activity
20162026
most citedRobust Question Answering against Distribution Shifts with Test-Time Adaptation: An Empirical Study

3 citations · 5 across the 16 of their papers we have counts for

collaborators

16 papers

cs.CL2026

OpenSeal: Good, Fast, and Cheap Construction of an Open-Source Southeast Asian LLM via Parallel Data

Tan Sang Nguyen, Muhammad Reza Qorib, Hwee Tou Ng

Large language models (LLMs) have proven to be effective tools for a wide range of natural language processing (NLP) applications. Although many LLMs are multilingual, most remain…

cs.CL2026

Game of Thought: Robust Information Seeking with Large Language Models Using Game Theory

Langyuan Cui, Chun Kai Ling, Hwee Tou Ng

Large Language Models (LLMs) are increasingly deployed in real-world scenarios where they may lack sufficient information to complete a given task. In such settings, the ability to…

cs.CV2026

FocusUI: Efficient UI Grounding via Position-Preserving Visual Token Selection

Mingyu Ouyang, Kevin Qinghong Lin, Mike Zheng Shou +1

Vision-Language Models (VLMs) have shown remarkable performance in User Interface (UI) grounding tasks, driven by their ability to process increasingly high-resolution screenshots.…

cs.CV2025

Factorized Learning for Temporally Grounded Video-Language Models

Wenzheng Zeng, Difei Gao, Mike Zheng Shou +1

Recent video-language models have shown great potential for video understanding, but still struggle with accurate temporal grounding for event-level perception. We observe that two…

cs.CL2025

SlideTailor: Personalized Presentation Slide Generation for Scientific Papers

Wenzheng Zeng, Mingyu Ouyang, Langyuan Cui +1

Automatic presentation slide generation can greatly streamline content creation. However, since preferences of each user may vary, existing under-specified formulations often lead…

cs.CL2025

Just Go Parallel: Improving the Multilingual Capabilities of Large Language Models

Muhammad Reza Qorib, Junyi Li, Hwee Tou Ng

Large language models (LLMs) have demonstrated impressive translation capabilities even without being explicitly trained on parallel data. This remarkable property has led some to…