Papers by Pierre Lison
OpenSubtitles2018: Statistical Rescoring of Sentence Alignments in Large, Noisy Parallel Corpora (L18-1)
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| Challenge: | Movie and TV subtitles are a valuable resource for the compilation of parallel corpora . however, the quality of the resulting sentence alignments is often lower than for other parallel corpoora. |
| Approach: | They propose to use movie and TV subtitles to extract parallel corpora from 3.7 million subtitles spread over 60 languages to obtain explicit quality scores for each sentence alignment. |
| Outcome: | The proposed model predicts translation probabilities with a root mean square error of 0.07 . the results show that the model can prune out low-quality alignments . |
Re-identification of De-identified Documents with Autoregressive Infilling (2025.acl-long)
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| Challenge: | Documents revealing sensitive information about individuals must typically be de-identified by masking all mentions of PII . |
| Approach: | They propose a method that attempts to reverse the process of re-identification based on a database of documents representing background knowledge. |
| Outcome: | The proposed method can recover as many as 80% of de-identified text spans and improve accuracy along with the level of background knowledge. |
Anonymisation Models for Text Data: State of the art, Challenges and Future Directions (2021.acl-long)
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| Challenge: | a paper examines the problem of automated text anonymisation . text anonymization is a prerequisite for secure sharing of documents containing sensitive information about individuals. |
| Approach: | They propose to incorporate explicit measures of disclosure risk into the text anonymisation process to reduce the risk of errors. |
| Outcome: | The proposed approach is based on a case study in which the authors outline the benefits and limitations of the proposed methods. |
skweak: Weak Supervision Made Easy for NLP (2021.acl-demo)
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| Challenge: | skweak is a Python-based toolkit for NLP developers to use weak supervision . labelled data remains a scarce resource in many practical NLP scenarios . |
| Approach: | They present a Python-based toolkit that allows NLP developers to use weak supervision . skweak is designed to facilitate the use of weak supervision for NLP tasks . |
| Outcome: | skweak is a Python-based toolkit that facilitates weak supervision . the toolkit provides a simple interface to apply labels to a large corpus of text data . |
Named Entity Recognition without Labelled Data: A Weak Supervision Approach (2020.acl-main)
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| Challenge: | Named Entity Recognition (NER) performance often degrades when applied to target domains that differ from the texts observed during training. |
| Approach: | They propose a method to learn NER models in the absence of labelled data through weak supervision by using a broad spectrum of labelling functions to automatically annotate texts from the target domain. |
| Outcome: | The proposed approach improves on two English datasets and shows that it improves by 7 percentage points on entity-level F1 scores compared to an out-of-domain neural NER model. |
Neural Text Sanitization with Explicit Measures of Privacy Risk (2022.aacl-main)
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| Challenge: | Personal data, also known as Personally Identifiable Information (PII), often abound in text documents. |
| Approach: | They propose a method for text sanitization that uses a neural entity recognizer to detect and classify potential personal identifiers and a classifier trained on labelled data to determine which entities to mask . |
| Outcome: | The proposed approach masks all personal identifiers and thereby conceals the identity of the individuals mentioned in the document. |
PyOpenDial: A Python-based Domain-Independent Toolkit for Developing Spoken Dialogue Systems with Probabilistic Rules (D19-3)
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| Challenge: | a recent development of spoken dialogue systems has enabled deep learning to achieve state-of-the-art performance. |
| Approach: | They propose a Python-based domain-independent, open-source toolkit for spoken dialogue systems. |
| Outcome: | The proposed toolkit extends OpenDial's Java-based architecture and provides new functions for neural dialogue state tracking and action planning. |
Bootstrapping Text Anonymization Models with Distant Supervision (2022.lrec-1)
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| Challenge: | Personal data is ubiquitous in text documents. |
| Approach: | They propose a method to bootstrap text anonymization models based on distant supervision by using a knowledge graph to annotate text documents including personal data. |
| Outcome: | The proposed method uses a knowledge graph to annotate text documents including personal data about a subset of individuals. |