4 citations · 6 across the 4 of their papers we have counts for
4 papers
Demystifying Low-Rank Knowledge Distillation in Large Language Models: Convergence, Generalization, and Information-Theoretic Guarantees
Alberlucia Rafael Soarez, Daniel Kim, Mariana Costa +1
Knowledge distillation has emerged as a powerful technique for compressing large language models (LLMs) into efficient, deployable architectures while preserving their advanced cap…
FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation
Dannong Wang, Daniel Kim, Bo Jin +4
Finetuned large language models (LLMs) have shown remarkable performance in financial tasks, such as sentiment analysis and information retrieval. Due to privacy concerns, finetuni…
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Jimin Huang, Mengxi Xiao, Dong Li +41
Financial LLMs hold promise for advancing financial tasks and domain-specific applications. However, they are limited by scarce corpora, weak multimodal capabilities, and narrow ev…
Pegasus-v1 Technical Report
Raehyuk Jung, Hyojun Go, Jaehyuk Yi +41
This technical report introduces Pegasus-1, a multimodal language model specialized in video content understanding and interaction through natural language. Pegasus-1 is designed t…