no code implementations • 10 Jan 2017 • Yang Xu, Jiawei Liu
In this paper, we propose three novel models to enhance word embedding by implicitly using morphological information.
no code implementations • 19 Nov 2018 • Jiawei Liu, Zheng-Jun Zha, Hongtao Xie, Zhiwei Xiong, Yongdong Zhang
An appearance network is developed to learn appearance features from the full body, horizontal and vertical body parts of pedestrians with spatial dependencies among body parts.
no code implementations • CVPR 2019 • Jiawei Liu, Zheng-Jun Zha, Di Chen, Richang Hong, Meng Wang
In particular, ATNet consists of a transfer network composed by multiple factor-wise CycleGANs and an ensemble CycleGAN as well as a selection network that infers the affects of different factors on transferring each image.
no code implementations • 10 Apr 2020 • Jiawei Liu, Zheng-Jun Zha, Xierong Zhu, Na Jiang
Person re-identification aims at identifying a certain pedestrian across non-overlapping camera networks.
no code implementations • 6 May 2020 • De-Sheng Wang, Jiawei Liu, Xiang Qi, Baolin Sun, Peng Zhang
The results demonstrate the effectiveness of our method, which outperforms the baseline on 10 kinds of data and achieves nearly 50 percent improvement on average.
no code implementations • 26 Jun 2020 • Jiawei Liu, Kumar Vijay Mishra, Mohammad Saquib
We consider a spectral sharing problem in which a statistical (or widely distributed) multiple-input multiple-output (MIMO) radar and an in-band full-duplex (IBFD) multi-user MIMO (MU-MIMO) communications system concurrently operate within the same frequency band.
1 code implementation • 29 Jun 2020 • Xiao Wang, Shaohua Fan, Kun Kuang, Chuan Shi, Jiawei Liu, Bai Wang
Most of existing clustering algorithms are proposed without considering the selection bias in data.
no code implementations • 9 Sep 2020 • Jiawei Liu, Xierong Zhu, Zheng-Jun Zha
TALNet simultaneously exploits human attributes and appearance to learn comprehensive and effective pedestrian representations from videos.
no code implementations • 10 Oct 2020 • Kecheng Zheng, Wu Liu, Jiawei Liu, Zheng-Jun Zha, Tao Mei
This hard selection strategy is able to fuse the strong-relevant multi-modality features for alleviating the problem of matching redundancy.
Ranked #16 on Text based Person Retrieval on CUHK-PEDES
no code implementations • CVPR 2021 • Jiawei Liu, Zheng-Jun Zha, Wei Wu, Kecheng Zheng, Qibin Sun
The key factor for video person re-identification is to effectively exploit both spatial and temporal clues from video sequences.
Ranked #10 on Video Deinterlacing on MSU Deinterlacer Benchmark
no code implementations • 7 May 2021 • Jiawei Liu, Zhipeng Huang, Kecheng Zheng, Dong Liu, Xiaoyan Sun, Zheng-Jun Zha
It describes unseen target domain as a combination of the known source ones, and explicitly learns domain-specific representation with target distribution to improve the model's generalization by a meta-learning pipeline.
no code implementations • 31 Jul 2021 • Kecheng Zheng, Cuiling Lan, Wenjun Zeng, Jiawei Liu, Zhizheng Zhang, Zheng-Jun Zha
Occluded person re-identification (ReID) aims to match person images with occlusion.
no code implementations • SEMEVAL 2021 • Jiaju Lin, Jing Ling, Zhiwei Wang, Jiawei Liu, Qin Chen, Liang He
The purpose of the task was to extract triples from a paper in the Nature Language Processing field for constructing an Open Research Knowledge Graph.
no code implementations • 29 Sep 2021 • Jiawei Liu, Hang Gao, Yunfeng Hu, Xun Gong
The proxy dataset selection stage calculates the proposed average patch saliency (APS) of each available dataset to select a high-APS proxy dataset that can guarantee patches' fooling abilities.
