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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 0Source ↗Scholar ↗
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 0Source ↗code ↗Scholar ↗
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…