AutoVerifier decomposes technical claims into triples and uses layered LLM verification to assess validity, demonstrated on a quantum computing paper by finding overclaims and conflicts.
Visual instruction tuning
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The work creates a new benchmark for humanizing GUI agent touch dynamics via a MinMax detector-agent model, a mobile touch dataset, and methods showing agents can match human behavior without losing task performance.
citing papers explorer
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AutoVerifier: An Agentic Automated Verification Framework Using Large Language Models
AutoVerifier decomposes technical claims into triples and uses layered LLM verification to assess validity, demonstrated on a quantum computing paper by finding overclaims and conflicts.
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Turing Test on Screen: A Benchmark for Mobile GUI Agent Humanization
The work creates a new benchmark for humanizing GUI agent touch dynamics via a MinMax detector-agent model, a mobile touch dataset, and methods showing agents can match human behavior without losing task performance.