Search Results for author: Fei Yu

Found 21 papers, 7 papers with code

Outcome-supervised Verifiers for Planning in Mathematical Reasoning

1 code implementation16 Nov 2023 Fei Yu, Anningzhe Gao, Benyou Wang

These findings offer a novel perspective on the role of outcome supervision in training verifiers for multi-step reasoning tasks and provide theoretical justification for its advantage in value estimation for planning.

GSM8K Mathematical Reasoning

Data-Centric Financial Large Language Models

no code implementations7 Oct 2023 Zhixuan Chu, Huaiyu Guo, Xinyuan Zhou, Yijia Wang, Fei Yu, Hong Chen, Wanqing Xu, Xin Lu, Qing Cui, Longfei Li, Jun Zhou, Sheng Li

Large language models (LLMs) show promise for natural language tasks but struggle when applied directly to complex domains like finance.

AceGPT, Localizing Large Language Models in Arabic

1 code implementation21 Sep 2023 Huang Huang, Fei Yu, Jianqing Zhu, Xuening Sun, Hao Cheng, Dingjie Song, Zhihong Chen, Abdulmohsen Alharthi, Bang An, Juncai He, Ziche Liu, Zhiyi Zhang, Junying Chen, Jianquan Li, Benyou Wang, Lian Zhang, Ruoyu Sun, Xiang Wan, Haizhou Li, Jinchao Xu

This paper is devoted to the development of a localized Large Language Model (LLM) specifically for Arabic, a language imbued with unique cultural characteristics inadequately addressed by current mainstream models.

Instruction Following Language Modelling +2

AGS: An Dataset and Taxonomy for Domestic Scene Sound Event Recognition

no code implementations30 Aug 2023 Nan Che, Chenrui Liu, Fei Yu

In particular, there is no public common data set for the research field of sound event recognition for the data set of the indoor environmental sound scene.

Stochastic Step-wise Feature Selection for Exponential Random Graph Models (ERGMs)

no code implementations24 Jul 2023 Helal El-Zaatari, Fei Yu, Michael R Kosorok

Statistical analysis of social networks provides valuable insights into complex network interactions across various scientific disciplines.

feature selection Variable Selection

MODA: Mapping-Once Audio-driven Portrait Animation with Dual Attentions

no code implementations ICCV 2023 Yunfei Liu, Lijian Lin, Fei Yu, Changyin Zhou, Yu Li

Audio-driven portrait animation aims to synthesize portrait videos that are conditioned by given audio.

HuatuoGPT, towards Taming Language Model to Be a Doctor

1 code implementation24 May 2023 Hongbo Zhang, Junying Chen, Feng Jiang, Fei Yu, Zhihong Chen, Jianquan Li, Guiming Chen, Xiangbo Wu, Zhiyi Zhang, Qingying Xiao, Xiang Wan, Benyou Wang, Haizhou Li

Experimental results demonstrate that HuatuoGPT achieves state-of-the-art results in performing medical consultation among open-source LLMs in GPT-4 evaluation, human evaluation, and medical benchmark datasets.

Language Modelling Large Language Model

Natural Language Reasoning, A Survey

1 code implementation26 Mar 2023 Fei Yu, Hongbo Zhang, Prayag Tiwari, Benyou Wang

This survey paper proposes a clearer view of natural language reasoning in the field of Natural Language Processing (NLP), both conceptually and practically.

Logical Reasoning Mathematical Reasoning +4

Accurate 3D Face Reconstruction with Facial Component Tokens

no code implementations ICCV 2023 Tianke Zhang, Xuangeng Chu, Yunfei Liu, Lijian Lin, Zhendong Yang, Zhengzhuo Xu, Chengkun Cao, Fei Yu, Changyin Zhou, Chun Yuan, Yu Li

However, the current deep learning-based methods face significant challenges in achieving accurate reconstruction with disentangled facial parameters and ensuring temporal stability in single-frame methods for 3D face tracking on video data.

3D Face Reconstruction

Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation

1 code implementation17 May 2022 Hexin Dong, ZiFan Chen, Mingze Yuan, Yutong Xie, Jie Zhao, Fei Yu, Bin Dong, Li Zhang

Therefore, we propose a method called region-aware metric learning (RAML), which first separates the regions of the images and generates region-aware features for further metric learning.

Few-Shot Learning Metric Learning +2

Unsupervised Domain Adaptation in Semantic Segmentation Based on Pixel Alignment and Self-Training

no code implementations29 Sep 2021 Hexin Dong, Fei Yu, Jie Zhao, Bin Dong, Li Zhang

This paper proposes an unsupervised cross-modality domain adaptation approach based on pixel alignment and self-training.

Segmentation Semantic Segmentation +1

Attentive Geo-Social Group Recommendation

no code implementations6 Nov 2019 Fei Yu, Feiyi Fan, Shouxu Jiang, Kaiping Zheng

In this paper, a novel group recommendation method, called attentive geo-social group recommendation, is proposed to recommend the target user with both activity locations and a group of users that may join the activities.

Decision Making

PGU-net+: Progressive Growing of U-net+ for Automated Cervical Nuclei Segmentation

1 code implementation4 Nov 2019 Jie Zhao, Lei Dai, Mo Zhang, Fei Yu, Meng Li, Hongfeng Li, Wenjia Wang, Li Zhang

The experimental results show that the PGU-net+ has superior accuracy than the previous state-of-the-art methods on cervical nuclei segmentation.


Multi-level Domain Adaptive learning for Cross-Domain Detection

no code implementations26 Jul 2019 Rongchang Xie, Fei Yu, Jiachao Wang, Yizhou Wang, Li Zhang

In recent years, object detection has shown impressive results using supervised deep learning, but it remains challenging in a cross-domain environment.

object-detection Object Detection

Annotation-Free Cardiac Vessel Segmentation via Knowledge Transfer from Retinal Images

no code implementations26 Jul 2019 Fei Yu, Jie Zhao, Yanjun Gong, Zhi Wang, Yuxi Li, Fan Yang, Bin Dong, Quanzheng Li, Li Zhang

Segmenting coronary arteries is challenging, as classic unsupervised methods fail to produce satisfactory results and modern supervised learning (deep learning) requires manual annotation which is often time-consuming and can some time be infeasible.

Transfer Learning

Differentially-Private Logistic Regression for Detecting Multiple-SNP Association in GWAS Databases

no code implementations30 Jul 2014 Fei Yu, Michal Rybar, Caroline Uhler, Stephen E. Fienberg

Following the publication of an attack on genome-wide association studies (GWAS) data proposed by Homer et al., considerable attention has been given to developing methods for releasing GWAS data in a privacy-preserving way.

Privacy Preserving regression

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