Search Results for author:
Found 9 papers, 5 papers with code
SPT: Spectral Transformer for Red Giant Stars Age and Mass Estimation
The age and mass of red giants are essential for understanding the structure and evolution of the Milky Way.
Image Restoration with Point Spread Function Regularization and Active Learning
Large-scale astronomical surveys can capture numerous images of celestial objects, including galaxies and nebulae.
Bridging Code Semantic and LLMs: Semantic Chain-of-Thought Prompting for Code Generation
Meanwhile, while traditional techniques leveraging such semantic information require complex static or dynamic code analysis to obtain features such as data flow and control flow, SeCoT demonstrates that this process can be fully automated via the intrinsic capabilities of LLMs (i. e., in-context learning), while being generalizable and applicable to challenging domains.
At Which Training Stage Does Code Data Help LLMs Reasoning?
Inspired by the great success of code data in training LLMs, we naturally wonder at which training stage introducing code data can really help LLMs reasoning.
One Adapter for All Programming Languages? Adapter Tuning for Code Search and Summarization
To alleviate the potentially catastrophic forgetting issue in multilingual models, we fix all pre-trained model parameters, insert the parameter-efficient structure adapter, and fine-tune it.
ProxyFormer: Proxy Alignment Assisted Point Cloud Completion with Missing Part Sensitive Transformer
Specifically, we fuse information into point proxy via feature and position extractor, and generate features for missing point proxies from the features of existing point proxies.
Bridging Pre-trained Models and Downstream Tasks for Source Code Understanding
In this paper, we propose an approach to bridge pre-trained models and code-related tasks.
An Attention-Fused Network for Semantic Segmentation of Very-High-Resolution Remote Sensing Imagery
Semantic segmentation is an essential part of deep learning.
deGraphCS: Embedding Variable-based Flow Graph for Neural Code Search
With the rapid increase in the amount of public code repositories, developers maintain a great desire to retrieve precise code snippets by using natural language.
