John Giorgi
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View article: TOPICAL: TOPIC Pages AutomagicaLly
TOPICAL: TOPIC Pages AutomagicaLly Open
Topic pages aggregate useful information about an entity or concept into a single succinct and accessible article. Automated creation of topic pages would enable their rapid curation as information resources, providing an alternative to tr…
View article: Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset
Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset Open
The quest for human imitative AI has been an enduring topic in AI research since its inception. The technical evolution and emerging capabilities of the latest cohort of large language models (LLMs) have reinvigorated the subject beyond ac…
View article: WangLab at MEDIQA-Chat 2023: Clinical Note Generation from Doctor-Patient Conversations using Large Language Models
WangLab at MEDIQA-Chat 2023: Clinical Note Generation from Doctor-Patient Conversations using Large Language Models Open
This paper describes our submission to the MEDIQA-Chat 2023 shared task for automatic clinical note generation from doctor-patient conversations. We report results for two approaches: the first fine-tunes a pre-trained language model (PLM)…
View article: Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval
Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval Open
Multi-document summarization (MDS) assumes a set of topic-related documents are provided as input. In practice, this document set is not always available; it would need to be retrieved given an information need, i.e. a question or topic st…
View article: WangLab at MEDIQA-Chat 2023: Clinical Note Generation from Doctor-Patient Conversations using Large Language Models
WangLab at MEDIQA-Chat 2023: Clinical Note Generation from Doctor-Patient Conversations using Large Language Models Open
This paper describes our submission to the MEDIQA-Chat 2023 shared task for automatic clinical note generation from doctor-patient conversations. We report results for two approaches: the first fine-tunes a pre-trained language model (PLM)…
View article: Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval
Open Domain Multi-document Summarization: A Comprehensive Study of Model Brittleness under Retrieval Open
Multi-document summarization (MDS) assumes a set of topic-related documents are provided as input. In practice, this document set is not always available; it would need to be retrieved given an information need, i.e. a question or topic st…
View article: A sequence-to-sequence approach for document-level relation extraction
A sequence-to-sequence approach for document-level relation extraction Open
Motivated by the fact that many relations cross the sentence boundary, there has been increasing interest in document-level relation extraction (DocRE). DocRE requires integrating information within and across sentences, capturing complex …
View article: A sequence-to-sequence approach for document-level relation extraction
A sequence-to-sequence approach for document-level relation extraction Open
Motivated by the fact that many relations cross the sentence boundary, there has been increasing interest in document-level relation extraction (DocRE). DocRE requires integrating information within and across sentences, capturing complex …
View article: A flexible search system for high-accuracy identification of biological entities and molecules
A flexible search system for high-accuracy identification of biological entities and molecules Open
Identifying subcellular biological entities (genes, gene products, and small molecules) is essential in using and creating bioinformatics analysis tools, text mining, and accessible biological research apps.When research information is uni…
View article: Author response: Author-sourced capture of pathway knowledge in computable form using Biofactoid
Author response: Author-sourced capture of pathway knowledge in computable form using Biofactoid Open
Article Figures and data Abstract Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Making the knowledge contained in scientif…
View article: Capturing scientific knowledge in computable form
Capturing scientific knowledge in computable form Open
Technological advances in computing provide major opportunities to accelerate scientific discovery. The wide availability of structured knowledge would allow us to take full advantage of these by enabling efficient human-computer interacti…
View article: DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations
DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations Open
John Giorgi, Osvald Nitski, Bo Wang, Gary Bader. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 20…
View article: Capturing scientific knowledge in computable form
Capturing scientific knowledge in computable form Open
Technological advances in computing provide major opportunities to complement human reasoning and to dramatically speed up science - but only if structured knowledge is available to enable efficient communication between humans and compute…
View article: DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations
DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations Open
Sentence embeddings are an important component of many natural language processing (NLP) systems. Like word embeddings, sentence embeddings are typically learned on large text corpora and then transferred to various downstream tasks, such …
View article: End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models
End-to-end Named Entity Recognition and Relation Extraction using Pre-trained Language Models Open
Named entity recognition (NER) and relation extraction (RE) are two important tasks in information extraction and retrieval (IE \& IR). Recent work has demonstrated that it is beneficial to learn these tasks jointly, which avoids the propa…
View article: Towards reliable named entity recognition in the biomedical domain
Towards reliable named entity recognition in the biomedical domain Open
Motivation Automatic biomedical named entity recognition (BioNER) is a key task in biomedical information extraction. For some time, state-of-the-art BioNER has been dominated by machine learning methods, particularly conditional random fi…
View article: Towards reliable named entity recognition in the biomedical domain
Towards reliable named entity recognition in the biomedical domain Open
Motivation: Automatic biomedical named entity recognition (BioNER) is a key task in biomedical information extraction (IE). For some time, state-of-the-art BioNER has been dominated by machine learning methods, particularly conditional ran…
View article: Transfer learning for biomedical named entity recognition with neural networks
Transfer learning for biomedical named entity recognition with neural networks Open
Motivation The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as ge…
View article: Transfer learning for biomedical named entity recognition with neural networks
Transfer learning for biomedical named entity recognition with neural networks Open
Motivation The explosive increase of biomedical literature has made information extraction an increasingly important tool for biomedical research. A fundamental task is the recognition of biomedical named entities in text (BNER) such as ge…
View article: High intraspecific genome diversity in the model arbuscular mycorrhizal symbiont <i>Rhizophagus irregularis</i>
High intraspecific genome diversity in the model arbuscular mycorrhizal symbiont <i>Rhizophagus irregularis</i> Open
Summary Arbuscular mycorrhizal fungi ( AMF ) are known to improve plant fitness through the establishment of mycorrhizal symbioses. Genetic and phenotypic variations among closely related AMF isolates can significantly affect plant growth,…