Search Results for author:
Found 7 papers, 4 papers with code
ChatASU: Evoking LLM's Reflexion to Truly Understand Aspect Sentiment in Dialogues
Specifically, this TSA treats the ACR task as an auxiliary task to boost the performance of the primary ASU task, and further integrates trusted learning into reflexion mechanisms to alleviate the LLMs-intrinsic factual hallucination problem in TSA.
Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform
We use this platform to demonstrate our research and development results on privacy preserving machine learning algorithms.
BioNavi-NP: Biosynthesis Navigator for Natural Products
Nature, a synthetic master, creates more than 300, 000 natural products (NPs) which are the major constituents of FDA-proved drugs owing to the vast chemical space of NPs.
Transformer-based Conditional Variational Autoencoder for Controllable Story Generation
In this paper, we advocate to revive latent variable modeling, essentially the power of representation learning, in the era of Transformers to enhance controllability without hurting state-of-the-art generation effectiveness.
Outline to Story: Fine-grained Controllable Story Generation from Cascaded Events
Our paper is among the first ones by our knowledge to propose a model and to create datasets for the task of "outline to story".
Ontology-based systematic classification and analysis of coronaviruses, hosts, and host-coronavirus interactions towards deep understanding of COVID-19
We hypothesized that ontology can be used as an integrative platform to classify and analyze HCI and disease outcomes.
Other Quantitative Biology
Reconstruction of Simulation-Based Physical Field by Reconstruction Neural Network Method
In such a framework, a reconstruction neural network (ReConNN) model designed for simulation-based physical field's reconstruction is proposed.
