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Aishan Liu

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#artificial intelligence Preprint Nov 2026

VagueBench: Benchmarking the Robustness of Embodied Agents on Ambient Context Illusions

This work identifies a novel phenomenon termed Ambient Context Illusion, where agents fail to execute tasks correctly when non-essential contextual details are omitted, despite unchanged task semantics, and demonstrates that this phenomenon persists in real-world robotic systems, where it can lead to incorrect decision...

Yang Qu, Qiang Fu, Zong-Hao Ying et al. · 0 citations

L pCoder ∞ : Scaling Code Intelligence via Looped Language Models

This work presents LoopCoder pre-trained on 12T+ code and general tokens, along with LoopCoder-Thinking and LoopCoder-Instruct variants, the first large-scale looped transformer for code, achieving comparable performance to standard dense architectures with more parameters.

Jian Yang, Wei Zhang, Shawn Guo et al. · 0 citations

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