Chris Hench — accepted AI-conference papers

2025

MASSIVE-Agents: A Benchmark for Multilingual Function-Calling in 52 Languages

Mayank Kulkarni, Vittorio Mazzia, Judith Gaspers, Chris Hench, Jack FitzGerald

EMNLP 2025

We present MASSIVE-Agents, a new benchmark for assessing multilingual function calling across 52 languages. We created MASSIVE-Agents by cleaning the original MASSIVE dataset and then reformatting it for evaluation within the Berkeley Function-Calling Leaderboard (BFCL) framework. The full benchmark

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2025

Tree-of-Prompts: Abstracting Control-Flow for Prompt Optimization

Jihyuk Kim, Shubham Garg, Lahari Poddar, Seung-won Hwang, Chris Hench

ACL 2025finding

Prompt optimization (PO) generates prompts to guide Large Language Models (LLMs) in performing tasks. Existing methods, such as PromptAgent, rely on a single static prompt, which struggles with disjoint cases in complex tasks. Although MoP uses multiple prompts, it fails to account for variations in…

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