no code implementations • 28 Dec 2021 • Jiawei Liu, Jing Zhang, Nick Barnes
We study semi-supervised salient object detection, with access to a small number of labeled samples and a large number of unlabeled samples.
no code implementations • 3 Mar 2022 • Zhipeng Huang, Jiawei Liu, Liang Li, Kecheng Zheng, Zheng-Jun Zha
RGB-infrared person re-identification is an emerging cross-modality re-identification task, which is very challenging due to significant modality discrepancy between RGB and infrared images.
no code implementations • 3 Mar 2022 • Jiawei Liu, Zhipeng Huang, Liang Li, Kecheng Zheng, Zheng-Jun Zha
In this paper, we propose a novel Debiased Batch Normalization via Gaussian Process approach (GDNorm) for generalizable person re-identification, which models the feature statistic estimation from BN layers as a dynamically self-refining Gaussian process to alleviate the bias to unseen domain for improving the generalization.
Generalizable Person Re-identification Representation Learning
no code implementations • 7 May 2022 • Qunsong Zeng, Jiawei Liu, Jun Lan, Yi Gong, Zhongrui Wang, Yida Li, Kaibin Huang
To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient (UFEE) baseband processors.
no code implementations • CVPR 2022 • Wei Wu, Jiawei Liu, Kecheng Zheng, Qibin Sun, Zheng-Jun Zha
Image-to-video person re-identification aims to retrieve the same pedestrian as the image-based query from a video-based gallery set.
Image-To-Video Person Re-Identification reinforcement-learning +4
no code implementations • 10 Jun 2022 • Jingyi Xie, Jiawei Liu, Zheng-Jun Zha
LNMT leverages unlabeled news and feedback comments of users to enlarge the amount of training data and facilitates model training by generating refined labels as weak supervision.
no code implementations • 20 Aug 2022 • Jiawei Liu, Jing Zhang, Ruikai Cui, Kaihao Zhang, Weihao Li, Nick Barnes
We propose a new setting that relaxes an assumption in the conventional Co-Salient Object Detection (CoSOD) setting by allowing the presence of "noisy images" which do not show the shared co-salient object.
no code implementations • 24 Jan 2023 • Yongqiang Ma, Jiawei Liu, Fan Yi, Qikai Cheng, Yong Huang, Wei Lu, Xiaozhong Liu
We find that there exists a "writing style" gap between AI-generated scientific text and human-written scientific text.
no code implementations • 8 Feb 2023 • Jiawei Liu, Xingping Dong, Sanyuan Zhao, Jianbing Shen
To achieve simultaneous detection for both common and rare objects, we propose a novel task, called generalized few-shot 3D object detection, where we have a large amount of training data for common (base) objects, but only a few data for rare (novel) classes.
no code implementations • 19 Mar 2023 • Yuan Zeng, Yi Gong, Jiawei Liu, Shangao Lin, Zidong Han, Ruoxiao Cao, Kaibin Huang, Khaled Ben Letaief
The features extracted from different channels are fused adaptively using a shared attention module, where the weights of neural features from multiple channels are learned during training the McAFF model.
no code implementations • 23 Mar 2023 • Zhihang Yuan, Jiawei Liu, Jiaxiang Wu, Dawei Yang, Qiang Wu, Guangyu Sun, Wenyu Liu, Xinggang Wang, Bingzhe Wu
Post-training quantization (PTQ) is a popular method for compressing deep neural networks (DNNs) without modifying their original architecture or training procedures.
no code implementations • 2 Apr 2023 • Bo Yan, Cheng Yang, Chuan Shi, Jiawei Liu, Xiaochen Wang
AEHCL designs the intra-event and inter-event contrastive modules to exploit self-supervised AHIN information.
no code implementations • 18 Apr 2023 • Yuanwei Fang, Zihao Liu, Yanheng Lu, Jiawei Liu, Jiajie Li, Yi Jin, Jian Chen, Yenkuang Chen, Hongzhong Zheng, Yuan Xie
Furthermore, NPS shows higher accuracy and generality than the state-of-the-art GNN approach in code behavior learning, enabling the generation of high-quality execution embeddings.
