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Harbin Institute of Technology, Shenzhen
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KnowAct-GUIClaw achieves a groundbreaking 64.1% success rate in long-horizon task execution, outperforming all existing agent frameworks and closed-source models.
Uncovering the root cause of modality interference, this work achieves a remarkable 28.5% improvement in full-duplex interaction fluidity without sacrificing efficiency.
Context-aware ASR corrections can be dramatically improved by leveraging a dynamically structured ontology memory, leading to more accurate and relevant corrections in long conversations.
Today's best GUI agents choke on real-world, multi-application workflows, achieving less than 21% success rate, revealing a critical gap in their ability to coordinate across applications and perform conditional reasoning.
