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cs.CL2026

Spider 2.0-AIFunc: Extending Real-World Text-to-SQL to AI-Native SQL Workflows

Tianyang Liu, Canwen Xu, Fangyu Lei +6

Major cloud data platforms now expose large language model capabilities as native SQL functions, enabling analysts to perform classification, filtering, sentiment analysis, extract…

cs.CL2026

AgentSpec: Understanding Embodied Agent Scaffolds Through Controlled Composition

Jixuan Chen, Jianzhi Shen, Haoqiang Kang +10

LLM agents are increasingly built not as single model calls, but as scaffolded systems that combine reasoning, memory, reflection, action execution, and learning. While such scaffo…

cs.CL2026

CocoaBench: Evaluating Unified Digital Agents in the Wild

CocoaBench Team, Shibo Hao, Zhining Zhang +29

LLM agents now perform strongly in software engineering, deep research, GUI automation, and various other applications, while recent agent scaffolds and models are increasingly int…

cs.CL2025

VideoAgentTrek: Computer Use Pretraining from Unlabeled Videos

Dunjie Lu, Yiheng Xu, Junli Wang +12

Training computer-use agents requires massive amounts of GUI interaction data, but manually annotating action trajectories at scale is prohibitively expensive. We present VideoAgen…

cs.CL2025

Spider 2.0: Evaluating Language Models on Real-World Enterprise Text-to-SQL Workflows

Fangyu Lei, Jixuan Chen, Yuxiao Ye +13

Real-world enterprise text-to-SQL workflows often involve complex cloud or local data across various database systems, multiple SQL queries in various dialects, and diverse operati…