no code implementations • 19 Apr 2023 • Lin Niu, Jiawei Liu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu
PTQ optimizes the quantization parameters by different metrics to minimize the perturbation of quantization.
no code implementations • 5 May 2023 • Jiawei Liu, Zi Xiong, Yi Jiang, Yongqiang Ma, Wei Lu, Yong Huang, Qikai Cheng
Inspired by recent advancement in prompt learning, in this paper, we propose the Mix Prompt Tuning (MPT), which is a semi-supervised method to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks with a small number of labeled examples.
no code implementations • CVPR 2023 • Dong Li, Jiaying Zhu, Menglu Wang, Jiawei Liu, Xueyang Fu, Zheng-Jun Zha
In the second step, guided by the learnable edges, a region message passing controller is devised to weaken the message passing between the forged and authentic regions.
no code implementations • 28 Jun 2023 • Jiawei Liu, Jingyi Xie, Fanrui Zhang, Qiang Zhang, Zheng-Jun Zha
The explosive growth of rumors with text and images on social media platforms has drawn great attention.
no code implementations • ICCV 2023 • Kecheng Zheng, Wei Wu, Ruili Feng, Kai Zhu, Jiawei Liu, Deli Zhao, Zheng-Jun Zha, Wei Chen, Yujun Shen
To bring the useful knowledge back into light, we first identify a set of parameters that are important to a given downstream task, then attach a binary mask to each parameter, and finally optimize these masks on the downstream data with the parameters frozen.
no code implementations • 19 Aug 2023 • Qunsong Zeng, Jiawei Liu, Mingrui Jiang, Jun Lan, Yi Gong, Zhongrui Wang, Yida Li, Can Li, Jim Ignowski, Kaibin Huang
To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient baseband processors.
no code implementations • 15 Oct 2023 • Jiahao Xia, Gavin Gong, Jiawei Liu, Zhigang Zhu, Hao Tang
In this paper, a Segment Anything Model (SAM)-based pedestrian infrastructure segmentation workflow is designed and optimized, which is capable of efficiently processing multi-sourced geospatial data including LiDAR data and satellite imagery data.
no code implementations • 18 Oct 2023 • Jiawei Liu, Cheng Yang, Zhiyuan Lu, Junze Chen, Yibo Li, Mengmei Zhang, Ting Bai, Yuan Fang, Lichao Sun, Philip S. Yu, Chuan Shi
Foundation models have emerged as critical components in a variety of artificial intelligence applications, and showcase significant success in natural language processing and several other domains.
no code implementations • 19 Oct 2023 • Xiang Shi, Jiawei Liu, Yinpeng Liu, Qikai Cheng, Wei Lu
The advent of Large Language Models (LLMs) has shown the potential to improve relevance and provide direct answers in web searches.
no code implementations • 1 Nov 2023 • Ruihang Lai, Junru Shao, Siyuan Feng, Steven S. Lyubomirsky, Bohan Hou, Wuwei Lin, Zihao Ye, Hongyi Jin, Yuchen Jin, Jiawei Liu, Lesheng Jin, Yaxing Cai, Ziheng Jiang, Yong Wu, Sunghyun Park, Prakalp Srivastava, Jared G. Roesch, Todd C. Mowry, Tianqi Chen
Dynamic shape computations have become critical in modern machine learning workloads, especially in emerging large language models.
no code implementations • 21 Dec 2023 • Miao Hua, Jiawei Liu, Fei Ding, Wei Liu, Jie Wu, Qian He
Diffusion-based models have demonstrated impressive capabilities for text-to-image generation and are expected for personalized applications of subject-driven generation, which require the generation of customized concepts with one or a few reference images.
