no code implementations • EMNLP 2021 • Xiangyu Lin, Tianyi Liu, Weijia Jia, Zhiguo Gong
Distantly supervised relation extraction is widely used in the construction of knowledge bases due to its high efficiency.
1 code implementation • 30 Nov 2024 • Bytedance-Seed-Foundation-Code-Team, :, Yao Cheng, Jianfeng Chen, Jie Chen, Li Chen, Liyu Chen, Wentao Chen, Zhengyu Chen, Shijie Geng, Aoyan Li, Bo Li, Bowen Li, Linyi Li, Boyi Liu, Jerry Liu, Kaibo Liu, Qi Liu, Shukai Liu, Siyao Liu, Tianyi Liu, Tingkai Liu, Yongfei Liu, Rui Long, Jing Mai, Guanghan Ning, Z. Y. Peng, Kai Shen, Jiahao Su, Jing Su, Tao Sun, Yifan Sun, Yunzhe Tao, Guoyin Wang, Siwei Wang, Xuwu Wang, Yite Wang, Zihan Wang, Jinxiang Xia, Liang Xiang, Xia Xiao, Yongsheng Xiao, Chenguang Xi, Shulin Xin, Jingjing Xu, Shikun Xu, Hongxia Yang, Jack Yang, Yingxiang Yang, Jianbo Yuan, Jun Zhang, Yufeng Zhang, Yuyu Zhang, Shen Zheng, He Zhu, Ming Zhu
As the capabilities of code large language models (LLMs) continue to expand, their applications across diverse code intelligence domains are rapidly increasing.
no code implementations • 9 Nov 2024 • Zhaorui Tan, Xi Yang, Tan Pan, Tianyi Liu, Chen Jiang, Xin Guo, Qiufeng Wang, Anh Nguyen, Yuan Qi, Kaizhu Huang, Yuan Cheng
We validate the feasibility and benefits of learning a personalized ${X}_h$, showing that this representation is highly generalizable and transferable across various multi-modal medical tasks.
1 code implementation • 28 Oct 2024 • Wenyang Liu, Kejun Wu, Tianyi Liu, Yi Wang, Kim-Hui Yap, Lap-Pui Chau
By looking inside bytes, the bit-level details of file fragments can be accessed, enabling a more accurate classification.
1 code implementation • 1 Oct 2024 • Xuwu Wang, Qiwen Cui, Yunzhe Tao, Yiran Wang, Ziwei Chai, Xiaotian Han, Boyi Liu, Jianbo Yuan, Jing Su, Guoyin Wang, Tingkai Liu, Liyu Chen, Tianyi Liu, Tao Sun, Yufeng Zhang, Sirui Zheng, Quanzeng You, Yang Yang, Hongxia Yang
BabelBench incorporates a dataset comprising 247 meticulously curated problems that challenge the models with tasks in perception, commonsense reasoning, logical reasoning, and so on.
no code implementations • 28 Sep 2024 • Tianyi Liu, Zhaorui Tan, Haochuan Jiang, Xi Yang, Kaizhu Huang
Brain tumor segmentation is often based on multiple magnetic resonance imaging (MRI).
no code implementations • 18 Aug 2024 • Tianyi Liu, Zhaorui Tan, Muyin Chen, Xi Yang, Haochuan Jiang, Kaizhu Huang
Along this line, in this paper, we propose a novel paradigm that aligns latent features of involved modalities to a well-defined distribution anchor as the substitution of the pre-trained model}.
no code implementations • 23 Jun 2024 • Tianyi Liu, Sai Pavan Deram, Khaled Ardah, Martin Haardt, Marc E. Pfetsch, Marius Pesavento
It is demonstrated that the proposed formulation can also be adopted in the fully calibrated case to improve the robustness of the subspace-based methods to the source correlation.
no code implementations • 20 Jun 2024 • Raphael Müller, Gianni Allevato, Matthias Rutsch, Christoph Haugwitz, Tianyi Liu, Mario Kupnik, Marius Pesavento
The experiment reveals that our array response model we learned with calibration data yields an imaging performance similar to that of the analytic array model, which requires perfect array geometry information.
