php/AAAI/article/view/29126 | https://ojs.aaai.org/index.php/AAAI/article/download/29126/30130 | [
"Dongxiao He",
"Shuwei Liu",
"Meng Ge",
"Zhizhi Yu",
"Guangquan Xu",
"Zhiyong Feng"
] | Graph Neural Networks (GNNs) have received widespread attention and applications due to their excellent performance in graph representation learning. Most existing GNNs can only aggregate 1-hop neighbors in a GNN layer, so they usually stack multiple GNN layers to obtain more information from larger neighborhoods. Howe... | main | null | 10.1609/aaai.v38i11.29126 | 38 | 11 | 12349-12357 | official | null | null |
10.1609/aaai.v38i8.28771 | Feature Distribution Matching by Optimal Transport for Effective and Robust Coreset Selection | https://ojs.aaai.org/index.php/AAAI/article/view/28771 | https://ojs.aaai.org/index.php/AAAI/article/download/28771/29480 | [
"Weiwei Xiao",
"Yongyong Chen",
"Qiben Shan",
"Yaowei Wang",
"Jingyong Su"
] | Training neural networks with good generalization requires large computational costs in many deep learning methods due to large-scale datasets and over-parameterized models. Despite the emergence of a number of coreset selection methods to reduce the computational costs, the problem of coreset distribution bias, i.e., ... | main | null | 10.1609/aaai.v38i8.28771 | 38 | 8 | 9196-9204 | official | null | null |
10.1609/aaai.v38i1.27770 | Improving PTM Site Prediction by Coupling of Multi-Granularity Structure and Multi-Scale Sequence Representation | https://ojs.aaai.org/index.php/AAAI/article/view/27770 | https://ojs.aaai.org/index.php/AAAI/article/download/27770/27580 | [
"Zhengyi Li",
"Menglu Li",
"Lida Zhu",
"Wen Zhang"
] | Protein post-translational modification (PTM) site prediction is a fundamental task in bioinformatics. Several computational methods have been developed to predict PTM sites. However, existing methods ignore the structure information and merely utilize protein sequences. Furthermore, designing a more fine-grained struc... | main | null | 10.1609/aaai.v38i1.27770 | 38 | 1 | 188-196 | official | 2401.10211 | title_snapshot |
10.1609/aaai.v38i16.29719 | All Should Be Equal in the Eyes of LMs: Counterfactually Aware Fair Text Generation | https://ojs.aaai.org/index.php/AAAI/article/view/29719 | https://ojs.aaai.org/index.php/AAAI/article/download/29719/31235 | [
"Pragyan Banerjee",
"Abhinav Java",
"Surgan Jandial",
"Simra Shahid",
"Shaz Furniturewala",
"Balaji Krishnamurthy",
"Sumit Bhatia"
] | Fairness in Language Models (LMs) remains a long-standing challenge, given the inherent biases in training data that can be perpetuated by models and affect the downstream tasks. Recent methods employ expensive retraining or attempt debiasing during inference by constraining model outputs to contrast from a reference s... | main | null | 10.1609/aaai.v38i16.29719 | 38 | 16 | 17673-17681 | official | 2311.05451 | title_judge |
10.1609/aaai.v38i15.29612 | FM-OV3D: Foundation Model-Based Cross-Modal Knowledge Blending for Open-Vocabulary 3D Detection | https://ojs.aaai.org/index.php/AAAI/article/view/29612 | https://ojs.aaai.org/index.php/AAAI/article/download/29612/31036 | [
"Dongmei Zhang",
"Chang Li",
"Renrui Zhang",
"Shenghao Xie",
"Wei Xue",
"Xiaodong Xie",
"Shanghang Zhang"
] | The superior performances of pre-trained foundation models in various visual tasks underscore their potential to enhance the 2D models' open-vocabulary ability. Existing methods explore analogous applications in the 3D space. However, most of them only center around knowledge extraction from singular foundation models,... | main | null | 10.1609/aaai.v38i15.29612 | 38 | 15 | 16723-16731 | official | 2312.14465 | title_snapshot |
10.1609/aaai.v38i12.29245 | Multi-Architecture Multi-Expert Diffusion Models | https://ojs.aaai.org/index.php/AAAI/article/view/29245 | https://ojs.aaai.org/index.php/AAAI/article/download/29245/30351 | [
"Yunsung Lee",
"JinYoung Kim",
"Hyojun Go",
"Myeongho Jeong",
"Shinhyeok Oh",
"Seungtaek Choi"
] | In this paper, we address the performance degradation of efficient diffusion models by introducing Multi-architecturE Multi-Expert diffusion models (MEME). We identify the need for tailored operations at different time-steps in diffusion processes and leverage this insight to create compact yet high-performing models. ... | main | null | 10.1609/aaai.v38i12.29245 | 38 | 12 | 13427-13436 | official | 2306.04990 | title_snapshot |
10.1609/aaai.v38i10.28963 | Generating Universal Adversarial Perturbations for Quantum Classifiers | https://ojs.aaai.org/index.php/AAAI/article/view/28963 | https://ojs.aaai.org/index.php/AAAI/article/download/28963/29831 | [
"Gautham Anil",
"Vishnu Vinod",
"Apurva Narayan"
] | Quantum Machine Learning (QML) has emerged as a promising field of research, aiming to leverage the capabilities of quantum computing to enhance existing machine learning methodologies. Recent studies have revealed that, like their classical counterparts, QML models based on Parametrized Quantum Circuits (PQCs) are als... | main | null | 10.1609/aaai.v38i10.28963 | 38 | 10 | 10891-10899 | official | 2402.08648 | title_snapshot |
10.1609/aaai.v38i13.29363 | A Primal-Dual Algorithm for Hybrid Federated Learning | https://ojs.aaai.org/index.php/AAAI/article/view/29363 | https://ojs.aaai.org/index.php/AAAI/article/download/29363/30572 | [
"Tom Overman",
"Garrett Blum",
"Diego Klabjan"
] | Very few methods for hybrid federated learning, where clients only hold subsets of both features and samples, exist. Yet, this scenario is very important in practical settings. We provide a fast, robust algorithm for hybrid federated learning that hinges on Fenchel Duality. We prove the convergence of the algorithm to ... | main | null | 10.1609/aaai.v38i13.29363 | 38 | 13 | 14482-14489 | official | 2210.08106 | title_snapshot |
10.1609/aaai.v38i8.28689 | Intra- and Inter-group Optimal Transport for User-Oriented Fairness in Recommender Systems | https://ojs.aaai.org/index.php/AAAI/article/view/28689 | https://ojs.aaai.org/index.php/AAAI/article/download/28689/29335 | [
"Zhongxuan Han",
"Chaochao Chen",
"Xiaolin Zheng",
"Meng Li",
"Weiming Liu",
"Binhui Yao",
"Yuyuan Li",
"Jianwei Yin"
] | Recommender systems are typically biased toward a small group of users, leading to severe unfairness in recommendation performance, i.e., User-Oriented Fairness (UOF) issue. Existing research on UOF exhibits notable limitations in two phases of recommendation models. In the training phase, current methods fail to tackl... | main | null | 10.1609/aaai.v38i8.28689 | 38 | 8 | 8463-8471 | official | null | null |
10.1609/aaai.v38i13.29336 | One-Step Forward and Backtrack: Overcoming Zig-Zagging in Loss-Aware Quantization Training | https://ojs.aaai.org/index.php/AAAI/article/view/29336 | https://ojs.aaai.org/index.php/AAAI/article/download/29336/30521 | [
