Search Results for author: Yuqing Yang

Found 35 papers, 18 papers with code

Uncertain Local-to-Global Networks for Document-Level Event Factuality Identification

1 code implementation EMNLP 2021 Pengfei Cao, Yubo Chen, Yuqing Yang, Kang Liu, Jun Zhao

Moreover, we propose an Uncertain Information Aggregation module to leverage the global structure for integrating the local information.

CoLLiE: Collaborative Training of Large Language Models in an Efficient Way

1 code implementation1 Dec 2023 Kai Lv, Shuo Zhang, Tianle Gu, Shuhao Xing, Jiawei Hong, Keyu Chen, Xiaoran Liu, Yuqing Yang, Honglin Guo, Tengxiao Liu, Yu Sun, Qipeng Guo, Hang Yan, Xipeng Qiu

This paper introduces CoLLiE, an efficient library that facilitates collaborative training of large language models using 3D parallelism, parameter-efficient fine-tuning (PEFT) methods, and optimizers such as Lion, Adan, Sophia, LOMO and AdaLomo.

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).

Plan, Verify and Switch: Integrated Reasoning with Diverse X-of-Thoughts

1 code implementation23 Oct 2023 Tengxiao Liu, Qipeng Guo, Yuqing Yang, Xiangkun Hu, Yue Zhang, Xipeng Qiu, Zheng Zhang

As large language models (LLMs) have shown effectiveness with different prompting methods, such as Chain of Thought, Program of Thought, we find that these methods have formed a great complementarity to each other on math reasoning tasks.

Logical Reasoning Math

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.


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.

Constraint-aware and Ranking-distilled Token Pruning for Efficient Transformer Inference

1 code implementation26 Jun 2023 Junyan Li, Li Lyna Zhang, Jiahang Xu, Yujing Wang, Shaoguang Yan, Yunqing Xia, Yuqing Yang, Ting Cao, Hao Sun, Weiwei Deng, Qi Zhang, Mao Yang

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 input sequence length.

Model Compression

Full Parameter Fine-tuning for Large Language Models with Limited Resources

1 code implementation16 Jun 2023 Kai Lv, Yuqing Yang, Tengxiao Liu, Qinghui Gao, Qipeng Guo, Xipeng Qiu

Large Language Models (LLMs) have revolutionized Natural Language Processing (NLP) but demand massive GPU resources for training.

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

An AMR-based Link Prediction Approach for Document-level Event Argument Extraction

1 code implementation30 May 2023 Yuqing Yang, Qipeng Guo, Xiangkun Hu, Yue Zhang, Xipeng Qiu, Zheng Zhang

Motivated by the fact that all event structures can be inferred from AMR, this work reformulates EAE as a link prediction problem on AMR graphs.

Event Argument Extraction Link Prediction +1

EfficientViT: Memory Efficient Vision Transformer with Cascaded Group Attention

3 code implementations CVPR 2023 Xinyu Liu, Houwen Peng, Ningxin Zheng, Yuqing Yang, Han Hu, Yixuan Yuan

Comprehensive experiments demonstrate EfficientViT outperforms existing efficient models, striking a good trade-off between speed and accuracy.

Learned Focused Plenoptic Image Compression with Microimage Preprocessing and Global Attention

1 code implementation30 Apr 2023 Kedeng Tong, Xin Jin, Yuqing Yang, Chen Wang, Jinshi Kang, Fan Jiang

Also, it achieves 18. 73% bitrate saving and generates perceptually pleasant reconstructions compared to the state-of-the-art end-to-end image compression methods, which benefits the applications of focused plenoptic cameras greatly.

Image Compression

MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks

no code implementations28 Apr 2023 Lei Zhang, Yuge Zhang, Kan Ren, Dongsheng Li, Yuqing Yang

In contrast, though human engineers have the incredible ability to understand tasks and reason about solutions, their experience and knowledge are often sparse and difficult to utilize by quantitative approaches.


ElasticViT: Conflict-aware Supernet Training for Deploying Fast Vision Transformer on Diverse Mobile Devices

1 code implementation ICCV 2023 Chen Tang, Li Lyna Zhang, Huiqiang Jiang, Jiahang Xu, Ting Cao, Quanlu Zhang, Yuqing Yang, Zhi Wang, Mao Yang

However, prior supernet training methods that rely on uniform sampling suffer from the gradient conflict issue: the sampled subnets can have vastly different model sizes (e. g., 50M vs. 2G FLOPs), leading to different optimization directions and inferior performance.

