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05/04/2023
An automatically discovered chain-of-thought prompt generalizes to novel models and datasets
Emergent chain-of-thought (CoT) reasoning capabilities promise to improv...
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03/30/2023
Model-agnostic explainable artificial intelligence for object detection in image data
Object detection is a fundamental task in computer vision, which has bee...
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03/15/2023
Applying unsupervised keyphrase methods on concepts extracted from discharge sheets
Clinical notes containing valuable patient information are written by di...
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01/27/2023
ThoughtSource: A central hub for large language model reasoning data
Large language models (LLMs) such as GPT-3 and ChatGPT have recently dem...
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04/25/2022
A global analysis of metrics used for measuring performance in natural language processing
Measuring the performance of natural language processing models is chall...
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03/09/2022
Mapping global dynamics of benchmark creation and saturation in artificial intelligence
Benchmarks are crucial to measuring and steering progress in artificial ...
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02/25/2022
Deep Learning, Natural Language Processing, and Explainable Artificial Intelligence in the Biomedical Domain
In this article, we first give an introduction to artificial intelligenc...
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01/18/2022
Benchmark datasets driving artificial intelligence development fail to capture the needs of medical professionals
Publicly accessible benchmarks that allow for assessing and comparing mo...
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11/16/2021
Improving the robustness and accuracy of biomedical language models through adversarial training
Deep transformer neural network models have improved the predictive accu...
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10/04/2021
A curated, ontology-based, large-scale knowledge graph of artificial intelligence tasks and benchmarks
Research in artificial intelligence (AI) is addressing a growing number ...
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09/16/2021
SAFRAN: An interpretable, rule-based link prediction method outperforming embedding models
Neural embedding-based machine learning models have shown promise for pr...
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09/06/2021
GPT-3 Models are Poor Few-Shot Learners in the Biomedical Domain
Deep neural language models have set new breakthroughs in many tasks of ...
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08/27/2021
Deep learning models are not robust against noise in clinical text
Artificial Intelligence (AI) systems are attracting increasing interest ...
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08/27/2021
Evaluating the Robustness of Neural Language Models to Input Perturbations
High-performance neural language models have obtained state-of-the-art r...
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12/20/2020
Explaining Black-box Models for Biomedical Text Classification
In this paper, we propose a novel method named Biomedical Confident Item...
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12/10/2020
Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs
Neural embedding-based machine learning models have shown promise for pr...
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10/21/2020
Explaining black-box text classifiers for disease-treatment information extraction
Deep neural networks and other intricate Artificial Intelligence (AI) mo...
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08/06/2020
A critical analysis of metrics used for measuring progress in artificial intelligence
Comparing model performances on benchmark datasets is an integral part o...
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05/15/2020
Benchmarking neural embeddings for link prediction in knowledge graphs under semantic and structural changes
Recently, link prediction algorithms based on neural embeddings have gai...
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05/05/2020
Post-hoc explanation of black-box classifiers using confident itemsets
It is difficult to trust decisions made by Black-box Artificial Intellig...
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02/25/2020
Dividing the Ontology Alignment Task with Semantic Embeddings and Logic-based Modules
Large ontologies still pose serious challenges to state-of-the-art ontol...
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12/10/2019
OpenBioLink: A benchmarking framework for large-scale biomedical link prediction
SUMMARY: Recently, novel machine-learning algorithms have shown potentia...
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12/10/2019
OpenBioLink: A resource and benchmarking framework for large-scale biomedical link prediction
SUMMARY: Recently, novel machine-learning algorithms have shown potentia...
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08/06/2019
Clustering of Deep Contextualized Representations for Summarization of Biomedical Texts
In recent years, summarizers that incorporate domain knowledge into the ...
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07/27/2018
Global and local evaluation of link prediction tasks with neural embeddings
We focus our attention on the link prediction problem for knowledge grap...
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05/31/2018
Breaking-down the Ontology Alignment Task with a Lexical Index and Neural Embeddings
Large ontologies still pose serious challenges to state-of-the-art ontol...
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04/30/2018
Fast and scalable learning of neuro-symbolic representations of biomedical knowledge
In this work we address the problem of fast and scalable learning of neu...
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02/12/2015