1 code implementation • COLING 2022 • Rui Liu, Zheng Lin, Huishan Ji, Jiangnan Li, Peng Fu, Weiping Wang
Despite the significant progress on this task, it is extremely time-consuming and budget-unfriendly to collect sufficient high-quality labeled data for every new target under fully-supervised learning, whereas unlabeled data can be collected easier.
1 code implementation • Findings (EMNLP) 2021 • Jiangnan Li, Zheng Lin, Peng Fu, Weiping Wang
Furthermore, we utilize CSK to enrich edges with knowledge representations and process the SKAIG with a graph transformer.
Ranked #9 on Emotion Recognition in Conversation on DailyDialog
no code implementations • COLING 2022 • Yubing Ren, Yanan Cao, Fang Fang, Ping Guo, Zheng Lin, Wei Ma, Yi Liu
Transforming the large amounts of unstructured text on the Internet into structured event knowledge is a critical, yet unsolved goal of NLP, especially when addressing document-level text.
1 code implementation • COLING 2022 • Chenxu Yang, Zheng Lin, Jiangnan Li, Fandong Meng, Weiping Wang, Lanrui Wang, Jie zhou
The knowledge selector generally constructs a query based on the dialogue context and selects the most appropriate knowledge to help response generation.
no code implementations • COLING 2022 • Qingyue Wang, Yanan Cao, Piji Li, Yanhe Fu, Zheng Lin, Li Guo
Zero-shot learning for Dialogue State Tracking (DST) focuses on generalizing to an unseen domain without the expense of collecting in domain data.
no code implementations • 7 May 2024 • Guanqiao Qu, Zheng Lin, Fangming Liu, Xianhao Chen, Kaibin Huang
To this end, we formulate a parameter-sharing model placement problem to maximize the cache hit ratio in multi-edge wireless networks by balancing the fundamental tradeoff between storage efficiency and service latency.
no code implementations • 3 May 2024 • Sicong Liu, Wentao Zhou, Zimu Zhou, Bin Guo, Minfan Wang, Cheng Fang, Zheng Lin, Zhiwen Yu
There is a growing demand to deploy computation-intensive deep learning (DL) models on resource-constrained mobile devices for real-time intelligent applications.
no code implementations • 12 Apr 2024 • Yuhang Qiu, Honghui Chen, Xingbo Dong, Zheng Lin, Iman Yi Liao, Massimo Tistarelli, Zhe Jin
The first module, an interpretable dense registration module, establishes a Vision Transformer (ViT)-based Siamese Network to capture long-range dependencies and the global context in fingerprint pairs.
no code implementations • 9 Apr 2024 • Zihan Fang, Zheng Lin, Zhe Chen, Xianhao Chen, Yue Gao, Yuguang Fang
Recently, there has been a surge in the development of advanced intelligent generative content (AIGC), especially large language models (LLMs).
1 code implementation • 2 Apr 2024 • Cheng Gong, Haoshuai Zheng, Mengting Hu, Zheng Lin, Deng-Ping Fan, Yuzhi Zhang, Tao Li
Quantization is a promising method that reduces memory usage and computational intensity of Deep Neural Networks (DNNs), but it often leads to significant output error that hinder model deployment.
no code implementations • 25 Mar 2024 • Yuxin Zhang, Haoyu Chen, Zheng Lin, Zhe Chen, Jin Zhao
Clustered federated learning (CFL) is proposed to mitigate the performance deterioration stemming from data heterogeneity in federated learning (FL) by grouping similar clients for cluster-wise model training.
no code implementations • 19 Mar 2024 • Zheng Lin, Guanqiao Qu, Wei Wei, Xianhao Chen, Kin K. Leung
In this paper, we provide a convergence analysis of SFL which quantifies the impact of model splitting (MS) and client-side model aggregation (MA) on the learning performance, serving as a theoretical foundation.
no code implementations • 11 Feb 2024 • Jiangnan Li, Qiujing Wang, Liyan Xu, Wenjie Pang, Mo Yu, Zheng Lin, Weiping Wang, Jie zhou
Similar to the "previously-on" scenes in TV shows, recaps can help book reading by recalling the readers' memory about the important elements in previous texts to better understand the ongoing plot.
no code implementations • 4 Feb 2024 • Hangwen Zhang, Qingyi Si, Peng Fu, Zheng Lin, Weiping Wang
Finally, we analyze some possible directions to promote the accuracy of TFV via LLMs, which is beneficial to further research of table reasoning.
