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Found 8 papers, 2 papers with code
Building the Directed Semantic Graph for Coherent Long Text Generation
These directed subgraphs are considered to well preserve extra but relevant content to the short input text, and then they are decoded by the employed pre-trained model to generate coherent long text.
Noisy Computing of the $\mathsf{OR}$ and $\mathsf{MAX}$ Functions
We consider the problem of computing a function of $n$ variables using noisy queries, where each query is incorrect with some fixed and known probability $p \in (0, 1/2)$.
An Effective Data Creation Pipeline to Generate High-quality Financial Instruction Data for Large Language Model
At the beginning era of large language model, it is quite critical to generate a high-quality financial dataset to fine-tune a large language model for financial related tasks.
FinVis-GPT: A Multimodal Large Language Model for Financial Chart Analysis
In this paper, we propose FinVis-GPT, a novel multimodal large language model (LLM) specifically designed for financial chart analysis.
On the Optimal Bounds for Noisy Computing
However, the upper and lower bounds do not match in terms of the dependence on $\delta$ and $p$.
PINNacle: A Comprehensive Benchmark of Physics-Informed Neural Networks for Solving PDEs
In addition to providing a standardized means of assessing performance, PINNacle also offers an in-depth analysis to guide future research, particularly in areas such as domain decomposition methods and loss reweighting for handling multi-scale problems and complex geometry.
Probing Negative Sampling Strategies to Learn GraphRepresentations via Unsupervised Contrastive Learning
Graph representation learning has long been an important yet challenging task for various real-world applications.
Generating Long Financial Report using Conditional Variational Autoencoders with Knowledge Distillation
Particularly, we choose Bi-GRU as the encoder and decoder component of CVAE, and learn the latent variable distribution from input news.
