12 citations · 17 across the 10 of their papers we have counts for
10 papers
Command A: An Enterprise-Ready Large Language Model
Team Cohere, :, Aakanksha +227
In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…
Leveraging Large Language Models for Zero-shot Lay Summarisation in Biomedicine and Beyond
Tomas Goldsack, Carolina Scarton, Chenghua Lin
In this work, we explore the application of Large Language Models to zero-shot Lay Summarisation. We propose a novel two-stage framework for Lay Summarisation based on real-life pr…
Observing Micromotives and Macrobehavior of Large Language Models
Yuyang Cheng, Xingwei Qu, Tomas Goldsack +2
Thomas C. Schelling, awarded the 2005 Nobel Memorial Prize in Economic Sciences, pointed out that ``individuals decisions (micromotives), while often personal and localized, can le…
From Facts to Insights: A Study on the Generation and Evaluation of Analytical Reports for Deciphering Earnings Calls
Tomas Goldsack, Yang Wang, Chenghua Lin +1
This paper explores the use of Large Language Models (LLMs) in the generation and evaluation of analytical reports derived from Earnings Calls (ECs). Addressing a current gap in re…
Overview of the BioLaySumm 2024 Shared Task on the Lay Summarization of Biomedical Research Articles
Tomas Goldsack, Carolina Scarton, Matthew Shardlow +1
This paper presents the setup and results of the second edition of the BioLaySumm shared task on the Lay Summarisation of Biomedical Research Articles, hosted at the BioNLP Worksho…
ATLAS: Improving Lay Summarisation with Attribute-based Control
Zhihao Zhang, Tomas Goldsack, Carolina Scarton +1
Lay summarisation aims to produce summaries of scientific articles that are comprehensible to non-expert audiences. However, previous work assumes a one-size-fits-all approach, whe…
Overview of the BioLaySumm 2023 Shared Task on Lay Summarization of Biomedical Research Articles
Tomas Goldsack, Zheheng Luo, Qianqian Xie +4
This paper presents the results of the shared task on Lay Summarisation of Biomedical Research Articles (BioLaySumm), hosted at the BioNLP Workshop at ACL 2023. The goal of this sh…
Enhancing Biomedical Lay Summarisation with External Knowledge Graphs
Tomas Goldsack, Zhihao Zhang, Chen Tang +2
Previous approaches for automatic lay summarisation are exclusively reliant on the source article that, given it is written for a technical audience (e.g., researchers), is unlikel…
Improving Biomedical Abstractive Summarisation with Knowledge Aggregation from Citation Papers
Chen Tang, Shun Wang, Tomas Goldsack +1
Abstracts derived from biomedical literature possess distinct domain-specific characteristics, including specialised writing styles and biomedical terminologies, which necessitate…
Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature
Tomas Goldsack, Zhihao Zhang, Chenghua Lin +1
Lay summarisation aims to jointly summarise and simplify a given text, thus making its content more comprehensible to non-experts. Automatic approaches for lay summarisation can pr…