no code implementations • 9 Jan 2024 • Weimin WANG, Jiawei Liu, Zhijie Lin, Jiangqiao Yan, Shuo Chen, Chetwin Low, Tuyen Hoang, Jie Wu, Jun Hao Liew, Hanshu Yan, Daquan Zhou, Jiashi Feng
The growing demand for high-fidelity video generation from textual descriptions has catalyzed significant research in this field.
no code implementations • 29 Feb 2024 • Anton Lozhkov, Raymond Li, Loubna Ben allal, Federico Cassano, Joel Lamy-Poirier, Nouamane Tazi, Ao Tang, Dmytro Pykhtar, Jiawei Liu, Yuxiang Wei, Tianyang Liu, Max Tian, Denis Kocetkov, Arthur Zucker, Younes Belkada, Zijian Wang, Qian Liu, Dmitry Abulkhanov, Indraneil Paul, Zhuang Li, Wen-Ding Li, Megan Risdal, Jia Li, Jian Zhu, Terry Yue Zhuo, Evgenii Zheltonozhskii, Nii Osae Osae Dade, Wenhao Yu, Lucas Krauß, Naman jain, Yixuan Su, Xuanli He, Manan Dey, Edoardo Abati, Yekun Chai, Niklas Muennighoff, Xiangru Tang, Muhtasham Oblokulov, Christopher Akiki, Marc Marone, Chenghao Mou, Mayank Mishra, Alex Gu, Binyuan Hui, Tri Dao, Armel Zebaze, Olivier Dehaene, Nicolas Patry, Canwen Xu, Julian McAuley, Han Hu, Torsten Scholak, Sebastien Paquet, Jennifer Robinson, Carolyn Jane Anderson, Nicolas Chapados, Mostofa Patwary, Nima Tajbakhsh, Yacine Jernite, Carlos Muñoz Ferrandis, Lingming Zhang, Sean Hughes, Thomas Wolf, Arjun Guha, Leandro von Werra, Harm de Vries
Our large model, StarCoder2- 15B, significantly outperforms other models of comparable size.
Ranked #25 on Code Generation on MBPP
no code implementations • 22 Mar 2024 • Qiang Zhang, Jiawei Liu, Fanrui Zhang, Xiaoling Zhu, Zheng-Jun Zha
Existing key node identification methods usually consider node influence only from the propagation structure perspective and have insufficient generalization ability to unknown scenarios.
no code implementations • 22 Mar 2024 • Fanrui Zhang, Jiawei Liu, Qiang Zhang, Xiaoling Zhu, Zheng-Jun Zha
In this work, we propose a novel Hierarchical Information Enhancement Network (HIENet) for cascade prediction.
no code implementations • 10 Apr 2024 • Yongqiang Ma, Lizhi Qing, Jiawei Liu, Yangyang Kang, Yue Zhang, Wei Lu, Xiaozhong Liu, Qikai Cheng
Therefore, our study shifts the focus from model-centered to human-centered evaluation in the context of AI-powered writing assistance applications.
no code implementations • 14 Apr 2024 • Siyuan Feng, Jiawei Liu, Ruihang Lai, Charlie F. Ruan, Yong Yu, Lingming Zhang, Tianqi Chen
While a traditional bottom-up development pipeline fails to close the gap timely, we introduce TapML, a top-down approach and tooling designed to streamline the deployment of ML systems on diverse platforms, optimized for developer productivity.
no code implementations • 18 Apr 2024 • Zi Xiong, Lizhi Qing, Yangyang Kang, Jiawei Liu, Hongsong Li, Changlong Sun, Xiaozhong Liu, Wei Lu
The widespread use of pre-trained language models (PLMs) in natural language processing (NLP) has greatly improved performance outcomes.
1 code implementation • 19 Nov 2021 • Yanni Li, Wenhui Zhang, Jiawei Liu, Xiaoli Kou, Hui Li, Jiangtao Cui
Despite the fact that deep neural networks (DNNs) have achieved prominent performance in various applications, it is well known that DNNs are vulnerable to adversarial examples/samples (AEs) with imperceptible perturbations in clean/original samples.
