Search Results for author:
Found 7 papers, 4 papers with code
Improving Audio-Visual Segmentation with Bidirectional Generation
In this paper, inspired by the human ability to mentally simulate the sound of an object and its visual appearance, we introduce a bidirectional generation framework.
TransNormerLLM: A Faster and Better Large Language Model with Improved TransNormer
TransNormerLLM evolves from the previous linear attention architecture TransNormer by making advanced modifications that include positional embedding, linear attention acceleration, gating mechanisms, tensor normalization, and inference acceleration and stabilization.
Linearized Relative Positional Encoding
Meanwhile, it emphasizes a general paradigm for designing broadly more relative positional encoding methods that are applicable to linear transformers.
Toeplitz Neural Network for Sequence Modeling
Sequence modeling has important applications in natural language processing and computer vision.
Fine-grained Audible Video Description
We explore a new task for audio-visual-language modeling called fine-grained audible video description (FAVD).
The Devil in Linear Transformer
In this paper, we examine existing kernel-based linear transformers and identify two key issues that lead to such performance gaps: 1) unbounded gradients in the attention computation adversely impact the convergence of linear transformer models; 2) attention dilution which trivially distributes attention scores over long sequences while neglecting neighbouring structures.
Linear Video Transformer with Feature Fixation
Therefore, we propose a feature fixation module to reweight the feature importance of the query and key before computing linear attention.
