Search Results for author: Lili Qiu

Found 19 papers, 4 papers with code

LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression

1 code implementation19 Mar 2024 Zhuoshi Pan, Qianhui Wu, Huiqiang Jiang, Menglin Xia, Xufang Luo, Jue Zhang, QIngwei Lin, Victor Rühle, Yuqing Yang, Chin-Yew Lin, H. Vicky Zhao, Lili Qiu, Dongmei Zhang

The challenge is that information entropy may be a suboptimal compression metric: (i) it only leverages unidirectional context and may fail to capture all essential information needed for prompt compression; (ii) it is not aligned with the prompt compression objective.

GSM8K Language Modelling +3

EEGFormer: Towards Transferable and Interpretable Large-Scale EEG Foundation Model

no code implementations11 Jan 2024 Yuqi Chen, Kan Ren, Kaitao Song, Yansen Wang, Yifan Wang, Dongsheng Li, Lili Qiu

Self-supervised learning has emerged as a highly effective approach in the fields of natural language processing and computer vision.

Anomaly Detection EEG +2

Unified Medical Image Pre-training in Language-Guided Common Semantic Space

no code implementations24 Nov 2023 Xiaoxuan He, Yifan Yang, Xinyang Jiang, Xufang Luo, Haoji Hu, Siyun Zhao, Dongsheng Li, Yuqing Yang, Lili Qiu

To overcome the aforementioned challenges, we propose an Unified Medical Image Pre-training framework, namely UniMedI, which utilizes diagnostic reports as common semantic space to create unified representations for diverse modalities of medical images (especially for 2D and 3D images).

LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression

1 code implementation10 Oct 2023 Huiqiang Jiang, Qianhui Wu, Xufang Luo, Dongsheng Li, Chin-Yew Lin, Yuqing Yang, Lili Qiu

Inspired by these findings, we propose LongLLMLingua for prompt compression towards improving LLMs' perception of the key information to simultaneously address the three challenges.

Code Completion Few-Shot Learning

LLMLingua: Compressing Prompts for Accelerated Inference of Large Language Models

1 code implementation9 Oct 2023 Huiqiang Jiang, Qianhui Wu, Chin-Yew Lin, Yuqing Yang, Lili Qiu

Large language models (LLMs) have been applied in various applications due to their astonishing capabilities.

GSM8K In-Context Learning

Accelerating In-Browser Deep Learning Inference on Diverse Edge Clients through Just-in-Time Kernel Optimizations

no code implementations16 Sep 2023 Fucheng Jia, Shiqi Jiang, Ting Cao, Wei Cui, Tianrui Xia, Xu Cao, Yuanchun Li, Deyu Zhang, Ju Ren, Yunxin Liu, Lili Qiu, Mao Yang

Web applications are increasingly becoming the primary platform for AI service delivery, making in-browser deep learning (DL) inference more prominent.

Seeing through the Brain: Image Reconstruction of Visual Perception from Human Brain Signals

no code implementations27 Jul 2023 Yu-Ting Lan, Kan Ren, Yansen Wang, Wei-Long Zheng, Dongsheng Li, Bao-liang Lu, Lili Qiu

Seeing is believing, however, the underlying mechanism of how human visual perceptions are intertwined with our cognitions is still a mystery.

EEG Image Reconstruction +1

Real-Time Neural Video Recovery and Enhancement on Mobile Devices

no code implementations22 Jul 2023 Zhaoyuan He, Yifan Yang, Lili Qiu, Kyoungjun Park

Although deep learning-based video enhancement techniques are gaining attention, most of them cannot support real-time enhancement on mobile devices.

Super-Resolution Video Enhancement

Enabling Real-time Neural Recovery for Cloud Gaming on Mobile Devices

no code implementations15 Jul 2023 Zhaoyuan He, Yifan Yang, Shuozhe Li, Diyuan Dai, Lili Qiu, Yuqing Yang

Our approach is extensively evaluated using iPhone 12 and laptop implementations, and we demonstrate the utility of game states in the game video recovery and the effectiveness of our overall design.

