2024

  • Large Language Models Enable Few-Shot Clustering. Vijay Viswanathan, Kiril Gashteovski, Carolin Lawrence, Tongshuang Wu, Grahama Neubig. In Transactions of the Association for Computational Linguistics, presenting at (NAACL 2024). (pdf)

  • Generating and Evaluating Plausible Explanations for Knowledge Graph Completion. Antonio Di Mauro, Zhao Xu, Wiem Ben Rim, Timo Sztyler, Carolin Lawrence. In 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024).

  • A Human-Centric Assessment of the Usefulness of Attribution Methods in Computer Vision Wiem Ben Rim, Ammar Shaker, Zhao Xu, Kiril Gashteovski, Bhushan Kotnis, Carolin Lawrence, Jürgen Quittek, Sascha Saralajew. In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2024).

  • AgentQuest: A Modular Benchmark Framework to Measure Progress and Improve LLM Agents. Luca Gioacchini, Giuseppe Siracusano, Davide Sanvito, Kiril Gashteovski, David Friede, Roberto Bifulco, Carolin Lawrence. In System Demonstrations of North American Chapter of the Association for Computational Linguistics (NAACL 2024). (pdf) (code)

  • A Human-Centric Evaluation Platform for Explainable Knowledge Graph Completion. Zhao Xu, Wiem Ben Rim, Kiril Gashteovski, Timo Sztyler, Carolin Lawrence. In System Demonstrations of European Chapter of the Association for Computational Linguistics (EACL 2024). (pdf)

  • Towards Safer Large Language Models (LLMs). Carolin Lawrence, Roberto Bifulco, Kiril Gastheovski, Chia-Chien Hung, Wiem Ben Rim, Ammar Shaker, Masafumi Oyamada, Kunihiko Sadamasa, Masafumi Enomoto, Kunihiro Takeoka. In NEC Technical Journal Vol.17 No.2 June 2024 Special Issue on Revolutionizing Business Practices with Generative AI — Advancing the Societal Adoption of AI with the Support of Generative AI Technologies. (pdf)

2023

  • Linking Surface Facts to Large-Scale Knowledge Graphs. Gorjan Radevski, Kiril Gashteovski, Chia-Chien Hung, Carolin Lawrence, Goran Glavaš. In Empirical Methods in Natural Language Processing (EMNLP 2023). (pdf)

  • Multi-Source Survival Domain Adaptation. Ammar Shaker, Carolin Lawrence. In 37th AAAI Conference on Artificial Intelligence (AAAI). (pdf)

  • Improving Cross-Lingual Transfer for Open Information Extraction with Linguistic Feature Projection. Youmi Ma, Bhushan Kotnis, Carolin Lawrence, Goran Glavaš and Naoaki Okazaki. In 3rd Multilingual Representation Learning Workshop, co-located with EMNLP 2023 .(pdf)

  • Walking a Tightrope -- Evaluating Large Language Models in High-Risk Domains. Chia-Chien Hung, Wiem Ben Rim, Lindsay Frost, Lars Bruckner, Carolin Lawrence. In the first workshop on benchmarking generalisation in NLP (GenBench), co-located with EMNLP 2023 . (pdf)

  • A Human-Centric Assessment Framework for AI. Sascha Saralajew, Ammar Shaker, Zhao Xu, Kiril Gashteovski, Bhushan Kotnis, Wiem Ben-Rim, Jürgen Quittek, Carolin Lawrence. In (AAAI 2023) Workshop on Representation Learning for Responsible Human-Centric AI (R2HCAI) .

Cross-Submissions & Abstracts

2022

  • 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). (pdf)

  • 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). (pdf)

  • 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). (pdf)

  • 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). (pdf)

  • 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). (pdf)

  • 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. In the 2nd HCI + NLP Workshop, co-located with NAACL. (pdf)

  • A Human-Centric Assessment Framework for AI. Sascha Saralajew, Ammar Shaker, Zhao Xu, Kiril Gashteovski, Bhushan Kotnis, Wiem Ben-Rim, Jürgen Quittek, Carolin Lawrence. In ICML 2022 Workshop on Human-Machine Collaboration and Teaming (HMCaT). (pdf)

Cross-Submissions & Abstracts

  • A Human-Centric Assessment Framework for AI. Sascha Saralajew, Ammar Shaker, Zhao Xu, Kiril Gashteovski, Bhushan Kotnis, Wiem Ben-Rim, Jürgen Quittek, Carolin Lawrence. 5th BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, co-located with (EMNLP).

  • Behavioral Testing of Knowledge Graph Embedding Models for Link Prediction. Wiem Ben Rim, Carolin Lawrence, Kiril Gashteovski, Mathias Niepert, Naoaki Okazaki. 5th BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, co-located with (EMNLP).

