no code implementations • 19 May 2025 • Liyan Tang, Grace Kim, Xinyu Zhao, Thom Lake, Wenxuan Ding, Fangcong Yin, Prasann Singhal, Manya Wadhwa, Zeyu Leo Liu, Zayne Sprague, Ramya Namuduri, Bodun Hu, Juan Diego Rodriguez, Puyuan Peng, Greg Durrett
Unlike prior chart understanding benchmarks -- where frontier models perform similarly and near saturation -- our benchmark exposes a substantial gap between model and human performance, while effectively differentiating model capabilities: although humans achieve 93% accuracy, the best-performing model Gemini-2. 5-Pro attains only 63. 0%, and the leading open-source LVLM Qwen2. 5-VL-72B-Instruct achieves only 38. 5%.
no code implementations • 17 Apr 2025 • Xinyu Zhao, Jun Liu, Faqiang Wang, Li Cui, Yuping Duan
This paper proposes a new approach to integrate the prior of elliptical shapes into the deep learning-based SAM image segmentation techniques using variational methods.
no code implementations • 25 Mar 2025 • Xiaohe Li, Haohua Wu, Jiahao Li, Zide Fan, Kaixin Zhang, Xinming Li, Yunping Ge, Xinyu Zhao
Experiments on real-world image classification and object segmentation datasets validate the effectiveness and reliability of the SAFE framework in complex remote sensing scenarios.
no code implementations • 29 Jan 2025 • Zijie Liu, Xinyu Zhao, Jie Peng, Zhuangdi Zhu, Qingyu Chen, Xia Hu, Tianlong Chen
Current medical AI systems often fail to replicate real-world clinical reasoning, as they are predominantly trained and evaluated on static text and question-answer tasks.
no code implementations • CVPR 2025 • Xinyu Zhao, Jun Xie, Shengzhe Chen, Jun Liu
Multi-center star shape is a prevalent object shape feature, which has proven effective in model-based image segmentation methods.
2 code implementations • 23 Dec 2024 • Song Wang, Zhenyu Lei, Zhen Tan, Jiaqi Ding, Xinyu Zhao, Yushun Dong, Guorong Wu, Tianlong Chen, Chen Chen, Aiying Zhang, Jundong Li
As such, conventional GNNs struggle to learn from these pathways due to the long-range dependencies of multiple pathways.
1 code implementation • 26 Nov 2024 • Guanjie Chen, Xinyu Zhao, Yucheng Zhou, Xiaoye Qu, Tianlong Chen, Yu Cheng
Diffusion Transformers (DiT) have emerged as a powerful architecture for image and video generation, offering superior quality and scalability.
no code implementations • 29 Oct 2024 • Xinyu Zhao, Fangcong Yin, Greg Durrett
To defray the cost of pretraining LLMs over long contexts, recent work takes an approach of synthetic context extension: fine-tuning LLMs with synthetically generated long-context data in a post-training stage.
1 code implementation • 7 Oct 2024 • Xinyu Zhao, Guoheng Sun, Ruisi Cai, Yukun Zhou, Pingzhi Li, Peihao Wang, Bowen Tan, Yexiao He, Li Chen, Yi Liang, Beidi Chen, Binhang Yuan, Hongyi Wang, Ang Li, Zhangyang Wang, Tianlong Chen
As Large Language Models (LLMs) excel across tasks and specialized domains, scaling LLMs based on existing models has garnered significant attention, which faces the challenge of decreasing performance when combining disparate models.
1 code implementation • 18 Sep 2024 • Zayne Sprague, Fangcong Yin, Juan Diego Rodriguez, Dongwei Jiang, Manya Wadhwa, Prasann Singhal, Xinyu Zhao, Xi Ye, Kyle Mahowald, Greg Durrett
Chain-of-thought (CoT) via prompting is the de facto method for eliciting reasoning capabilities from large language models (LLMs).
no code implementations • 24 Jul 2024 • Bernardo Consoli, Xizhi Wu, Song Wang, Xinyu Zhao, Yanshan Wang, Justin Rousseau, Tom Hartvigsen, Li Shen, Huanmei Wu, Yifan Peng, Qi Long, Tianlong Chen, Ying Ding
Extracting social determinants of health (SDoH) from unstructured medical notes depends heavily on labor-intensive annotations, which are typically task-specific, hampering reusability and limiting sharing.
1 code implementation • 2 Jul 2024 • Manya Wadhwa, Xinyu Zhao, Junyi Jessy Li, Greg Durrett
Recent work has explored the capability of large language models (LLMs) to identify and correct errors in LLM-generated responses.
