Search Results for author: Zihao Lin

Found 15 papers, 6 papers with code

Persona-SQ: A Personalized Suggested Question Generation Framework For Real-world Documents

1 code implementation17 Dec 2024 Zihao Lin, Zichao Wang, Yuanting Pan, Varun Manjunatha, Ryan Rossi, Angela Lau, Lifu Huang, Tong Sun

Suggested questions (SQs) provide an effective initial interface for users to engage with their documents in AI-powered reading applications.

Question Generation Question-Generation

Rethinking the Uncertainty: A Critical Review and Analysis in the Era of Large Language Models

no code implementations26 Oct 2024 Mohammad Beigi, Sijia Wang, Ying Shen, Zihao Lin, Adithya Kulkarni, Jianfeng He, Feng Chen, Ming Jin, Jin-Hee Cho, Dawei Zhou, Chang-Tien Lu, Lifu Huang

In recent years, Large Language Models (LLMs) have become fundamental to a broad spectrum of artificial intelligence applications.

MMedAgent: Learning to Use Medical Tools with Multi-modal Agent

1 code implementation2 Jul 2024 Binxu Li, Tiankai Yan, Yuanting Pan, Jie Luo, Ruiyang Ji, Jiayuan Ding, Zhe Xu, Shilong Liu, Haoyu Dong, Zihao Lin, Yixin Wang

We curate an instruction-tuning dataset comprising six medical tools solving seven tasks across five modalities, enabling the agent to choose the most suitable tools for a given task.

InternalInspector $I^2$: Robust Confidence Estimation in LLMs through Internal States

no code implementations17 Jun 2024 Mohammad Beigi, Ying Shen, Runing Yang, Zihao Lin, Qifan Wang, Ankith Mohan, Jianfeng He, Ming Jin, Chang-Tien Lu, Lifu Huang

Despite their vast capabilities, Large Language Models (LLMs) often struggle with generating reliable outputs, frequently producing high-confidence inaccuracies known as hallucinations.

Benchmarking Contrastive Learning +4

Efficient Federated Prompt Tuning for Black-box Large Pre-trained Models

no code implementations4 Oct 2023 Zihao Lin, Yan Sun, Yifan Shi, Xueqian Wang, Lifu Huang, Li Shen, DaCheng Tao

With the blowout development of pre-trained models (PTMs), the efficient tuning of these models for diverse downstream applications has emerged as a pivotal research concern.

Rethinking Medical Report Generation: Disease Revealing Enhancement with Knowledge Graph

1 code implementation24 Jul 2023 Yixin Wang, Zihao Lin, Haoyu Dong

Knowledge Graph (KG) plays a crucial role in Medical Report Generation (MRG) because it reveals the relations among diseases and thus can be utilized to guide the generation process.

Medical Report Generation

Towards More Suitable Personalization in Federated Learning via Decentralized Partial Model Training

no code implementations24 May 2023 Yifan Shi, Yingqi Liu, Yan Sun, Zihao Lin, Li Shen, Xueqian Wang, DaCheng Tao

Personalized federated learning (PFL) aims to produce the greatest personalized model for each client to face an insurmountable problem--data heterogeneity in real FL systems.

Personalized Federated Learning

Spatial Attention and Syntax Rule Enhanced Tree Decoder for Offine Handwritten Mathematical Expression Recognition

no code implementations13 Mar 2023 Zihao Lin, Jinrong Li, Fan Yang, Shuangping Huang, Xu Yang, Jianmin Lin, Ming Yang

In this paper, we propose a novel model called Spatial Attention and Syntax Rule Enhanced Tree Decoder (SS-TD), which is equipped with spatial attention mechanism to alleviate the prediction error of tree structure and use syntax masks (obtained from the transformation of syntax rules) to constrain the occurrence of ungrammatical mathematical expression.

Decoder

Learning-based Inverse Rendering of Complex Indoor Scenes with Differentiable Monte Carlo Raytracing

no code implementations6 Nov 2022 Jingsen Zhu, Fujun Luan, Yuchi Huo, Zihao Lin, Zhihua Zhong, Dianbing Xi, Jiaxiang Zheng, Rui Tang, Hujun Bao, Rui Wang

Indoor scenes typically exhibit complex, spatially-varying appearance from global illumination, making inverse rendering a challenging ill-posed problem.

Inverse Rendering

ACN: Adversarial Co-training Network for Brain Tumor Segmentation with Missing Modalities

2 code implementations28 Jun 2021 Yixin Wang, Yang Zhang, Yang Liu, Zihao Lin, Jiang Tian, Cheng Zhong, Zhongchao shi, Jianping Fan, Zhiqiang He

Specifically, ACN adopts a novel co-training network, which enables a coupled learning process for both full modality and missing modality to supplement each other's domain and feature representations, and more importantly, to recover the `missing' information of absent modalities.

Brain Tumor Segmentation Transfer Learning +1

Trust It or Not: Confidence-Guided Automatic Radiology Report Generation

no code implementations21 Jun 2021 Yixin Wang, Zihao Lin, Zhe Xu, Haoyu Dong, Jiang Tian, Jie Luo, Zhongchao shi, Yang Zhang, Jianping Fan, Zhiqiang He

Experimental results have demonstrated that the proposed method for model uncertainty characterization and estimation can produce more reliable confidence scores for radiology report generation, and the modified loss function, which takes into account the uncertainties, leads to better model performance on two public radiology report datasets.

Decision Making Image Captioning +2

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