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Ryan Aponte

5 papers

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papers

Publications (5)

cs.AI2025

GUI Agents: A Survey

Dang Nguyen, Jian Chen, Yu Wang +27

Graphical User Interface (GUI) agents, powered by Large Foundation Models, have emerged as a transformative approach to automating human-computer interaction. These agents autonomo…

cs.CL2024

A Framework for Fine-Tuning LLMs using Heterogeneous Feedback

Ryan Aponte, Ryan A. Rossi, Shunan Guo +5

Large language models (LLMs) have been applied to a wide range of tasks, including text summarization, web navigation, and chatbots. They have benefitted from supervised fine-tunin…

cs.LG2022

A Hypergraph Neural Network Framework for Learning Hyperedge-Dependent Node Embeddings

Ryan Aponte, Ryan A. Rossi, Shunan Guo +6

In this work, we introduce a hypergraph representation learning framework called Hypergraph Neural Networks (HNN) that jointly learns hyperedge embeddings along with a set of hyper…

cs.LG2025

From Selection to Generation: A Survey of LLM-based Active Learning

Yu Xia, Subhojyoti Mukherjee, Zhouhang Xie +31

Active Learning (AL) has been a powerful paradigm for improving model efficiency and performance by selecting the most informative data points for labeling and training. In recent…

cs.CL2024

A Survey of Small Language Models

Chien Van Nguyen, Xuan Shen, Ryan Aponte +25

Small Language Models (SLMs) have become increasingly important due to their efficiency and performance to perform various language tasks with minimal computational resources, maki…

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