ACCEPTED PAPERS

At ACML 2024, each accepted paper will feature both an oral presentation and a poster presentation. For oral presentations, please ensure that the presentation slides are in PDF format. The detailed schedule for each accepted paper will be updated shortly.

For poster presentations, the poster boards will be in portrait orientation, and the standard size is A0 (84.1 cm width x 118.9 cm height or 33.1 inches width x 46.8 inches height). Poster sessions are scheduled on December 5 and 6, 2024.

We are pleased to announce the accepted papers at ACML 2024 as follows:

ACCEPTED JOURNAL TRACK PAPERS

• On the Convergence Analysis of Over-Parameterized Variational Autoencoders: A Neural Tangent Kernel Perspective Li Wang, Wei Huang

• SA-LfV: Self-Annotated Labeling from Videos for Object Detection Arun Kumar Sivapuram, Prashanth Komurevelli, Rama Krishna Sai Gorthi

• Concentration properties of fractional posterior in 1-bit matrix completion The Tien Mai

• Progressive Semantic Learning for Unsupervised Skeleton-Based Action Recognition Hao Qin, Luyuan Chen, Ming Kong, Zhuoran Zhao, Xianzhou Zeng, Mengxu Lu, Qiang Zhu

• Probabilistic Instance Dependent Label Refinement for Noisy Label Learning Hao-Yuan He, Yu Liu, Ren-Biao Liu, Zheng Xie, Ming Li

• Misclassification bounds for PAC-Bayesian sparse deep learning The Tien Mai

• NetTOP: A light-weight network of orthogonal-plane features for image recognition Thanh Tuan NGUYEN, Thanh Phuong NGUYEN

• Efficient Federated Unlearning under Plausible Deniability Ayush K. Varshney, Vicenç Torra

• HorNets: Learning from Discrete and Continuous Signals with Routing Neural Networks Boshko Koloski, Nada Lavrac, Blaž Škrlj

• Semantic-Aware Contrastive Learning via Multi-Prompt Alignment Zhuoran Zhao, Hao Qin, Ming Kong, Luyuan Chen, Di Xie, Jiang Zhu, Qiang Zhu

• Toward Finding Strong Pareto Optimal Policies in Multi-Agent Reinforcement Learning Bang Giang Le, Viet Cuong Ta

• Let the Noise Flow Away: Combating Noisy Labels using Normalizing Flows Kuan-An Su, YiHao Su, Yun-Hsuan Lien, Yu-Shuen Wang

• ShuttleFlow: Learning the Distribution of Subsequent Badminton Shots using Normalizing Flows Yun-Hsuan Lien, Chia-Tung Lian, Yu-Shuen Wang

• Knoop: Practical Enhancement of Knockoff with Over-Parameterization for Variable Selection Xiaochen Zhang, Yunfeng Cai, Haoyi Xiong

• Is it Still Fair? A Comparative Evaluation of Fairness Algorithms through the Lens of Covariate Drift Oscar Blessed Deho, Michael Bewong, Selasi Kwashie, Jiuyong Li, Jixue Liu, Lin Liu, Srecko Joksimovic

• SpatioTemporal-View Member Preferences Contrastive Representation Learning for Group Recommendation Yangtao Zhou, Qingshan Li, Hua Chu, Jianan Li, Biaobiao Wei, Shuai Zhang, Jialong Han

• A Prompt-Driven Framework for Multi-Domain Knowledge Tracing Zitao Liu, Shuyan Huang, Guo Teng, Mingliang Hou, Qianru Liang

• Distribution Aligned Semantics Adaption for Lifelong Person Re-Identification Qizao Wang, Xuelin Qian, Bin Li, Xiangyang Xue

• Synthesizing Efficient Data with Diffusion Models for Person Re-Identification Pre-Training Ke Niu, Haiyang Yu, Xuelin Qian, Teng Fu, Bin Li, Xiangyang Xue

• A Survey on Self-Supervised Learning for Non-Sequential Tabular Data Wei-Yao Wang, Wei-Wei Du, Derek Xu, Wei Wang, Wen-Chih Peng

