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Grace Kim

4 accepted papers

2026

GDPval: Evaluating AI Model Performance on Real-World Economically Valuable Tasks

ICLR 2026poster

We introduce GDPval, a benchmark evaluating AI model capabilities on real-world economically valuable knowledge-work tasks. GDPval covers the majority of Department of Labor O*NET Work Activities for 44 occupations across the top 9 sectors contributing to U.S. GDP (Gross Domestic Product). Tasks are…

Cited by 0SourceScholar
2025

ChartMuseum: Testing Visual Reasoning Capabilities of Large Vision-Language Models

NeurIPS 2025poster

Chart understanding presents a unique challenge for large vision-language models (LVLMs), as it requires the integration of sophisticated textual and visual reasoning capabilities. However, current LVLMs exhibit a notable imbalance between these skills, falling short on visual reasoning that is diff…

Cited by 0SourcecodeScholar
2025

Is the Top Still Spinning? Evaluating Subjectivity in Narrative Understanding

EMNLP 2025

Determining faithfulness of a claim to a source document is an important problem across many domains. This task is generally treated as a binary judgment of whether the claim is supported or unsupported in relation to the source. In many cases, though, whether a claim is supported can be ambiguous.

2024

Complex Claim Verification with Evidence Retrieved in the Wild

NAACL 2024long

Retrieving evidence to support or refute claims is a core part of automatic fact-checking. Prior work makes simplifying assumptions in retrieval that depart from real-world use cases: either no access to evidence, access to evidence curated by a human fact-checker, or access to evidence published af…