25 citations · 40 across the 24 of their papers we have counts for
6 papers · 1 filter
AppSelectBench: Application-Level Tool Selection Benchmark
Tianyi Chen, Michael Solodko, Sen Wang +14
Computer Using Agents (CUAs) are increasingly equipped with external tools, enabling them to perform complex and realistic tasks. For CUAs to operate effectively, application selec…
Hierarchical Self-Attention: Generalizing Neural Attention Mechanics to Multi-Scale Problems
Saeed Amizadeh, Sara Abdali, Yinheng Li +1
Transformers and their attention mechanism have been revolutionary in the field of Machine Learning. While originally proposed for the language data, they quickly found their way t…
Instruction Agent: Enhancing Agent with Expert Demonstration
Yinheng Li, Hailey Hultquist, Justin Wagle +1
Graphical user interface (GUI) agents have advanced rapidly but still struggle with complex tasks involving novel UI elements, long-horizon actions, and personalized trajectories.…
WinClick: GUI Grounding with Multimodal Large Language Models
Zheng Hui, Yinheng Li, Dan zhao +3
Graphical User Interface (GUI) tasks are vital for automating workflows such as software testing, user interface navigation. For users, the GUI is the most intuitive platform for i…
Automatic Joint Structured Pruning and Quantization for Efficient Neural Network Training and Compression
Xiaoyi Qu, David Aponte, Colby Banbury +5
Structured pruning and quantization are fundamental techniques used to reduce the size of deep neural networks (DNNs) and typically are applied independently. Applying these techni…
Self-reflecting Large Language Models: A Hegelian Dialectical Approach
Sara Abdali, Michael Solodko, Can Goksen +4
In this paper, we introduce a self-reflection framework for Large Language Models (LLMs) grounded in the Hegelian Dialectic, a philosophical method in which an initial proposition…