"Lianbo Ma",
"Yuee Zhou",
"Jianlun Ma",
"Guo Yu",
"Qing Li"
] | Weight quantization is an effective technique to compress deep neural networks for their deployment on edge devices with limited resources. Traditional loss-aware quantization methods commonly use the quantized gradient to replace the full-precision gradient. However, we discover that the gradient error will lead to an... | main | null | 10.1609/aaai.v38i13.29336 | 38 | 13 | 14246-14254 | official | 2401.16760 | title_snapshot |
10.1609/aaai.v38i4.28178 | Improving Cross-Modal Alignment with Synthetic Pairs for Text-Only Image Captioning | https://ojs.aaai.org/index.php/AAAI/article/view/28178 | https://ojs.aaai.org/index.php/AAAI/article/download/28178/28354 | [
"Zhiyue Liu",
"Jinyuan Liu",
"Fanrong Ma"
] | Although image captioning models have made significant advancements in recent years, the majority of them heavily depend on high-quality datasets containing paired images and texts which are costly to acquire. Previous works leverage the CLIP's cross-modal association ability for image captioning, relying solely on tex... | main | null | 10.1609/aaai.v38i4.28178 | 38 | 4 | 3864-3872 | official | 2312.08865 | title_snapshot |
10.1609/aaai.v38i13.29333 | Leveraging Diffusion Perturbations for Measuring Fairness in Computer Vision | https://ojs.aaai.org/index.php/AAAI/article/view/29333 | https://ojs.aaai.org/index.php/AAAI/article/download/29333/30515 | [
"Nicholas Lui",
"Bryan Chia",
"William Berrios",
"Candace Ross",
"Douwe Kiela"
] | Computer vision models have been known to encode harmful biases, leading to the potentially unfair treatment of historically marginalized groups, such as people of color. However, there remains a lack of datasets balanced along demographic traits that can be used to evaluate the downstream fairness of these models. In ... | main | null | 10.1609/aaai.v38i13.29333 | 38 | 13 | 14220-14228 | official | 2311.15108 | title_snapshot |
10.1609/aaai.v38i8.28713 | CONSIDER: Commonalities and Specialties Driven Multilingual Code Retrieval Framework | https://ojs.aaai.org/index.php/AAAI/article/view/28713 | https://ojs.aaai.org/index.php/AAAI/article/download/28713/29378 | [
"Rui Li",
"Liyang He",
"Qi Liu",
"Yuze Zhao",
"Zheng Zhang",
"Zhenya Huang",
"Yu Su",
"Shijin Wang"
] | Multilingual code retrieval aims to find code snippets relevant to a user's query from a multilingual codebase, which plays a crucial role in software development and expands their application scenarios compared to classical monolingual code retrieval. Despite the performance improvements achieved by previous studies, ... | main | null | 10.1609/aaai.v38i8.28713 | 38 | 8 | 8679-8687 | official | null | null |
10.1609/aaai.v38i7.28513 | KeDuSR: Real-World Dual-Lens Super-Resolution via Kernel-Free Matching | https://ojs.aaai.org/index.php/AAAI/article/view/28513 | https://ojs.aaai.org/index.php/AAAI/article/download/28513/29000 | [
"Huanjing Yue",
"Zifan Cui",
"Kun Li",
"Jingyu Yang"
] | Dual-lens super-resolution (SR) is a practical scenario for reference (Ref) based SR by utilizing the telephoto image (Ref) to assist the super-resolution of the low-resolution wide-angle image (LR input). Different from general RefSR, the Ref in dual-lens SR only covers the overlapped field of view (FoV) area. However... | main | null | 10.1609/aaai.v38i7.28513 | 38 | 7 | 6881-6889 | official | 2312.17050 | title_snapshot |
10.1609/aaai.v38i2.27851 | Disguise without Disruption: Utility-Preserving Face De-identification | https://ojs.aaai.org/index.php/AAAI/article/view/27851 | https://ojs.aaai.org/index.php/AAAI/article/download/27851/27728 | [
"Zikui Cai",
"Zhongpai Gao",
"Benjamin Planche",
"Meng Zheng",
"Terrence Chen",
"M. Salman Asif",
"Ziyan Wu"
] | With the rise of cameras and smart sensors, humanity generates an exponential amount of data. This valuable information, including underrepresented cases like AI in medical settings, can fuel new deep-learning tools. However, data scientists must prioritize ensuring privacy for individuals in these untapped datasets, e... | main | null | 10.1609/aaai.v38i2.27851 | 38 | 2 | 918-926 | official | 2303.13269 | title_snapshot |
10.1609/aaai.v38i9.28830 | Information Design for Congestion Games with Unknown Demand | https://ojs.aaai.org/index.php/AAAI/article/view/28830 | https://ojs.aaai.org/index.php/AAAI/article/download/28830/29581 | [
"Svenja M. Griesbach",
"Martin Hoefer",
"Max Klimm",
"Tim Koglin"
] | We study a novel approach to information design in the standard traffic model of network congestion games. It captures the natural condition that the demand is unknown to the users of the network. A principal (e.g., a mobility service) commits to a signaling strategy, observes the realized demand and sends a (public) s... | main | null | 10.1609/aaai.v38i9.28830 | 38 | 9 | 9722-9730 | official | 2310.08314 | title_snapshot |
10.1609/aaai.v38i6.28441 | G2P-DDM: Generating Sign Pose Sequence from Gloss Sequence with Discrete Diffusion Model | https://ojs.aaai.org/index.php/AAAI/article/view/28441 | https://ojs.aaai.org/index.php/AAAI/article/download/28441/28860 | [
"Pan Xie",
"Qipeng Zhang",
"Peng Taiying",
"Hao Tang",
"Yao Du",
"Zexian Li"
] | The Sign Language Production (SLP) project aims to automatically translate spoken languages into sign sequences. Our approach focuses on the transformation of sign gloss sequences into their corresponding sign pose sequences (G2P). In this paper, we present a novel solution for this task by converting the continuous po... | main | null | 10.1609/aaai.v38i6.28441 | 38 | 6 | 6234-6242 | official | 2208.09141 | title_snapshot |
10.1609/aaai.v38i17.29903 | Question Calibration and Multi-Hop Modeling for Temporal Question Answering | https://ojs.aaai.org/index.php/AAAI/article/view/29903 | https://ojs.aaai.org/index.php/AAAI/article/download/29903/31579 | [
"Chao Xue",
"Di Liang",
"Pengfei Wang",
"Jing Zhang"
] | Many models that leverage knowledge graphs (KGs) have recently demonstrated remarkable success in question answering (QA) tasks. In the real world, many facts contained in KGs are time-constrained thus temporal KGQA has received increasing attention. Despite the fruitful efforts of previous models in temporal KGQA, the... | main | null | 10.1609/aaai.v38i17.29903 | 38 | 17 | 19332-19340 | official | 2402.13188 | title_snapshot |
10.1609/aaai.v38i4.28182 | MLNet: Mutual Learning Network with Neighborhood Invariance for Universal Domain Adaptation | https://ojs.aaai.org/index.php/AAAI/article/view/28182 | https://ojs.aaai.org/index.php/AAAI/article/download/28182/28362 | [
"Yanzuo Lu",
"Meng Shen",
"Andy J Ma",
"Xiaohua Xie",
"Jian-Huang Lai"
