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cs.AI2026
Model or Harness? An Interaction-Centric Taxonomy for Localizing Agent Failures
Harsh Raj, Vipul Gupta, Anas Mahmoud +4
Existing evaluations often reduce agent failures to system-level outcomes, obscuring where the fault originated and which intervention would improve the agent system. This creates…
cs.AI2025
UpBench: A Dynamically Evolving Real-World Labor-Market Agentic Benchmark Framework Built for Human-Centric AI
Darvin Yi, Teng Liu, Mattie Terzolo +4
As large language model (LLM) agents increasingly undertake digital work, reliable frameworks are needed to evaluate their real-world competence, adaptability, and capacity for hum…