58 citations · 188 across the 90 of their papers we have counts for
14 papers · 1 filter
Unified Medical Image Pre-training in Language-Guided Common Semantic Space
Xiaoxuan He, Yifan Yang, Xinyang Jiang +6
Vision-Language Pre-training (VLP) has shown the merits of analysing medical images, by leveraging the semantic congruence between medical images and their corresponding reports. I…
LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression
Huiqiang Jiang, Qianhui Wu, Xufang Luo +4
In long context scenarios, large language models (LLMs) face three main challenges: higher computational cost, performance reduction, and position bias. Research indicates that LLM…
LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models
Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin +2
Large language models (LLMs) have been applied in various applications due to their astonishing capabilities. With advancements in technologies such as chain-of-thought (CoT) promp…
ImageBrush: Learning Visual In-Context Instructions for Exemplar-Based Image Manipulation
Yasheng Sun, Yifan Yang, Houwen Peng +5
While language-guided image manipulation has made remarkable progress, the challenge of how to instruct the manipulation process faithfully reflecting human intentions persists. An…
Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference
Junyan Li, Li Lyna Zhang, Jiahang Xu +9
Deploying pre-trained transformer models like BERT on downstream tasks in resource-constrained scenarios is challenging due to their high inference cost, which grows rapidly with i…
End-to-End Word-Level Pronunciation Assessment with MASK Pre-training
Yukang Liang, Kaitao Song, Shaoguang Mao +6
Pronunciation assessment is a major challenge in the computer-aided pronunciation training system, especially at the word (phoneme)-level. To obtain word (phoneme)-level scores, cu…
Accurate and Structured Pruning for Efficient Automatic Speech Recognition
Huiqiang Jiang, Li Lyna Zhang, Yuang Li +7
Automatic Speech Recognition (ASR) has seen remarkable advancements with deep neural networks, such as Transformer and Conformer. However, these models typically have large model s…
MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks
Lei Zhang, Yuge Zhang, Kan Ren +2
The field of machine learning (ML) has gained widespread adoption, leading to significant demand for adapting ML to specific scenarios, which is yet expensive and non-trivial. The…
ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile Devices
Chen Tang, Li Lyna Zhang, Huiqiang Jiang +6
Neural Architecture Search (NAS) has shown promising performance in the automatic design of vision transformers (ViT) exceeding 1G FLOPs. However, designing lightweight and low-lat…
SpaceEvo: Hardware-Friendly Search Space Design for Efficient INT8 Inference
Li Lyna Zhang, Xudong Wang, Jiahang Xu +6
The combination of Neural Architecture Search (NAS) and quantization has proven successful in automatically designing low-FLOPs INT8 quantized neural networks (QNN). However, direc…
Online Streaming Video Super-Resolution with Convolutional Look-Up Table
Guanghao Yin, Zefan Qu, Xinyang Jiang +8
Online video streaming has fundamental limitations on the transmission bandwidth and computational capacity and super-resolution is a promising potential solution. However, applyin…
Unsupervised Video Anomaly Detection for Stereotypical Behaviours in Autism
Jiaqi Gao, Xinyang Jiang, Yuqing Yang +2
Monitoring and analyzing stereotypical behaviours is important for early intervention and care taking in Autism Spectrum Disorder (ASD). This paper focuses on automatically detecti…
Towards Inference Efficient Deep Ensemble Learning
Ziyue Li, Kan Ren, Yifan Yang +3
Ensemble methods can deliver surprising performance gains but also bring significantly higher computational costs, e.g., can be up to 2048X in large-scale ensemble tasks. However,…
PIT: Optimization of Dynamic Sparse Deep Learning Models via Permutation Invariant Transformation
Ningxin Zheng, Huiqiang Jiang, Quanlu Zhang +8
Dynamic sparsity, where the sparsity patterns are unknown until runtime, poses a significant challenge to deep learning. The state-of-the-art sparsity-aware deep learning solutions…