no code implementations • 28 Mar 2024 • Tianyi Liu, Zhaorui Tan, Kaizhu Huang, Haochuan Jiang
Medical image segmentation presents the challenge of segmenting various-size targets, demanding the model to effectively capture both local and global information.
no code implementations • 6 Nov 2023 • Tianyi Liu, Frederic Matter, Alexander Sorg, Marc E. Pfetsch, Martin Haardt, Marius Pesavento
In this paper, we consider the maximum a posteriori (MAP) estimation for the multiple measurement vectors (MMV) problem with application to direction-of-arrival (DOA) estimation, which is classically formulated as a regularized least-squares (LS) problem with an $\ell_{2, 0}$-norm constraint, and derive an equivalent mixed-integer semidefinite program (MISDP) reformulation.
1 code implementation • 12 Oct 2023 • Yite Wang, Jiahao Su, Hanlin Lu, Cong Xie, Tianyi Liu, Jianbo Yuan, Haibin Lin, Ruoyu Sun, Hongxia Yang
Our empirical results demonstrate that LEMON reduces computational costs by 56. 7% for Vision Transformers and 33. 2% for BERT when compared to training from scratch.
no code implementations • 10 Oct 2023 • Chau Pham, Boyi Liu, Yingxiang Yang, Zhengyu Chen, Tianyi Liu, Jianbo Yuan, Bryan A. Plummer, Zhaoran Wang, Hongxia Yang
Although natural language is an obvious choice for communication due to LLM's language understanding capability, the token sampling step needed when generating natural language poses a potential risk of information loss, as it uses only one token to represent the model's belief across the entire vocabulary.
1 code implementation • NeurIPS 2023 • Tianyi Liu, Kejun Wu, Yi Wang, Wenyang Liu, Kim-Hui Yap, Lap-Pui Chau
The past decade has witnessed great strides in video recovery by specialist technologies, like video inpainting, completion, and error concealment.
1 code implementation • 7 Sep 2023 • Zhuokai Zhao, Harish Palani, Tianyi Liu, Lena Evans, Ruth Toner
Multimodal deep learning, especially vision-language models, have gained significant traction in recent years, greatly improving performance on many downstream tasks, including content moderation and violence detection.
2 code implementations • 13 Jun 2023 • Tianyi Liu, Zihao Xu, Hao He, Guang-Yuan Hao, Guang-He Lee, Hao Wang
Domain adaptation aims to mitigate distribution shifts among different domains.
1 code implementation • 5 Jun 2023 • Alexander Bukharin, Tianyi Liu, Shengjie Wang, Simiao Zuo, Weihao Gao, Wen Yan, Tuo Zhao
To address this issue, we propose a multi-stage computational framework -- ASTEROID, which lowers the data cost of MLFFs by leveraging a combination of cheap inaccurate data and expensive accurate data.
1 code implementation • 18 Jan 2023 • Shangyu Xie, Xin Yang, Yuanshun Yao, Tianyi Liu, Taiqing Wang, Jiankai Sun
In this work, we step further to study the leakage in the scenario of the regression model, where the private labels are continuous numbers (instead of discrete labels in classification).
no code implementations • 11 Oct 2022 • Tianyi Liu, Size Hou, Jiayuan Zhu, Zilong Zhao, Haochuan Jiang
an enhanced transformer module with deformable convolutions to improve the blending of the transformer information with convolutional information and help predict irregular LAs and scar shapes.
no code implementations • 15 Sep 2022 • Simiao Zuo, Tianyi Liu, Tuo Zhao, Hongyuan Zha
Point process models are of great importance in real world applications.
no code implementations • 16 Jun 2022 • Ruihan Wu, Xin Yang, Yuanshun Yao, Jiankai Sun, Tianyi Liu, Kilian Q. Weinberger, Chong Wang
Differentially Private (DP) data release is a promising technique to disseminate data without compromising the privacy of data subjects.
