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cs.AI2026
OfficeQA Pro: An Enterprise Benchmark for End-to-End Grounded Reasoning
Krista Opsahl-Ong, Arnav Singhvi, Jasmine Collins +10
We introduce OfficeQA Pro, a benchmark for evaluating AI agents on grounded, multi-document reasoning over a large and heterogeneous document corpus. The corpus consists of U.S. Tr…
cs.AI2026
KARL: Knowledge Agents via Reinforcement Learning
Jonathan D. Chang, Andrew Drozdov, Shubham Toshniwal +23
We present a system for training enterprise search agents via reinforcement learning that achieves state-of-the-art performance across a diverse suite of hard-to-verify agentic sea…
cs.RO2026
Bidirectional Human-Robot Communication for Physical Human-Robot Interaction
Junxiang Wang, Cindy Wang, Rana Soltani Zarrin +1
Effective physical human-robot interaction requires systems that are not only adaptable to user preferences but also transparent about their actions. This paper introduces BRIDGE,…