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07/02/2023
Large Language Models Enable Few-Shot Clustering
Unlike traditional unsupervised clustering, semi-supervised clustering a...
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04/03/2023
Uncertainty Propagation in Node Classification
Quantifying predictive uncertainty of neural networks has recently attra...
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12/10/2022
State-Regularized Recurrent Neural Networks to Extract Automata and Explain Predictions
Recurrent neural networks are a widely used class of neural architecture...
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12/01/2022
Multi-Source Survival Domain Adaptation
Survival analysis is the branch of statistics that studies the relation ...
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08/23/2022
KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Models
Knowledge Graphs (KGs) store information in the form of (head, predicate...
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07/10/2022
Human-Centric Research for NLP: Towards a Definition and Guiding Questions
With Human-Centric Research (HCR) we can steer research activities so th...
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05/25/2022
A Human-Centric Assessment Framework for AI
With the rise of AI systems in real-world applications comes the need fo...
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10/15/2021
Integrating diverse extraction pathways using iterative predictions for Multilingual Open Information Extraction
In this paper we investigate a simple hypothesis for the Open Informatio...
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09/15/2021
AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark
Open Information Extraction (OIE) is the task of extracting facts from s...
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09/14/2021
BenchIE: Open Information Extraction Evaluation Based on Facts, Not Tokens
Intrinsic evaluations of OIE systems are carried out either manually – w...
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06/25/2021
VEGN: Variant Effect Prediction with Graph Neural Networks
Genetic mutations can cause disease by disrupting normal gene function. ...
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11/24/2020
Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs
Uncertainty quantification is crucial for building reliable and trustabl...
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11/04/2020
Learning from Human Feedback: Challenges for Real-World Reinforcement Learning in NLP
Large volumes of interaction logs can be collected from NLP systems that...
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10/12/2020
Explaining Neural Matrix Factorization with Gradient Rollback
Explaining the predictions of neural black-box models is an important pr...
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04/06/2020
Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders
Representation learning for knowledge graphs (KGs) has focused on the pr...
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08/16/2019
Attending to Future Tokens For Bidirectional Sequence Generation
Neural sequence generation is typically performed token-by-token and lef...
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07/06/2019
Learning Neural Sequence-to-Sequence Models from Weak Feedback with Bipolar Ramp Loss
In many machine learning scenarios, supervision by gold labels is not av...
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11/29/2018
Counterfactual Learning from Human Proofreading Feedback for Semantic Parsing
In semantic parsing for question-answering, it is often too expensive to...
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05/03/2018
Improving a Neural Semantic Parser by Counterfactual Learning from Human Bandit Feedback
Counterfactual learning from human bandit feedback describes a scenario ...
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11/23/2017
Counterfactual Learning for Machine Translation: Degeneracies and Solutions
Counterfactual learning is a natural scenario to improve web-based machi...
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07/28/2017