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Daniel Adu-Ampratwum

2 accepted papers

2025

ScienceAgentBench: Toward Rigorous Assessment of Language Agents for Data-Driven Scientific Discovery

ICLR 2025poster

The advancements of language language models (LLMs) have piqued growing interest in developing LLM-based language agents to automate scientific discovery end-to-end, which has sparked both excitement and skepticism about the true capabilities of such agents. In this work, we argue that for an agent…

Cited by 21SourcePDFScholar
2025

Tooling or Not Tooling? The Impact of Tools on Language Agents for Chemistry Problem Solving

NAACL 2025findings

To enhance large language models (LLMs) for chemistry problem solving, several LLM-based agents augmented with tools have been proposed, such as ChemCrow and Coscientist. However, their evaluations are narrow in scope, leaving a large gap in understanding the benefits of tools across diverse chemist…