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Found 11 papers, 5 papers with code
Combining Cognitive and Generative AI for Self-explanation in Interactive AI Agents
The Virtual Experimental Research Assistant (VERA) is an inquiry-based learning environment that empowers a learner to build conceptual models of complex ecological systems and experiment with agent-based simulations of the models.
Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains
By integrating CoI-M with the rain-/detail-aware Contrastive learning, we develop CoIC, an innovative and potent algorithm tailored for training models on mixed datasets.
SimulFlow: Simultaneously Extracting Feature and Identifying Target for Unsupervised Video Object Segmentation
We evaluate our method on several benchmark datasets and achieve state-of-the-art results.
Improved Prognostic Prediction of Pancreatic Cancer Using Multi-Phase CT by Integrating Neural Distance and Texture-Aware Transformer
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer in which the tumor-vascular involvement greatly affects the resectability and, thus, overall survival of patients.
Utilizing Large Language Models for Natural Interface to Pharmacology Databases
The drug development process necessitates that pharmacologists undertake various tasks, such as reviewing literature, formulating hypotheses, designing experiments, and interpreting results.
A deep local attention network for pre-operative lymph node metastasis prediction in pancreatic cancer via multiphase CT imaging
Lymph node (LN) metastasis status is one of the most critical prognostic and cancer staging factors for patients with resectable pancreatic ductal adenocarcinoma (PDAC), or in general, for any types of solid malignant tumors.
Interactive Data Analysis with Next-step Natural Language Query Recommendation
Natural language interfaces (NLIs) provide users with a convenient way to interactively analyze data through natural language queries.
TRNR: Task-Driven Image Rain and Noise Removal with a Few Images Based on Patch Analysis
To alleviate the reliance of deep models on large labeled datasets, we propose the task-driven image rain and noise removal (TRNR) based on a patch analysis strategy.
ACNet: Approaching-and-Centralizing Network for Zero-Shot Sketch-Based Image Retrieval
The huge domain gap between sketches and photos and the highly abstract sketch representations pose challenges for sketch-based image retrieval (\underline{SBIR}).
Evaluating Generalization Ability of Convolutional Neural Networks and Capsule Networks for Image Classification via Top-2 Classification
In this paper, we propose a new image classification task called Top-2 classification to evaluate the generalization ability of CNNs and CapsNets.
Compositional Coding Capsule Network with K-Means Routing for Text Classification
Combined with our compositional weighted coding method and the routing algorithm, we design a neural network for text classification.
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Text Classification
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