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Maxime Jean Julien Peyrard

Publications associées (8)

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Generative language models (LMs) have become omnipresent across data science. For a wide variety of tasks, inputs can be phrased as natural language prompts for an LM, from whose output the solution can then be extracted. LM performance has consistently be ...

Assoc Computing Machinery2024

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A critical component of a successful language generation pipeline is the decoding algorithm. However, the general principles that should guide the choice of a decoding algorithm re- main unclear. Previous works only compare decoding algorithms in narrow sc ...

2023

Distribution Inference Risks: Identifying and Mitigating Sources of Leakage

Robert West, Maxime Jean Julien Peyrard, Valentin Hartmann, Léo Nicolas René Meynent

A large body of work shows that machine learning (ML) models can leak sensitive or confidential information about their training data. Recently, leakage due to distribution inference (or property inference) attacks is gaining attention. In this attack, the ...

IEEE COMPUTER SOC2023

REFINER: Reasoning Feedback on Intermediate Representations

Boi Faltings, Robert West, Maxime Jean Julien Peyrard, Antoine Bosselut, Beatriz Maria Borges Ribeiro, Debjit Paul, Mahammad Ismayilzada

Language models (LMs) have recently shown remarkable performance on reasoning tasks by explicitly generating intermediate inferences, e.g., chain-of-thought prompting. However, these intermediate inference steps may be in- appropriate deductions from the i ...

2023

GenIE: Generative Information Extraction

Robert West, Maxime Jean Julien Peyrard, Martin Josifoski

Structured and grounded representation of text is typically formalized by closed information extraction, the problem of extracting an exhaustive set of (subject, relation, object) triplets that are consistent with a predefined set of entities and relations ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2022

On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation

Robert West, Maxime Jean Julien Peyrard, Yang Gao, Wei Zhao

Evaluation of cross-lingual encoders is usually performed either via zero-shot cross-lingual transfer in supervised downstream tasks or via unsupervised cross-lingual textual similarity. In this paper, we concern ourselves with reference-free machine trans ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2020

Studying Summarization Evaluation Metrics in the Appropriate Scoring Range

Maxime Jean Julien Peyrard

In summarization, automatic evaluation metrics are usually compared based on their ability to correlate with human judgments. Unfortunately, the few existing human judgment datasets have been created as by-products of the manual evaluations performed durin ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2019

Research on summarization has mainly been driven by empirical approaches, crafting systems to perform well on standard datasets with the notion of information Importance remaining latent. We argue that establishing theoretical models of Importance will adv ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2019