collaborators

5 papers

cs.CL2026

Configurable Reward Model for Balanced Safety Alignment

Zhengping Jiang, Mehran Khodabandeh, Akash Bharadwaj +5

Aligning large language models (LLMs) to heterogeneous and rapidly evolving safety requirements remains a critical challenge. Existing instruction-tuned LLMs and standalone safety…

cs.CL2026

Always Tell Me The Odds: Fine-grained Conditional Probability Estimation

Liaoyaqi Wang, Zhengping Jiang, Anqi Liu +1

We present a state-of-the-art model for fine-grained probability estimation of propositions conditioned on context. Recent advances in large language models (LLMs) have significant…

cs.CL2025

How Grounded is Wikipedia? A Study on Structured Evidential Support and Retrieval

William Walden, Kathryn Ricci, Miriam Wanner +4

Wikipedia is a critical resource for modern NLP, serving as a rich repository of up-to-date and citation-backed information on a wide variety of subjects. The reliability of Wikipe…

cs.CL2025

Conformal Linguistic Calibration: Trading-off between Factuality and Specificity

Zhengping Jiang, Anqi Liu, Benjamin Van Durme

Language model outputs are not always reliable, thus prompting research into how to adapt model responses based on uncertainty. Common approaches include: \emph{abstention}, where…

cs.CL2025

CLAIMCHECK: How Grounded are LLM Critiques of Scientific Papers?

Jiefu Ou, William Gantt Walden, Kate Sanders +13

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 genera…