1 code implementation • 17 Jun 2024 • Guanjie Chen, Xinyu Zhao, Tianlong Chen, Yu Cheng
Motivated by the research gap and counter-intuitive phenomenon, we propose $\texttt{MoE-RBench}$, the first comprehensive assessment of SMoE reliability from three aspects: $\textit{(i)}$ safety and hallucination, $\textit{(ii)}$ resilience to adversarial attacks, and $\textit{(iii)}$ out-of-distribution robustness.
no code implementations • 26 Mar 2024 • Xinyu Zhao, Hao Yan, Yongming Liu
This article argues that we can identify the events more accurately by leveraging the event taxonomy.
no code implementations • 2 Mar 2024 • Song Wang, Zhen Tan, Xinyu Zhao, Tianlong Chen, Huan Liu, Jundong Li
In contrast, in this work, we propose a novel self-conditioned graph generation framework designed to explicitly model graph distributions and employ these distributions to guide the generation process.
no code implementations • 6 Jan 2024 • Jiaxin Huang, Xinyu Zhao, Chang Che, Qunwei Lin, Bo Liu
To address the specific needs of ELLs, we propose the use of DeBERTa, a state-of-the-art neural language model, for improving automated feedback tools.
no code implementations • 6 Jan 2024 • Liqiang Yu, Bo Liu, Qunwei Lin, Xinyu Zhao, Chang Che
In the realm of patent document analysis, assessing semantic similarity between phrases presents a significant challenge, notably amplifying the inherent complexities of Cooperative Patent Classification (CPC) research.
no code implementations • 20 Dec 2023 • Bo Liu, Liqiang Yu, Chang Che, Qunwei Lin, Hao Hu, Xinyu Zhao
This paper focuses on the analysis of the application effectiveness of the integration of deep learning and computer vision technologies.
no code implementations • 25 Jun 2023 • Zhoufutu Wen, Xinyu Zhao, Zhipeng Jin, Yi Yang, Wei Jia, Xiaodong Chen, Shuanglong Li, Lin Liu
The core of DIA is a query-image matching module performing ad image retrieval and relevance modeling.
no code implementations • 18 May 2023 • Xinyu Zhao, Sa Huang, Wei Pang, You Zhou
In this paper, we propose a novel registration model called Cascade-Dilation Inter-Layer Differential Network (CDIDN), which exhibits both high deformation impedance capability (DIC) and accuracy.
1 code implementation • 14 May 2023 • Qijie Wei, Jingyuan Yang, Bo wang, Jinrui Wang, Jianchun Zhao, Xinyu Zhao, Sheng Yang, Niranchana Manivannan, Youxin Chen, Dayong Ding, Jing Zhou, Xirong Li
This paper addresses the emerging task of recognizing multiple retinal diseases from wide-field (WF) and ultra-wide-field (UWF) fundus images.
no code implementations • 11 Nov 2022 • Xinyu Zhao, Razvan C. Fetecau, Mo Chen
Our proposed network architecture includes the incorporation of LSTM and self-attention, which allows the trained policy to adapt to a variable number of agents.
Multi-agent Reinforcement Learning
Reinforcement Learning (RL)
no code implementations • 13 Oct 2022 • HanCong Feng, XinHai Yan, Kaili Jiang, Xinyu Zhao, Bin Tang
The automatic classification of radar waveform is a fundamental technique in electronic countermeasures (ECM). Recent supervised deep learning-based methods have achieved great success in a such classification task. However, those methods require enough labeled samples to work properly and in many circumstances, it is not available. To tackle this problem, in this paper, we propose a three-stages deep radar waveform clustering(DRSC) technique to automatically group the received signal samples without labels. Firstly, a pretext model is trained in a self-supervised way with the help of several data augmentation techniques to extract the class-dependent features. Next, the pseudo-supervised contrastive training is involved to further promote the separation between the extracted class-dependent features. And finally, the unsupervised problem is converted to a semi-supervised classification problem via pseudo label generation.
no code implementations • 9 Aug 2022 • Xinyu Zhao, Jiuyun Hu, Yajun Mei, Hao Yan
High-dimensional data has become popular due to the easy accessibility of sensors in modern industrial applications.
no code implementations • 20 Sep 2021 • Xinyu Zhao, Hao Yan, Zhiyong Hu, Dongping Du
Electrical conduction among cardiac tissue is commonly modeled with partial differential equations, i. e., reaction-diffusion equation, where the reaction term describes cellular stimulation and diffusion term describes electrical propagation.
no code implementations • 3 Jul 2021 • Mingliang Bai, Xinyu Zhao, Zhenhua Long, Jinfu Liu, Daren Yu
Photovoltaic (PV) power is an important way to utilize solar energy.
1 code implementation • EMNLP 2021 • Kaj Bostrom, Xinyu Zhao, Swarat Chaudhuri, Greg Durrett
Natural language is an attractive representation for this purpose -- it is both highly expressive and easy for humans to understand.
no code implementations • 11 Mar 2021 • Xinyu Zhao, Xuedong Hu
In Si quantum dots, valley degree of freedom, in particular the generally small valley splitting and the dot-dependent valley-orbit phase, adds complexities to the low-energy electron dynamics and the associated spin qubit manipulation.
Mesoscale and Nanoscale Physics Quantum Physics
no code implementations • 1 Dec 2020 • Hasret Turkeri, Xinyu Zhao, Metin Muradgolu
The parametric studies show that the differential diffusion has a negligible effect on the mean and r. m. s.
Fluid Dynamics
2 code implementations • EACL (AdaptNLP) 2021 • Xinyu Zhao, Shih-ting Lin, Greg Durrett
A principal barrier to training temporal relation extraction models in new domains is the lack of varied, high quality examples and the challenge of collecting more.
no code implementations • 5 May 2017 • Xinyu Zhao, Michael Kesden, Davide Gerosa
We use analytic solutions for generic spin precession at 2PN order to derive Fourier series for the total and orbital angular momenta in which each term is a sinusoid with frequency $\Omega - n\omega$ for integer $n$.
General Relativity and Quantum Cosmology High Energy Astrophysical Phenomena