1 code implementation • ICCV 2023 • Jiawei Liu, Changkun Ye, Shan Wang, Ruikai Cui, Jing Zhang, Kaihao Zhang, Nick Barnes
To improve model calibration, we propose Adaptive Stochastic Label Perturbation (ASLP) which learns a unique label perturbation level for each training image.
1 code implementation • 19 Feb 2024 • Zhongjian Zhang, Mengmei Zhang, Yue Yu, Cheng Yang, Jiawei Liu, Chuan Shi
Furthermore, with GraphPAR, we quantify whether the fairness of each node is provable, i. e., predictions are always fair within a certain range of sensitive attribute semantics.
1 code implementation • 1 Jan 2024 • Quanjun Zhang, Juan Zhai, Chunrong Fang, Jiawei Liu, Weisong Sun, Haichuan Hu, Qingyu Wang
The results show that STP can accurately find 5, 073 unique erroneous translations in Google Translate and 5, 100 unique erroneous translations in Bing Microsoft Translator (400% more than state-of-the-art techniques), with 64. 5% and 65. 4% precision, respectively.
1 code implementation • 15 Apr 2021 • Jiawei Liu, Jing Zhang, Yicong Hong, Nick Barnes
Within this pipeline, the class activation map (CAM) is obtained and further processed to serve as a pseudo label to train the semantic segmentation model in a fully-supervised manner.
1 code implementation • 30 Jan 2024 • Fei Teng, Jiaming Zhang, Jiawei Liu, Kunyu Peng, Xina Cheng, Zhiyong Li, Kailun Yang
Previous approaches predominantly employ a custom two-stream design to discover the implicit angular feature within light field cameras, leading to significant information isolation between different LF representations.
1 code implementation • 16 Feb 2024 • Yinpeng Liu, Jiawei Liu, Xiang Shi, Qikai Cheng, Wei Lu
We advocate the few-shot in-context curriculum learning (ICCL), a simple but effective demonstration ordering method for ICL, which implies gradually increasing the complexity of prompt demonstrations during the inference process.
1 code implementation • 13 Jun 2022 • Jiawei Liu, Kaiyu Zhang, Weitai Hu, Qing Yang
To address this problem, we propose a step-by-step training super-net scheme from one-shot NAS to few-shot NAS.
1 code implementation • ACL 2018 • Yang Xu, Jiawei Liu, Wei Yang, Liusheng Huang
Experiments on word similarity, syntactic analogy and text classification are conducted to validate the feasibility of our models.
1 code implementation • 29 Mar 2023 • Jiawei Liu, Weining Wang, Sihan Chen, Xinxin Zhu, Jing Liu
In this work, we concentrate on a rarely investigated problem of text guided sounding video generation and propose the Sounding Video Generator (SVG), a unified framework for generating realistic videos along with audio signals.
2 code implementations • 14 Dec 2020 • Jiawei Liu, Zhe Gao, Yangyang Kang, Zhuoren Jiang, Guoxiu He, Changlong Sun, Xiaozhong Liu, Wei Lu
Is chatbot able to completely replace the human agent?
1 code implementation • EMNLP 2021 • Jiawei Liu, Kaisong Song, Yangyang Kang, Guoxiu He, Zhuoren Jiang, Changlong Sun, Wei Lu, Xiaozhong Liu
Chatbot is increasingly thriving in different domains, however, because of unexpected discourse complexity and training data sparseness, its potential distrust hatches vital apprehension.
1 code implementation • 13 Sep 2023 • Jiayang Song, Zhehua Zhou, Jiawei Liu, Chunrong Fang, Zhan Shu, Lei Ma
Then, the performance of the reward function is assessed, and the results are presented back to the LLM for guiding its self-refinement process.
1 code implementation • 27 Nov 2021 • Kecheng Zheng, Jiawei Liu, Wei Wu, Liang Li, Zheng-Jun Zha
The calibrated person representation is subtly decomposed into the identity-relevant feature, domain feature, and the remaining entangled one.