• Learning to Rank Aspects and Opinions for Comparative Explanations Trung-Hoang Le, Hady W. Lauw

• Capturing the Context-Aware Code Change via Dynamic Control Flow Graph for Commit Message Generation Yali Du, Ying Li, Yi-Fan Ma, Ming Li

• Shift Guided Active Learning Jianan Yang, Jimin Tan, Haobo Wang, Gang Chen, Sai Wu, Junbo Zhao

• Gradient-based Causal Discovery with Latent Variables Haotian Ni, Tian-Zuo Wang, Hong Tao, Xiuqi Huang, Chenping Hou

• Optimizing Sharpe Ratio: Risk-Adjusted Decision-Making in Multi-Armed Bandits Sabrina Khurshid, Mohammed Shahid Abdulla, Gourab Ghatak

• Scalable Individual Treatment Effect Estimator for Large Graphs Xiaofeng Lin, Han Bao, Yan Cui, Koh Takeuchi, Hisashi Kashima

• Active Model Selection: A Variance Minimization Approach Satoshi Hara, Mitsuru Matsuura, Junya Honda, Shinji Ito

• SketchMLP: Effectively Utilize Rasterized Images and Drawing Sequences for Sketch Recognition Tengjie Li, Shikui Tu, Lei Xu

• Dual-view Data Augmentation at Subgraph Level and Graph Contrastive Learning for Sequential Recommendation Caihong Mu, Haikun Yu, Lang Qin, Yi Liu

• Enhanced Route Planning with Calibrated Uncertainty Set Lingxuan Tang, Rui Luo, Zhixin Zhou, Nicolo Colombo

• Per-Example Gradient Regularization Improves Learning Signals from Noisy Data Xuran Meng, Yuan Cao, Difan Zou

• Towards Efficient Pareto-optimal Utility-Fairness between Groups in Repeated Rankings Phuong Dinh Mai, Duc-Trong Le, Tuan-Anh Hoang, Dung D. Le

• Adaptive Adapter Routing for Long-Tailed Class-Incremental Learning Zhi-Hong Qi, Da-Wei Zhou, Yiran Yao, Han-Jia Ye, De-Chuan Zhan

• State-Novelty Guided Action Persistence in Deep Reinforcement Learning Jianshu Hu, Paul Weng, Yutong Ban

• Warping resilient Robust Anomaly Detection for Multivariate Time Series Abilasha S, Sahely Bhadra

• Re-assessing Accuracy Degradation: A Framework for Understanding DNN Behavior on Similar-but-non-identical Test Datasets Esla Timothy Anzaku, Haohan Wang, Ajiboye Babalola, Arnout Van Messem, Wesley De Neve

• SA-CAM: Semantic-Aware Visual Explanations for Deep Convolutional Networks Anni Yu, Qing-Long Zhang, Lu Rao, Yu-Bin Yang

• Schema-Tune: Noise-Driven Bias Mitigation in Transformer-based Language Models Omid Shokrollahi, Ruthvik Penumatcha, Faezeh Ensan, Zeinab Noorian

• Artificial Intelligence for Laryngoscopy in Vocal Fold Diseases: A Review of Dataset Technology and Ethics Thao Thi Phuong Dao, Tan-Cong Nguyen, Viet-Tham Huynh, Xuan-Hai Bui, Trung-Nghia Le, Minh-Triet Tran

• Commonsense Knowledge Enhanced Event Graph Representation Learning for Script Event Prediction Xiang Li, Xinxi Jiang, Qifeng Zhou

• PT4Rec: A Universal Prompt-Tuning Framework for Graph Contrastive Learning-Based Recommendations Wei Xiao, Qifeng Zhou

• Verification on Out-of-Distribution Detectors under Natural Perturbations Chi Zhang, Zhen Chen, Peipei Xu, Geyong Min, Wenjie Ruan

• ArithmeticGPT: Empowering Small-size Large Language Models with Advanced Arithmetic Skills Zitao Liu, Ying Zheng, Zhibo Yin, Jiahao Chen, Tianqiao Liu, Mi Tian, Weiqi Luo

