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Huangxuan Wu

2 accepted papers

2026

RoboOmni: Proactive Robot Manipulation in Omni-modal Context

ICLR 2026poster

Recent advances in Multimodal Large Language Models (MLLMs) have driven rapid progress in Vision–Language–Action (VLA) models for robotic manipulation. Although effective in many scenarios, current approaches largely rely on explicit instructions, whereas in real-world interactions, humans rarely is…

Cited by 0SourcecodeScholar
2025

CS-Bench: A Comprehensive Benchmark for Large Language Models towards Computer Science Mastery

ICLR 2025poster

Large language models (LLMs) have demonstrated significant potential in advancing various fields of research and society. However, the current community of LLMs overly focuses on benchmarks for analyzing specific foundational skills (e.g. mathematics and code generation), neglecting an all-round eva…