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Evaluating RAG Metrics in Applied Contexts: An Experiment, Its Findings and Its Limitations
Quentin Brabant
This paper reports an empirical study evaluating the relevance of several RAG metrics. The experiment is based on a question-answering dataset created by human annotators from busi…
Factual Knowledge in Language Models: Robustness and Anomalies under Simple Temporal Context Variations
Hichem Ammar Khodja, Frédéric Béchet, Quentin Brabant +2
This paper explores the robustness of language models (LMs) to variations in the temporal context within factual knowledge. It examines whether LMs can correctly associate a tempor…
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…
WikiFactDiff: A Large, Realistic, and Temporally Adaptable Dataset for Atomic Factual Knowledge Update in Causal Language Models
Hichem Ammar Khodja, Frédéric Béchet, Quentin Brabant +2
The factuality of large language model (LLMs) tends to decay over time since events posterior to their training are "unknown" to them. One way to keep models up-to-date could be fa…
WEBDial, a Multi-domain, Multitask Statistical Dialogue Framework with RDF
Morgan Veyret, Jean-Baptiste Duchene, Kekeli Afonouvi +3
Typically available dialogue frameworks have adopted a semantic representation based on dialogue-acts and slot-value pairs. Despite its simplicity, this representation has disadvan…
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…
CoQAR: Question Rewriting on CoQA
Quentin Brabant, Gwenole Lecorve, Lina M. Rojas-Barahona
Questions asked by humans during a conversation often contain contextual dependencies, i.e., explicit or implicit references to previous dialogue turns. These dependencies take the…
Active Learning and Multi-label Classification for Ellipsis and Coreference Detection in Conversational Question-Answering
Quentin Brabant, Lina Maria Rojas-Barahona, Claire Gardent
In human conversations, ellipsis and coreference are commonly occurring linguistic phenomena. Although these phenomena are a mean of making human-machine conversations more fluent…