Carolin Lawrence

According to our database, Carolin Lawrence authored at least 31 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

A Human-Centric Evaluation Platform for Explainable Knowledge Graph Completion.

Zhao Xu, Wiem Ben Rim, Kiril Gashteovski, Timo Sztyler, Carolin Lawrence

Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

2023

State-Regularized Recurrent Neural Networks to Extract Automata and Explain Predictions.

Cheng Wang, Carolin Lawrence, Mathias Niepert

IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

Walking a Tightrope - Evaluating Large Language Models in High-Risk Domains.

Chia-Chien Hung, Wiem Ben Rim, Lindsay Frost, Lars Brückner, Carolin Lawrence

CoRR, 2023

Large Language Models Enable Few-Shot Clustering.

Vijay Viswanathan, Kiril Gashteovski, Carolin Lawrence, Tongshuang Wu, Graham Neubig

CoRR, 2023

Linking Surface Facts to Large-Scale Knowledge Graphs.

Gorjan Radevski, Kiril Gashteovski, Chia-Chien Hung, Carolin Lawrence, Goran Glavas

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Multi-Source Survival Domain Adaptation.

Ammar Shaker, Carolin Lawrence

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Human-Centric Research for NLP: Towards a Definition and Guiding Questions.

Bhushan Kotnis, Kiril Gashteovski, Julia Gastinger, Giuseppe Serra, Francesco Alesiani, Timo Sztyler, Ammar Shaker, Na Gong, Carolin Lawrence, Zhao Xu

CoRR, 2022

A Human-Centric Assessment Framework for AI.

Sascha Saralajew, Ammar Shaker, Zhao Xu, Kiril Gashteovski, Bhushan Kotnis, Wiem Ben Rim, Jürgen Quittek, Carolin Lawrence

CoRR, 2022

Uncertainty Propagation in Node Classification.

Zhao Xu, Carolin Lawrence, Ammar Shaker, Raman Siarheyeu

Proceedings of the IEEE International Conference on Data Mining, 2022

KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Models.

Haris Widjaja, Kiril Gashteovski, Wiem Ben Rim, Pengfei Liu, Christopher Malon, Daniel Ruffinelli, Carolin Lawrence, Graham Neubig

Proceedings of the The 2022 Conference on Empirical Methods in Natural Language Processing, 2022

MILIE: Modular & Iterative Multilingual Open Information Extraction.

Bhushan Kotnis, Kiril Gashteovski, Daniel Rubio, Ammar Shaker, Vanesa Rodriguez-Tembras, Makoto Takamoto, Mathias Niepert, Carolin Lawrence

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation.

Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Mathias Niepert, Goran Glavas

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark.

Niklas Friedrich, Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Mathias Niepert, Goran Glavas

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022

2021

Integrating diverse extraction pathways using iterative predictions for Multilingual Open Information Extraction.

Bhushan Kotnis, Kiril Gashteovski, Carolin Lawrence, Daniel Oñoro-Rubio, Vanesa Rodriguez-Tembras, Makoto Takamoto, Mathias Niepert

CoRR, 2021

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

Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Goran Glavas, Mathias Niepert

CoRR, 2021

VEGN: Variant Effect Prediction with Graph Neural Networks.

Jun Cheng, Carolin Lawrence, Mathias Niepert

CoRR, 2021

Interpreting Node Embedding with Text-labeled Graphs.

Giuseppe Serra, Zhao Xu, Mathias Niepert, Carolin Lawrence, Peter Tiño, Xin Yao

Proceedings of the International Joint Conference on Neural Networks, 2021

Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs.

Cheng Wang, Carolin Lawrence, Mathias Niepert

Proceedings of the 9th International Conference on Learning Representations, 2021

Behavioral Testing of Knowledge Graph Embedding Models for Link Prediction.

Wiem Ben Rim, Carolin Lawrence, Kiril Gashteovski, Mathias Niepert, Naoaki Okazaki

Proceedings of the 3rd Conference on Automated Knowledge Base Construction, 2021

Offline Reinforcement Learning from Human Feedback in Real-World Sequence-to-Sequence Tasks.

Julia Kreutzer, Stefan Riezler, Carolin Lawrence

Proceedings of the 5th Workshop on Structured Prediction for NLP, 2021

Explaining Neural Matrix Factorization with Gradient Rollback.

Carolin Lawrence, Timo Sztyler, Mathias Niepert

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders.

Bhushan Kotnis, Carolin Lawrence, Mathias Niepert

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Learning from Human Feedback: Challenges for Real-World Reinforcement Learning in NLP.

Julia Kreutzer, Stefan Riezler, Carolin Lawrence

CoRR, 2020

2019

Response-Based and Counterfactual Learning for Sequence-to-Sequence Tasks in NLP.

Carolin Lawrence

PhD thesis, 2019

Learning Neural Sequence-to-Sequence Models from Weak Feedback with Bipolar Ramp Loss.

Laura Jehl, Carolin Lawrence, Stefan Riezler

Trans. Assoc. Comput. Linguistics, 2019

Attending to Future Tokens for Bidirectional Sequence Generation.

Carolin Lawrence, Bhushan Kotnis, Mathias Niepert

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

2018

Counterfactual Learning from Human Proofreading Feedback for Semantic Parsing.

Carolin Lawrence, Stefan Riezler

CoRR, 2018

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

Carolin Lawrence, Stefan Riezler

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Counterfactual Learning for Machine Translation: Degeneracies and Solutions.

Carolin Lawrence, Pratik Gajane, Stefan Riezler

CoRR, 2017

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

Carolin Lawrence, Artem Sokolov, Stefan Riezler

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

2016

NLmaps: A Natural Language Interface to Query OpenStreetMap.

Carolin Lawrence, Stefan Riezler

Proceedings of the COLING 2016, 2016