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Timothée Bernard

4 accepted papers

2025

On the Relation Between Fine-Tuning, Topological Properties, and Task Performance in Sense-Enhanced Embeddings

ACL 2025long

Topological properties of embeddings, such as isotropy and uniformity, are closely linked to their expressiveness, and improving these properties enhances the embeddings’ ability to capture nuanced semantic distinctions. However, fine-tuning can reduce the expressiveness of the embeddings of languag…

Cited by 0SourcePDFScholar
2024

NuNER: Entity Recognition Encoder Pre-training via LLM-Annotated Data

EMNLP 2024main

Large Language Models (LLMs) have shown impressive abilities in data annotation, opening the way for new approaches to solve classic NLP problems. In this paper, we show how to use LLMs to create NuNER, a compact language representation model specialized in the Named Entity Recognition (NER) task. N…

2023

So many design choices: Improving and interpreting neural agent communication in signaling games

ACL 2023findings

Emergent language games are experimental protocols designed to model how communication may arise among a group of agents. In this paper, we focus on how to improve performances of neural agents playing a signaling game: a sender is exposed to an image and generates a sequence of symbols that is tran…

Cited by 5SourcePDFScholar
2020

What Meaning-Form Correlation Has to Compose With: A Study of MFC on Artificial and Natural Language

COLING 2020main

Compositionality is a widely discussed property of natural languages, although its exact definition has been elusive. We focus on the proposal that compositionality can be assessed by measuring meaning-form correlation. We analyze meaning-form correlation on three sets of languages: (i) artificial t…