• Robust Query Performance Prediction for Dense Retrievers via Adaptive Disturbance Generation Abbas Saleminezhad, Negar Arabzadeh, Radin Hamidi Rad, Soosan Beheshti, Ebrahim Bagheri

• Adaptive Transformer Modelling of Density Function for Nonparametric Survival Analysis Xin Zhang, Deval Mehta, Yanan Hu, Chao Zhu, David Darby, Zhen Yu, Daniel Merlo, Melissa Gresle, Anneke van der Walt, Helmut Butzkueven, Zongyuan Ge

• Gender Disentangled Representation Learning in Neural Rankers Shirin Seyedsalehi, Sara Salamat, Negar Arabzadeh, Sajad Ebrahimi, Morteza Zihayat, Ebrahim Bagheri

• Learning Global Object-Centric Representations via Disentangled Slot Attention Tonglin Chen, Yinxuan Huang, Zhimeng Shen, Jinghao Huang, Bin Li, Xiangyang Xue

• Sandbox: Safeguarded Multi-label Learning through Safe Optimal Transport Lefei Zhang, Geng Yu, Jiangchao Yao, Yew-soon Ong, Ivor W. Tsang, James T. Kwok

ACCEPTED CONFERENCE TRACK PAPERS

• DCoT: Dual Chain-of-Thought Prompting for Large Multimodal Models

  Zixi Jia, Jiqiang Liu, Hexiao Li, Qinghua Liu, Hongbin Gao

• Fast Stealthily Biased Sampling Using Sliced Wasserstein Distance

  Yudai Yamamoto, Satoshi Hara

• SceneWeaver: Text-Driven Scene Generation with Geometry-aware Gaussian Splatting

  Xiaolu Hou, Mingcheng Li, Jiawei Chen, Dingkang Yang, Ziyun Qian, Lihua Zhang

• Understanding Transcriptional Regulatory Redundancy by Learnable Global Subset Perturbations

  Junhao Liu, Siwei Xu, Dylan Riffle, Ziheng Duan, Martin Renqiang Min, Jing Zhang

• Towards Robust Saliency Maps

  Nham Le, Arie Gurfinkel, Xujie Si, Chuqin Geng

• Multi-Task Network Guided Multimodal Fusion for Fake News Detection

  Jinke Ma, Liyuan Zhang, Yong Liu, Wei Zhang

• On Learning Frequency-Instance Correlations by Model-Agnostic Training for Synthetic Speech Detection

  Zining Wang, Lijian Gao, Jialin Zhang, Qirong Mao

• Orchestrating Plasticity and Stability: A Continual Knowledge Graph Embedding Framework with Bio-Inspired Dual-Mask Mechanism

  Ailin Song, Yuhong Chen, Yusong Wang, Shuai Zhong, Mingkun Xu

• Causal ATTention Multiple Instance Learning for Whole Slide Image Classification

  Xiaochun Wu, Haitao Wang, Hejun Wu

• Prompting Vision-Language Fusion for Zero-Shot Composed Image Retrieval

  Peng Wang, Zining Chen, Zhicheng Zhao, Fei Su

• Convergence Analysis of Inexact Over-Relaxed ADMM via Dissipativity Theory

  Qiang Zhou, Sinno Jialin Pan

• Knowledge Graph Large Language Model (KG-LLM) for Link Prediction

  Dong Shu, Tianle Chen, Mingyu Jin, Chong Zhang, Mengnan Du, Yongfeng Zhang

• Multilevel Position-aware Attention Enhanced Network for Skeleton-Based Action Recognition

  Dandan Zhang, Jia Wang, Sicong Zhan

• Preserving Spatial-Temporal Relationship with Adaptive Node Sampling in Hierarchical Dynamic Graph Transformers

  Linh Thi Hoang, Tuan Dung Pham, Son T. Mai, Viet Cuong Ta

• Non-Oblivious Performance of Random Projections

  Maciej Skorski, Alessandro Temperoni

• FTP: A Human Pose Estimation Method Integrating Temporal and Fine-Grained Feature Fusion

  Shuqiang Cai, Chennan Ma, Xin Wang, Li Lin, Ming Yan, Xincheng Lin, Shuqi Fan, Siqi Shen

