papers

Publications (25)

cs.CL2025

Prior Lessons of Incremental Dialogue and Robot Action Management for the Age of Language Models

Casey Kennington, Pierre Lison, David Schlangen

Efforts towards endowing robots with the ability to speak have benefited from recent advancements in natural language processing, in particular large language models. However, curr…

cs.CL2023

Retrieval-Augmented Neural Response Generation Using Logical Reasoning and Relevance Scoring

Nicholas Thomas Walker, Stefan Ultes, Pierre Lison

Constructing responses in task-oriented dialogue systems typically relies on information sources such the current dialogue state or external databases. This paper presents a novel…

cs.CL2023

Neural Text Sanitization with Privacy Risk Indicators: An Empirical Analysis

Anthi Papadopoulou, Pierre Lison, Mark Anderson +2

Text sanitization is the task of redacting a document to mask all occurrences of (direct or indirect) personal identifiers, with the goal of concealing the identity of the individu…

cs.CL2022

Bootstrapping Text Anonymization Models with Distant Supervision

Anthi Papadopoulou, Pierre Lison, Lilja Øvrelid +1

We propose a novel method to bootstrap text anonymization models based on distant supervision. Instead of requiring manually labeled training data, the approach relies on a knowled…

cs.CL2021

skweak: Weak Supervision Made Easy for NLP

Pierre Lison, Jeremy Barnes, Aliaksandr Hubin

We present skweak, a versatile, Python-based software toolkit enabling NLP developers to apply weak supervision to a wide range of NLP tasks. Weak supervision is an emerging machin…

cs.CL2026

Protecting De-identified Documents from Search-based Linkage Attacks

Pierre Lison, Mark Anderson

While de-identification models can help conceal the identity of the individuals mentioned in a document, they fail to address linkage risks, defined as the potential to map the de-…