activity
20232026
most citedDissecting Adversarial Robustness of Multimodal LM Agents

1 citations · 2 across the 6 of their papers we have counts for

collaborators

7 papers

cs.LG2026

cua-speedrun: Standardized Benchmarking of the Speed of Computer-Use Agents

Pranjal Aggarwal, Lawrence Keunho Jang, Sean Welleck +3

Computer use agents (CUAs), which use graphical user interfaces (GUIs) to complete tasks on a computer, have recently surpassed human performance on many standard benchmarks, inclu…

cs.CL2026

Improving LLM-based Autonomous Web Agents with Filtering

Zhitong Guo, Jing Yu Koh, Ruiyu Li

Autonomous web agents, powered by Large Language Models (LLMs), have garnered significant attention for automating various web-based tasks with multi-step reasoning and decision-ma…

cs.LG2026

MyPCBench: A Benchmark for Personally Intelligent Computer-Use Agents

Lawrence Keunho Jang, Andrew Keunwoo Jang, Jing Yu Koh +1

Current benchmarks for computer-use agents evaluate models in impersonal environments. This leaves a gap between evaluation and deployment where personal assistants are expected to…

cs.LG2026

iOSWorld: A Benchmark for Personally Intelligent Phone Agents

Lawrence Keunho Jang, Mareks Woodside, Geronimo Carom +3

A useful phone agent needs to be personally intelligent. It should reason over a user's identity, history, and preferences as they exist on the device, not just follow isolated ins…

cs.LG2024★ 1 cited

Dissecting Adversarial Robustness of Multimodal LM Agents

Chen Henry Wu, Rishi Shah, Jing Yu Koh +3

As language models (LMs) are used to build autonomous agents in real environments, ensuring their adversarial robustness becomes a critical challenge. Unlike chatbots, agents are c…

cs.LG2024★ 1 cited

VisualWebArena: Evaluating Multimodal Agents on Realistic Visual Web Tasks

Jing Yu Koh, Robert Lo, Lawrence Jang +7

Autonomous agents capable of planning, reasoning, and executing actions on the web offer a promising avenue for automating computer tasks. However, the majority of existing benchma…

cs.AI2023

Multimodal Graph Learning for Generative Tasks

Minji Yoon, Jing Yu Koh, Bryan Hooi +1

Multimodal learning combines multiple data modalities, broadening the types and complexity of data our models can utilize: for example, from plain text to image-caption pairs. Most…