no code implementations • 3 May 2024 • Wanlong Liu, Li Zhou, Dingyi Zeng, Yichen Xiao, Shaohuan Cheng, Chen Zhang, Grandee Lee, Malu Zhang, Wenyu Chen
Recent mainstream event argument extraction methods process each event in isolation, resulting in inefficient inference and ignoring the correlations among multiple events.
no code implementations • 10 Apr 2024 • Li Zhou, Taelin Karidi, Nicolas Garneau, Yong Cao, Wanlong Liu, Wenyu Chen, Daniel Hershcovich
Recent studies have highlighted the presence of cultural biases in Large Language Models (LLMs), yet often lack a robust methodology to dissect these phenomena comprehensively.
no code implementations • 24 Mar 2024 • Ali Shojaie, Wenyu Chen
In general, learning the DAG structure is both computationally and statistically challenging.
1 code implementation • 11 Mar 2024 • Xiang Meng, Wenyu Chen, Riade Benbaki, Rahul Mazumder
In this paper, we propose FALCON, a novel combinatorial-optimization-based framework for network pruning that jointly takes into account model accuracy (fidelity), FLOPs, and sparsity constraints.
no code implementations • 6 Mar 2024 • Chuanyu Luo, Nuo Cheng, Ren Zhong, Haipeng Jiang, Wenyu Chen, Aoli Wang, Pu Li
With the rapid advancement of hardware and software technologies, research in autonomous driving has seen significant growth.
no code implementations • 6 Mar 2024 • Xuanting Xie, Zhao Kang, Wenyu Chen
In this regard, we propose a novel robust graph structure learning method to achieve a high-quality graph from heterophilic data for downstream tasks.
no code implementations • 6 Mar 2024 • Xuanting Xie, Erlin Pan, Zhao Kang, Wenyu Chen, Bingheng Li
Motivated by this finding, we construct two graphs that are highly homophilic and heterophilic, respectively.
no code implementations • 3 Jan 2024 • Li Zhou, Wenyu Chen, Yong Cao, Dingyi Zeng, Wanlong Liu, Hong Qu
While Transformer-based pre-trained language models and their variants exhibit strong semantic representation capabilities, the question of comprehending the information gain derived from the additional components of PLMs remains an open question in this field.
no code implementations • 15 Oct 2023 • Li Zhou, Wenyu Chen, Dingyi Zeng, Malu Zhang, Daniel Hershcovich
In the field of natural language understanding, the intersection of neural models and graph meaning representations (GMRs) remains a compelling area of research.
1 code implementation • 10 Oct 2023 • Li Zhou, Antonia Karamolegkou, Wenyu Chen, Daniel Hershcovich
The increasing ubiquity of language technology necessitates a shift towards considering cultural diversity in the machine learning realm, particularly for subjective tasks that rely heavily on cultural nuances, such as Offensive Language Detection (OLD).
no code implementations • 8 Oct 2023 • Wanlong Liu, Dingyi Zeng, Li Zhou, Yichen Xiao, Weishan Kong, Malu Zhang, Shaohuan Cheng, Hongyang Zhao, Wenyu Chen
Document-level event argument extraction is a crucial yet challenging task within the field of information extraction.
no code implementations • 18 Aug 2023 • YunSong Luo, Wenyu Chen, Ling Zhan, Jiang Qiu, Tao Jia
In addition, the generalizability of MFMC is validated by the good performance when the training and testing subjects are from independent sites.
no code implementations • 18 Jul 2023 • Kayhan Behdin, Wenyu Chen, Rahul Mazumder
To solve the MIP, we propose a custom nonlinear branch-and-bound (BnB) framework that solves node relaxations with tailored first-order methods.
1 code implementation • 5 Jun 2023 • Shibal Ibrahim, Wenyu Chen, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
To deal with this challenge, we propose a novel, permutation-based local search method that can complement first-order methods in training any sparse gate, e. g., Hash routing, Top-k, DSelect-k, and COMET.
no code implementations • 28 Feb 2023 • Riade Benbaki, Wenyu Chen, Xiang Meng, Hussein Hazimeh, Natalia Ponomareva, Zhe Zhao, Rahul Mazumder
Our approach, CHITA, extends the classical Optimal Brain Surgeon framework and results in significant improvements in speed, memory, and performance over existing optimization-based approaches for network pruning.
1 code implementation • 13 Jul 2022 • Zekun Li, Zhengyang Geng, Zhao Kang, Wenyu Chen, Yibo Yang
To understand the instability in training, we detect the gradient flow of attention and observe gradient conflict among attention branches.
no code implementations • 8 May 2022 • YunSong Luo, Wenyu Chen, Jiang Qiu, Tao Jia
The positive brain-PAD observed in participants in China confirms the presence of accelerated brain aging in MDD patients.
no code implementations • 15 Oct 2021 • Li Zhou, Wenyu Chen, Dingyi Zeng, Shaohuan Cheng, Wanlong Liu, Malu Zhang, Hong Qu
To address these drawbacks, we present a novel message-passing paradigm, based on the properties of multi-step message source, node-specific message output, and multi-space message interaction.
1 code implementation • 20 May 2021 • Wenyu Chen, Mathias Drton, Ali Shojaie
Ancestral relations between variables play an important role in causal modeling.
1 code implementation • 23 May 2020 • Wenyu Chen, Rahul Mazumder
We present new large-scale algorithms for fitting a subgradient regularized multivariate convex regression function to $n$ samples in $d$ dimensions -- a key problem in shape constrained nonparametric regression with applications in statistics, engineering and the applied sciences.
1 code implementation • 16 Sep 2019 • Zhao Kang, Guoxin Shi, Shudong Huang, Wenyu Chen, Xiaorong Pu, Joey Tianyi Zhou, Zenglin Xu
Most existing methods don't pay attention to the quality of the graphs and perform graph learning and spectral clustering separately.
1 code implementation • 13 Sep 2019 • Zhao Kang, Zipeng Guo, Shudong Huang, Siying Wang, Wenyu Chen, Yuanzhang Su, Zenglin Xu
Most existing multi-view clustering methods explore the heterogeneous information in the space where the data points lie.
1 code implementation • 9 Sep 2019 • Xiaofan Bo, Zhao Kang, Zhitong Zhao, Yuanzhang Su, Wenyu Chen
To explore underlying complementary information from multiple views, in this paper, we propose a novel Latent Multi-view Semi-Supervised Classification (LMSSC) method.
no code implementations • 14 Mar 2019 • Zhao Kang, Liangjian Wen, Wenyu Chen, Zenglin Xu
By formulating graph construction and kernel learning in a unified framework, the graph and consensus kernel can be iteratively enhanced by each other.
2 code implementations • 9 Jul 2018 • Wenyu Chen, Mathias Drton, Y. Samuel Wang
Prior work has shown that causal structure can be uniquely identified from observational data when these follow a structural equation model whose error terms have equal variances.
Methodology Computation