] | Universal domain adaptation (UniDA) is a practical but challenging problem, in which information about the relation between the source and the target domains is not given for knowledge transfer. Existing UniDA methods may suffer from the problems of overlooking intra-domain variations in the target domain and difficult... | main | null | 10.1609/aaai.v38i4.28182 | 38 | 4 | 3900-3908 | official | 2312.07871 | title_snapshot |
10.1609/aaai.v38i1.27764 | LogFormer: A Pre-train and Tuning Pipeline for Log Anomaly Detection | https://ojs.aaai.org/index.php/AAAI/article/view/27764 | https://ojs.aaai.org/index.php/AAAI/article/download/27764/27569 | [
"Hongcheng Guo",
"Jian Yang",
"Jiaheng Liu",
"Jiaqi Bai",
"Boyang Wang",
"Zhoujun Li",
"Tieqiao Zheng",
"Bo Zhang",
"Junran Peng",
"Qi Tian"
] | Log anomaly detection is a key component in the field of artificial intelligence for IT operations (AIOps). Considering log data of variant domains, retraining the whole network for unknown domains is inefficient in real industrial scenarios. However, previous deep models merely focused on extracting the semantics of l... | main | null | 10.1609/aaai.v38i1.27764 | 38 | 1 | 135-143 | official | 2401.04749 | title_snapshot |
10.1609/aaai.v38i8.28789 | Temporal Graph Contrastive Learning for Sequential Recommendation | https://ojs.aaai.org/index.php/AAAI/article/view/28789 | https://ojs.aaai.org/index.php/AAAI/article/download/28789/29511 | [
"Shengzhe Zhang",
"Liyi Chen",
"Chao Wang",
"Shuangli Li",
"Hui Xiong"
] | Sequential recommendation is a crucial task in understanding users' evolving interests and predicting their future behaviors. While existing approaches on sequence or graph modeling to learn interaction sequences of users have shown promising performance, how to effectively exploit temporal information and deal with th... | main | null | 10.1609/aaai.v38i8.28789 | 38 | 8 | 9359-9367 | official | null | null |
10.1609/aaai.v38i2.27939 | Simple Image-Level Classification Improves Open-Vocabulary Object Detection | https://ojs.aaai.org/index.php/AAAI/article/view/27939 | https://ojs.aaai.org/index.php/AAAI/article/download/27939/27899 | [
"Ruohuan Fang",
"Guansong Pang",
"Xiao Bai"
] | Open-Vocabulary Object Detection (OVOD) aims to detect novel objects beyond a given set of base categories on which the detection model is trained. Recent OVOD methods focus on adapting the image-level pre-trained vision-language models (VLMs), such as CLIP, to a region-level object detection task via, eg., region-leve... | main | null | 10.1609/aaai.v38i2.27939 | 38 | 2 | 1716-1725 | official | 2312.10439 | title_snapshot |
10.1609/aaai.v38i1.27821 | Open-Set Facial Expression Recognition | https://ojs.aaai.org/index.php/AAAI/article/view/27821 | https://ojs.aaai.org/index.php/AAAI/article/download/27821/27672 | [
"Yuhang Zhang",
"Yue Yao",
"Xuannan Liu",
"Lixiong Qin",
"Wenjing Wang",
"Weihong Deng"
] | Facial expression recognition (FER) models are typically trained on datasets with a fixed number of seven basic classes. However, recent research works (Cowen et al. 2021; Bryant et al. 2022; Kollias 2023) point out that there are far more expressions than the basic ones. Thus, when these models are deployed in the rea... | main | null | 10.1609/aaai.v38i1.27821 | 38 | 1 | 646-654 | official | 2401.12507 | title_snapshot |
10.1609/aaai.v38i13.29430 | Multi-Dimensional Fair Federated Learning | https://ojs.aaai.org/index.php/AAAI/article/view/29430 | https://ojs.aaai.org/index.php/AAAI/article/download/29430/30698 | [
"Cong Su",
"Guoxian Yu",
"Jun Wang",
"Hui Li",
"Qingzhong Li",
"Han Yu"
] | Federated learning (FL) has emerged as a promising collaborative and secure paradigm for training a model from decentralized data without compromising privacy. Group fairness and client fairness are two dimensions of fairness that are important for FL. Standard FL can result in disproportionate disadvantages for certai... | main | null | 10.1609/aaai.v38i13.29430 | 38 | 13 | 15083-15090 | official | 2312.05551 | title_snapshot |
10.1609/aaai.v38i3.28004 | Dynamic Weighted Combiner for Mixed-Modal Image Retrieval | https://ojs.aaai.org/index.php/AAAI/article/view/28004 | https://ojs.aaai.org/index.php/AAAI/article/download/28004/28023 | [
"Fuxiang Huang",
"Lei Zhang",
"Xiaowei Fu",
"Suqi Song"
] | Mixed-Modal Image Retrieval (MMIR) as a flexible search paradigm has attracted wide attention. However, previous approaches always achieve limited performance, due to two critical factors are seriously overlooked. 1) The contribution of image and text modalities is different, but incorrectly treated equally. 2) There e... | main | null | 10.1609/aaai.v38i3.28004 | 38 | 3 | 2303-2311 | official | 2312.06179 | title_snapshot |
10.1609/aaai.v38i8.28747 | An Attentive Inductive Bias for Sequential Recommendation beyond the Self-Attention | https://ojs.aaai.org/index.php/AAAI/article/view/28747 | https://ojs.aaai.org/index.php/AAAI/article/download/28747/29438 | [
"Yehjin Shin",
"Jeongwhan Choi",
"Hyowon Wi",
"Noseong Park"
] | Sequential recommendation (SR) models based on Transformers have achieved remarkable successes. The self-attention mechanism of Transformers for computer vision and natural language processing suffers from the oversmoothing problem, i.e., hidden representations becoming similar to tokens. In the SR domain, we, for the ... | main | null | 10.1609/aaai.v38i8.28747 | 38 | 8 | 8984-8992 | official | 2312.10325 | title_snapshot |
10.1609/aaai.v38i5.28217 | Out-of-Distribution Detection in Long-Tailed Recognition with Calibrated Outlier Class Learning | https://ojs.aaai.org/index.php/AAAI/article/view/28217 | https://ojs.aaai.org/index.php/AAAI/article/download/28217/28429 | [
"Wenjun Miao",
"Guansong Pang",
"Xiao Bai",
"Tianqi Li",
"Jin Zheng"
] | Existing out-of-distribution (OOD) methods have shown great success on balanced datasets but become ineffective in long-tailed recognition (LTR) scenarios where 1) OOD samples are often wrongly classified into head classes and/or 2) tail-class samples are treated as OOD samples. To address these issues, current studies... | main | null | 10.1609/aaai.v38i5.28217 | 38 | 5 | 4216-4224 | official | 2312.10686 | title_snapshot |
10.1609/aaai.v38i8.28678 | Enhancing Job Recommendation through LLM-Based Generative Adversarial Networks | https://ojs.aaai.org/index.php/AAAI/article/view/28678 | https://ojs.aaai.org/index.php/AAAI/article/download/28678/29317 | [
"Yingpeng Du",
"Di Luo",
"Rui Yan",
"Xiaopei Wang",
"Hongzhi Liu",
"Hengshu Zhu",
"Yang Song",
"Jie Zhang"
] | Recommending suitable jobs to users is a critical task in online recruitment platforms. While existing job recommendation methods encounter challenges such as the low quality of users' resumes, which hampers their accuracy and practical effectiveness.With the rapid development of large language models (LLMs), utilizing... | main | null | 10.1609/aaai.v38i8.28678 | 38 | 8 | 8363-8371 | official | 2307.10747 | title_snapshot |