Domain Generalization Generalizable Person Re-identification
1 code implementation • 26 Jul 2022 • Jiawei Liu, JinKun Lin, Fabian Ruffy, Cheng Tan, Jinyang Li, Aurojit Panda, Lingming Zhang
In this work, we propose a new fuzz testing approach for finding bugs in deep-learning compilers.
1 code implementation • 14 Sep 2022 • Jiawei Liu, Yangyang Kang, Di Tang, Kaisong Song, Changlong Sun, XiaoFeng Wang, Wei Lu, Xiaozhong Liu
In this study, we propose an imitation adversarial attack on black-box neural passage ranking models.
1 code implementation • IEEE Transactions on Multimedia 2023 • Jiawei Liu, Qiang Wang, Huijie Fan, Wentao Li, Liangqiong Qu, Yandong Tang
Last, these features are converted to a target shadow-free image, affiliated shadow matte, and shadow image, supervised by multi-task joint loss functions.
1 code implementation • IEEE Transactions on Neural Networks and Learning Systems 2023 • Jiawei Liu, Qiang Wang, Huijie Fan, Jiandong Tian, Yandong Tang
Thus, our network ensures the fidelity of nonshadow areas and restores the light intensity of shadow areas through three-branch collaboration.
1 code implementation • 23 Apr 2024 • Yifeng Ding, Jiawei Liu, Yuxiang Wei, Terry Yue Zhuo, Lingming Zhang
We introduce XFT, a simple yet powerful training scheme, by simply merging upcycled Mixture-of-Experts (MoE) to unleash the performance limit of instruction-tuned code Large Language Models (LLMs).
1 code implementation • 21 Feb 2022 • Jiawei Liu, Yuxiang Wei, Sen yang, Yinlin Deng, Lingming Zhang
Our results show that Tzer substantially outperforms existing fuzzing techniques on tensor compiler testing, with 75% higher coverage and 50% more valuable tests than the 2nd-best technique.
2 code implementations • 23 Jan 2019 • Jiawei Liu, Yang Xu, Yaguang Zhu
Current state-of-art feature-engineered and end-to-end Automated Essay Score (AES) methods are proven to be unable to detect adversarial samples, e. g. the essays composed of permuted sentences and the prompt-irrelevant essays.
1 code implementation • 22 Jun 2021 • Jiawei Liu, Jing Zhang, Nick Barnes
Then, we concatenate it with the input image and feed it to the confidence estimation network to produce an one channel confidence map. We generate dynamic supervision for the confidence estimation network, representing the agreement of camouflage prediction with the ground truth camouflage map.
1 code implementation • 5 Oct 2020 • Jiawei Liu, Huijie Fan, Qiang Wang, Wentao Li, Yandong Tang, Danbo Wang, Mingyi Zhou, Li Chen
The qualitative and quantitative experimental results show that our LLPC can improve the quality of manual labels and the accuracy of overlapping cell edge detection.
1 code implementation • 4 Feb 2023 • Jiawei Liu, Jinjun Peng, Yuyao Wang, Lingming Zhang
NeuRI finds 100 new bugs for PyTorch and TensorFlow in four months, with 81 already fixed or confirmed.
1 code implementation • 8 Nov 2018 • Mengwei Xu, Jiawei Liu, Yuanqiang Liu, Felix Xiaozhu Lin, Yunxin Liu, Xuanzhe Liu
We are in the dawn of deep learning explosion for smartphones.
1 code implementation • 21 Dec 2023 • Qinying Liu, Wei Wu, Kecheng Zheng, Zhan Tong, Jiawei Liu, Yu Liu, Wei Chen, Zilei Wang, Yujun Shen
The crux of learning vision-language models is to extract semantically aligned information from visual and linguistic data.
