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Nigel Collier

6 أوراق في مجموعة PaperMetrix

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أوراق هذا المؤلف

  1. Self-Alignment Pretraining for Biomedical Entity Representations

    2021

    Fangyu Liu, Ehsan Shareghi, Zaiqiao Meng, Marco Basaldella, Nigel Collier. Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. 2021.

  2. FireAct: Toward Language Agent Fine-tuning

    2023 · arXiv (Cornell University)

    Recent efforts have augmented language models (LMs) with external tools or environments, leading to the development of language agents that can reason and act. However, most of these agents rely on few-shot prompting techniques with …

  3. LUQ: Long-text Uncertainty Quantification for LLMs

    2024

    Large Language Models (LLMs) have demonstrated remarkable capability in a variety of NLP tasks.However, LLMs are also prone to generate nonfactual content.Uncertainty Quantification (UQ) is pivotal in enhancing our understanding of a model's confidence on …

  4. Prompt Compression for Large Language Models: A Survey

    2025

    Zongqian Li, Yinhong Liu, Yixuan Su, Nigel Collier. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2025.

  5. Normalising Medical Concepts in Social Media Texts by Learning Semantic Representation

    2016

    Automatically recognising medical concepts mentioned in social media messages (e.g. tweets) enables several applications for enhancing health quality of people in a community, e.g. real-time monitoring of infectious diseases in population. However, the discrepancy between …

  6. SemEval-2017 Task 2: Multilingual and Cross-lingual Semantic Word Similarity

    2017

    This paper introduces a new task on Multilingual and Cross-lingual Semantic Word Similarity which measures the semantic similarity of word pairs within and across five languages: English, Farsi, German, Italian and Spanish. High quality datasets …