10.1609/aaai.v38i2.27923 | Learning Multi-Modal Cross-Scale Deformable Transformer Network for Unregistered Hyperspectral Image Super-resolution | https://ojs.aaai.org/index.php/AAAI/article/view/27923 | https://ojs.aaai.org/index.php/AAAI/article/download/27923/27868 | [
"Wenqian Dong",
"Yang Xu",
"Jiahui Qu",
"Shaoxiong Hou"
] | Hyperspectral image super-resolution (HSI-SR) is a technology to improve the spatial resolution of HSI. Existing fusion-based SR methods have shown great performance, but still have some problems as follows: 1) existing methods assume that the auxiliary image providing spatial information is strictly registered with th... | main | null | 10.1609/aaai.v38i2.27923 | 38 | 2 | 1573-1581 | official | null | null |
10.1609/aaai.v38i11.29141 | Complete Neural Networks for Complete Euclidean Graphs | https://ojs.aaai.org/index.php/AAAI/article/view/29141 | https://ojs.aaai.org/index.php/AAAI/article/download/29141/30159 | [
"Snir Hordan",
"Tal Amir",
"Steven J. Gortler",
"Nadav Dym"
] | Neural networks for point clouds, which respect their natural invariance to permutation and rigid motion, have enjoyed recent success in modeling geometric phenomena, from molecular dynamics to recommender systems. Yet, to date, no architecture with polynomial complexity is known to be complete, that is, able to distin... | main | null | 10.1609/aaai.v38i11.29141 | 38 | 11 | 12482-12490 | official | 2301.13821 | title_snapshot |
10.1609/aaai.v38i9.28858 | Greedy-Based Online Fair Allocation with Adversarial Input: Enabling Best-of-Many-Worlds Guarantees | https://ojs.aaai.org/index.php/AAAI/article/view/28858 | https://ojs.aaai.org/index.php/AAAI/article/download/28858/29632 | [
"Zongjun Yang",
"Luofeng Liao",
"Christian Kroer"
] | We study an online allocation problem with sequentially arriving items and adversarially chosen agent values, with the goal of balancing fairness and efficiency. Our goal is to study the performance of algorithms that achieve strong guarantees under other input models such as stochastic inputs, in order to achieve robu... | main | null | 10.1609/aaai.v38i9.28858 | 38 | 9 | 9960-9968 | official | 2308.09277 | title_snapshot |
10.1609/aaai.v38i13.29339 | PPIDSG: A Privacy-Preserving Image Distribution Sharing Scheme with GAN in Federated Learning | https://ojs.aaai.org/index.php/AAAI/article/view/29339 | https://ojs.aaai.org/index.php/AAAI/article/download/29339/30527 | [
"Yuting Ma",
"Yuanzhi Yao",
"Xiaohua Xu"
] | Federated learning (FL) has attracted growing attention since it allows for privacy-preserving collaborative training on decentralized clients without explicitly uploading sensitive data to the central server. However, recent works have revealed that it still has the risk of exposing private data to adversaries. In thi... | main | null | 10.1609/aaai.v38i13.29339 | 38 | 13 | 14272-14280 | official | 2312.10380 | title_snapshot |
10.1609/aaai.v38i10.29053 | Deletion-Robust Submodular Maximization with Knapsack Constraints | https://ojs.aaai.org/index.php/AAAI/article/view/29053 | https://ojs.aaai.org/index.php/AAAI/article/download/29053/29995 | [
"Shuang Cui",
"Kai Han",
"He Huang"
] | Submodular maximization algorithms have found wide applications in various fields such as data summarization, recommendation systems, and active learning. In recent years, deletion-robust submodular maximization algorithms have garnered attention due to their significant implications in scenarios where some data points... | main | null | 10.1609/aaai.v38i10.29053 | 38 | 10 | 11695-11703 | official | null | null |
10.1609/aaai.v38i14.29550 | Relative Policy-Transition Optimization for Fast Policy Transfer | https://ojs.aaai.org/index.php/AAAI/article/view/29550 | https://ojs.aaai.org/index.php/AAAI/article/download/29550/30919 | [
"Jiawei Xu",
"Cheng Zhou",
"Yizheng Zhang",
"Baoxiang Wang",
"Lei Han"
] | We consider the problem of policy transfer between two Markov Decision Processes (MDPs). We introduce a lemma based on existing theoretical results in reinforcement learning to measure the relativity gap between two arbitrary MDPs, that is the difference between any two cumulative expected returns defined on different ... | main | null | 10.1609/aaai.v38i14.29550 | 38 | 14 | 16164-16172 | official | 2206.06009 | title_snapshot |
10.1609/aaai.v38i9.28884 | Visual Redundancy Removal for Composite Images: A Benchmark Dataset and a Multi-Visual-Effects Driven Incremental Method | https://ojs.aaai.org/index.php/AAAI/article/view/28884 | https://ojs.aaai.org/index.php/AAAI/article/download/28884/29680 | [
"Miaohui Wang",
"Rong Zhang",
"Lirong Huang",
"Yanshan Li"
] | Composite images (CIs) typically combine various elements from different scenes, views, and styles, which are a very important information carrier in the era of mixed media such as virtual reality, mixed reality, metaverse, etc. However, the complexity of CI content presents a significant challenge for subsequent visua... | main | null | 10.1609/aaai.v38i9.28884 | 38 | 9 | 10189-10197 | official | null | null |
10.1609/aaai.v38i10.29027 | Continuous Rotation Group Equivariant Network Inspired by Neural Population Coding | https://ojs.aaai.org/index.php/AAAI/article/view/29027 | https://ojs.aaai.org/index.php/AAAI/article/download/29027/29946 | [
"Zhiqiang Chen",
"Yang Chen",
"Xiaolong Zou",
"Shan Yu"
] | Neural population coding can represent continuous information by neurons with a series of discrete preferred stimuli, and we find that the bell-shaped tuning curve plays an important role in this mechanism. Inspired by this, we incorporate a bell-shaped tuning curve into the discrete group convolution to achieve contin... | main | null | 10.1609/aaai.v38i10.29027 | 38 | 10 | 11462-11470 | official | null | null |
10.1609/aaai.v38i18.30039 | Learning Bayesian Network Classifiers to Minimize the Class Variable Parameters | https://ojs.aaai.org/index.php/AAAI/article/view/30039 | https://ojs.aaai.org/index.php/AAAI/article/download/30039/31828 | [
"Shouta Sugahara",
"Koya Kato",
"Maomi Ueno"
] | This study proposes and evaluates a new Bayesian network classifier (BNC) having an I-map structure with the fewest class variable parameters among all structures for which the class variable has no parent. Moreover, a new learning algorithm to learn our proposed model is presented. The proposed method is guaranteed to... | main | null | 10.1609/aaai.v38i18.30039 | 38 | 18 | 20540-20549 | official | null | null |
10.1609/aaai.v38i8.28657 | Encoding Constraints as Binary Constraint Networks Satisfying BTP | https://ojs.aaai.org/index.php/AAAI/article/view/28657 | https://ojs.aaai.org/index.php/AAAI/article/download/28657/29276 | [
"Ruiwei Wang"
