Search Results for author: Xin Su

Found 22 papers, 4 papers with code

A Comparison of Strategies for Source-Free Domain Adaptation

1 code implementation ACL 2022 Xin Su, Yiyun Zhao, Steven Bethard

Data sharing restrictions are common in NLP, especially in the clinical domain, but there is limited research on adapting models to new domains without access to the original training data, a setting known as source-free domain adaptation.

Active Learning Data Augmentation +1

Task Understanding from Confusing Multi-task Data

no code implementations ICML 2020 Xin Su, Yizhou Jiang, Shangqi Guo, Feng Chen

Beyond machine learning's success in the specific tasks, research for learning multiple tasks simultaneously is referred to as multi-task learning.

Multi-Task Learning

Source-free Domain Adaptive Object Detection in Remote Sensing Images

no code implementations31 Jan 2024 Weixing Liu, Jun Liu, Xin Su, Han Nie, Bin Luo

To address this challenge, we propose a practical source-free object detection (SFOD) setting for RS images, which aims to perform target domain adaptation using only the source pre-trained model.

Domain Adaptation object-detection +1

Remote Sensing ChatGPT: Solving Remote Sensing Tasks with ChatGPT and Visual Models

1 code implementation17 Jan 2024 HaoNan Guo, Xin Su, Chen Wu, Bo Du, Liangpei Zhang, Deren Li

Recently, the flourishing large language models(LLM), especially ChatGPT, have shown exceptional performance in language understanding, reasoning, and interaction, attracting users and researchers from multiple fields and domains.

Semi-Structured Chain-of-Thought: Integrating Multiple Sources of Knowledge for Improved Language Model Reasoning

no code implementations14 Nov 2023 Xin Su, Tiep Le, Steven Bethard, Phillip Howard

An important open question pertaining to the use of large language models for knowledge-intensive tasks is how to effectively integrate knowledge from three sources: the model's parametric memory, external structured knowledge, and external unstructured knowledge.

Knowledge Graphs Language Modelling +2

Fusing Temporal Graphs into Transformers for Time-Sensitive Question Answering

no code implementations30 Oct 2023 Xin Su, Phillip Howard, Nagib Hakim, Steven Bethard

Answering time-sensitive questions from long documents requires temporal reasoning over the times in questions and documents.

Question Answering Temporal Information Extraction

SAAN: Similarity-aware attention flow network for change detection with VHR remote sensing images

no code implementations28 Aug 2023 HaoNan Guo, Xin Su, Chen Wu, Bo Du, Liangpei Zhang

These CD methods, however, still perform far from satisfactorily as we observe that 1) deep encoder layers focus on irrelevant background regions and 2) the models' confidence in the change regions is inconsistent at different decoder stages.

Change Detection Earth Observation

Building-road Collaborative Extraction from Remotely Sensed Images via Cross-Interaction

no code implementations23 Jul 2023 HaoNan Guo, Xin Su, Chen Wu, Bo Du, Liangpei Zhang

Compared with many existing methods that train each task individually, the proposed collaborative extraction method can utilize the complementary advantages between buildings and roads by the proposed inter-task and inter-scale feature interactions, and automatically select the optimal reception field for different tasks.

Expediting Building Footprint Segmentation from High-resolution Remote Sensing Images via progressive lenient supervision

1 code implementation23 Jul 2023 HaoNan Guo, Bo Du, Chen Wu, Xin Su, Liangpei Zhang

The efficacy of building footprint segmentation from remotely sensed images has been hindered by model transfer effectiveness.

