Papers by Huixin Liu

2 papers
Embodied-Reasoner: Synergizing Visual Search, Reasoning, and Action for Embodied Interactive Tasks (2026.acl-long)

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Challenge: Recent advances in reasoning models have demonstrated remarkable capabilities on mathematical and coding tasks, but their effectiveness in embodied domains remains largely unexplored.
Approach: They propose a reasoning model for interactive embodied tasks that synthesizes 9.3k coherent Observation-Thought-Action trajectories containing 64k ego-centric images and 90k diverse reasoning processes.
Outcome: The proposed model outperforms existing visual reasoning models by +9%, 24%, and +13% on long-horizon tasks.
FroM: Frobenius Norm-Based Data-Free Adaptive Model Merging (2025.findings-emnlp)

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Challenge: a new adaptive merging method is proposed to improve fine-tuning performance . traditional methods often encounter task interference when merging full fine-uning models .
Approach: They propose an adaptive merging method that directly measures model parameters using the Frobenius norm .
Outcome: The proposed method outperforms baseline methods in various fine-tuning scenarios.

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