2021

  • 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). (pdf)

  • VEGN: Variant Effect Prediction with Graph Neural Networks. Jun Cheng, Carolin Lawrence, Mathias Niepert. In Workshop on Computational Biology (WCB), at the Thirty-eighth International Conference on Machine Learning (ICML). (pdf)

  • Learning from Human Feedback: Challenges for Real-World Reinforcement Learning in NLP. Julia Kreutzer, Stefan Riezler and Carolin Lawrence. In 5th Workshop on Structured Prediction for NLP (SPNLP), at 59th Annual Meeting of the Association for Computational Linguistics (ACL). (pdf)

  • Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs. Cheng Wang, Carolin Lawrence, Mathias Niepert. Ninth International Conference on Learning Representations (ICLR). (pdf)

  • Explaining Neural Matrix Factorization with Gradient Rollback. Carolin Lawrence, Timo Sztyler, Mathias Niepert. 35th AAAI Conference on Artificial Intelligence (AAAI). (pdf)

  • Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders. Bhushan Kotnis, Carolin Lawrence, Mathias Niepert. 35th AAAI Conference on Artificial Intelligence (AAAI). (pdf)

  • Interpreting Node Embedding with Text-labeled Graphs. Giuseppe Serra, Zhao Xu, Mathias Niepert, Carolin Lawrence, Peter Tino and Xin Yao. International Joint Conference on Neural Networks (IJCNN).

Cross-Submissions & Abstracts

  • Human Evaluation Study for Explaining Knowledge Graph Completion. Timo Sztyler, Carolin Lawrence. 4th BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, co-located with (EMNLP).

  • Behavioral Testing of Knowledge Graph Embedding Models for Link Prediction. Wiem Ben Rim, Carolin Lawrence, Kiril Gashteovski, Mathias Niepert, Naoaki Okazaki. In Widening NLP, co-located with (EMNLP).

  • Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders. Bhushan Kotnis, Carolin Lawrence, Mathias Niepert. In 5th Workshop on Structured Prediction for NLP (SPNLP), at 59th Annual Meeting of the Association for Computational Linguistics (ACL).

  • Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders. Bhushan Kotnis, Carolin Lawrence, Mathias Niepert. In 6th Workshop on Representation Learning for NLP (Repl4NLP), at 59th Annual Meeting of the Association for Computational Linguistics (ACL).

  • Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs. Bhushan Kotnis, Carolin Lawrence, Mathias Niepert. In 6th Workshop on Representation Learning for NLP (Repl4NLP), at 59th Annual Meeting of the Association for Computational Linguistics (ACL).

  • Explaining Neural Matrix Factorization with Gradient Rollback. Carolin Lawrence, Timo Sztyler, Mathias Niepert. Graphs and More Complex Structures for Learning and Reasoning (GCLR) at 35th AAAI Conference on Artificial Intelligence (AAAI).

  • Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders. Bhushan Kotnis, Carolin Lawrence, Mathias Niepert. Graphs and More Complex Structures for Learning and Reasoning (GCLR) at 35th AAAI Conference on Artificial Intelligence (AAAI).


2020

  • Learning from Human Feedback: Challenges for Real-World Reinforcement Learning in NLP. Julia Kreutzer, Stefan Riezler, Carolin Lawrence. In RWRL Workshop at the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020), hosted virtually.

  • Extended Abstract. Explaining Neural Matrix Factorization with Gradient Rollback. Carolin Lawrence, Timo Sztyler, Mathias Niepert. In WiML Workshop at the Thirty-fourth Conference on Neural Information Processing Systems (NeurIPS 2020), hosted virtually.

2019

  • 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). (pdf)

  • 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). (pdf)

  • 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). (pdf)

  • 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). (pdf)

2018

  • Response-Based and Counterfactual Learning for Sequence-to-Sequence Tasks in NLP. Carolin Lawrence. Doctoral Thesis (summa cum laude), Heidelberg, Germany. (pdf)

  • 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), Montréal, Canada. (pdf)

  • 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. (pdf)

2017

  • 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 (NIPS 2017), Long Beach, CA. (pdf)

  • 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. (pdf)

2016

  • 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. (pdf)

  • A Corpus and Semantic Parser for Natural Language Querying of OpenStreetMap. Carolin Haas / Lawrence, 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. (pdf)

2015

  • Response-based Learning for Machine Translation of Open-domain Database Queries. Carolin Haas / Lawrence, 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. (pdf)

2014

  • Response-based Learning for Grounded Machine Translation. Stefan Riezler, Patrick Simianer and Carolin Haas / Lawrence. In Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (ACL 2014), Baltimore, MD. (pdf)