Segmentation

A optimization framework for herbal prescription planning based on deep reinforcement learning

no code implementations25 Apr 2023 Kuo Yang, Zecong Yu, Xin Su, Xiong He, Ning Wang, Qiguang Zheng, Feidie Yu, Zhuang Liu, Tiancai Wen, Xuezhong Zhou

We constructed a high-quality benchmark dataset for sequential diagnosis and treatment of diabetes and evaluated PrescDRL against this benchmark.

reinforcement-learning Sequential Diagnosis

Subjective Learning for Open-Ended Data

no code implementations27 Aug 2021 Tianren Zhang, Yizhou Jiang, Xin Su, Shangqi Guo, Feng Chen

In this paper, we present a novel supervised learning framework of learning from open-ended data, which is modeled as data implicitly sampled from multiple domains with the data in each domain obeying a domain-specific target function.

The University of Arizona at SemEval-2021 Task 10: Applying Self-training, Active Learning and Data Augmentation to Source-free Domain Adaptation

no code implementations SEMEVAL 2021 Xin Su, Yiyun Zhao, Steven Bethard

This paper describes our systems for negation detection and time expression recognition in SemEval 2021 Task 10, Source-Free Domain Adaptation for Semantic Processing.

Active Learning Data Augmentation +3

Classifying Long Clinical Documents with Pre-trained Transformers

no code implementations14 May 2021 Xin Su, Timothy Miller, Xiyu Ding, Majid Afshar, Dmitriy Dligach

Automatic phenotyping is a task of identifying cohorts of patients that match a predefined set of criteria.

Sentence

Performance Comparison between Reconfigurable Intelligent Surface and Relays: Theoretical Methods and a Perspective from Operator

no code implementations28 Jan 2021 Qi Gu, Dan Wu, Xin Su, Jing Jin, Yifei Yuan, Jiangzhou Wang

On the other hand, a relay node in a traditional relay network has to be active, which indicates that it will consume energy when it is relaying the signal or information between the source and destination nodes.

Information Theory Information Theory

Object Detection based on OcSaFPN in Aerial Images with Noise

no code implementations18 Dec 2020 Chengyuan Li, Jun Liu, Hailong Hong, Wenju Mao, Chenjie Wang, Chudi Hu, Xin Su, Bin Luo

On the basis of this, a novel octave convolution-based semantic attention feature pyramid network (OcSaFPN) is proposed to get higher accuracy in object detection with noise.

Attribute Denoising +2

DymSLAM:4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation

no code implementations10 Mar 2020 Chenjie Wang, Bin Luo, Yun Zhang, Qing Zhao, Lu Yin, Wei Wang, Xin Su, Yajun Wang, Chengyuan Li

The only input of DymSLAM is stereo video, and its output includes a dense map of the static environment, 3D model of the moving objects and the trajectories of the camera and the moving objects.

Motion Segmentation

Cloud Removal with Fusion of High Resolution Optical and SAR Images Using Generative Adversarial Networks

no code implementations MDPI Remote Sensing 2020 Jianhao Gao, Qiangqiang Yuan, Jie Li, Hai Zhang, Xin Su

The approach can be roughly divided into two steps: in the first step, a specially designed convolutional neural network (CNN) translates the synthetic aperture radar (SAR) images into simulated optical images in an object-to-object manner; in the second step, the simulated optical image, together with the SAR image and the optical image corrupted by clouds, is fused to reconstruct the corrupted area by a generative adversarial network (GAN) with a particular loss function.

Cloud Removal Earth Observation +2

Subjective Reinforcement Learning for Open Complex Environments

no code implementations25 Sep 2019 Zhile Yang*, Haichuan Gao*, Xin Su, Shangqi Guo, Feng Chen

In this paper, Subjective Reinforcement Learning Framework is proposed to state the problem from a broader and systematic view, and subjective policy is proposed to represent existing related algorithms in general.

reinforcement-learning Reinforcement Learning (RL)

Subjectivity Learning Theory towards Artificial General Intelligence

no code implementations9 Sep 2019 Xin Su, Shangqi Guo, Feng Chen

The construction of artificial general intelligence (AGI) was a long-term goal of AI research aiming to deal with the complex data in the real world and make reasonable judgments in various cases like a human.

Learning Theory

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