1 citations · 1 across the 6 of their papers we have counts for
6 papers
Scalable Video-to-Dataset Generation for Cross-Platform Mobile Agents
Yunseok Jang, Yeda Song, Sungryull Sohn +5
Recent advancements in Large Language Models (LLMs) and Vision-Language Models (VLMs) have sparked significant interest in developing GUI visual agents. We introduce MONDAY (Mobile…
Auto-Intent: Automated Intent Discovery and Self-Exploration for Large Language Model Web Agents
Jaekyeom Kim, Dong-Ki Kim, Lajanugen Logeswaran +2
In this paper, we introduce Auto-Intent, a method to adapt a pre-trained large language model (LLM) as an agent for a target domain without direct fine-tuning, where we empirically…
AutoGuide: Automated Generation and Selection of Context-Aware Guidelines for Large Language Model Agents
Yao Fu, Dong-Ki Kim, Jaekyeom Kim +4
Recent advances in large language models (LLMs) have empowered AI agents capable of performing various sequential decision-making tasks. However, effectively guiding LLMs to perfor…
TOD-Flow: Modeling the Structure of Task-Oriented Dialogues
Sungryull Sohn, Yiwei Lyu, Anthony Liu +4
Task-Oriented Dialogue (TOD) systems have become crucial components in interactive artificial intelligence applications. While recent advances have capitalized on pre-trained langu…
Code Models are Zero-shot Precondition Reasoners
Lajanugen Logeswaran, Sungryull Sohn, Yiwei Lyu +5
One of the fundamental skills required for an agent acting in an environment to complete tasks is the ability to understand what actions are plausible at any given point. This work…
MultiPrompter: Cooperative Prompt Optimization with Multi-Agent Reinforcement Learning
Dong-Ki Kim, Sungryull Sohn, Lajanugen Logeswaran +2
Recently, there has been an increasing interest in automated prompt optimization based on reinforcement learning (RL). This approach offers important advantages, such as generating…