6 papers
Quant Convergence: Bridging Classical Value Investing and Modern Factor Models for Systematic Equity Selection
Augusto Eiji Yamazaki, Hugo Garrido-Lestache Belinchon
Modern finance relies heavily on complex machine learning models to find patterns in the stock market. However, as these AI models get more complicated, they often memorize short-t…
Multimodal Image Colorization: Quantifying the Impact of Text-Conditioned Guidance on Grayscale-to-Color Translation
Colten Reissmann, Hugo Garrido-Lestache Belinchon
Grayscale images are commonly found in historical photography restoration, medical imaging, and artistic media. However, automatically applying color to these images remains a sign…
The Effect of Text Chunk Size on Retrieval-Augmented Generation Performance
German Garrido-Lestache Belinchon, Hugo Garrido-Lestache Belinchon
Retrieval-Augmented Generation (RAG) systems have emerged as a powerful process for allowing large language models (LLMs) to retrieve relevant information to use as source material…
Source-Aware Reranking for Retrieval-Augmented Generation: A Reliability Prior Approach
Yuktha Tata Koganti, Hugo Garrido-Lestache Belinchon
Standard Retrieval-Augmented Generation pipelines rank retrieved documents by semantic similarity alone, without accounting for source provenance or credibility. This work evaluate…
Scribby: A Multi-Level LLM Framework for Semantic Video Analysis
Julian Abelarde, Hugo Garrido-Lestache Belinchon
As video content continues to expand across educational platforms, recorded lectures, and live-streamed entertainment, the need for efficient and structured analysis of long-form f…
Synthesizing Audio from Silent Video using Sequence to Sequence Modeling
Hugo Garrido-Lestache Belinchon, Helina Mulugeta, Adam Haile
Generating audio from a video's visual context has multiple practical applications in improving how we interact with audio-visual media - for example, enhancing CCTV footage analys…