• InfantCryNet: A Data-driven Framework for Intelligent Analysis of Infant Cries

  Mengze Hong, Chen Jason Zhang, Lingxiao Yang, Yuanfeng SONG, Di Jiang

• Diffusion Model Based Posterior Sampling for Noisy Linear Inverse Problems

  Xiangming Meng, Yoshiyuki Kabashima

• RedditEM: Unveiling Diachronic Semantic Shifts in Social Network Discourse

  Jiajun Zou, Sixing Wu, Jinshuai Yang, Minghu Jiang, Yongfeng Huang

• Enhancing Textbook Question Answering with Knowledge Graph-Augmented Large Language Models

  Mengliang He, Aimin Zhou, Xiaoming Shi

• The data-driven transferable adversarial space

  Yuan Liu, Stephane Canu

• GRU-M: A Joint Impute and Learn Approach for Sequential Prediction under Missing Data

  Soumen Pachal, Avinash Achar, Nancy Bhutani, Akash Das

• LPNER: Label Prompt for Few-shot Nested Named Entity Recognition

  Jiaoyun Yang, Zhihan Zhu, Hong Ming, Lili Jiang, Ning An

• Constrained Implicit Learning Framework for Neural Network Sparsification

  Alicia Y. Tsai, Wenzhi Gao, Laurent Ghaoui

• FedDGL: Federated Dynamic Graph Learning for Temporal Evolution and Data Heterogeneity

  Zaipeng Xie, Li Likun, Xiangbin Chen, Hao Yu, Qian Huang

• When and How to Grow? On Efficient Pre-training via Model Growth

  Jikai Wang, Juntao Li, Min Zhang, Zechang Li, Qingrong Xia, Xinyu Duan, Zhefeng Wang, Baoxing Huai

• Vision Transformer with High Spatial Structure Sensitivity

  Zhiwei Xu

• How Classification Baseline Works for Deep Metric Learning: A Perspective of Metric Space

  Yuanqu Mou, Zhengxue Jian, Haiyang Bai, Chang Gou

• Enhancing Aspect Sentiment Quad Prediction through Dual-Sequence Data Augmentation and Contrastive Learning

  Shihao Li, Nankai Lin, Pinmo Wu, Dong Zhou, Aimin Yang

• Constructing a Knowledge-Guided Mental Health Chatbot with LLMs

  Xi Fan, Lishan Yang, Xiangyu Wang, Derui Lyu, Huanhuan Chen

• Chain Association-based Attacking and Shielding Natural Language Processing Systems

  JiaCheng Huang, Long Chen

• Middle Code Prediction: Enhancing Code Generation for Uncommon Programming Languages in Robotics

  Zixi Jia, Hongbin Gao, Hexiao Li

• Zero-Reference Lighting Estimation Diffusion Model for Low-Light Image Enhancement

  Jinhong He, Minglong Xue, Aoxiang Ning, Chengyun Song

• A Novel Evolutionary Multitasking Feature Selection Approach for Genomic Data Classification

  Yu Yifan, Wang Dazhi, Chen Yanhua, Wang Hongfeng, Huang Min

• Saliency Maps Give a False Sense of Explanability to Image Classifiers: An Empirical Evaluation across Methods and Metrics

  Hanwei Zhang, Felipe Torres Figueroa, Holger Hermanns

• Membership Inference Attacks Against Time-Series Models

  Noam Koren, Abigail Goldsteen, Guy Amit, Ariel Farkash

• Adapting the Attention of Cloud-Based Recognition Model to Client-Side Images without Local Re-Training

  Yangwenjian Tan, Yikai Yan, Chaoyue Niu

• Differentially Private Deep Learning with Importance-based Adaptive Gradient Processing

  Ping Li, Mingwei Liang, Zhao Jiang, Jun Zhang

• One-Shot Machine Unlearning with Mnemonic Code

  Tomoya Yamashita, Masanori Yamada, Takashi Shibata

• FedLF: Adaptive Logit Adjustment and Feature Optimization in Federated Long-Tailed Learning

  Xiuhua Lu, Peng Li, Xuefeng Jiang

• Toward Data Efficient Model Merging between Different Datasets without Performance Degradation

