3 papers
cs.LG2026
Rethinking Layer Relevance in Large Language Models Beyond Cosine Similarity
Cristian Hinostroza, Rodrigo Toro Icarte, Christ Devia +4
Large language models (LLMs) have revolutionized natural language processing. Understanding their internal mechanisms is crucial for developing more interpretable and optimized arc…
cs.CL2023
Large Language Models are biased to overestimate profoundness
Eugenio Herrera-Berg, Tomás Vergara Browne, Pablo León-Villagrá +2
Recent advancements in natural language processing by large language models (LLMs), such as GPT-4, have been suggested to approach Artificial General Intelligence. And yet, it is s…
cs.CV2023
Targeted Image Data Augmentation Increases Basic Skills Captioning Robustness
Valentin Barriere, Felipe del Rio, Andres Carvallo De Ferari +3
Artificial neural networks typically struggle in generalizing to out-of-context examples. One reason for this limitation is caused by having datasets that incorporate only partial…