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People
Dr. Carolin Lawrence

Manager, Human-Centric AI and Chief Research Scientist

Carolin leads the Human-Centric AI group in the area of artificial intelligence that research and develop machine learning, natural language processing and explainable AI. The Human-Centric AI  team works towards enabling human-AI collaboration to empower society.

Group Involvement, NEC Laboratories Europe

Human-Centric AI Group

Research Interests

Natural Language Processing
Explainable AI
Machine Learning
Human-Centric AI that enables human-AI collaboration to empower society

Publications

  • Large Language Models Enable Few-Shot Clustering. Vijay Viswanathan, Kiril Gashteovski, Carolin Lawrence, Tongshuang Wu, Graham Neubig. Transactions of the Association for Computational Linguistics (ACL) 2024.
  • Improving Cross-Lingual Transfer for Open Information Extraction with Linguistic Feature Projection. Youmi Ma, Bhushan Kotnis, Carolin Lawrence, Goran Glavaš, Naoaki Okazaki. The 3rd Multilingual Representation Learning (MRL) Workshop [Co-located with EMNLP] 2023.
  • Walking a Tightrope – Evaluating Large Language Models in High-Risk Domains. Chia-Chien Hung, Wiem Ben Rim, Lindsay Frost, Lars Bruckner, Carolin Lawrence. GenBench Workshop [The first workshop on (benchmarking) generalisation in NLP] (EMNLP Workshop) 2023.
  • Linking Surface Facts to Large-Scale Knowledge Graphs. Gorjan Radevski, Kiril Gashteovski, Chia-Chien Hung, Carolin Lawrence, Goran Glavaš. EMNLP 2023.
  • Uncertainty Propagation in Node Classification. Zhao Xu, Carolin Lawrence, Ammar Shaker, Raman Siarheyeu. International Conference on Data Mining (ICDM) 2022.
  • Multi-Source Survival Domain Adaptation. Ammar Shaker, Carolin Lawrence. The 37th AAAI Conference on Artificial Intelligence (AAAI).
  • 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. In System Demonstrations of the 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP).
  • State-Regularized Recurrent Neural Networks to Extract Automata and Explain Predictions. Cheng Wang, Mathias Niepert, Carolin Lawrence. In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
  • Towards Modeling Uncertainty Propagation in Node Classification. Zhao Xu, Carolin Lawrence, Ammar Shaker, Raman Siarheyeu. In IEEE International Conference on Data Mining 2022 (ICDM).
  • MillIE: Modular & Iterative Multilingual Open Information Extraction. Bhushan Kotnis, Kiril Gashteovski, Daniel Onoro Rubio, Ammar Shaker, Vanesa Rodriguez-Tembras, Makoto Takamoto, Mathias Niepert, Carolin Lawrence. In 60th Annual Meeting of the Association for Computational Linguistics (ACL).
  • BenchIE: A Framework for Multi-Faceted Fact-Based Open Information Extraction Evaluation. Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Mathias Niepert, Goran Glavaš. In 60th Annual Meeting of the Association for Computational Linguistics (ACL).
  • AnnIE: An Annotation Platform for Constructing Complete Open Information Extraction Benchmark. Niklas Friedrich, Kiril Gashteovski, Mingying Yu, Bhushan Kotnis, Carolin Lawrence, Mathias Niepert, Goran Glavaš. In System Demonstrations of 60th Annual Meeting of the Association for Computational Linguistics (ACL).
  • Outstanding Paper Award Behavioral Testing of Knowledge Graph Embedding Models for Link Prediction. Wiem Ben Rim, Carolin Lawrence, Kiril Gashteovski, Mathias Niepert, Naoaki Okazaki. In Conference on Automated Knowledge Base Construction (AKBC).
  • Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs. Cheng Wang, Carolin Lawrence, Mathias Niepert. Ninth International Conference on Learning Representations (ICLR).
  • Explaining Neural Matrix Factorization with Gradient Rollback. Carolin Lawrence, Timo Sztyler, Mathias Niepert. 35th AAAI Conference on Artificial Intelligence (AAAI).
  • Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders. Bhushan Kotnis, Carolin Lawrence, Mathias Niepert. 35th AAAI Conference on Artificial Intelligence (AAAI).
  • Attending to Future Tokens for Bidirectional Sequence Generation. Carolin Lawrence, Bhushan Kotnis, Mathias Niepert. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP).
  • Attending to Future Tokens for Bidirectional Sequence Generation. Carolin Lawrence, Bhushan Kotnis, Mathias Niepert. Presented at the 3rd Workshop on Neural Generation and Translation (WNGT 2019).
  • Learning Neural Sequence-to-Sequence Models from Weak Feedback with Bipolar Ramp Loss. Laura Jehl, Carolin Lawrence, Stefan Riezler. In Transactions of the Association for Computational Linguistics (TACL Vol. 7).
  • Building a Biomedical Knowledge Graph and Predicting Novel Relations. Timo Sztyler, Carolin Lawrence, Brandon Malone. In the workshop Scientific Literature Knowledge Bases, co-located with Automated Knowledge Base Construction (AKBC).
  • Response-Based and Counterfactual Learning for Sequence-to-Sequence Tasks in NLP. Carolin Lawrence. Doctoral Thesis (summa cum laude), Heidelberg, Germany.
  • Counterfactual Learning from Human Proofreading Feedback for Semantic Parsing Carolin Lawrence, Stefan Riezler. Presented at the Workshop “Learning by Instruction” at the 32nd Conference on Neural Information Processing Systems (NeurIPS 2018), MontrĂ©al, Canada.
  • Improving a Neural Semantic Parser by Counterfactual Learning from Human Bandit Feedback. Carolin Lawrence, Stefan Riezler. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (ACL 2018), Melbourne, Australia.
  • Counterfactual Learning for Machine Translation: Degeneracies and Solutions Carolin Lawrence, Pratik Gajane, Stefan Riezler. Presented at the Workshop “From ’What If?’ To ’What Next?’” at the 31st Conference on Neural Information Processing Systems (NeurIPS 2017), Long Beach, CA.
  • Counterfactual Learning from Bandit Feedback under Deterministic Logging: A Case Study in Statistical Machine Translation. Carolin Lawrence, Artem Sokolov, Stefan Riezler. In Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP 2017), Copenhagen, Denmark.
  • NLmaps: A Natural Language Interface to Query OpenStreetMap. Carolin Lawrence, Stefan Riezler. In Proceedings of the International Conference on Computational Linguistics: System Demonstrations (COLING 2016), Osaka, Japan.
  • A Corpus and Semantic Parser for Natural Language Querying of OpenStreetMap. Carolin Haas, Stefan Riezler. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT 2016), San Diego, CA.
  • Response-based Learning for Machine Translation of Open-domain Database Queries. Carolin Haas, Stefan Riezler. In Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics – Human Language Technologies (NAACL HLT 2015), Denver, CO.
  • Response-based Learning for Grounded Machine Translation. Stefan Riezler, Patrick Simianer and Carolin Haas. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014), Baltimore, MD.
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