] | Recently, the Binary Constraint Tree (BCT), a tree structured Binary Constraint Network (BCN), has been shown to be more succinct than various ad-hoc constraints. In this paper, we investigate the modelling power of a well-known tractable hybrid class generalizing BCT, i.e. the class of BCNs satisfying Broken Triangle ... | main | null | 10.1609/aaai.v38i8.28657 | 38 | 8 | 8172-8181 | official | null | null |
10.1609/aaai.v38i9.28896 | Interactive Visual Task Learning for Robots | https://ojs.aaai.org/index.php/AAAI/article/view/28896 | https://ojs.aaai.org/index.php/AAAI/article/download/28896/29704 | [
"Weiwei Gu",
"Anant Sah",
"Nakul Gopalan"
] | We present a framework for robots to learn novel visual concepts and tasks via in-situ linguistic interactions with human users. Previous approaches have either used large pre-trained visual models to infer novel objects zero-shot, or added novel concepts along with their attributes and representations to a concept hie... | main | null | 10.1609/aaai.v38i9.28896 | 38 | 9 | 10297-10305 | official | 2312.13219 | title_snapshot |
10.1609/aaai.v38i12.29219 | Structure-Aware Multimodal Sequential Learning for Visual Dialog | https://ojs.aaai.org/index.php/AAAI/article/view/29219 | https://ojs.aaai.org/index.php/AAAI/article/download/29219/30300 | [
"Young-Jin Kim",
"Min-Jun Kim",
"Kyunghwan An",
"Jinwoo Ahn",
"Jaeseok Kim",
"Yu-Jung Heo",
"Du-Seong Chang",
"Eun-Sol Kim"
] | With the ability to collect vast amounts of image and natural language data from the web, there has been a remarkable advancement in Large-scale Language Models (LLMs). This progress has led to the emergence of chatbots and dialogue systems capable of fluent conversations with humans. As the variety of devices enabling... | main | null | 10.1609/aaai.v38i12.29219 | 38 | 12 | 13193-13201 | official | null | null |
10.1609/aaai.v38i13.29398 | NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation | https://ojs.aaai.org/index.php/AAAI/article/view/29398 | https://ojs.aaai.org/index.php/AAAI/article/download/29398/30641 | [
"Abbavaram Gowtham Reddy",
"Vineeth N Balasubramanian"
] | Causal effect estimation from observational data is a central problem in causal inference. Methods based on potential outcomes framework solve this problem by exploiting inductive biases and heuristics from causal inference. Each of these methods addresses a specific aspect of causal effect estimation, such as controll... | main | null | 10.1609/aaai.v38i13.29398 | 38 | 13 | 14793-14801 | official | 2211.04370 | title_snapshot |
10.1609/aaai.v38i14.29512 | Hyperbolic Graph Diffusion Model | https://ojs.aaai.org/index.php/AAAI/article/view/29512 | https://ojs.aaai.org/index.php/AAAI/article/download/29512/30849 | [
"Lingfeng Wen",
"Xuan Tang",
"Mingjie Ouyang",
"Xiangxiang Shen",
"Jian Yang",
"Daxin Zhu",
"Mingsong Chen",
"Xian Wei"
] | Diffusion generative models (DMs) have achieved promising results in image and graph generation. However, real-world graphs, such as social networks, molecular graphs, and traffic graphs, generally share non-Euclidean topologies and hidden hierarchies. For example, the degree distributions of graphs are mostly power-la... | main | null | 10.1609/aaai.v38i14.29512 | 38 | 14 | 15823-15831 | official | 2306.07618 | title_snapshot |
10.1609/aaai.v38i18.29985 | Symbolic Numeric Planning with Patterns | https://ojs.aaai.org/index.php/AAAI/article/view/29985 | https://ojs.aaai.org/index.php/AAAI/article/download/29985/31729 | [
"Matteo Cardellini",
"Enrico Giunchiglia",
"Marco Maratea"
] | In this paper, we propose a novel approach for solving linear numeric planning problems, called Symbolic Pattern Planning. Given a planning problem Pi, a bound n and a pattern --defined as an arbitrary sequence of actions-- we encode the problem of finding a plan for Pi with bound n as a formula with fewer variables an... | main | null | 10.1609/aaai.v38i18.29985 | 38 | 18 | 20070-20077 | official | 2312.09963 | title_snapshot |
10.1609/aaai.v38i17.29883 | Learning from Failure: Improving Meeting Summarization without Good Samples | https://ojs.aaai.org/index.php/AAAI/article/view/29883 | https://ojs.aaai.org/index.php/AAAI/article/download/29883/31541 | [
"Ke Wang",
"Xiutian Zhao",
"Wei Peng"
] | Existing methods aligning language models with various human needs are reliant heavily on high-quality and task-specific data. However, industrial deployment of task-specific language models often encounter challenges in the availability of appropriate training samples. Taking meeting summarization for instance, public... | main | null | 10.1609/aaai.v38i17.29883 | 38 | 17 | 19153-19161 | official | null | null |
10.1609/aaai.v38i14.29538 | AUC Optimization from Multiple Unlabeled Datasets | https://ojs.aaai.org/index.php/AAAI/article/view/29538 | https://ojs.aaai.org/index.php/AAAI/article/download/29538/30896 | [
"Zheng Xie",
"Yu Liu",
"Ming Li"
] | Weakly supervised learning aims to make machine learning more powerful when the perfect supervision is unavailable, and has attracted much attention from researchers. Among the various scenarios of weak supervision, one of the most challenging cases is learning from multiple unlabeled (U) datasets with only a little kn... | main | null | 10.1609/aaai.v38i14.29538 | 38 | 14 | 16058-16066 | official | 2305.15776 | title_snapshot |
10.1609/aaai.v38i4.28140 | Independency Adversarial Learning for Cross-Modal Sound Separation | https://ojs.aaai.org/index.php/AAAI/article/view/28140 | https://ojs.aaai.org/index.php/AAAI/article/download/28140/28283 | [
"Zhenkai Lin",
"Yanli Ji",
"Yang Yang"
] | The sound mixture separation is still challenging due to heavy sound overlapping and disturbance from noise. Unsupervised separation would significantly increase the difficulty. As sound overlapping always hinders accurate sound separation, we propose an Independency Adversarial Learning based Cross-Modal Sound Separat... | main | null | 10.1609/aaai.v38i4.28140 | 38 | 4 | 3522-3530 | official | null | null |
10.1609/aaai.v38i1.27752 | SeGA: Preference-Aware Self-Contrastive Learning with Prompts for Anomalous User Detection on Twitter | https://ojs.aaai.org/index.php/AAAI/article/view/27752 | https://ojs.aaai.org/index.php/AAAI/article/download/27752/27547 | [
"Ying-Ying Chang",
"Wei-Yao Wang",
"Wen-Chih Peng"
] | In the dynamic and rapidly evolving world of social media, detecting anomalous users has become a crucial task to address malicious activities such as misinformation and cyberbullying. As the increasing number of anomalous users improves the ability to mimic normal users and evade detection, existing methods only focus... | main | null | 10.1609/aaai.v38i1.27752 | 38 | 1 | 30-37 | official | 2312.11553 | title_snapshot |
