Author

Matthew Lee

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#natural language process... Preprint Oct 2026

Evaluating LLMs as Agentic Workflow Executors in Real-World Customer Support Skills

Enterprise customer-support agents increasingly rely on Large Language Models (LLMs) to execute bounded, tool-using workflows. We study this problem through the lens of Skill LLMs: specialized executors that operate within a selected skill context and must complete a narrow, stateful workflow under policy and tool cons...

Md Tahmid Rahman Laskar, Gundeep Singh, Xue-Yong Fu et al. · 0 citations

#natural language process... Preprint Oct 2026

Prompts versus Rules: Auditing and Controlling Speech Naturalness Behaviors in Voice User Simulators

As voice agents gain more popularity commercially, the user simulators used to evaluate the deployed agents are also being developed to include more realistic, variable, and diverse speech naturalness behaviors -- disfluency, interruption and backchanneling. The quality of the user simulator directly affects the validi...

Riqiang Wang, Elena Khasanova, Harsh Saini et al. · 0 citations

#natural language process... Preprint Sep 2026

When Better Turns Do Not Make Better Agents: Diagnosing the Gap Between Next-Turn Metrics and Workflow Success

It is found that SFT consistently improves text-turn success, and that overall next-turn success increases for every model under gold-history evaluation, but these improvements do not transfer to autonomous workflow execution.

Md Tahmid Rahman Laskar, Xue-Yong Fu, Gundeep Singh et al. · 1 citation · ⚡1