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Yong Xien Chng

3 accepted papers

2026

SenseSearch: Empowering Vision-Language Models with High-Resolution Agentic Search-Reasoning via Reinforcement Learning

CVPR 2026

Vision-Language Models (VLMs) are limited by static knowledge and insufficient fine-grained visual analysis, hindering their performance on knowledge-intensive and visually complex tasks. While recent research has explored VLMs that employ external tools like search or cropping to enhance model perf

Cited by 0SourcecodeScholar
2025

DenseGrounding: Improving Dense Language-Vision Semantics for Ego-centric 3D Visual Grounding

ICLR 2025poster

Enabling intelligent agents to comprehend and interact with 3D environments through natural language is crucial for advancing robotics and human-computer interaction. A fundamental task in this field is ego-centric 3D visual grounding, where agents locate target objects in real-world 3D spaces based…

Cited by 0SourcePDFScholar
2024

Mask Grounding for Referring Image Segmentation

CVPR 2024poster

Referring Image Segmentation (RIS) is a challenging task that requires an algorithm to segment objects referred by free-form language expressions. Despite significant progress in recent years most state-of-the-art (SOTA) methods still suffer from considerable language-image modality gap at the pixel…