10.1609/aaai.v38i5.28289 | DPA-P2PNet: Deformable Proposal-Aware P2PNet for Accurate Point-Based Cell Detection | https://ojs.aaai.org/index.php/AAAI/article/view/28289 | https://ojs.aaai.org/index.php/AAAI/article/download/28289/28569 | [
"Zhongyi Shui",
"Sunyi Zheng",
"Chenglu Zhu",
"Shichuan Zhang",
"Xiaoxuan Yu",
"Honglin Li",
"Jingxiong Li",
"Pingyi Chen",
"Lin Yang"
] | Point-based cell detection (PCD), which pursues high-performance cell sensing under low-cost data annotation, has garnered increased attention in computational pathology community. Unlike mainstream PCD methods that rely on intermediate density map representations, the Point-to-Point network (P2PNet) has recently emerg... | main | null | 10.1609/aaai.v38i5.28289 | 38 | 5 | 4864-4872 | official | 2303.02602 | title_snapshot |
10.1609/aaai.v38i16.29786 | Uncovering and Mitigating the Hidden Chasm: A Study on the Text-Text Domain Gap in Euphemism Identification | https://ojs.aaai.org/index.php/AAAI/article/view/29786 | https://ojs.aaai.org/index.php/AAAI/article/download/29786/31358 | [
"Yuxue Hu",
"Junsong Li",
"Mingmin Wu",
"Zhongqiang Huang",
"Gang Chen",
"Ying Sha"
] | Euphemisms are commonly used on social media and darknet marketplaces to evade platform regulations by masking their true meanings with innocent ones. For instance, “weed” is used instead of “marijuana” for illicit transactions. Thus, euphemism identification, i.e., mapping a given euphemism (“weed”) to its specific ta... | main | null | 10.1609/aaai.v38i16.29786 | 38 | 16 | 18270-18278 | official | null | null |
10.1609/aaai.v38i4.28137 | TD²-Net: Toward Denoising and Debiasing for Video Scene Graph Generation | https://ojs.aaai.org/index.php/AAAI/article/view/28137 | https://ojs.aaai.org/index.php/AAAI/article/download/28137/28277 | [
"Xin Lin",
"Chong Shi",
"Yibing Zhan",
"Zuopeng Yang",
"Yaqi Wu",
"Dacheng Tao"
] | Dynamic scene graph generation (SGG) focuses on detecting objects in a video and determining their pairwise relationships. Existing dynamic SGG methods usually suffer from several issues, including 1) Contextual noise, as some frames might contain occluded and blurred objects. 2) Label bias, primarily due to the high i... | main | null | 10.1609/aaai.v38i4.28137 | 38 | 4 | 3495-3503 | official | 2401.12479 | title_judge |
10.1609/aaai.v38i18.29976 | Robustness Verification of Deep Reinforcement Learning Based Control Systems Using Reward Martingales | https://ojs.aaai.org/index.php/AAAI/article/view/29976 | https://ojs.aaai.org/index.php/AAAI/article/download/29976/31711 | [
"Dapeng Zhi",
"Peixin Wang",
"Cheng Chen",
"Min Zhang"
] | Deep Reinforcement Learning (DRL) has gained prominence as an effective approach for control systems. However, its practical deployment is impeded by state perturbations that can severely impact system performance. Addressing this critical challenge requires robustness verification about system performance, which invol... | main | null | 10.1609/aaai.v38i18.29976 | 38 | 18 | 19992-20000 | official | 2312.09695 | title_snapshot |
10.1609/aaai.v38i3.27962 | ContactGen: Contact-Guided Interactive 3D Human Generation for Partners | https://ojs.aaai.org/index.php/AAAI/article/view/27962 | https://ojs.aaai.org/index.php/AAAI/article/download/27962/27943 | [
"Dongjun Gu",
"Jaehyeok Shim",
"Jaehoon Jang",
"Changwoo Kang",
"Kyungdon Joo"
] | Among various interactions between humans, such as eye contact and gestures, physical interactions by contact can act as an essential moment in understanding human behaviors. Inspired by this fact, given a 3D partner human with the desired interaction label, we introduce a new task of 3D human generation in terms of ph... | main | null | 10.1609/aaai.v38i3.27962 | 38 | 3 | 1923-1931 | official | 2401.17212 | title_snapshot |
10.1609/aaai.v38i17.29882 | Restoring Speaking Lips from Occlusion for Audio-Visual Speech Recognition | https://ojs.aaai.org/index.php/AAAI/article/view/29882 | https://ojs.aaai.org/index.php/AAAI/article/download/29882/31539 | [
"Jiadong Wang",
"Zexu Pan",
"Malu Zhang",
"Robby T. Tan",
"Haizhou Li"
] | Prior studies on audio-visual speech recognition typically assume the visibility of speaking lips, ignoring the fact that visual occlusion occurs in real-world videos, thus adversely affecting recognition performance. To address this issue, we propose a framework that restores occluded lips in a video by utilizing both... | main | null | 10.1609/aaai.v38i17.29882 | 38 | 17 | 19144-19152 | official | null | null |
10.1609/aaai.v38i15.29573 | Leveraging Normalization Layer in Adapters with Progressive Learning and Adaptive Distillation for Cross-Domain Few-Shot Learning | https://ojs.aaai.org/index.php/AAAI/article/view/29573 | https://ojs.aaai.org/index.php/AAAI/article/download/29573/30962 | [
"YongJin Yang",
"Taehyeon Kim",
"Se-Young Yun"
] | Cross-domain few-shot learning presents a formidable challenge, as models must be trained on base classes and then tested on novel classes from various domains with only a few samples at hand. While prior approaches have primarily focused on parameter-efficient methods of using adapters, they often overlook two critica... | main | null | 10.1609/aaai.v38i15.29573 | 38 | 15 | 16370-16378 | official | 2312.11260 | title_snapshot |
10.1609/aaai.v38i2.27843 | VIXEN: Visual Text Comparison Network for Image Difference Captioning | https://ojs.aaai.org/index.php/AAAI/article/view/27843 | https://ojs.aaai.org/index.php/AAAI/article/download/27843/27712 | [
"Alexander Black",
"Jing Shi",
"Yifei Fan",
"Tu Bui",
"John Collomosse"
] | We present VIXEN - a technique that succinctly summarizes in text the visual differences between a pair of images in order to highlight any content manipulation present. Our proposed network linearly maps image features in a pairwise manner, constructing a soft prompt for a pretrained large language model. We address t... | main | null | 10.1609/aaai.v38i2.27843 | 38 | 2 | 846-854 | official | 2402.19119 | title_snapshot |
10.1609/aaai.v38i15.29649 | DCLP: Neural Architecture Predictor with Curriculum Contrastive Learning | https://ojs.aaai.org/index.php/AAAI/article/view/29649 | https://ojs.aaai.org/index.php/AAAI/article/download/29649/31103 | [
"Shenghe Zheng",
"Hongzhi Wang",
"Tianyu Mu"
] | Neural predictors have shown great potential in the evaluation process of neural architecture search (NAS). However, current predictor-based approaches overlook the fact that training a predictor necessitates a considerable number of trained neural networks as the labeled training set, which is costly to obtain. Theref... | main | null | 10.1609/aaai.v38i15.29649 | 38 | 15 | 17051-17059 | official | 2302.13020 | title_snapshot |
10.1609/aaai.v38i5.28305 | UniAP: Towards Universal Animal Perception in Vision via Few-Shot Learning | https://ojs.aaai.org/index.php/AAAI/article/view/28305 | https://ojs.aaai.org/index.php/AAAI/article/download/28305/28600 | [
