3 papers
cs.AI2026
ExtractBench: A Benchmark for Schema-Guided Enterprise Document Extraction
Boyang Zhang, Adrian Lyjak, Eli Stewart +2
Enterprise workflows increasingly rely on agents for \emph{schema-guided extraction}: given a document and a user-defined schema, the agent faithfully follows the schema to produce…
cs.CV2026
ParseBench: A Document Parsing Benchmark for AI Agents
Boyang Zhang, Sebastián G. Acosta, Preston Carlson +4
AI agents are changing the requirements for document parsing. What matters is semantic correctness: parsed output must preserve the structure and meaning needed for autonomous deci…
cs.RO2023
Learning Realistic Traffic Agents in Closed-loop
Chris Zhang, James Tu, Lunjun Zhang +3
Realistic traffic simulation is crucial for developing self-driving software in a safe and scalable manner prior to real-world deployment. Typically, imitation learning (IL) is use…