no code implementations • 20 Dec 2023 • Peize Li, Qingyi Si, Peng Fu, Zheng Lin, Yan Wang
In this paper, we propose a novel VQA approach from the perspective of utilizing object attribute, aiming to achieve better object-level visual-language alignment and multimodal scene understanding.
no code implementations • 7 Dec 2023 • Xuying Zhang, Bo-Wen Yin, Yuming Chen, Zheng Lin, Yunheng Li, Qibin Hou, Ming-Ming Cheng
Particularly, a cross-modal graph is constructed to align the object points accurately and noun phrases decoupled from the 3D mesh and textual description.
no code implementations • 26 Nov 2023 • Lanrui Wang, Jiangnan Li, Chenxu Yang, Zheng Lin, Weiping Wang
The interest in Empathetic and Emotional Support conversations among the public has significantly increased.
no code implementations • 2 Nov 2023 • Zheng Lin, Zhe Chen, Zihan Fang, Xianhao Chen, Xiong Wang, Yue Gao
To this end, we propose FedSN as a general FL framework to tackle the above challenges, and fully explore data diversity on LEO satellites.
no code implementations • 13 Oct 2023 • Chenxu Yang, Zheng Lin, Lanrui Wang, Chong Tian, Liang Pang, Jiangnan Li, Qirong Ho, Yanan Cao, Weiping Wang
Knowledge-grounded dialogue generation aims to mitigate the issue of text degeneration by incorporating external knowledge to supplement the context.
1 code implementation • 11 Oct 2023 • Qingyi Si, Tong Wang, Zheng Lin, Xu Zhang, Yanan Cao, Weiping Wang
This paper will release a powerful Chinese LLMs that is comparable to ChatGLM.
no code implementations • 28 Sep 2023 • Zheng Lin, Guanqiao Qu, Qiyuan Chen, Xianhao Chen, Zhe Chen, Kaibin Huang
In both aspects, considering the inherent resource limitations at the edge, we discuss various cutting-edge techniques, including split learning/inference, parameter-efficient fine-tuning, quantization, and parameter-sharing inference, to facilitate the efficient deployment of LLMs.
no code implementations • 17 Aug 2023 • Song Lyu, Zheng Lin, Guanqiao Qu, Xianhao Chen, Xiaoxia Huang, Pan Li
In this paper, we develop a novel parallel U-shaped split learning and devise the optimal resource optimization scheme to improve the performance of edge networks.
no code implementations • 21 Jun 2023 • Zheng Lin, Guanqiao Qu, Xianhao Chen, Kaibin Huang
With the proliferation of distributed edge computing resources, the 6G mobile network will evolve into a network for connected intelligence.
1 code implementation • 13 Jun 2023 • Xuying Zhang, Bowen Yin, Zheng Lin, Qibin Hou, Deng-Ping Fan, Ming-Ming Cheng
We consider the problem of referring camouflaged object detection (Ref-COD), a new task that aims to segment specified camouflaged objects based on a small set of referring images with salient target objects.
no code implementations • 2 Jun 2023 • Guanqun Bi, Lei Shen, Yanan Cao, Meng Chen, Yuqiang Xie, Zheng Lin, Xiaodong He
Empathy is a crucial factor in open-domain conversations, which naturally shows one's caring and understanding to others.
no code implementations • 1 Jun 2023 • Qingyue Wang, Liang Ding, Yanan Cao, Yibing Zhan, Zheng Lin, Shi Wang, DaCheng Tao, Li Guo
Zero-shot transfer learning for Dialogue State Tracking (DST) helps to handle a variety of task-oriented dialogue domains without the cost of collecting in-domain data.
1 code implementation • 10 May 2023 • Qingyi Si, Yuchen Mo, Zheng Lin, Huishan Ji, Weiping Wang
Some existing solutions draw external knowledge into the cross-modality space which overlooks the much vaster textual knowledge in natural-language space, while others transform the image into a text that further fuses with the textual knowledge into the natural-language space and completely abandons the use of visual features.
no code implementations • 26 Mar 2023 • Zheng Lin, Guangyu Zhu, Yiqin Deng, Xianhao Chen, Yue Gao, Kaibin Huang, Yuguang Fang
The increasingly deeper neural networks hinder the democratization of privacy-enhancing distributed learning, such as federated learning (FL), to resource-constrained devices.
