9 citations · 27 across the 24 of their papers we have counts for
7 papers · 1 filter
Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models
Liangwei Yang, Shiyu Wang, Haolin Chen +12
As large language models (LLMs) transition from research prototypes to real-world systems, customization has emerged as a central bottleneck. While text prompts can already customi…
Prompt Optimization Via Diffusion Language Models
Shiyu Wang, Haolin Chen, Liangwei Yang +8
We propose a diffusion-based framework for prompt optimization that leverages Diffusion Language Models (DLMs) to iteratively refine system prompts through masked denoising. By con…
Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models
Rithesh Murthy, Ming Zhu, Liangwei Yang +6
Large Language Models (LLMs) perform best with well-crafted prompts, yet prompt engineering remains manual, inconsistent, and inaccessible to non-experts. We introduce Promptomatix…
xLAM: A Family of Large Action Models to Empower AI Agent Systems
Jianguo Zhang, Tian Lan, Ming Zhu +19
Autonomous agents powered by large language models (LLMs) have attracted significant research interest. However, the open-source community faces many challenges in developing speci…
APIGen: Automated Pipeline for Generating Verifiable and Diverse Function-Calling Datasets
Zuxin Liu, Thai Hoang, Jianguo Zhang +14
The advancement of function-calling agent models requires diverse, reliable, and high-quality datasets. This paper presents APIGen, an automated data generation pipeline designed t…
MobileAIBench: Benchmarking LLMs and LMMs for On-Device Use Cases
Rithesh Murthy, Liangwei Yang, Juntao Tan +15
The deployment of Large Language Models (LLMs) and Large Multimodal Models (LMMs) on mobile devices has gained significant attention due to the benefits of enhanced privacy, stabil…
Retroformer: Retrospective Large Language Agents with Policy Gradient Optimization
Weiran Yao, Shelby Heinecke, Juan Carlos Niebles +12
Recent months have seen the emergence of a powerful new trend in which large language models (LLMs) are augmented to become autonomous language agents capable of performing objecti…