  Masanori Yamada, Tomoya Yamashita, Shin'ya Yamaguchi, Daiki Chijiwa

• Towards Calibrated Losses for Adversarial Robust Reject Option Classification

  VRUND SHAH, Tejas Kiran Chaudhari, Naresh Manwani

• Robust Multi-Agent Reinforcement Learning for Autonomous Vehicle in Noisy Highway Environments

  Lilan Lin, Xiaotong Nie, Jian Hou

• Improve Diverse Commonsense Generation by Enhancing Subgraphs

  Jianman Tan, Shuo Yang

• A Single-Stage Multi-Style License Plate Recognition Method Based on Attention

  Longbin Wu, Sen Liu, Yufei Xie, Haowei Lee, Xiaohui Duan

• Hierarchical Global Asynchronous Federated Learning Across Multi-Center

  Wei Xie, Runqun Xiong, Junzhou Luo

• An Efficient Query Optimization Framework Based on MCTS and LTR

  Chaofan Zhao, Yize Sui, Ruochun Jin, Jing Ren

• Motion meets Attention: Video Motion Prompts

  Qixiang Chen, Lei Wang, Piotr Koniusz, Tom Gedeon

• Visible-Infrared Person Re-Identification via Feature Fusion and Deep Mutual Learning

  Ziyang Lin, Banghai Wang

• Large Vision-Language Models as Emotion Recognizers in Context Awareness

  Yuxuan Lei, Dingkang Yang, Zhaoyu Chen, Jiawei Chen, Peng Zhai, Lihua Zhang

• Multi-Scale Dual-Attention Unfolding Network for Compressed Sensing Image Reconstruction

  Liangjun Wang, Meixin Wang

• Combinatorial Causal Bandits without Graph Skeleton

  Shi Feng, Nuoya Xiong, Wei Chen

• EVaDE: Event-Based Variational Thompson Sampling for Model-Based Reinforcement Learning

  Siddharth Aravindan, Dixant Mittal, Wee Sun Lee

• Exploring Beyond Curiosity Rewards: Language-Driven Exploration in RL

  Nicolas Bougie, Narimasa Watanabe

• Multi-level Relational Learning with Synergistic Graphs for Multivariate Time Series Forecasting

  Yang Xie, Qiao Liu, Rui Hou, Tingting Dai, Tian Lan

• Counterfactual Fairness for Graph Neural Networks with Limited and Privacy Protected Sensitive Attributes

  Xuemin Wang, Lei Wang, Tianlong Gu, Xuguang Bao

• Enhancing DETRs for Small Object Detection via Multi-Scale Refinement and Query-Aided Mining

  Sisi Fu, Zhiming Chen, Xiaocheng Fang, Jieyi Cai, Huanyu Liu, Huosheng Wen, Bingzhi Chen

• DataFrame QA: A Universal LLM Framework on DataFrame Question Answering Without Data Exposure

  Junyi Ye, Mengnan Du, Guiling Wang

• Fairness and Privacy Guarantees in Federated Contextual Bandits

  Sambhav Solanki, Shweta Jain, Sujit Gujar

• Diffusion-based Adversarial Attack to Automatic Speech Recognition

  Ying Wang, Yuchuan Luo, Shaojing Fu, Zhenyu Qiu, Lin Liu

• MLCL: A Framework for Reducing Language Imbalance in Sino-Tibetan Languages through Adapter Structures

  JiaJun Fang, Wentao Huang, Aimin Yang, Dong Zhou, Nankai Lin

• I Mean I Am a Mouse: Memeets for Bilingual Multimodal Meme Sarcasm Classification from Large Language Models

  Yunzhe Liu, Xuxinyi Xie

• A Retrieval-Augmented Contrastive Framework for Legal Case Retrieval Based on Event Information

  Changyong Fan, Nankai Lin, Dong Zhou, Yongmei Zhou, Aimin Yang

• Joint Learning of Gaussian Graphical Models in Heterogeneous Dependencies of High-Dimensional Transcriptomic Data

