Papers by Benjamin Rozonoyer

3 papers
xLM: A Python Package for Non-Autoregressive Language Models (2026.eacl-demo)

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Challenge: Autoregressive language models generate text sequentially from left to right by adding one token at a time.
Approach: They propose a python package that provides a suite of small non-autoregressive language models that can be used by researchers.
Outcome: The proposed package makes implementing small non-autoregressive language models faster and provides a suite of pre-trained models that can be used by the research community.
ExcavatorCovid: Extracting Events and Relations from Text Corpora for Temporal and Causal Analysis for COVID-19 (2021.emnlp-demo)

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Challenge: a new machine reading system ingests open-source text documents to analyze COVID-19 events . the system extracts COVId-19 related events and relations between them .
Approach: They propose a machine reading system that ingests open-source text documents and extracts COVID-19 related events and relations between them.
Outcome: The proposed system extracts COVID-19 related events and relations from open-source text . it will help government agencies alleviate the information overload and respond to COVId-19 .
Multistage Collaborative Knowledge Distillation from a Large Language Model for Semi-Supervised Sequence Generation (2024.acl-long)

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Challenge: Low-resource tasks such as semi-supervised sequence generation require expert knowledge and cost.
Approach: They propose a method for semi-supervised sequence generation where few examples are too scarce to fine tune a model.
Outcome: The proposed method can generalize better than its teacher to unseen examples on semi-supervised sequence generation tasks.

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