Poster "attention mechanism" Papers

272 papers found • Page 6 of 6

SAMformer: Unlocking the Potential of Transformers in Time Series Forecasting with Sharpness-Aware Minimization and Channel-Wise Attention

Romain Ilbert, Ambroise Odonnat, Vasilii Feofanov et al.

ICML 2024posterarXiv:2402.10198

Scene-Graph ViT: End-to-End Open-Vocabulary Visual Relationship Detection

Tim Salzmann, Markus Ryll, Alex Bewley et al.

ECCV 2024posterarXiv:2403.14270
8
citations

Self-Attention through Kernel-Eigen Pair Sparse Variational Gaussian Processes

Yingyi Chen, Qinghua Tao, Francesco Tonin et al.

ICML 2024posterarXiv:2402.01476

SFPNet: Sparse Focal Point Network for Semantic Segmentation on General LiDAR Point Clouds

Yanbo Wang, Wentao Zhao, Cao Chuan et al.

ECCV 2024posterarXiv:2407.11569
17
citations

SparQ Attention: Bandwidth-Efficient LLM Inference

Luka Ribar, Ivan Chelombiev, Luke Hudlass-Galley et al.

ICML 2024posterarXiv:2312.04985

SpecFormer: Guarding Vision Transformer Robustness via Maximum Singular Value Penalization

Xixu Hu, Runkai Zheng, Jindong Wang et al.

ECCV 2024posterarXiv:2402.03317
5
citations

StableMask: Refining Causal Masking in Decoder-only Transformer

Qingyu Yin, Xuzheng He, Xiang Zhuang et al.

ICML 2024posterarXiv:2402.04779

Statistical Test for Attention Maps in Vision Transformers

Tomohiro Shiraishi, Daiki Miwa, Teruyuki Katsuoka et al.

ICML 2024poster

Stripe Observation Guided Inference Cost-free Attention Mechanism

Zhongzhan Huang, Shanshan Zhong, Wushao Wen et al.

ECCV 2024poster
1
citations

Subgraphormer: Unifying Subgraph GNNs and Graph Transformers via Graph Products

Guy Bar Shalom, Beatrice Bevilacqua, Haggai Maron

ICML 2024posterarXiv:2402.08450

Tandem Transformers for Inference Efficient LLMs

Aishwarya P S, Pranav Nair, Yashas Samaga et al.

ICML 2024posterarXiv:2402.08644

TexGen: Text-Guided 3D Texture Generation with Multi-view Sampling and Resampling

Dong Huo, Zixin Guo, Xinxin Zuo et al.

ECCV 2024posterarXiv:2408.01291
19
citations

Towards Efficient Spiking Transformer: a Token Sparsification Framework for Training and Inference Acceleration

Zhengyang Zhuge, Peisong Wang, Xingting Yao et al.

ICML 2024poster

Towards Understanding the Word Sensitivity of Attention Layers: A Study via Random Features

Simone Bombari, Marco Mondelli

ICML 2024posterarXiv:2402.02969

Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Tri Dao, Albert Gu

ICML 2024posterarXiv:2405.21060

Transformers Learn Nonlinear Features In Context: Nonconvex Mean-field Dynamics on the Attention Landscape

Juno Kim, Taiji Suzuki

ICML 2024posterarXiv:2402.01258

UDiffText: A Unified Framework for High-quality Text Synthesis in Arbitrary Images via Character-aware Diffusion Models

Yiming Zhao, Zhouhui Lian

ECCV 2024posterarXiv:2312.04884
48
citations

Unveiling and Harnessing Hidden Attention Sinks: Enhancing Large Language Models without Training through Attention Calibration

Zhongzhi Yu, Zheng Wang, Yonggan Fu et al.

ICML 2024posterarXiv:2406.15765

Viewing Transformers Through the Lens of Long Convolutions Layers

Itamar Zimerman, Lior Wolf

ICML 2024poster

Visual Transformer with Differentiable Channel Selection: An Information Bottleneck Inspired Approach

Yancheng Wang, Ping Li, Yingzhen Yang

ICML 2024poster

Wavelength-Embedding-guided Filter-Array Transformer for Spectral Demosaicing

haijin zeng, Hiep Luong, Wilfried Philips

ECCV 2024poster
1
citations

What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasks

Xingwu Chen, Difan Zou

ICML 2024posterarXiv:2404.01601
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