6 papers
Efficient Quantification of Time-Series Prediction Error: Optimal Selection Conformal Prediction
Boyu Pang, Kostas Margellos
Designing effective score functions in Conformal Prediction (CP) for time-series data remains challenging due to conservativeness and/or computational inefficiency. We propose Opti…
Efficient Long-context Language Model Training by Core Attention Disaggregation
Yonghao Zhuang, Junda Chen, Bo Pang +6
We present core attention disaggregation (CAD), a technique that improves long-context large language model training by decoupling the core attention computation, softmax(QK^T)V, f…
FEVO: Financial Knowledge Expansion and Reasoning Evolution for Large Language Models
Bo Pang, Yalu Ouyang, Hangfei Xu +6
Advancements in reasoning for large language models (LLMs) have lead to significant performance improvements for LLMs in various fields such as mathematics and programming. However…
Temporal Consistency Constrained Transferable Adversarial Attacks with Background Mixup for Action Recognition
Ping Li, Jianan Ni, Bo Pang
Action recognition models using deep learning are vulnerable to adversarial examples, which are transferable across other models trained on the same data modality. Existing transfe…
Let AI Read First: Enhancing Reading Abilities for Individuals with Dyslexia through Artificial Intelligence
Sihang Zhao, Shoucong Carol Xiong, Bo Pang +2
Dyslexia, a neurological condition affecting approximately 12% of the global population, presents significant challenges to reading ability and quality of life. Existing assistive…
Fire-Image-DenseNet (FIDN) for predicting wildfire burnt area using remote sensing data
Bo Pang, Sibo Cheng, Yuhan Huang +5
Predicting the extent of massive wildfires once ignited is essential to reduce the subsequent socioeconomic losses and environmental damage, but challenging because of the complexi…