Papers by Céline Hudelot
A French Corpus for Event Detection on Twitter (2020.lrec-1)
Copied to clipboard
| Challenge: | Existing datasets may have different definitions of event or topic, which leads to inconsistent results. |
| Approach: | They present a corpus annotated for event detection tasks consisting of 38 million tweets in French and 130,000 manually annotating tweets as related or unrelated to a given event. |
| Outcome: | The proposed method performs best on 38 million tweets in French and another publicly available dataset of tweets. |
Revisiting Instruction Fine-tuned Model Evaluation to Guide Industrial Applications (2023.emnlp-main)
Copied to clipboard
| Challenge: | Instruction fine-tuned (IFT) models are gaining traction in industrial NLP to unlock task-specific performance gains and strengthen model alignment with industry requirements. |
| Approach: | They propose to use instruction fine-tuned (IFT) models to enhance the zero-shot capabilities of Large Language Models (LLMs) they also propose to leverage IFT models to analyze the trade-offs that emerge in industrial settings. |
| Outcome: | The proposed model is well adapted to new evaluation metric requirements, and offers practical insights for real-world LLM deployment. |