Protecting the Future: Neonatal Seizure Detection with Spatial-Temporal Modeling

no code implementations2 Jul 2023 Ziyue Li, Yuchen Fang, You Li, Kan Ren, Yansen Wang, Xufang Luo, Juanyong Duan, Congrui Huang, Dongsheng Li, Lili Qiu

A timely detection of seizures for newborn infants with electroencephalogram (EEG) has been a common yet life-saving practice in the Neonatal Intensive Care Unit (NICU).

EEG Electroencephalogram (EEG) +1

End-to-End Word-Level Pronunciation Assessment with MASK Pre-training

no code implementations5 Jun 2023 Yukang Liang, Kaitao Song, Shaoguang Mao, Huiqiang Jiang, Luna Qiu, Yuqing Yang, Dongsheng Li, Linli Xu, Lili Qiu

Pronunciation assessment is a major challenge in the computer-aided pronunciation training system, especially at the word (phoneme)-level.

Accurate and Structured Pruning for Efficient Automatic Speech Recognition

no code implementations31 May 2023 Huiqiang Jiang, Li Lyna Zhang, Yuang Li, Yu Wu, Shijie Cao, Ting Cao, Yuqing Yang, Jinyu Li, Mao Yang, Lili Qiu

In this paper, we propose a novel compression strategy that leverages structured pruning and knowledge distillation to reduce the model size and inference cost of the Conformer model while preserving high recognition performance.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +2

Adaptive Scheduling for Edge-Assisted DNN Serving

no code implementations19 Apr 2023 Jian He, Chenxi Yang, Zhaoyuan He, Ghufran Baig, Lili Qiu

Based on this observation, we first design a novel scheduling algorithm to exploit the batching benefits of all requests that run the same DNN.

Scheduling

Online Streaming Video Super-Resolution with Convolutional Look-Up Table

no code implementations1 Mar 2023 Guanghao Yin, Zefan Qu, Xinyang Jiang, Shan Jiang, Zhenhua Han, Ningxin Zheng, Xiaohong Liu, Huan Yang, Yuqing Yang, Dongsheng Li, Lili Qiu

To facilitate the research on this problem, a new benchmark dataset named LDV-WebRTC is constructed based on a real-world online streaming system.

Video Super-Resolution

Unsupervised Video Anomaly Detection for Stereotypical Behaviours in Autism

no code implementations27 Feb 2023 Jiaqi Gao, Xinyang Jiang, Yuqing Yang, Dongsheng Li, Lili Qiu

Correspondingly, we propose a Dual Stream deep model for Stereotypical Behaviours Detection, DS-SBD, based on the temporal trajectory of human poses and the repetition patterns of human actions.

Activity Recognition Anomaly Detection +1

Attentive Mask CLIP

1 code implementation ICCV 2023 Yifan Yang, Weiquan Huang, Yixuan Wei, Houwen Peng, Xinyang Jiang, Huiqiang Jiang, Fangyun Wei, Yin Wang, Han Hu, Lili Qiu, Yuqing Yang

To address this issue, we propose an attentive token removal approach for CLIP training, which retains tokens with a high semantic correlation to the text description.

Contrastive Learning Retrieval +1

Improving Hypernasality Estimation with Automatic Speech Recognition in Cleft Palate Speech

no code implementations10 Aug 2022 Kaitao Song, Teng Wan, Bixia Wang, Huiqiang Jiang, Luna Qiu, Jiahang Xu, Liping Jiang, Qun Lou, Yuqing Yang, Dongsheng Li, Xudong Wang, Lili Qiu

Specifically, we first pre-train an encoder-decoder framework in an automatic speech recognition (ASR) objective by using speech-to-text dataset, and then fine-tune ASR encoder on the cleft palate dataset for hypernasality estimation.

Automatic Speech Recognition Automatic Speech Recognition (ASR) +1

CMMD: Cross-Metric Multi-Dimensional Root Cause Analysis

no code implementations30 Mar 2022 Shifu Yan, Caihua Shan, Wenyi Yang, Bixiong Xu, Dongsheng Li, Lili Qiu, Jie Tong, Qi Zhang

To this end, we propose a cross-metric multi-dimensional root cause analysis method, named CMMD, which consists of two key components: 1) relationship modeling, which utilizes graph neural network (GNN) to model the unknown complex calculation among metrics and aggregation function among dimensions from historical data; 2) root cause localization, which adopts the genetic algorithm to efficiently and effectively dive into the raw data and localize the abnormal dimension(s) once the KPI anomalies are detected.

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