1 code implementation • 8 Apr 2024 • Shibo Hao, Yi Gu, Haotian Luo, Tianyang Liu, Xiyan Shao, Xinyuan Wang, Shuhua Xie, Haodi Ma, Adithya Samavedhi, Qiyue Gao, Zhen Wang, Zhiting Hu
(2) We develop LLM Reasoners, a library for standardized modular implementation of existing and new reasoning algorithms, under a unified formulation of the search, reward, and world model components.
1 code implementation • 12 Feb 2024 • Yueqin Yin, Zhendong Wang, Yi Gu, Hai Huang, Weizhu Chen, Mingyuan Zhou
In the field of large language models (LLMs), aligning models with the diverse preferences of users is a critical challenge.
no code implementations • 6 Feb 2024 • Chao Chen, Kai Liu, Ze Chen, Yi Gu, Yue Wu, Mingyuan Tao, Zhihang Fu, Jieping Ye
Knowledge hallucination have raised widespread concerns for the security and reliability of deployed LLMs.
1 code implementation • 30 Dec 2023 • Masachika Masuda, Mazen Soufi, Yoshito Otake, Keisuke Uemura, Sotaro Kono, Kazuma Takashima, Hidetoshi Hamada, Yi Gu, Masaki Takao, Seiji Okada, Nobuhiko Sugano, Yoshinobu Sato
However, as the classification is subjective, we aimed to develop an automated approach to classify the disease severity based on the two grades using digitally-reconstructed radiographs (DRRs) from CT images.
1 code implementation • 11 Dec 2023 • Zhengzhong Liu, Aurick Qiao, Willie Neiswanger, Hongyi Wang, Bowen Tan, Tianhua Tao, Junbo Li, Yuqi Wang, Suqi Sun, Omkar Pangarkar, Richard Fan, Yi Gu, Victor Miller, Yonghao Zhuang, Guowei He, Haonan Li, Fajri Koto, Liping Tang, Nikhil Ranjan, Zhiqiang Shen, Xuguang Ren, Roberto Iriondo, Cun Mu, Zhiting Hu, Mark Schulze, Preslav Nakov, Tim Baldwin, Eric P. Xing
The recent surge in open-source Large Language Models (LLMs), such as LLaMA, Falcon, and Mistral, provides diverse options for AI practitioners and researchers.
no code implementations • 1 Aug 2023 • Yubao Zhang, Xin Chen, Yi Gu, Zhicheng Li, Wu Kai
On the grid side, load fluctuations and renewable energy consumption are considered, while on the EVA side, energy constraints and charging costs are considered.
1 code implementation • 21 Jul 2023 • Yi Gu, Yoshito Otake, Keisuke Uemura, Mazen Soufi, Masaki Takao, Hugues Talbot, Seiji Okada, Nobuhiko Sugano, Yoshinobu Sato
The proposed method achieved high accuracy in BMD estimation, where Pearson correlation coefficients of 0. 880 and 0. 920 were observed for DXA-measured BMD and QCT-measured BMD estimation tasks, respectively, and the root mean square of the coefficient of variation values were 3. 27 to 3. 79% for four measurements with different poses.
2 code implementations • ICCV 2023 • Chonghao Sima, Wenwen Tong, Tai Wang, Li Chen, Silei Wu, Hanming Deng, Yi Gu, Lewei Lu, Ping Luo, Dahua Lin, Hongyang Li
Human driver can easily describe the complex traffic scene by visual system.
no code implementations • 31 May 2023 • Yi Gu, Yoshito Otake, Keisuke Uemura, Masaki Takao, Mazen Soufi, Yuta Hiasa, Hugues Talbot, Seiji Okata, Nobuhiko Sugano, Yoshinobu Sato
We propose a method (named MSKdeX) to estimate fine-grained muscle properties from a plain X-ray image, a low-cost, low-radiation, and highly accessible imaging modality, through musculoskeletal decomposition leveraging fine-grained segmentation in CT. We train a multi-channel quantitative image translation model to decompose an X-ray image into projections of CT of individual muscles to infer the lean muscle mass and muscle volume.
3 code implementations • 24 May 2023 • Shibo Hao, Yi Gu, Haodi Ma, Joshua Jiahua Hong, Zhen Wang, Daisy Zhe Wang, Zhiting Hu
RAP on LLAMA-33B surpasses CoT on GPT-4 with 33% relative improvement in a plan generation setting.
no code implementations • 23 May 2023 • Yuming Huang, Yi Gu, Chengzhong Xu, Hui Kong
Specifically, semantic segmentation is achieved by a new mask-range transformer network in a mask-classfication paradigm.
1 code implementation • NeurIPS 2023 • Jiannan Xiang, Tianhua Tao, Yi Gu, Tianmin Shu, ZiRui Wang, Zichao Yang, Zhiting Hu
While large language models (LMs) have shown remarkable capabilities across numerous tasks, they often struggle with simple reasoning and planning in physical environments, such as understanding object permanence or planning household activities.
1 code implementation • 1 Dec 2022 • Nan Jiang, Yi Gu, Yexiang Xue
Contrastive divergence is then applied to separate these samples from those in the training set.
