Search Results for author:
Found 18 papers, 9 papers with code
COPNER: Contrastive Learning with Prompt Guiding for Few-shot Named Entity Recognition
Second, the referents may be far from representing corresponding entity classes due to the label scarcity in the few-shot setting.
Contrasformer: A Brain Network Contrastive Transformer for Neurodegenerative Condition Identification
It generates a prior-knowledge-enhanced contrast graph to address the distribution shifts across sub-populations by a two-stream attention mechanism.
Has Multimodal Learning Delivered Universal Intelligence in Healthcare? A Comprehensive Survey
The rapid development of artificial intelligence has constantly reshaped the field of intelligent healthcare and medicine.
Language Modeling on Tabular Data: A Survey of Foundations, Techniques and Evolution
This paper fills this gap by providing a systematic review of the development of language modeling for tabular data, encompassing: (1) a categorization of different tabular data structures and data types; (2) a review of key datasets used in model training and tasks used for evaluation; (3) a summary of modeling techniques including widely-adopted data processing methods, popular architectures, and training objectives; (4) the evolution from adapting traditional Pre-training/Pre-trained language models to the utilization of large language models; (5) an identification of persistent challenges and potential future research directions in language modeling for tabular data analysis.
Unsupervised Image Prior via Prompt Learning and CLIP Semantic Guidance for Low-Light Image Enhancement
Currently, low-light conditions present a significant challenge for machine cognition.
DressCode: Autoregressively Sewing and Generating Garments from Text Guidance
We first introduce SewingGPT, a GPT-based architecture integrating cross-attention with text-conditioned embedding to generate sewing patterns with text guidance.
A Survey on Semantic Processing Techniques
We connect the surveyed tasks with downstream applications because this may inspire future scholars to fuse these low-level semantic processing tasks with high-level natural language processing tasks.
A Survey of Large Language Models for Healthcare: from Data, Technology, and Applications to Accountability and Ethics
Secondly, we conduct a comparison between the previous PLMs and the latest LLMs, as well as comparing various LLMs with each other.
Relightable Neural Human Assets from Multi-view Gradient Illuminations
UltraStage will be publicly available to the community to stimulate significant future developments in various human modeling and rendering tasks.
Learning Interpretable Decision Rule Sets: A Submodular Optimization Approach
The learning problem is framed as a subset selection task in which a subset of all possible rules needs to be selected to form an accurate and interpretable rule set.
GenISP: Neural ISP for Low-Light Machine Cognition
We propose to improve generalization to unseen camera sensors by implementing a minimal neural ISP pipeline for machine cognition, named GenISP, that explicitly incorporates Color Space Transformation to a device-independent color space.
NetRCA: An Effective Network Fault Cause Localization Algorithm
Localizing the root cause of network faults is crucial to network operation and maintenance.
Portfolio analysis with mean-CVaR and mean-CVaR-skewness criteria based on mean-variance mixture models
In this note, we give approximate closed form expressions for VaR and CVaR of portfolios of returns with NMVM distributions.
A note on closed-form spread option valuation under log-normal models
In the papers Carmona and Durrleman [7] and Bjerksund and Stensland [1], closed form approximations for spread call option prices were studied under the log normal models.
The Detection of Thoracic Abnormalities ChestX-Det10 Challenge Results
The detection of thoracic abnormalities challenge is organized by the Deepwise AI Lab.
RobustPeriod: Time-Frequency Mining for Robust Multiple Periodicity Detection
Periodicity detection is a crucial step in time series tasks, including monitoring and forecasting of metrics in many areas, such as IoT applications and self-driving database management system.
Extracting Kinship from Obituary to Enhance Electronic Health Records for Genetic Research
Claims database and electronic health records database do not usually capture kinship or family relationship information, which is imperative for genetic research.