"Meiqi Sun",
"Zhonghan Zhao",
"Wenhao Chai",
"Hanjun Luo",
"Shidong Cao",
"Yanting Zhang",
"Jenq-Neng Hwang",
"Gaoang Wang"
] | Animal visual perception is an important technique for automatically monitoring animal health, understanding animal behaviors, and assisting animal-related research. However, it is challenging to design a deep learning-based perception model that can freely adapt to different animals across various perception tasks, du... | main | null | 10.1609/aaai.v38i5.28305 | 38 | 5 | 5008-5016 | official | 2308.09953 | title_snapshot |
10.1609/aaai.v38i9.28920 | Dynamic Tangled Derivative Logic of Metric Spaces | https://ojs.aaai.org/index.php/AAAI/article/view/28920 | https://ojs.aaai.org/index.php/AAAI/article/download/28920/29750 | [
"David Fernández-Duque",
"Yoàv Montacute"
] | Dynamical systems are abstract models of interaction between space and time. They are often used in fields such as physics and engineering to understand complex processes, but due to their general nature, they have found applications for studying computational processes, interaction in multi-agent systems, machine lear... | main | null | 10.1609/aaai.v38i9.28920 | 38 | 9 | 10509-10516 | official | 2301.09904 | title_snapshot |
10.1609/aaai.v38i1.27753 | Neural Embeddings for kNN Search in Biological Sequence | https://ojs.aaai.org/index.php/AAAI/article/view/27753 | https://ojs.aaai.org/index.php/AAAI/article/download/27753/27549 | [
"Zhihao Chang",
"Linzhu Yu",
"Yanchao Xu",
"Wentao Hu"
] | Biological sequence nearest neighbor search plays a fundamental role in bioinformatics. To alleviate the pain of quadratic complexity for conventional distance computation, neural distance embeddings, which project sequences into geometric space, have been recognized as a promising paradigm. To maintain the distance or... | main | null | 10.1609/aaai.v38i1.27753 | 38 | 1 | 38-45 | official | null | null |
10.1609/aaai.v38i6.28348 | Triple Feature Disentanglement for One-Stage Adaptive Object Detection | https://ojs.aaai.org/index.php/AAAI/article/view/28348 | https://ojs.aaai.org/index.php/AAAI/article/download/28348/28682 | [
"Haoan Wang",
"Shilong Jia",
"Tieyong Zeng",
"Guixu Zhang",
"Zhi Li"
] | In recent advancements concerning Domain Adaptive Object Detection (DAOD), unsupervised domain adaptation techniques have proven instrumental. These methods enable enhanced detection capabilities within unlabeled target domains by mitigating distribution differences between source and target domains. A subset of DAOD m... | main | null | 10.1609/aaai.v38i6.28348 | 38 | 6 | 5401-5409 | official | null | null |
10.1609/aaai.v38i13.29324 | Layer Collaboration in the Forward-Forward Algorithm | https://ojs.aaai.org/index.php/AAAI/article/view/29324 | https://ojs.aaai.org/index.php/AAAI/article/download/29324/30498 | [
"Guy Lorberbom",
"Itai Gat",
"Yossi Adi",
"Alexander Schwing",
"Tamir Hazan"
] | Backpropagation, which uses the chain rule, is the de-facto standard algorithm for optimizing neural networks nowadays. Recently, Hinton (2022) proposed the forward-forward algorithm, a promising alternative that optimizes neural nets layer-by-layer, without propagating gradients throughout the network. Although such a... | main | null | 10.1609/aaai.v38i13.29324 | 38 | 13 | 14141-14148 | official | 2305.12393 | title_snapshot |
10.1609/aaai.v38i12.29286 | Mitigating Label Noise through Data Ambiguation | https://ojs.aaai.org/index.php/AAAI/article/view/29286 | https://ojs.aaai.org/index.php/AAAI/article/download/29286/30425 | [
"Julian Lienen",
"Eyke Hüllermeier"
] | Label noise poses an important challenge in machine learning, especially in deep learning, in which large models with high expressive power dominate the field. Models of that kind are prone to memorizing incorrect labels, thereby harming generalization performance. Many methods have been proposed to address this proble... | main | null | 10.1609/aaai.v38i12.29286 | 38 | 12 | 13799-13807 | official | 2305.13764 | title_snapshot |
10.1609/aaai.v38i9.28824 | Refined Characterizations of Approval-Based Committee Scoring Rules | https://ojs.aaai.org/index.php/AAAI/article/view/28824 | https://ojs.aaai.org/index.php/AAAI/article/download/28824/29570 | [
"Chris Dong",
"Patrick Lederer"
] | In approval-based committee (ABC) elections, the goal is to select a fixed-size subset of the candidates, a so-called committee, based on the voters' approval ballots over the candidates. One of the most popular classes of ABC voting rules are ABC scoring rules, for which voters give points to each committee and the co... | main | null | 10.1609/aaai.v38i9.28824 | 38 | 9 | 9670-9678 | official | 2312.08799 | title_snapshot |
10.1609/aaai.v38i8.28768 | Pairwise-Label-Based Deep Incremental Hashing with Simultaneous Code Expansion | https://ojs.aaai.org/index.php/AAAI/article/view/28768 | https://ojs.aaai.org/index.php/AAAI/article/download/28768/29474 | [
"Dayan Wu",
"Qinghang Su",
"Bo Li",
"Weiping Wang"
] | Deep incremental hashing has become a subject of considerable interest due to its capability to learn hash codes in an incremental manner, eliminating the need to generate codes for classes that have already been learned. However, accommodating more classes requires longer hash codes, and regenerating database codes be... | main | null | 10.1609/aaai.v38i8.28768 | 38 | 8 | 9169-9177 | official | null | null |
10.1609/aaai.v38i11.29160 | Higher-Order Graph Convolutional Network with Flower-Petals Laplacians on Simplicial Complexes | https://ojs.aaai.org/index.php/AAAI/article/view/29160 | https://ojs.aaai.org/index.php/AAAI/article/download/29160/30194 | [
"Yiming Huang",
"Yujie Zeng",
"Qiang Wu",
"Linyuan Lü"
] | Despite the recent successes of vanilla Graph Neural Networks (GNNs) on various tasks, their foundation on pairwise networks inherently limits their capacity to discern latent higher-order interactions in complex systems. To bridge this capability gap, we propose a novel approach exploiting the rich mathematical theory... | main | null | 10.1609/aaai.v38i11.29160 | 38 | 11 | 12653-12661 | official | 2309.12971 | title_snapshot |
10.1609/aaai.v38i18.30062 | Parallel Beam Search Algorithms for Domain-Independent Dynamic Programming | https://ojs.aaai.org/index.php/AAAI/article/view/30062 | https://ojs.aaai.org/index.php/AAAI/article/download/30062/31869 | [
"Ryo Kuroiwa",
"J. Christopher Beck"
] | Domain-independent dynamic programming (DIDP), a model-based paradigm based on dynamic programming, has shown promising performance on multiple combinatorial optimization problems compared with mixed integer programming (MIP) and constraint programming (CP). The current DIDP solvers are based on heuristic search, and t... | main | null | 10.1609/aaai.v38i18.30062 | 38 | 18 | 20743-20750 | official | null | null |