1 code implementation • 18 Oct 2022 • Mo Yu, Yi Gu, Xiaoxiao Guo, Yufei Feng, Xiaodan Zhu, Michael Greenspan, Murray Campbell, Chuang Gan
Hence, in order to achieve higher performance on our tasks, models need to effectively utilize such functional knowledge to infer the outcomes of actions, rather than relying solely on memorizing facts.
no code implementations • 15 Oct 2022 • Yi Gu, Shunyu Yao, Chuang Gan, Joshua B. Tenenbaum, Mo Yu
Text games present opportunities for natural language understanding (NLU) methods to tackle reinforcement learning (RL) challenges.
1 code implementation • 7 Jul 2022 • Yi Gu, Yoshito Otake, Keisuke Uemura, Mazen Soufi, Masaki Takao, Nobuhiko Sugano, Yoshinobu Sato
We propose a method for estimating the bone mineral density (BMD) from a plain x-ray image.
no code implementations • CVPR 2022 • Chuang Gan, Yi Gu, Siyuan Zhou, Jeremy Schwartz, Seth Alter, James Traer, Dan Gutfreund, Joshua B. Tenenbaum, Josh Mcdermott, Antonio Torralba
The way an object looks and sounds provide complementary reflections of its physical properties.
no code implementations • 24 Jun 2022 • Yi Gu, Yuming Huang, Chengzhong Xu, Hui Kong
To answer this question, we propose a unified mask-classification model, MaskRange, for the range-view based LiDAR semantic and panoptic segmentation.
no code implementations • 21 Jun 2022 • Yi Gu, Chao Han, Yuhan Chen, Shenggang Liu, Xinwei Wang
A greedy initialization-based resampling particle swarm optimization (GI-RPSO) algorithm is proposed to solve the model.
no code implementations • 2 Mar 2022 • Yi Gu, Hongzhi Cheng, Kafeng Wang, Dejing Dou, Chengzhong Xu, Hui Kong
In this paper, we propose a learning-based moving-object tracking method utilizing our newly developed LiDAR sensor, Frequency Modulated Continuous Wave (FMCW) LiDAR.
no code implementations • 29 Sep 2021 • Jingwei Liu, Yi Gu, Shentong Mo, Zhun Sun, Shumin Han, Jiafeng Guo, Xueqi Cheng
In self-supervised learning frameworks, deep networks are optimized to align different views of an instance that contains the similar visual semantic information.
no code implementations • 16 Dec 2020 • Yi Gu
Let $(M, g)$ be a compact Riemann surface with no boundary and $u=(u_1, u_2)$ be a solution of the following singular Liouville system: $$\Delta_g u_i+\sum_{j=1}^2 a_{ij}\rho_j(\frac{h_je^{u_j}}{\int_M h_je^{u_j}dV_g}-1)=\sum_{l=1}^{N}4\pi\gamma_l(\delta_{p_l}-1), $$ where $h_1, h_2$ are positive smooth functions, $p_1,\cdots, p_N$ are distinct points on $M$, $\delta_{p_l}$ are Dirac masses, $\rho=(\rho_1,\rho_2)(\rho_i\geq 0)$ and $(\gamma_1,\cdots,\gamma_N)(\gamma_l > -1)$ are constant vectors.
Analysis of PDEs 35A01, 35B44, 35B45
no code implementations • 27 Nov 2020 • Yi Gu, Jie Li, Yuting Gao, Ruoxin Chen, Chentao Wu, Feiyang Cai, Chao Wang, Zirui Zhang
Neural networks are susceptible to catastrophic forgetting.
no code implementations • 11 Nov 2020 • Yi Gu, Yuting Gao, Jie Li, Chentao Wu, Weijia Jia
Due to the uncertainty in the distortion variation, restoring distorted images caused by liquify filter is a challenging task.
no code implementations • 27 May 2020 • Zichao Wang, Yi Gu, Andrew Lan, Richard Baraniuk
We propose VarFA, a variational inference factor analysis framework that extends existing factor analysis models for educational data mining to efficiently output uncertainty estimation in the model's estimated factors.
no code implementations • 14 Mar 2020 • Chao Han, Yi Gu, Guohua Wu, Xinwei Wang
We are the first to address multiple agile EOSs scheduling problem under cloud coverage uncertainty where the objective aims to maximize the entire observation profit.
no code implementations • 2 Mar 2017 • Yanyan Geng, Guohui Zhang, Weizhi Li, Yi Gu, Ru-Ze Liang, Gaoyuan Liang, Jingbin Wang, Yanbin Wu, Nitin Patil, Jing-Yan Wang
In this paper, we study the problem of image tag complete and proposed a novel method for this problem based on a popular image representation method, convolutional neural network (CNN).
1 code implementation • NeurIPS 2016 • Noah J. Apthorpe, Alexander J. Riordan, Rob E. Aguilar, Jan Homann, Yi Gu, David W. Tank, H. Sebastian Seung
Calcium imaging is an important technique for monitoring the activity of thousands of neurons simultaneously.
no code implementations • 22 Apr 2016 • Ru-Ze Liang, Lihui Shi, Haoxiang Wang, Jiandong Meng, Jim Jing-Yan Wang, Qingquan Sun, Yi Gu
To fill this gap, in this paper, we propose a novel similarity learning method to maximize the top precision measure.