3 citations · 8 across the 13 of their papers we have counts for
13 papers
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…
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…
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…
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…
Question Generation in Knowledge-Driven Dialog: Explainability and Evaluation
Juliette Faille, Quentin Brabant, Gwenole Lecorve +2
We explore question generation in the context of knowledge-grounded dialogs focusing on explainability and evaluation. Inspired by previous work on planning-based summarisation, we…
Evaluating Document Simplification: On the Importance of Separately Assessing Simplicity and Meaning Preservation
Liam Cripwell, Joël Legrand, Claire Gardent
Text simplification intends to make a text easier to read while preserving its core meaning. Intuitively and as shown in previous works, these two dimensions (simplification and me…
Simplicity Level Estimate (SLE): A Learned Reference-Less Metric for Sentence Simplification
Liam Cripwell, Joël Legrand, Claire Gardent
Automatic evaluation for sentence simplification remains a challenging problem. Most popular evaluation metrics require multiple high-quality references -- something not readily av…
Automatic and Human-AI Interactive Text Generation
Yao Dou, Philippe Laban, Claire Gardent +1
In this tutorial, we focus on text-to-text generation, a class of natural language generation (NLG) tasks, that takes a piece of text as input and then generates a revision that is…
KGConv, a Conversational Corpus grounded in Wikidata
Quentin Brabant, Gwenole Lecorve, Lina M. Rojas-Barahona +1
We present KGConv, a large, conversational corpus of 71k conversations where each question-answer pair is grounded in a Wikidata fact. Conversations contain on average 8.6 question…
Context-Aware Document Simplification
Liam Cripwell, Joël Legrand, Claire Gardent
To date, most work on text simplification has focused on sentence-level inputs. Early attempts at document simplification merely applied these approaches iteratively over the sente…
Joint Representations of Text and Knowledge Graphs for Retrieval and Evaluation
Teven Le Scao, Claire Gardent
A key feature of neural models is that they can produce semantic vector representations of objects (texts, images, speech, etc.) ensuring that similar objects are close to each oth…
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…
A specification language for Lexical Functional Grammars
Patrick Blackburn, Claire Gardent
This paper defines a language L for specifying LFG grammars. This enables constraints on LFG's composite ontology (c-structures synchronised with f-structures) to be stated directl…