Neural Architecture Search

SpaceEvo: Hardware-Friendly Search Space Design for Efficient INT8 Inference

1 code implementation ICCV 2023 Li Lyna Zhang, Xudong Wang, Jiahang Xu, Quanlu Zhang, Yujing Wang, Yuqing Yang, Ningxin Zheng, Ting Cao, Mao Yang

The combination of Neural Architecture Search (NAS) and quantization has proven successful in automatically designing low-FLOPs INT8 quantized neural networks (QNN).

Neural Architecture Search Quantization

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

1 code implementation1 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

Towards Inference Efficient Deep Ensemble Learning

no code implementations29 Jan 2023 Ziyue Li, Kan Ren, Yifan Yang, Xinyang Jiang, Yuqing Yang, Dongsheng Li

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.

Ensemble Learning

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

DORE: Document Ordered Relation Extraction based on Generative Framework

1 code implementation28 Oct 2022 Qipeng Guo, Yuqing Yang, Hang Yan, Xipeng Qiu, Zheng Zhang

In this paper, we investigate the root cause of the underwhelming performance of the existing generative DocRE models and discover that the culprit is the inadequacy of the training paradigm, instead of the capacities of the models.

Document-level Relation Extraction

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

Online Video Super-Resolution with Convolutional Kernel Bypass Graft

no code implementations4 Aug 2022 Jun Xiao, Xinyang Jiang, Ningxin Zheng, Huan Yang, Yifan Yang, Yuqing Yang, Dongsheng Li, Kin-Man Lam

Then, our proposed CKBG method enhances this lightweight base model by bypassing the original network with ``kernel grafts'', which are extra convolutional kernels containing the prior knowledge of external pretrained image SR models.

Transfer Learning Video Super-Resolution

Privacy-preserving Online AutoML for Domain-Specific Face Detection

no code implementations CVPR 2022 Chenqian Yan, Yuge Zhang, Quanlu Zhang, Yaming Yang, Xinyang Jiang, Yuqing Yang, Baoyuan Wang

Thanks to HyperFD, each local task (client) is able to effectively leverage the learning "experience" of previous tasks without uploading raw images to the platform; meanwhile, the meta-feature extractor is continuously learned to better trade off the bias and variance.

AutoML Face Detection +1

Game of Privacy: Towards Better Federated Platform Collaboration under Privacy Restriction

no code implementations10 Feb 2022 Chuhan Wu, Fangzhao Wu, Tao Qi, Yanlin Wang, Yuqing Yang, Yongfeng Huang, Xing Xie

To solve the game, we propose a platform negotiation method that simulates the bargaining among platforms and locally optimizes their policies via gradient descent.

Federated Learning

Towards Generating Real-World Time Series Data

1 code implementation16 Nov 2021 Hengzhi Pei, Kan Ren, Yuqing Yang, Chang Liu, Tao Qin, Dongsheng Li

In this paper, we propose a novel generative framework for RTS data - RTSGAN to tackle the aforementioned challenges.

Time Series Time Series Analysis

AARL: Automated Auxiliary Loss for Reinforcement Learning

no code implementations29 Sep 2021 Tairan He, Yuge Zhang, Kan Ren, Che Wang, Weinan Zhang, Dongsheng Li, Yuqing Yang

A good state representation is crucial to reinforcement learning (RL) while an ideal representation is hard to learn only with signals from the RL objective.

reinforcement-learning Reinforcement Learning (RL)

Full-Cycle Energy Consumption Benchmark for Low-Carbon Computer Vision

no code implementations30 Aug 2021 Bo Li, Xinyang Jiang, Donglin Bai, Yuge Zhang, Ningxin Zheng, Xuanyi Dong, Lu Liu, Yuqing Yang, Dongsheng Li

The energy consumption of deep learning models is increasing at a breathtaking rate, which raises concerns due to potential negative effects on carbon neutrality in the context of global warming and climate change.

Model Compression

Fast Hardware-Aware Neural Architecture Search

1 code implementation25 Oct 2019 Li Lyna Zhang, Yuqing Yang, Yuhang Jiang, Wenwu Zhu, Yunxin Liu

Unlike previous approaches that apply search algorithms on a small, human-designed search space without considering hardware diversity, we propose HURRICANE that explores the automatic hardware-aware search over a much larger search space and a two-stage search algorithm, to efficiently generate tailored models for different types of hardware.

Hardware Aware Neural Architecture Search Neural Architecture Search

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