Papers
AnyTouch: Learning Unified Static-Dynamic Representation across Multiple Visuo-tactile Sensors
Ruoxuan Feng, Jiangyu Hu, Wenke Xia et al.
Anywhere: A Multi-Agent Framework for User-Guided, Reliable, and Diverse Foreground-Conditioned Image Generation
Xie Tianyidan, Rui Ma, Qian Wang et al.
AoI-MDP: An AoI Optimized Markov Decision Process Dedicated in the Underwater Task (Student Abstract)
Yimian Ding, Jingzehua Xu, Yiyuan Yang et al.
AoP-SAM: Automation of Prompts for Efficient Segmentation
Yi Chen, Muyoung Son, Chuanbo Hua et al.
Aorta Multi-class Segmentation via Anatomically Constrained Plane Detection
Jonghoon An, Dong Hyun Lee, So Hyun Kim et al.
A PAC-Bayesian Link Between Generalisation and Flat Minima
Maxime Haddouche, Paul Viallard, Umut Simsekli et al.
A Parallelized Framework for Simulating Large-Scale LLM Agents with Realistic Environments and Interactions
Jun Zhang, Yuwei Yan, Junbo Yan et al.
A Parallel Network for LRCT Segmentation and Uncertainty Mitigation with Fuzzy Sets
Shiyi Wang, Yang Nan, Xiaodan Xing et al.
A Parameter-Efficient and Fine-Grained Prompt Learning for Vision-Language Models
Yongbin Guo, Shuzhen Li, Zhulin Liu et al.
A Parametric Approach to Adversarial Augmentation for Cross-Domain Iris Presentation Attack Detection
Debasmita Pal, Redwan Sony, Arun Ross
A Parametric Contextual Online Learning Theory of Brokerage
François Bachoc, Tommaso Cesari, Roberto Colomboni
APAR: Modeling Irregular Target Functions in Tabular Regression via Arithmetic-Aware Pre-Training and Adaptive-Regularized Fine-Tuning
Hong-Wei Wu, Wei-Yao Wang, Kuang-Da Wang et al.
APB: Accelerating Distributed Long-Context Inference by Passing Compressed Context Blocks across GPUs
Yuxiang Huang, Mingye Li, Xu Han et al.
A Peer-review Look on Multi-modal Clustering: An Information Bottleneck Realization Method
Zhengzheng Lou, Hang Xue, Chaoyang Zhang et al.
APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding
Xinyu Yang, Tianqi Chen, Beidi Chen
A Percolation Model of Emergence: Analyzing Transformers Trained on a Formal Language
Ekdeep Singh Lubana, Kyogo Kawaguchi, Robert P. Dick et al.
A Periodic Bayesian Flow for Material Generation
Hanlin Wu, Yuxuan Song, Jingjing Gong et al.
A Persona-Aware LLM-Enhanced Framework for Multi-Session Personalized Dialogue Generation
Dongshuo Liu, Zhijing Wu, Dandan Song et al.
A Perspective on LLM Data Generation with Few-shot Examples: from Intent to Kubernetes Manifest
Antonino Angi, Liubov Nedoshivina, Alessio Sacco et al.
APEX-MR: Multi-Robot Asynchronous Planning and Execution for Cooperative Assembly
Philip Huang, Ruixuan Liu, Shobhit Aggarwal et al.
APHQ-ViT: Post-Training Quantization with Average Perturbation Hessian Based Reconstruction for Vision Transformers
Zhuguanyu Wu, Jiayi Zhang, Jiaxin Chen et al.
A Physics-Augmented Deep Learning Framework for Classifying Single Molecule Force Spectroscopy Data
Cailong Hua, Sivaraman Rajaganapathy, Rebecca A Slick et al.
A Physics-Informed Blur Learning Framework for Imaging Systems
Liqun Chen, Yuxuan Li, Jun Dai et al.
A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems
Manan Tayal, Aditya Singh, Shishir Kolathaya et al.