NLmaps: A Natural Language Interface to Query OpenStreetMap. - Carolin Lawrence; Stefan Riezler (COLING (Demos), 2016)

Counterfactual Learning from Bandit Feedback under Deterministic Logging : A Case Study in Statistical Machine Translation. - Carolin Lawrence; Artem Sokolov; Stefan Riezler (EMNLP, 2017)

Counterfactual Learning for Machine Translation: Degeneracies and Solutions. - Carolin Lawrence; Pratik Gajane; Stefan Riezler (CoRR, 2017)

Improving a Neural Semantic Parser by Counterfactual Learning from Human Bandit Feedback. - Carolin Lawrence; Stefan Riezler (ACL (1), 2018)

Counterfactual Learning from Human Proofreading Feedback for Semantic Parsing. - Carolin Lawrence; Stefan Riezler (CoRR, 2018)

Attending to Future Tokens for Bidirectional Sequence Generation. - Carolin Lawrence; Bhushan Kotnis; Mathias Niepert (EMNLP/IJCNLP (1), 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)

Response-Based and Counterfactual Learning for Sequence-to-Sequence Tasks in NLP. - Carolin Lawrence (2019)

Learning from Human Feedback: Challenges for Real-World Reinforcement Learning in NLP. - Julia Kreutzer; Stefan Riezler; Carolin Lawrence (CoRR, 2020)

Answering Complex Queries in Knowledge Graphs with Bidirectional Sequence Encoders. - Bhushan Kotnis; Carolin Lawrence; Mathias Niepert (AAAI, 2021)

Explaining Neural Matrix Factorization with Gradient Rollback. - Carolin Lawrence; Timo Sztyler; Mathias Niepert (AAAI, 2021)

Offline Reinforcement Learning from Human Feedback in Real-World Sequence-to-Sequence Tasks. - Julia Kreutzer; Stefan Riezler; Carolin Lawrence (SPNLP@ACL-IJCNLP, 2021)

Behavioral Testing of Knowledge Graph Embedding Models for Link Prediction. - Wiem Ben Rim; Carolin Lawrence; Kiril Gashteovski; Mathias Niepert; Naoaki Okazaki (AKBC, 2021)

Uncertainty Estimation and Calibration with Finite-State Probabilistic RNNs. - Cheng Wang 002; Carolin Lawrence; Mathias Niepert (ICLR, 2021)

Interpreting Node Embedding with Text-labeled Graphs. - Giuseppe Serra 002; Zhao Xu 001; Mathias Niepert; Carolin Lawrence; Peter Tiño; Xin Yao 001 (IJCNN, 2021)

VEGN: Variant Effect Prediction with Graph Neural Networks. - Jun Cheng 007; Carolin Lawrence; 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)

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)

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 (ACL (demo), 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 (ACL (1), 2022)

MILIE: Modular & Iterative Multilingual Open Information Extraction. - Bhushan Kotnis; Kiril Gashteovski; Daniel Oñoro-Rubio; Ammar Shaker; Vanesa Rodriguez-Tembras; Makoto Takamoto; Mathias Niepert; Carolin Lawrence (ACL (1), 2022)

KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Models. - Haris Widjaja; Kiril Gashteovski; Wiem Ben Rim; Pengfei Liu 003; Christopher Malon; Daniel Ruffinelli; Carolin Lawrence; Graham Neubig (EMNLP (Demos), 2022)

Uncertainty Propagation in Node Classification. - Zhao Xu 001; Carolin Lawrence; Ammar Shaker; Raman Siarheyeu (ICDM, 2022)

A Human-Centric Assessment Framework for AI. - Sascha Saralajew; Ammar Shaker; Zhao Xu 001; Kiril Gashteovski; Bhushan Kotnis; Wiem Ben Rim; Jürgen Quittek; Carolin Lawrence (CoRR, 2022)

Human-Centric Research for NLP: Towards a Definition and Guiding Questions. - Bhushan Kotnis; Kiril Gashteovski; Julia Gastinger; Giuseppe Serra 002; Francesco Alesiani; Timo Sztyler; Ammar Shaker; Na Gong; Carolin Lawrence; Zhao Xu 001 (CoRR, 2022)

Multi-Source Survival Domain Adaptation. - Ammar Shaker; Carolin Lawrence (AAAI, 2023)

Linking Surface Facts to Large-Scale Knowledge Graphs. - Gorjan Radevski; Kiril Gashteovski; Chia-Chien Hung; Carolin Lawrence; Goran Glavas (EMNLP, 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)

State-Regularized Recurrent Neural Networks to Extract Automata and Explain Predictions. - Cheng Wang 002; Carolin Lawrence; Mathias Niepert (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Generating and Evaluating Plausible Explanations for Knowledge Graph Completion. - Antonio Di Mauro; Zhao Xu 001; Wiem Ben Rim; Timo Sztyler; Carolin Lawrence (ACL (1), 2024)

A Human-Centric Evaluation Platform for Explainable Knowledge Graph Completion. - Zhao Xu 001; Wiem Ben Rim; Kiril Gashteovski; Timo Sztyler; Carolin Lawrence (EACL (Demonstrations), 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 (NAACL (Demonstrations), 2024)

A Human-Centric Assessment of the Usefulness of Attribution Methods in Computer Vision. - Wiem Ben Rim; Ammar Shaker; Zhao Xu 001; Kiril Gashteovski; Bhushan Kotnis; Carolin Lawrence; Jürgen Quittek; Sascha Saralajew (ECML/PKDD (5), 2024)

Large Language Models Enable Few-Shot Clustering. - Vijay Viswanathan 002; Kiril Gashteovski; Carolin Lawrence; Tongshuang Wu; Graham Neubig (Trans. Assoc. Comput. Linguistics, 2024)

Evaluating Language Models as Synthetic Data Generators. - Seungone Kim; Juyoung Suk; Xiang Yue; Vijay Viswanathan 002; Seongyun Lee; Yizhong Wang; Kiril Gashteovski; Carolin Lawrence; Sean Welleck; Graham Neubig (ACL (1), 2025)

On Synthesizing Data for Context Attribution in Question Answering. - Gorjan Radevski; Kiril Gashteovski; Shahbaz Syed; Christopher Malon; Sebastien Nicolas; Chia-Chien Hung; Timo Sztyler; Verena Heußer; Wiem Ben Rim; Masafumi Enomoto; Kunihiro Takeoka; Masafumi Oyamada; et al. (ACL (1), 2025)

MEDDxAgent: A Unified Modular Agent Framework for Explainable Automatic Differential Diagnosis. - Daniel Philip Rose; Chia-Chien Hung; Marco Lepri; Israa Alqassem; Kiril Gashteovski; Carolin Lawrence (ACL (1), 2025)

Not-Just-Scaling Laws: Towards a Better Understanding of the Downstream Impact of Language Model Design Decisions. - Emmy Liu; Amanda Bertsch; Lintang Sutawika; Lindia Tjuatja; Patrick Fernandes; Lara Marinov; Michael Chen; Shreya Singhal; Carolin Lawrence; Aditi Raghunathan; Kiril Gashteovski; Graham Neubig (CoRR, 2025)

Scaling Evaluation-time Compute with Reasoning Models as Process Evaluators. - Seungone Kim; Ian Wu; Jinu Lee; Xiang Yue; Seongyun Lee; Mingyeong Moon; Kiril Gashteovski; Carolin Lawrence; Julia Hockenmaier; Graham Neubig; Sean Welleck (CoRR, 2025)