19 citations · 42 across the 13 of their papers we have counts for
16 papers
Why Far Looks Up: Probing Spatial Representation in Vision-Language Models
Cheolhong Min, Jaeyun Jung, Daeun Lee +5
Vision-language models (VLMs) achieve strong performance on spatial reasoning benchmarks, yet it remains unclear whether this reflects structured 3D understanding or reliance on st…
SpaceTools: Tool-Augmented Spatial Reasoning via Double Interactive RL
Siyi Chen, Mikaela Angelina Uy, Chan Hee Song +6
Vision Language Models (VLMs) demonstrate strong qualitative visual understanding, but struggle with metrically precise spatial reasoning required for embodied applications. The ag…
AutoSynth: Automated Workflow Optimization for High-Quality Synthetic Dataset Generation via Monte Carlo Tree Search
Shuzhen Bi, Chang Song, Siyu Song +5
Supervised fine-tuning (SFT) of large language models (LLMs) for specialized tasks requires high-quality datasets, but manual curation is prohibitively expensive. Synthetic data ge…
WebGraphEval: Multi-Turn Trajectory Evaluation for Web Agents using Graph Representation
Yaoyao Qian, Yuanli Wang, Jinda Zhang +8
Current evaluation of web agents largely reduces to binary success metrics or conformity to a single reference trajectory, ignoring the structural diversity present in benchmark da…
Watch and Learn: Learning to Use Computers from Online Videos
Chan Hee Song, Yiwen Song, Palash Goyal +4
Computer-using agents (CUAs) must plan task workflows across diverse and evolving applications, yet progress is limited by the lack of large-scale, high-quality training data. Exis…
Step-Audio 2 Technical Report
Boyong Wu, Chao Yan, Chen Hu +106
This paper presents Step-Audio 2, an end-to-end multi-modal large language model designed for industry-strength audio understanding and speech conversation. By integrating a latent…
Mind2Web 2: Evaluating Agentic Search with Agent-as-a-Judge
Boyu Gou, Zanming Huang, Yuting Ning +23
Agentic search such as Deep Research systems-where agents autonomously browse the web, synthesize information, and return comprehensive citation-backed answers-represents a major s…
An Illusion of Progress? Assessing the Current State of Web Agents
Tianci Xue, Weijian Qi, Tianneng Shi +5
As digitalization and cloud technologies evolve, the web is becoming increasingly important in the modern society. Autonomous web agents based on large language models (LLMs) hold…
RoboSpatial: Teaching Spatial Understanding to 2D and 3D Vision-Language Models for Robotics
Chan Hee Song, Valts Blukis, Jonathan Tremblay +3
Spatial understanding is a crucial capability that enables robots to perceive their surroundings, reason about their environment, and interact with it meaningfully. In modern robot…
VisualAgentBench: Towards Large Multimodal Models as Visual Foundation Agents
Xiao Liu, Tianjie Zhang, Yu Gu +27
Large Multimodal Models (LMMs) have ushered in a new era in artificial intelligence, merging capabilities in both language and vision to form highly capable Visual Foundation Agent…
Dual-View Visual Contextualization for Web Navigation
Jihyung Kil, Chan Hee Song, Boyuan Zheng +3
Automatic web navigation aims to build a web agent that can follow language instructions to execute complex and diverse tasks on real-world websites. Existing work primarily takes…
BioCLIP: A Vision Foundation Model for the Tree of Life
Samuel Stevens, Jiaman Wu, Matthew J Thompson +9
Images of the natural world, collected by a variety of cameras, from drones to individual phones, are increasingly abundant sources of biological information. There is an explosion…
LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models
Chan Hee Song, Jiaman Wu, Clayton Washington +3
This study focuses on using large language models (LLMs) as a planner for embodied agents that can follow natural language instructions to complete complex tasks in a visually-perc…
One Step at a Time: Long-Horizon Vision-and-Language Navigation with Milestones
Chan Hee Song, Jihyung Kil, Tai-Yu Pan +3
We study the problem of developing autonomous agents that can follow human instructions to infer and perform a sequence of actions to complete the underlying task. Significant prog…
Improving Neural Named Entity Recognition with Gazetteers
Chan Hee Song, Dawn Lawrie, Tim Finin +1
The goal of this work is to improve the performance of a neural named entity recognition system by adding input features that indicate a word is part of a name included in a gazett…
Using Chinese Glyphs for Named Entity Recognition
Arijit Sehanobish, Chan Hee Song
Most Named Entity Recognition (NER) systems use additional features like part-of-speech (POS) tags, shallow parsing, gazetteers, etc. Such kind of information requires external kno…