3 papers
cs.CL2025
Interpretable and Robust Dialogue State Tracking via Natural Language Summarization with LLMs
Rafael Carranza, Mateo Alejandro Rojas
This paper introduces a novel approach to Dialogue State Tracking (DST) that leverages Large Language Models (LLMs) to generate natural language descriptions of dialogue states, mo…
cs.CL2024
Align, Generate, Learn: A Novel Closed-Loop Framework for Cross-Lingual In-Context Learning
Mateo Alejandro Rojas, Rafael Carranza
Cross-lingual in-context learning (XICL) has emerged as a transformative paradigm for leveraging large language models (LLMs) to tackle multilingual tasks, especially for low-resou…
cs.CV2024
Enhancing Scientific Figure Captioning Through Cross-modal Learning
Mateo Alejandro Rojas, Rafael Carranza
Scientific charts are essential tools for effectively communicating research findings, serving as a vital medium for conveying information and revealing data patterns. With the rap…