2024 Poster Papers
8,865 papers found • Page 164 of 178
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks
Federico Errica, Mathias Niepert
TrafficNight : An Aerial Multimodal Benchmark For Nighttime Vehicle Surveillance
Guoxing Zhang, Yiming Liu, xiaoyu yang et al.
Traffic Scene Parsing through the TSP6K Dataset
Peng-Tao Jiang, Yuqi Yang, Yang Cao et al.
Trainable Highly-expressive Activation Functions
Irit Chelly, Shahaf Finder, Shira Ifergane et al.
Trainable Transformer in Transformer
Abhishek Panigrahi, Sadhika Malladi, Mengzhou Xia et al.
Trained Random Forests Completely Reveal your Dataset
Julien Ferry, Ricardo Fukasawa, Timothée Pascal et al.
Training A Secure Model against Data-Free Model Extraction
Zhenyi Wang, Li Shen, junfeng guo et al.
Training A Small Emotional Vision Language Model for Visual Art Comprehension
Jing Zhang, Liang Zheng, Meng Wang et al.
Training Bayesian Neural Networks with Sparse Subspace Variational Inference
Junbo Li, Zichen Miao, Qiang Qiu et al.
Training Diffusion Models Towards Diverse Image Generation with Reinforcement Learning
Zichen Miao, Jiang Wang, Ze Wang et al.
Training Diffusion Models with Reinforcement Learning
Kevin Black, Michael Janner, Yilun Du et al.
Training-free Composite Scene Generation for Layout-to-Image Synthesis
Jiaqi Liu, Tao Huang, Chang Xu
Training-Free Long-Context Scaling of Large Language Models
Chenxin An, Fei Huang, Jun Zhang et al.
Training-Free Model Merging for Multi-target Domain Adaptation
Wenyi Li, Huan-ang Gao, Mingju Gao et al.
Training-free Multi-objective Diffusion Model for 3D Molecule Generation
XU HAN, Caihua Shan, Yifei Shen et al.
Training-Free Open-Vocabulary Segmentation with Offline Diffusion-Augmented Prototype Generation
Luca Barsellotti, Roberto Amoroso, Marcella Cornia et al.
Training-Free Pretrained Model Merging
Zhengqi Xu, Ke Yuan, Huiqiong Wang et al.
Training-free Video Temporal Grounding using Large-scale Pre-trained Models
Minghang Zheng, Xinhao Cai, Qingchao Chen et al.
Training Generative Image Super-Resolution Models by Wavelet-Domain Losses Enables Better Control of Artifacts
Cansu Korkmaz, Ahmet Murat Tekalp, Zafer Dogan
Training Graph Transformers via Curriculum-Enhanced Attention Distillation
Yisong Huang, Jin Li, Xinlong Chen et al.
Training Greedy Policy for Proposal Batch Selection in Expensive Multi-Objective Combinatorial Optimization
Deokjae Lee, Hyun Oh Song, Kyunghyun Cho
Training Large Language Models for Reasoning through Reverse Curriculum Reinforcement Learning
Zhiheng Xi, Wenxiang Chen, Boyang Hong et al.
Training Like a Medical Resident: Context-Prior Learning Toward Universal Medical Image Segmentation
Yunhe Gao
Training Socially Aligned Language Models on Simulated Social Interactions
Ruibo Liu, Ruixin Yang, Chenyan Jia et al.
Training Unbiased Diffusion Models From Biased Dataset
Yeongmin Kim, Byeonghu Na, Minsang Park et al.
Training Vision Transformers for Semi-Supervised Semantic Segmentation
Xinting Hu, Li Jiang, Bernt Schiele
Train Till You Drop: Towards Stable and Robust Source-free Unsupervised 3D Domain Adaptation
Bjoern Michele, Alexandre Boulch, Tuan Hung Vu et al.
Trajectory-aligned Space-time Tokens for Few-shot Action Recognition
Pulkit Kumar, Namitha Padmanabhan, Luke Luo et al.
Trajeglish: Traffic Modeling as Next-Token Prediction
Jonah Philion, Xue Bin Peng, Sanja Fidler
TrajPrompt: Aligning Color Trajectory with Vision-Language Representations
Li-Wu Tsao, Hao-Tang Tsui, Yu-Rou Tuan et al.
TRAM: Global Trajectory and Motion of 3D Humans from in-the-wild Videos
Yufu Wang, Ziyun Wang, Lingjie Liu et al.
TransCAD: A Hierarchical Transformer for CAD Sequence Inference from Point Clouds
Dupont Elona, Kseniya Cherenkova, Dimitrios Mallis et al.
Transcending Forgery Specificity with Latent Space Augmentation for Generalizable Deepfake Detection
Zhiyuan Yan, Yuhao Luo, Siwei Lyu et al.
Transcending the Limit of Local Window: Advanced Super-Resolution Transformer with Adaptive Token Dictionary
Leheng Zhang, Yawei Li, Xingyu Zhou et al.
Transcriptomics-guided Slide Representation Learning in Computational Pathology
Guillaume Jaume, Lukas Oldenburg, Anurag Vaidya et al.
Transferable 3D Adversarial Shape Completion using Diffusion Models
Xuelong Dai, Bin Xiao
Transferable and Principled Efficiency for Open-Vocabulary Segmentation
Jingxuan Xu, Wuyang Chen, Yao Zhao et al.
Transferable Facial Privacy Protection against Blind Face Restoration via Domain-Consistent Adversarial Obfuscation
Kui Zhang, Hang Zhou, Jie Zhang et al.
Transferable Structural Sparse Adversarial Attack Via Exact Group Sparsity Training
Di Ming, Peng Ren, Yunlong Wang et al.
Transfer CLIP for Generalizable Image Denoising
Jun Cheng, Dong Liang, Shan Tan
Transferring Knowledge From Large Foundation Models to Small Downstream Models
Shikai Qiu, Boran Han, Danielle Robinson et al.
Transferring Labels to Solve Annotation Mismatches Across Object Detection Datasets
Yuan-Hong Liao, David Acuna, Rafid Mahmood et al.
Transferring Learning Trajectories of Neural Networks
Daiki Chijiwa
Transformer Fusion with Optimal Transport
Moritz Imfeld, Jacopo Graldi, Marco Giordano et al.
Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting
Yuxin Li, Wenchao Chen, Xinyue Hu et al.
Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality
Tri Dao, Albert Gu
Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining
Licong Lin, Yu Bai, Song Mei
Transformers can optimally learn regression mixture models
Reese Pathak, Rajat Sen, Weihao Kong et al.
Transformers Get Stable: An End-to-End Signal Propagation Theory for Language Models
Akhil Kedia, Mohd Abbas Zaidi, Sushil Khyalia et al.
Transformers Implement Functional Gradient Descent to Learn Non-Linear Functions In Context
Xiang Cheng, Yuxin Chen, Suvrit Sra