1 code implementation • 14 Mar 2023 • Ziyue Zhu, Zhao Zhang, Zheng Lin, Xing Sun, Ming-Ming Cheng
Such irrelevant information in the co-representation interferes with its locating of co-salient objects.
1 code implementation • 27 Oct 2022 • Bowen Shen, Zheng Lin, Yuanxin Liu, Zhengxiao Liu, Lei Wang, Weiping Wang
Motivated by such considerations, we propose a collaborative optimization for PLMs that integrates static model compression and dynamic inference acceleration.
no code implementations • 26 Oct 2022 • Jiangnan Li, Mo Yu, Fandong Meng, Zheng Lin, Peng Fu, Weiping Wang, Jie zhou
Although these tasks are effective, there are still urging problems: (1) randomly masking speakers regardless of the question cannot map the speaker mentioned in the question to the corresponding speaker in the dialogue, and ignores the speaker-centric nature of utterances.
1 code implementation • 26 Oct 2022 • Qingyi Si, Yuanxin Liu, Zheng Lin, Peng Fu, Weiping Wang
To this end, we systematically study the design of a training and compression pipeline to search the subnetworks, as well as the assignment of sparsity to different modality-specific modules.
1 code implementation • 21 Oct 2022 • Lanrui Wang, Jiangnan Li, Zheng Lin, Fandong Meng, Chenxu Yang, Weiping Wang, Jie zhou
We use a fine-grained encoding strategy which is more sensitive to the emotion dynamics (emotion flow) in the conversations to predict the emotion-intent characteristic of response.
1 code implementation • 11 Oct 2022 • Yuanxin Liu, Fandong Meng, Zheng Lin, Jiangnan Li, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou
In response to the efficiency problem, recent studies show that dense PLMs can be replaced with sparse subnetworks without hurting the performance.
1 code implementation • 10 Oct 2022 • Qingyi Si, Yuanxin Liu, Fandong Meng, Zheng Lin, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou
However, these models reveal a trade-off that the improvements on OOD data severely sacrifice the performance on the in-distribution (ID) data (which is dominated by the biased samples).
1 code implementation • 10 Oct 2022 • Qingyi Si, Fandong Meng, Mingyu Zheng, Zheng Lin, Yuanxin Liu, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou
To overcome this limitation, we propose a new dataset that considers varying types of shortcuts by constructing different distribution shifts in multiple OOD test sets.
1 code implementation • 2 May 2022 • Jiangnan Li, Fandong Meng, Zheng Lin, Rui Liu, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou
Conversational Causal Emotion Entailment aims to detect causal utterances for a non-neutral targeted utterance from a conversation.
Ranked #1 on Causal Emotion Entailment on RECCON
no code implementations • ACL 2022 • Ruipeng Jia, Xingxing Zhang, Yanan Cao, Shi Wang, Zheng Lin, Furu Wei
In zero-shot multilingual extractive text summarization, a model is typically trained on English summarization dataset and then applied on summarization datasets of other languages.
1 code implementation • NAACL 2022 • Yuanxin Liu, Fandong Meng, Zheng Lin, Peng Fu, Yanan Cao, Weiping Wang, Jie zhou
Firstly, we discover that the success of magnitude pruning can be attributed to the preserved pre-training performance, which correlates with the downstream transferability.
no code implementations • 10 Apr 2022 • Ziyue Zhu, Zhao Zhang, Zheng Lin, Ruiqi Wu, Zhi Chai, Chun-Le Guo
To achieve visual consistency in composite images, recent image harmonization methods typically summarize the appearance pattern of global background and apply it to the global foreground without location discrepancy.
no code implementations • 25 Mar 2022 • Zheng Lin, Zhao Zhang, Kang-Rui Zhang, Bo Ren, Ming-Ming Cheng
Our IST method can serve as a brush, dip style from anywhere, and then paint to any region of the target content image.
2 code implementations • CVPR 2022 • Zheng Lin, Zheng-Peng Duan, Zhao Zhang, Chun-Le Guo, Ming-Ming Cheng
However, the global view makes the model lose focus from later clicks, and is not in line with user intentions.
Ranked #5 on Interactive Segmentation on SBD
1 code implementation • ACL 2021 • Qingyi Si, Zheng Lin, Ming yu Zheng, Peng Fu, Weiping Wang
Besides, they only explore the interaction between image and question, ignoring the semantics of candidate answers.