  Dung Ngoc Nguyen, Zitong Li

• Clustering-Augmented Fraud Detection on Graphs Using Label-Aware Feature Aggregation

  Shixiong Jing, Lingwei Chen, Dinghao Wu

• PISDR: Page and Item Sequential Decision for Re-ranking Based on Offline Reinforcement Learning

  Zheng Yuan, Qian Wan, Tao Zhang, Chengfu Huo

• Graph Neural Networks (with Proper Weights) Can Escape Oversmoothing

  Zhijian Zhuo, Yifei Wang, Jinwen Ma, Yisen Wang

• Rethinking Literary Plagiarism in LLMs through the Lens of Copyright Laws

  Huachen Tan, Moming Duan, Duo Liu, Haojie Lu, Yuexin Mu, Longyi Zhou, Ao Ren, Yujuan Tan, Kan Zhong

• AMG-AVSR: Adaptive Modality Guidance for Audio-Visual Speech Recognition via Progressive Feature Enhancement

  Zhishuo Zhao, Dongyue Guo, Wenjie Ou, Hong Liu, Yi Lin

• Dude: Dual Distribution-Aware Context Prompt Learning For Large Vision-Language Model

  Duy Minh Ho Nguyen, An Thai Le, Trung Quoc Nguyen, Nghiem Tuong Diep, Tai Nguyen, Duy Duong-Tran, Jan Peters, Li Shen, Mathias Niepert, Daniel Sonntag

• HiRAG: A Historical Information-Driven Retrieval-Augmented Generation Framework for Background Summarization

  Dong Zhou, Binli Zeng, Nankai Lin, Yongmei Zhou, Aimin Yang

• Universal Video Face Restoration Method Based on Vision-Language Model

  Yipiao Xu, Zhenbo Song, Jianfeng Lu

• FedLTF: Linear Probing Teaches Fine-tuning to Mitigate Noisy Labels in Federated Learning

  Shaojie Zhan, Lixing Yu, Hanqi Chen, Tianxi Ji

• A More Efficient Inference Model for Multimodal Emotion Recognition

  Liang Jia, Jin Tan, Lijin Qi, Mingwen Lin

• Refining Visual Perception for Decoration Display: A Self-Enhanced Deep Captioning Model

  Longfei Huang, Xiangyu Wu, Jingyuan Wang, Weili Guo, Yang Yang

• ColorMamba: Towards High-quality NIR-to-RGB Spectral Translation with Mamba

  Huiyu Zhai, Guang Jin, Xingxing Yang, Guosheng Kang

• MLP-Mixer based surrogate model for seismic ground motion with spatial source and geometry parameters

  Hirotaka Hachiya, Yuto Kuroki, Asako Iwaki, Takahiro Maeda, Naonori Ueda, Hiroyuki Fujiwara

• IST-YOLO: Infrared Small Target Detector based on Improved YOLOv8

  Ruoyu Wang, Bicao Li, Bei Wang, Danting Niu, Yongzhao Wang

• Analyzing Diffusion Models on Synthesizing Training Datasets

  Shin'ya Yamaguchi

• LabelPrompt: Effective prompt-based learning for relation classification

  Wenjie Zhang, Xiaoning Song, Zhenhua Feng, Tianyang Xu, Xiaojun Wu

• Robust Transfer Learning for Active Level Set Estimation with Locally Adaptive Gaussian Process Prior

  Giang Ngo, Dang Nguyen, Sunil Gupta

• Countering Relearning with Perception Revising Unlearning

  Chenhao Zhang, Weitong Chen, Wei Emma Zhang, Miao Xu

• TSMCR: Two-stage Supervised Multi-modality Contrastive Representation for Ultrasound-based Breast Cancer Diagnosis

  Bangming Gong

• Pic@Point: Cross-Modal Learning by Local and Global Point-Picture Correspondence

  Vencia Herzog, Stefan Suwelack

• On the sample complexity of privately learning half-spaces

  Yi Hsiang Huang, Wei-Hong Chen, Shi-Chun Tsai

• Cross-Level Feature Relocation: Mitigating Information Loss in Cross-Layer Feature Fusion for Crowd Counting

  Yuanyang Yin, Baoqun Yin