activity
20222026
most citedGenerating Full Length Wikipedia Biographies: The Impact of Gender Bias on the Retrieval-Based Generation of Women Biographies

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

XQDT: eXplainable and Quantitative Data-Text Alignment Metric with Feedback Signals

Kun Efimov-Zhang, Yifei Song, Claire Gardent

Evaluating data-text alignment remains challenging: existing metrics often provide limited explanations for the scores, while prompt-based LLM-as-Judge methods can be expensive and…

cs.CL2026

Cross-lingual Biography Enrichment via Claim Extraction and Alignment

Yifei Song, Ziyang Chen, Emil Sayilov +1

English Wikipedia is often treated as the default encyclopedic source, yet non-English Wikipedia editions can contain richer locally grounded information for long-tail figures. We…

cs.CL2026

Cross-Domain, Multi-Task Data-to-Text Generation without In-Domain Training Data

Yifei Song, Kun Efimov-Zhang, Claire Gardent

Structured data exists in many forms (tables, knowledge graphs, charts, and time series), and converting it into text may involve different generation tasks. However, most prior wo…

cs.CL20241 cited

Probing Omissions and Distortions in Transformer-based RDF-to-Text Models

Juliette Faille, Albert Gatt, Claire Gardent

In Natural Language Generation (NLG), important information is sometimes omitted in the output text. To better understand and analyse how this type of mistake arises, we focus on R…

cs.CL20222 cited

Generating Full Length Wikipedia Biographies: The Impact of Gender Bias on the Retrieval-Based Generation of Women Biographies

Angela Fan, Claire Gardent

Generating factual, long-form text such as Wikipedia articles raises three key challenges: how to gather relevant evidence, how to structure information into well-formed text, and…