1 code implementation • ACL 2021 • Yuanxin Liu, Fandong Meng, Zheng Lin, Weiping Wang, Jie zhou
In this paper, however, we observe that although distilling the teacher's hidden state knowledge (HSK) is helpful, the performance gain (marginal utility) diminishes quickly as more HSK is distilled.
1 code implementation • 8 Jun 2021 • Qingyi Si, Zheng Lin, Mingyu Zheng, Peng Fu, Weiping Wang
Besides, they only explore the interaction between image and question, ignoring the semantics of candidate answers.
1 code implementation • 21 Mar 2021 • Yuanxin Liu, Zheng Lin, Fengcheng Yuan
Based on the empirical findings, our best compressed model, dubbed Refined BERT cOmpreSsion with InTegrAted techniques (ROSITA), is $7. 5 \times$ smaller than BERT while maintains $98. 5\%$ of the performance on five tasks of the GLUE benchmark, outperforming the previous BERT compression methods with similar parameter budget.
1 code implementation • 29 Dec 2020 • Jiangnan Li, Zheng Lin, Peng Fu, Qingyi Si, Weiping Wang
It can be regarded as a personalized and interactive emotion recognition task, which is supposed to consider not only the semantic information of text but also the influences from speakers.
Ranked #34 on Emotion Recognition in Conversation on IEMOCAP
1 code implementation • 3 Dec 2020 • Qingyi Si, Yuanxin Liu, Peng Fu, Zheng Lin, Jiangnan Li, Weiping Wang
A critical problem behind these limitations is that the representations of unseen intents cannot be learned in the training stage.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Hongliang Pan, Zheng Lin, Peng Fu, Yatao Qi, Weiping Wang
Inspired by this, we propose a BERT architecture-based model, which concentrates on both intra and inter-modality incongruity for multi-modal sarcasm detection.
2 code implementations • 7 Jul 2020 • Deng-Ping Fan, Tengpeng Li, Zheng Lin, Ge-Peng Ji, Dingwen Zhang, Ming-Ming Cheng, Huazhu Fu, Jianbing Shen
CoSOD is an emerging and rapidly growing extension of salient object detection (SOD), which aims to detect the co-occurring salient objects in a group of images.
Ranked #7 on Co-Salient Object Detection on CoCA
2 code implementations • CVPR 2020 • Zheng Lin, Zhao Zhang, Lin-Zhuo Chen, Ming-Ming Cheng, Shao-Ping Lu
In the task of interactive image segmentation, users initially click one point to segment the main body of the target object and then provide more points on mislabeled regions iteratively for a precise segmentation.
1 code implementation • 30 Apr 2020 • Zhao Zhang, Zheng Lin, Jun Xu, Wenda Jin, Shao-Ping Lu, Deng-Ping Fan
To better explore salient information in both foreground and background regions, this paper proposes a Bilateral Attention Network (BiANet) for the RGB-D SOD task.
Ranked #3 on RGB-D Salient Object Detection on RGBD135
no code implementations • 22 Apr 2020 • Rui Liu, Zheng Lin, Weiping Wang
Considering the different characteristics of extractive and generative methods, we propose to divide the keyphrase prediction into two subtasks, i. e., present keyphrase extraction (PKE) and absent keyphrase generation (AKG), to fully exploit their respective advantages.
1 code implementation • 9 Apr 2020 • Lin-Zhuo Chen, Zheng Lin, Ziqin Wang, Yong-Liang Yang, Ming-Ming Cheng
S-Conv is competent to infer the sampling offset of the convolution kernel guided by the 3D spatial information, helping the convolutional layer adjust the receptive field and adapt to geometric transformations.
Ranked #20 on Semantic Segmentation on SUN-RGBD (using extra training data)
no code implementations • 13 Nov 2019 • Yuanxin Liu, Zheng Lin
They are classified into architecture-based methods and strategy-based methods, based on their way of handling the above obstacle.
no code implementations • IJCNLP 2019 • Yanfu Xu, Zheng Lin, Yuanxin Liu, Rui Liu, Weiping Wang, Dan Meng
Open-domain question answering (OpenQA) aims to answer questions based on a number of unlabeled paragraphs.
2 code implementations • 15 Jul 2019 • Deng-Ping Fan, Zheng Lin, Jia-Xing Zhao, Yun Liu, Zhao Zhang, Qibin Hou, Menglong Zhu, Ming-Ming Cheng
The use of RGB-D information for salient object detection has been extensively explored in recent years.
Ranked #4 on RGB-D Salient Object Detection on RGBD135