3 papers
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.IR2025
FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents
Nandan Thakur, Jimmy Lin, Sam Havens +3
We introduce FreshStack, a holistic framework for automatically building information retrieval (IR) evaluation benchmarks by incorporating challenging questions and answers. FreshS…