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This paper proposes Embodied-BenchClaw, an autonomous multi-agent system that automatically constructs embodied spatial intelligence benchmarks from user intent through a five-stage pipeline with process quality control and an extensible Skill Library.
Introduces Benchmark Agent, a fully autonomous system for creating diverse benchmarks with minimal human intervention, enabling continuous model assessment across domains.
This paper presents QuestBench, a benchmark built by students to evaluate deep research systems across humanities and social science domains. Results show that even advanced systems like GPT-5.5 pass only 57.58% of questions, highlighting failures in trustworthiness.