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Miriam Wanner

4 accepted papers

2025

CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers?

EMNLP 2025

A core part of scientific peer review involves providing expert critiques that directly assess the scientific claims a paper makes. While it is now possible to automatically generate plausible (if generic) reviews, ensuring that these reviews are sound and grounded in the papers’ claims remains chal

2025

Core: Robust Factual Precision with Informative Sub-Claim Identification

ACL 2025finding

Hallucinations pose a challenge to the application of large language models (LLMs) thereby motivating the development of metrics to evaluate factual precision. We observe that popular metrics using the Decompose-Then-Verify framework, such as FActScore, can be manipulated by adding obvious or repeti…

2025

DnDScore: Decontextualization and Decomposition for Factuality Verification in Long-Form Text Generation

EMNLP 2025

The decompose-then-verify strategy for verification of Large Language Model (LLM) generations decomposes claims that are then independently verified. Decontextualization augments text (claims) to ensure it can be verified outside of the original context, enabling reliable verification. While decompo

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2022

Revisiting the Effects of Leakage on Dependency Parsing

ACL 2022findings

Recent work by Søgaard (2020) showed that, treebank size aside, overlap between training and test graphs (termed leakage) explains more of the observed variation in dependency parsing performance than other explanations. In this work we revisit this claim, testing it on more models and languages. We…