10.1609/aaai.v38i11.29125 | A New Mechanism for Eliminating Implicit Conflict in Graph Contrastive Learning | https://ojs.aaai.org/index.php/AAAI/article/view/29125 | https://ojs.aaai.org/index.php/AAAI/article/download/29125/30128 | [
"Dongxiao He",
"Jitao Zhao",
"Cuiying Huo",
"Yongqi Huang",
"Yuxiao Huang",
"Zhiyong Feng"
] | Graph contrastive learning (GCL) has attracted considerable attention because it can self-supervisedly extract low-dimensional representation of graph data. InfoNCE-based loss function is widely used in graph contrastive learning, which pulls the representations of positive pairs close to each other and pulls the repre... | main | null | 10.1609/aaai.v38i11.29125 | 38 | 11 | 12340-12348 | official | null | null |
10.1609/aaai.v38i4.28152 | M3SOT: Multi-Frame, Multi-Field, Multi-Space 3D Single Object Tracking | https://ojs.aaai.org/index.php/AAAI/article/view/28152 | https://ojs.aaai.org/index.php/AAAI/article/download/28152/28306 | [
"Jiaming Liu",
"Yue Wu",
"Maoguo Gong",
"Qiguang Miao",
"Wenping Ma",
"Cai Xu",
"Can Qin"
] | 3D Single Object Tracking (SOT) stands a forefront task of computer vision, proving essential for applications like autonomous driving. Sparse and occluded data in scene point clouds introduce variations in the appearance of tracked objects, adding complexity to the task. In this research, we unveil M3SOT, a novel 3D S... | main | null | 10.1609/aaai.v38i4.28152 | 38 | 4 | 3630-3638 | official | 2312.06117 | title_snapshot |
10.1609/aaai.v38i16.29721 | When Do Program-of-Thought Works for Reasoning? | https://ojs.aaai.org/index.php/AAAI/article/view/29721 | https://ojs.aaai.org/index.php/AAAI/article/download/29721/31237 | [
"Zhen Bi",
"Ningyu Zhang",
"Yinuo Jiang",
"Shumin Deng",
"Guozhou Zheng",
"Huajun Chen"
] | In the realm of embodied artificial intelligence, the reasoning capabilities of Large Language Models (LLMs) play a pivotal role. Although there are effective methods like program-of-thought prompting for LLMs which uses programming language to tackle complex reasoning tasks, the specific impact of code data on the imp... | main | null | 10.1609/aaai.v38i16.29721 | 38 | 16 | 17691-17699 | official | null | null |
10.1609/aaai.v38i7.28526 | Amodal Scene Analysis via Holistic Occlusion Relation Inference and Generative Mask Completion | https://ojs.aaai.org/index.php/AAAI/article/view/28526 | https://ojs.aaai.org/index.php/AAAI/article/download/28526/29025 | [
"Bowen Zhang",
"Qing Liu",
"Jianming Zhang",
"Yilin Wang",
"Liyang Liu",
"Zhe Lin",
"Yifan Liu"
] | Amodal scene analysis entails interpreting the occlusion relationship among scene elements and inferring the possible shapes of the invisible parts. Existing methods typically frame this task as an extended instance segmentation or a pair-wise object de-occlusion problem. In this work, we propose a new framework, which... | main | null | 10.1609/aaai.v38i7.28526 | 38 | 7 | 6997-7005 | official | null | null |
10.1609/aaai.v38i10.28990 | Where and How to Attack? A Causality-Inspired Recipe for Generating Counterfactual Adversarial Examples | https://ojs.aaai.org/index.php/AAAI/article/view/28990 | https://ojs.aaai.org/index.php/AAAI/article/download/28990/29881 | [
"Ruichu Cai",
"Yuxuan Zhu",
"Jie Qiao",
"Zefeng Liang",
"Furui Liu",
"Zhifeng Hao"
] | Deep neural networks (DNNs) have been demonstrated to be vulnerable to well-crafted adversarial examples, which are generated through either well-conceived L_p-norm restricted or unrestricted attacks. Nevertheless, the majority of those approaches assume that adversaries can modify any features as they wish, and neglec... | main | null | 10.1609/aaai.v38i10.28990 | 38 | 10 | 11132-11140 | official | 2312.13628 | title_snapshot |
10.1609/aaai.v38i18.30075 | Threshold-Based Responsive Simulated Annealing for Directed Feedback Vertex Set Problem | https://ojs.aaai.org/index.php/AAAI/article/view/30075 | https://ojs.aaai.org/index.php/AAAI/article/download/30075/31893 | [
"Qingyun Zhang",
"Yuming Du",
"Zhouxing Su",
"Chu-Min Li",
"Junzhou Xu",
"Zhihuai Chen",
"Zhipeng Lü"
] | As a classical NP-hard problem and the topic of the PACE 2022 competition, the directed feedback vertex set problem (DFVSP) aims to find a minimum subset of vertices such that, when vertices in the subset and all their adjacent edges are removed from the directed graph, the remainder graph is acyclic. In this paper, we... | main | null | 10.1609/aaai.v38i18.30075 | 38 | 18 | 20856-20864 | official | null | null |
10.1609/aaai.v38i6.28391 | QAGait: Revisit Gait Recognition from a Quality Perspective | https://ojs.aaai.org/index.php/AAAI/article/view/28391 | https://ojs.aaai.org/index.php/AAAI/article/download/28391/28764 | [
"Zengbin Wang",
"Saihui Hou",
"Man Zhang",
"Xu Liu",
"Chunshui Cao",
"Yongzhen Huang",
"Peipei Li",
"Shibiao Xu"
] | Gait recognition is a promising biometric method that aims to identify pedestrians from their unique walking patterns. Silhouette modality, renowned for its easy acquisition, simple structure, sparse representation, and convenient modeling, has been widely employed in controlled in-the-lab research. However, as gait re... | main | null | 10.1609/aaai.v38i6.28391 | 38 | 6 | 5785-5793 | official | 2401.13531 | title_snapshot |
10.1609/aaai.v38i6.28437 | Attention Disturbance and Dual-Path Constraint Network for Occluded Person Re-identification | https://ojs.aaai.org/index.php/AAAI/article/view/28437 | https://ojs.aaai.org/index.php/AAAI/article/download/28437/28852 | [
"Jiaer Xia",
"Lei Tan",
"Pingyang Dai",
"Mingbo Zhao",
"Yongjian Wu",
"Liujuan Cao"
] | Occluded person re-identification (Re-ID) aims to address the potential occlusion problem when matching occluded or holistic pedestrians from different camera views. Many methods use the background as artificial occlusion and rely on attention networks to exclude noisy interference. However, the significant discrepancy... | main | null | 10.1609/aaai.v38i6.28437 | 38 | 6 | 6198-6206 | official | 2303.10976 | title_snapshot |
10.1609/aaai.v38i1.27819 | DMMR: Cross-Subject Domain Generalization for EEG-Based Emotion Recognition via Denoising Mixed Mutual Reconstruction | https://ojs.aaai.org/index.php/AAAI/article/view/27819 | https://ojs.aaai.org/index.php/AAAI/article/download/27819/27668 | [
"Yiming Wang",
"Bin Zhang",
"Yujiao Tang"
] | Electroencephalography (EEG) has proven to be effective in emotion analysis. However, current methods struggle with individual variations, complicating the generalization of models trained on data from source subjects to unseen target subjects. To tackle this issue, we propose the Denoising Mixed Mutual Reconstruction ... | main | null | 10.1609/aaai.v38i1.27819 | 38 | 1 | 628-636 | official | null | null |
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