6 papers
Hierarchical Policies from Verbal and Egocentric Human Signals for Natural Human-Robot Interaction
Dongjun Lee, Juheon Choi, Dong Kyu Shin +2
For natural human-robot interaction, a robot must understand human intent expressed not only through language but also through nonverbal signals such as gestures and gaze. However,…
Efficient LLM Collaboration via Planning
Byeongchan Lee, Jonghoon Lee, Dongyoung Kim +4
Recently, large language models (LLMs) have demonstrated strong performance, ranging from simple to complex tasks. However, while large models achieve remarkable results across div…
Learning Multi-View Spatial Reasoning from Cross-View Relations
Suchae Jeong, Jaehwi Song, Haeone Lee +9
Vision-language models (VLMs) have achieved impressive results on single-view vision tasks, but lack the multi-view spatial reasoning capabilities essential for embodied AI systems…
Learning to Generate Unit Test via Adversarial Reinforcement Learning
Dongjun Lee, Changho Hwang, Kimin Lee
Unit testing is a core practice in programming, enabling systematic evaluation of programs produced by human developers or large language models (LLMs). Given the challenges in wri…
Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents
Dongjun Lee, Juyong Lee, Kyuyoung Kim +4
Recent advances in large language models (LLMs) have led to a growing interest in developing LLM-based agents for automating web tasks. However, these agents often struggle with ev…
Automated Skill Discovery for Language Agents through Exploration and Iterative Feedback
Yongjin Yang, Sinjae Kang, Juyong Lee +3
Training large language model (LLM) agents to acquire necessary skills and perform diverse tasks within an environment is gaining interest as a means to enable open-endedness. Howe…