10 papers
Safe and Scalable Web Agent Learning via Recreated Websites
Hyungjoo Chae, Jungsoo Park, Alan Ritter
Training autonomous web agents is fundamentally limited by the environments they learn from: real-world websites are unsafe to explore, hard to reset, and rarely provide verifiable…
LEGO-Eval: Towards Fine-Grained Evaluation on Synthesizing 3D Embodied Environments with Tool Augmentation
Gyeom Hwangbo, Hyungjoo Chae, Minseok Kang +3
Despite recent progress in using Large Language Models (LLMs) for automatically generating 3D scenes, generated scenes often lack realistic spatial layouts and object attributes fo…
Web-Shepherd: Advancing PRMs for Reinforcing Web Agents
Hyungjoo Chae, Sunghwan Kim, Junhee Cho +18
Web navigation is a unique domain that can automate many repetitive real-life tasks and is challenging as it requires long-horizon sequential decision making beyond typical multimo…
ToolHaystack: Stress-Testing Tool-Augmented Language Models in Realistic Long-Term Interactions
Beong-woo Kwak, Minju Kim, Dongha Lim +5
Large language models (LLMs) have demonstrated strong capabilities in using external tools to address user inquiries. However, most existing evaluations assume tool use in short co…
Can You Share Your Story? Modeling Clients' Metacognition and Openness for LLM Therapist Evaluation
Minju Kim, Dongje Yoo, Yeonjun Hwang +11
Understanding clients' thoughts and beliefs is fundamental in counseling, yet current evaluations of LLM therapists often fail to assess this ability. Existing evaluation methods r…
One Missing Piece for Open-Source Reasoning Models: A Dataset to Mitigate Cold-Starting Short CoT LLMs in RL
Hyungjoo Chae, Dongjin Kang, Jihyuk Kim +6
With the release of R1, a publicly available large reasoning model (LRM), researchers commonly train new LRMs by training language models on R1's long chain-of-thought (CoT) infere…