1 code implementation • 24 Oct 2023 • Chenyuan Yang, Yinlin Deng, Runyu Lu, Jiayi Yao, Jiawei Liu, Reyhaneh Jabbarvand, Lingming Zhang
Nonetheless, prompting LLMs with compiler source-code information remains a missing piece of research in compiler testing.
1 code implementation • CVPR 2023 • Jiawei Liu, Lin Niu, Zhihang Yuan, Dawei Yang, Xinggang Wang, Wenyu Liu
It determines the quantization parameters by using the information of differences between network prediction before and after quantization.
1 code implementation • 28 Jan 2024 • Weifeng Liu, Tianyi She, Jiawei Liu, Run Wang, Dongyu Yao, Ziyou Liang
In recent years, DeepFake technology has achieved unprecedented success in high-quality video synthesis, whereas these methods also pose potential and severe security threats to humanity.
1 code implementation • 4 Mar 2021 • Cheng Yang, Jiawei Liu, Chuan Shi
Our framework extracts the knowledge of an arbitrary learned GNN model (teacher model), and injects it into a well-designed student model.
Ranked #1 on Node Classification on Cora (0.5%)
1 code implementation • ICCV 2023 • Ruikai Cui, Shi Qiu, Saeed Anwar, Jiawei Liu, Chaoyue Xing, Jing Zhang, Nick Barnes
Point cloud completion aims to recover the complete shape based on a partial observation.
1 code implementation • 11 Mar 2024 • Tianhao Qi, Shancheng Fang, Yanze Wu, Hongtao Xie, Jiawei Liu, Lang Chen, Qian He, Yongdong Zhang
The Q-Formers are trained using paired images rather than the identical target, in which the reference image and the ground-truth image are with the same style or semantics.
1 code implementation • 3 Apr 2023 • Zhihang Yuan, Lin Niu, Jiawei Liu, Wenyu Liu, Xinggang Wang, Yuzhang Shang, Guangyu Sun, Qiang Wu, Jiaxiang Wu, Bingzhe Wu
In this paper, we identify that the challenge in quantizing activations in LLMs arises from varying ranges across channels, rather than solely the presence of outliers.
1 code implementation • 25 Aug 2023 • Jiawei Liu, Qiang Wang, Huijie Fan, Yinong Wang, Yandong Tang, Liangqiong Qu
We propose residual denoising diffusion models (RDDM), a novel dual diffusion process that decouples the traditional single denoising diffusion process into residual diffusion and noise diffusion.
2 code implementations • ICCV 2023 • Shan Wang, Chuong Nguyen, Jiawei Liu, Kaihao Zhang, Wenhan Luo, Yanhao Zhang, Sundaram Muthu, Fahira Afzal Maken, Hongdong Li
Reliable segmentation of road lines and markings is critical to autonomous driving.
1 code implementation • 12 Oct 2023 • Rui Zhao, YuChao Gu, Jay Zhangjie Wu, David Junhao Zhang, Jiawei Liu, Weijia Wu, Jussi Keppo, Mike Zheng Shou
Given a set of video clips of the same motion concept, the task of Motion Customization is to adapt existing text-to-video diffusion models to generate videos with this motion.
1 code implementation • NeurIPS 2023 • Jiawei Liu, Chunqiu Steven Xia, Yuyao Wang, Lingming Zhang
While EvalPlus is general, we extend the test-cases of the popular HumanEval benchmark by 80x to build HumanEval+.
1 code implementation • 26 Aug 2021 • Yixiao Guo, Jiawei Liu, Guo Li, Luo Mai, Hao Dong
When it comes to customising these algorithms for real-world applications, none of the existing libraries can offer both the flexibility of developing custom pose estimation algorithms and the high-performance of executing these algorithms on commodity devices.
1 code implementation • 4 Dec 2023 • Yuxiang Wei, Zhe Wang, Jiawei Liu, Yifeng Ding, Lingming Zhang
Magicoder models are trained on 75K synthetic instruction data using OSS-Instruct, a novel approach to enlightening LLMs with open-source code snippets to generate high-quality instruction data for code.