Carolin Lawrence | DeepAI

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∙ 07/02/2023

Large Language Models Enable Few-Shot Clustering

Unlike traditional unsupervised clustering, semi-supervised clustering a...

0 Vijay Viswanathan, et al. ∙

∙ 04/03/2023

Uncertainty Propagation in Node Classification

Quantifying predictive uncertainty of neural networks has recently attra...

4 Zhao Xu, et al. ∙

∙ 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...

0 Cheng Wang, et al. ∙

∙ 12/01/2022

Multi-Source Survival Domain Adaptation

Survival analysis is the branch of statistics that studies the relation ...

0 Ammar Shaker, et al. ∙

∙ 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...

0 Haris Widjaja, et al. ∙

∙ 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...

7 Bhushan Kotnis, et al. ∙

∙ 05/25/2022

A Human-Centric Assessment Framework for AI

With the rise of AI systems in real-world applications comes the need fo...

0 Sascha Saralajew, et al. ∙

∙ 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...

0 Bhushan Kotnis, et al. ∙

∙ 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...

0 Niklas Friedrich, et al. ∙

∙ 09/14/2021

BenchIE: Open Information Extraction Evaluation Based on Facts, Not Tokens

Intrinsic evaluations of OIE systems are carried out either manually – w...

0 Kiril Gashteovski, et al. ∙

∙ 06/25/2021

VEGN: Variant Effect Prediction with Graph Neural Networks

Genetic mutations can cause disease by disrupting normal gene function. ...

6 Jun Cheng, et al. ∙

∙ 11/24/2020

Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs

Uncertainty quantification is crucial for building reliable and trustabl...

2 Cheng Wang, et al. ∙

∙ 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...

73 Julia Kreutzer, et al. ∙

∙ 10/12/2020

Explaining Neural Matrix Factorization with Gradient Rollback

Explaining the predictions of neural black-box models is an important pr...

0 Carolin Lawrence, et al. ∙

∙ 04/06/2020

Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders

Representation learning for knowledge graphs (KGs) has focused on the pr...

0 Bhushan Kotnis, et al. ∙

∙ 08/16/2019

Attending to Future Tokens For Bidirectional Sequence Generation

Neural sequence generation is typically performed token-by-token and lef...

3 Carolin Lawrence, et al. ∙

∙ 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...

0 Laura Jehl, et al. ∙

∙ 11/29/2018

Counterfactual Learning from Human Proofreading Feedback for Semantic Parsing

In semantic parsing for question-answering, it is often too expensive to...

0 Carolin Lawrence, et al. ∙

∙ 05/03/2018

Improving a Neural Semantic Parser by Counterfactual Learning from Human Bandit Feedback

Counterfactual learning from human bandit feedback describes a scenario ...

0 Carolin Lawrence, et al. ∙

∙ 11/23/2017

Counterfactual Learning for Machine Translation: Degeneracies and Solutions

Counterfactual learning is a natural scenario to improve web-based machi...

0 Carolin Lawrence, et al. ∙

∙ 07/28/2017

Counterfactual Learning from Bandit Feedback under Deterministic Logging: A Case Study in Statistical Machine Translation

The goal of counterfactual learning for statistical machine translation ...

0 Carolin Lawrence, et al. ∙

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