1 code implementation • 28 Apr 2022 • Jiandian Zeng, Tianyi Liu, Jiantao Zhou
Specifically, we design a tag encoding module to cover both the single modality and multiple modalities missing cases, so as to guide the network's attention to those missing modalities.
no code implementations • 7 Feb 2022 • Tianyi Liu, Yan Li, Enlu Zhou, Tuo Zhao
We investigate the role of noise in optimization algorithms for learning over-parameterized models.
no code implementations • 10 Dec 2021 • Tianyi Liu, Zuxuan Wu, Wenhan Xiong, Jingjing Chen, Yu-Gang Jiang
Our experiments show that there is a trade-off between understanding tasks and generation tasks while using the same model, and a feasible way to improve both tasks is to use more data.
no code implementations • 1 Oct 2021 • Guojing Cong, Tianyi Liu
We propose a momentum method for such model averaging approaches.
no code implementations • 13 Sep 2021 • Tianyi Liu, Andreas M. Tillmann, Yang Yang, Yonina C. Eldar, Marius Pesavento
The second algorithm, referred to as SCAphase, uses auxiliary variables and is favorable in the case of highly diverse mixture models.
no code implementations • 17 Jun 2021 • Khaled Ardah, Martin Haardt, Tianyi Liu, Frederic Matter, Marius Pesavento, Marc E. Pfetsch
Finally, we address the measurement system design for linear and nonlinear measurements of sparse signals.
no code implementations • 24 Feb 2021 • Tianyi Liu, Yan Li, Song Wei, Enlu Zhou, Tuo Zhao
Numerous empirical evidences have corroborated the importance of noise in nonconvex optimization problems.
no code implementations • COLING 2020 • Tianyi Liu, Xiangyu Lin, Weijia Jia, Mingliang Zhou, Wei Zhao
Distantly supervised relation extraction has been widely applied in knowledge base construction due to its less requirement of human efforts.
no code implementations • ICLR 2020 • Minshuo Chen, Yizhou Wang, Tianyi Liu, Zhuoran Yang, Xingguo Li, Zhaoran Wang, Tuo Zhao
Generative Adversarial Imitation Learning (GAIL) is a powerful and practical approach for learning sequential decision-making policies.
no code implementations • NeurIPS 2019 • Tianyi Liu, Minshuo Chen, Mo Zhou, Simon S. Du, Enlu Zhou, Tuo Zhao
We show, however, that gradient descent combined with proper normalization, avoids being trapped by the spurious local optimum, and converges to a global optimum in polynomial time, when the weight of the first layer is initialized at 0, and that of the second layer is initialized arbitrarily in a ball.
no code implementations • 7 Sep 2019 • Mo Zhou, Tianyi Liu, Yan Li, Dachao Lin, Enlu Zhou, Tuo Zhao
Numerous empirical evidence has corroborated that the noise plays a crucial rule in effective and efficient training of neural networks.
no code implementations • ACL 2019 • Yongjian You, Weijia Jia, Tianyi Liu, Wenmian Yang
Comprehensive document encoding and salient information selection are two major difficulties for generating summaries with adequate salient information.
no code implementations • EMNLP 2018 • Tianyi Liu, Xinsong Zhang, Wanhao Zhou, Weijia Jia
Extracting relations is critical for knowledge base completion and construction in which distant supervised methods are widely used to extract relational facts automatically with the existing knowledge bases.
Ranked #1 on
Relationship Extraction (Distant Supervised)
on New York Times Corpus
(Average Precision metric)
no code implementations • NeurIPS 2018 • Tianyi Liu, Shiyang Li, Jianping Shi, Enlu Zhou, Tuo Zhao
Asynchronous momentum stochastic gradient descent algorithms (Async-MSGD) is one of the most popular algorithms in distributed machine learning.
no code implementations • 14 Feb 2018 • Tianyi Liu, Zhehui Chen, Enlu Zhou, Tuo Zhao
Our theoretical discovery partially corroborates the empirical success of MSGD in training deep neural networks.
no code implementations • 3 Jun 2015 • Tianyi Liu, Shuangsang Fang, Yuehui Zhao, Peng Wang, Jun Zhang
Deep learning refers to the shining branch of machine learning that is based on learning levels of representations.