Author

Mingqi Gao

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#artificial intelligence Preprint Jun 2026

Planning Takes More Than Token Prediction: Causal Plan for Benchmarking and Building Physically Grounded Embodied Reasoners

This work introduces Causal-Plan-Bench, a high-fidelity diagnostic suite spanning four causal dimensions, curated via multi-stage verification, and initiate the first effort to turn agents from superficial token predictors into physically grounded causal reasoners, bridging language modeling and world modeling.

Zi-Rong Song, Zheng Lu, Ming-Qi Gao et al. · 3 citations

Preprint Aug 2026

Competitive Memory Readout for Robust Video Object Segmentation: 2nd Place Technical Report for the MOSEv2 Track of the 8th LSVOS Challenge

This work introduces Competitive Memory Readout, which explicitly incorporates same-class competitor evidence when retrieving target information from memory when retrieving target information from memory, and applies a lightweight adaptive restoration rule after competition.

Mingqi Gao, Si-E Li, Jun-Gong Han · 0 citations

Jul 2026

Hy-Embodied-VLM-1.0: Efficient Physical-World Agents

The model achieves the best performance among similarly sized models on 19 of the 38 benchmarks and substantially outperforms strong competitors, including Qwen3.6-A3B and Cosmos 3.5 MoT-2B, and demonstrates strong performance on embodied agentic tasks requiring multi-turn interaction and long-horizon reasoning.

Ziyi Wang, Xu-Min Yu, Yongming Rao et al. · arXiv.org · 6 citations