18 citations · 29 across the 7 of their papers we have counts for
4 papers · 1 filter
SemiKong: Curating, Training, and Evaluating A Semiconductor Industry-Specific Large Language Model
Christopher Nguyen, William Nguyen, Atsushi Suzuki +10
Large Language Models (LLMs) have demonstrated the potential to address some issues within the semiconductor industry. However, they are often general-purpose models that lack the…
DANA: Domain-Aware Neurosymbolic Agents for Consistency and Accuracy
Vinh Luong, Sang Dinh, Shruti Raghavan +9
Large Language Models (LLMs) have shown remarkable capabilities, but their inherent probabilistic nature often leads to inconsistency and inaccuracy in complex problem-solving task…
Using Galaxy Evolution as Source of Physics-Based Ground Truth for Generative Models
Yun Qi Li, Tuan Do, Evan Jones +3
Generative models producing images have enormous potential to advance discoveries across scientific fields and require metrics capable of quantifying the high dimensional output. W…
Enhancing Q&A with Domain-Specific Fine-Tuning and Iterative Reasoning: A Comparative Study
Zooey Nguyen, Anthony Annunziata, Vinh Luong +7
This paper investigates the impact of domain-specific model fine-tuning and of reasoning mechanisms on the performance of question-answering (Q&A) systems powered by large language…