Pierre Colombo

According to our database1, Pierre Colombo authored at least 47 papers between 2018 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
SaulLM-7B: A pioneering Large Language Model for Law.
CoRR, 2024

Tower: An Open Multilingual Large Language Model for Translation-Related Tasks.
CoRR, 2024

Enhanced Hallucination Detection in Neural Machine Translation through Simple Detector Aggregation.
CoRR, 2024

Towards Trustworthy Reranking: A Simple yet Effective Abstention Mechanism.
CoRR, 2024

Towards Cross-Tokenizer Distillation: the Universal Logit Distillation Loss for LLMs.
CoRR, 2024

CroissantLLM: A Truly Bilingual French-English Language Model.
CoRR, 2024

Unsupervised Layer-Wise Score Aggregation for Textual OOD Detection.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
A Halfspace-Mass Depth-Based Method for Adversarial Attack Detection.
Trans. Mach. Learn. Res., 2023

Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models.
CoRR, 2023

xCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detection.
CoRR, 2023

A Functional Data Perspective and Baseline On Multi-Layer Out-of-Distribution Detection.
CoRR, 2023

Towards More Robust NLP System Evaluation: Handling Missing Scores in Benchmarks.
CoRR, 2023

Hallucinations in Large Multilingual Translation Models.
CoRR, 2023

The Glass Ceiling of Automatic Evaluation in Natural Language Generation.
Proceedings of the Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023, 2023

A Novel Information Theoretic Objective to Disentangle Representations for Fair Classification.
Proceedings of the Findings of the Association for Computational Linguistics: IJCNLP-AACL 2023, 2023

Revisiting Instruction Fine-tuned Model Evaluation to Guide Industrial Applications.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

RainProof: An Umbrella to Shield Text Generator from Out-Of-Distribution Data.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Toward Stronger Textual Attack Detectors.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Transductive Learning for Textual Few-Shot Classification in API-based Embedding Models.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Steering Large Language Models for Machine Translation with Finetuning and In-Context Learning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Optimal Transport for Unsupervised Hallucination Detection in Neural Machine Translation.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
Rainproof: An Umbrella To Shield Text Generators From Out-Of-Distribution Data.
CoRR, 2022

Beyond Mahalanobis-Based Scores for Textual OOD Detection.
CoRR, 2022

KNIFE: Kernelized-Neural Differential Entropy Estimation.
CoRR, 2022


What are the best Systems? New Perspectives on NLP Benchmarking.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Beyond Mahalanobis Distance for Textual OOD Detection.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A Differential Entropy Estimator for Training Neural Networks.
Proceedings of the International Conference on Machine Learning, 2022

Of Human Criteria and Automatic Metrics: A Benchmark of the Evaluation of Story Generation.
Proceedings of the 29th International Conference on Computational Linguistics, 2022

Learning Disentangled Textual Representations via Statistical Measures of Similarity.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

InfoLM: A New Metric to Evaluate Summarization & Data2Text Generation.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Apprendre à représenter et à générer du texte en utilisant des mesures d'information. (Learning to represent and generate text using information measures).
PhD thesis, 2021

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation.
CoRR, 2021

Code-switched inspired losses for generic spoken dialog representations.
CoRR, 2021

Beam Search with Bidirectional Strategies for Neural Response Generation.
Proceedings of the 4th International Conference on Natural Language and Speech Processing, 2021

Automatic Text Evaluation through the Lens of Wasserstein Barycenters.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Code-switched inspired losses for spoken dialog representations.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Improving Multimodal fusion via Mutual Dependency Maximisation.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

A Novel Estimator of Mutual Information for Learning to Disentangle Textual Representations.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Guider l'attention dans les modeles de sequence a sequence pour la prediction des actes de dialogue.
CoRR, 2020

Heavy-tailed Representations, Text Polarity Classification & Data Augmentation.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

The importance of fillers for text representations of speech transcripts.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Hierarchical Pre-training for Sequence Labelling in Spoken Dialog.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Guiding Attention in Sequence-to-Sequence Models for Dialogue Act Prediction.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Affect-Driven Dialog Generation.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

From the Token to the Review: A Hierarchical Multimodal approach to Opinion Mining.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018
Disney at IEST 2018: Predicting Emotions using an Ensemble.
Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, 2018


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