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Zhuohan Xie

7 accepted papers

2025

A Head to Predict and a Head to Question: Pre-trained Uncertainty Quantification Heads for Hallucination Detection in LLM Outputs

EMNLP 2025

LLMs have the tendency to hallucinate, i.e., to sporadically generate false or fabricated information, and users generally lack the tools to detect when this happens. Uncertainty quantification (UQ) provides a framework for assessing the reliability of model outputs, aiding in the identification of

Cited by 0SourcePDFScholar
2025

Entity Framing and Role Portrayal in the News

ACL 2025finding

We introduce a novel multilingual and hierarchical corpus annotated for entity framing and role portrayal in news articles. The dataset uses a unique taxonomy inspired by storytelling elements, comprising 22 fine-grained roles, or archetypes, nested within three main categories: protagonist, antagon…

Cited by 0SourcePDFScholar
2025

FIRE: Fact-checking with Iterative Retrieval and Verification

NAACL 2025findings

Fact-checking long-form text is challenging, and it is therefore common practice to break it down into multiple atomic claims. The typical approach to fact-checking these atomic claims involves retrieving a fixed number of pieces of evidence, followed by a verification step. However, this method is…

2025

KazMMLU: Evaluating Language Models on Kazakh, Russian, and Regional Knowledge of Kazakhstan

ACL 2025long

Despite having a population of twenty million, Kazakhstan’s culture and language remain underrepresented in the field of natural language processing. Although large language models (LLMs) continue to advance worldwide, progress in Kazakh language has been limited, as seen in the scarcity of dedicate…

Cited by 0SourcePDFScholar
2025

VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration

ACL 2025finding

The rapid advancement of vision-language models (VLMs) has brought a lot of attention to their safety alignment. However, existing methods have primarily focused on model undersafety, where the model responds to hazardous queries, while neglecting oversafety, where the model refuses to answer safe q…

2024

LLM-DetectAIve: a Tool for Fine-Grained Machine-Generated Text Detection

EMNLP 2024system demonstrations

The ease of access to large language models (LLMs) has enabled a widespread of machine-generated texts, and now it is often hard to tell whether a piece of text was human-written or machine-generated. This raises concerns about potential misuse, particularly within educational and academic domains.…

2023

DeltaScore: Fine-Grained Story Evaluation with Perturbations

EMNLP 2023long findings

Numerous evaluation metrics have been developed for natural language generation tasks, but their effectiveness in evaluating stories is limited as they are not specifically tailored to assess intricate aspects of storytelling, such as fluency and interestingness. In this paper, we introduce DeltaSco…

Cited by 0SourcecodeScholar