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Xiaodong Han

7 accepted papers

2024

Improving Audio-Visual Segmentation with Bidirectional Generation

AAAI 2024technical

The aim of audio-visual segmentation (AVS) is to precisely differentiate audible objects within videos down to the pixel level. Traditional approaches often tackle this challenge by combining information from various modalities, where the contribution of each modality is implicitly or explicitly mod…

2024

PyramidInfer: Pyramid KV Cache Compression for High-throughput LLM Inference

ACL 2024findings

Large Language Models (LLMs) have shown remarkable comprehension abilities but face challenges in GPU memory usage during inference, hindering their scalability for real-time applications like chatbots. To accelerate inference, we store computed keys and values (KV cache) in the GPU memory. Existing…

2024

Vript: A Video Is Worth Thousands of Words

NeurIPS 2024poster

Advancements in multimodal learning, particularly in video understanding and generation, require high-quality video-text datasets for improved model performance. Vript addresses this issue with a meticulously annotated corpus of 12K high-resolution videos, offering detailed, dense, and script-like c…

2023

Fine-Grained Audible Video Description

CVPR 2023poster

We explore a new task for audio-visual-language modeling called fine-grained audible video description (FAVD). It aims to provide detailed textual descriptions for the given audible videos, including the appearance and spatial locations of each object, the actions of moving objects, and the sounds i…

2023

Toeplitz Neural Network for Sequence Modeling

ICLR 2023top-25%

Sequence modeling has important applications in natural language processing and computer vision. Recently, the transformer-based models have shown strong performance on various sequence modeling tasks, which rely on attention to capture pairwise token relations, and position embedding to inject posi…

2022

The Devil in Linear Transformer

EMNLP 2022main

Linear transformers aim to reduce the quadratic space-time complexity of vanilla transformers. However, they usually suffer from degraded performances on various tasks and corpus. In this paper, we examine existing kernel-based linear transformers and identify two key issues that lead to such perfor…