2 code implementations • 20 May 2024 • Junlong Jia, Ying Hu, Xi Weng, Yiming Shi, Miao Li, Xingjian Zhang, Baichuan Zhou, Ziyu Liu, Jie Luo, Lei Huang, Ji Wu
We present TinyLLaVA Factory, an open-source modular codebase for small-scale large multimodal models (LMMs) with a focus on simplicity of code implementations, extensibility of new features, and reproducibility of training results.
no code implementations • 18 Apr 2024 • Shanshan Wang, Ying Hu, Xun Yang, Zhongzhou Zhang, Keyang Wang, Xingyi Zhang
To address these problems, we propose a Concept-driven Personalized Forgetting knowledge tracing model (CPF) which integrates hierarchical relationships between knowledge concepts and incorporates students' personalized cognitive abilities.
2 code implementations • 22 Feb 2024 • Baichuan Zhou, Ying Hu, Xi Weng, Junlong Jia, Jie Luo, Xien Liu, Ji Wu, Lei Huang
We present the TinyLLaVA framework that provides a unified perspective in designing and analyzing the small-scale Large Multimodal Models (LMMs).
Ranked #70 on Visual Question Answering on MM-Vet
1 code implementation • 7 Jul 2023 • Zhongliang Jiang, Yuan Bi, Mingchuan Zhou, Ying Hu, Michael Burke, Nassir Navab
The results demonstrated that the proposed advanced framework can robustly work on a variety of seen and unseen phantoms as well as in-vivo human carotid data.
no code implementations • 29 Dec 2022 • Ying Hu, Xiaomin Shi, Zuo Quan Xu
This paper studies the monotone mean-variance (MMV) problem and the classical mean-variance (MV) problem with convex cone trading constraints in a market with random coefficients.
no code implementations • 12 Jul 2022 • Connor J. Parde, Virginia E. Strehle, Vivekjyoti Banerjee, Ying Hu, Jacqueline G. Cavazos, Carlos D. Castillo, Alice J. O'Toole
These findings also contribute to our understanding of DCNN performance for discriminating high-resemblance faces, demonstrate that the DCNN performs at a level at or above humans, and suggest a degree of parity between the features used by humans and the DCNN.
no code implementations • 3 Jul 2022 • Ying Hu, Yuwu Tang, Hao Huang, Liang He
Speech emotion recognition (SER) is an essential part of human-computer interaction.
no code implementations • IEEE Signal Processing Letters 2022 • Ying Hu, Yadong Chen, Wenzhong Yang, Liang He, Hao Huang
In this paper, we propose a model which combines the complexed spectrogram domain feature and time-domain feature by a cross-domain encoder (CDE) and adopts the hierarchic temporal convolutional network (HTCN) for multiple music sources separation.
Ranked #8 on Music Source Separation on MUSDB18
no code implementations • 19 Jun 2022 • Jun Li, Shibo Li, Ying Hu, Huiren Tao
Moreover, SGF successfully improves the accuracy and length of medical report generation by incorporating a similarity comparison mechanism that imitates the process of human self-improvement through compar-ative practice.
no code implementations • 22 Jun 2021 • Géraldine Jeckeln, Ying Hu, Jacqueline G. Cavazos, Amy N. Yates, Carina A. Hahn, Larry Tang, P. Jonathon Phillips, Alice J. O'Toole
Multiple tests of equal difficulty can be constructed then using subsets of items.
no code implementations • 27 Jan 2021 • Ying Hu, Shanjian Tang, Falei Wang
In this paper, we first study one-dimensional quadratic backward stochastic differential equations driven by $G$-Brownian motions ($G$-BSDEs) with unbounded terminal values.
Probability 60H10
no code implementations • 5 Jan 2021 • Ying Hu, Jian Huang, Jin-Feng Huang, Qiong-Tao Xie, Jie-Qiao Liao
We study the dynamic sensitivity of the quantum Rabi model, which exhibits quantum criticality in the finite-component-system case.
Quantum Physics
no code implementations • 2 Jun 2020 • Ying Hu, Hanqing Jin, Xun Yu Zhou
We study portfolio selection in a complete continuous-time market where the preference is dictated by the rank-dependent utility.
no code implementations • 3 Dec 2019 • Ying Hu
Lastly, we prove that given any $\mathbb{Q}$-homology solid torus, the set of slopes for which the corresponding Dehn fillings admit a taut foliation transverse to the core with zero Euler class is nowhere dense in $\mathbb{R}\cup \{\frac{1}{0}\}$.
Geometric Topology 57M50, 57M25, 57R30, 20F60