Papers by Annemarie Friedrich
A Kind Introduction to Lexical and Grammatical Aspect, with a Survey of Computational Approaches (2023.eacl-main)
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| Challenge: | Lexical and grammatical aspect plays essential roles in semantic interpretation, but many systems do not address it systematically. |
| Approach: | They propose to model lexical and grammatical aspect using computational approaches . they argue that a good computational understanding of lexic and grammmatical aspects is needed . |
| Outcome: | The proposed models are based on the lexical and grammatical aspect of a situation, the authors argue . they argue that the models need to be able to handle and evaluate the aspect systematically . |
QUITE: Quantifying Uncertainty in Natural Language Text in Bayesian Reasoning Scenarios (2024.emnlp-main)
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| Challenge: | Existing probabilistic reasoning datasets require the model to only rank textual alternatives or use limited set of templates. |
| Approach: | They propose a question-answering dataset that uses probabilistic rules to express degrees of certainty. |
| Outcome: | The proposed model outperforms existing models on all reasoning types . it is available on Github and is expected to be used in clinical documentation . |
PAP2PAT: Benchmarking Outline-Guided Long-Text Patent Generation with Patent-Paper Pairs (2025.findings-acl)
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| Challenge: | In patents, the description constitutes more than 90% of the document on average, yet its automatic generation remains understudied. |
| Approach: | They propose a method to generate patent documents using a research paper as an invention specification. |
| Outcome: | The proposed model can generate 1.8k patent-paper pairs describing the same inventions, but it's difficult to provide the level of detail required. |
Coordinate Constructions in English Enhanced Universal Dependencies: Analysis and Computational Modeling (2021.eacl-main)
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| Challenge: | Enhanced Universal Dependencies (UD) parses are used to represent syntactic dependencies between words, prioritizing links between content words. |
| Approach: | They propose to use a heuristic rule-based converter to propagate conjuncts from conjunction heads to other conjunctions to determine which set of links to propagation from a semantic perspective. |
| Outcome: | The proposed method outperforms existing methods using basic-layer tree parsers and converters. |
Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges (2025.acl-long)
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Bolei Ma, Yuting Li, Wei Zhou, Ziwei Gong, Yang Janet Liu, Katja Jasinskaja, Annemarie Friedrich, Julia Hirschberg, Frauke Kreuter, Barbara Plank
| Challenge: | linguistics studies how context influences meaning of language and how people use it to convey implied meanings, emotions, and intentions. |
| Approach: | They analyze task designs, data collection methods, evaluation approaches and their relevance to real-world applications. |
| Outcome: | The findings highlight emerging trends, challenges, and gaps in existing benchmarks . the findings will contribute to more nuanced and context-aware NLP models . |
Efficient Multi-Agent Collaboration with Tool Use for Online Planning in Complex Table Question Answering (2025.findings-naacl)
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| Challenge: | Recent studies on complex table question answering focus more and more on complex instances, as they are ubiquitous in table data analysis. |
| Approach: | They propose a framework that requires neither fine-tuning nor closed-source models to solve complex table question answering (TQA) their framework outperforms previous SoTA systems on three out of four benchmarks and performs comparably to the larger and more expensive closed-sourced model GPT-4 on two benchmarks. |
| Outcome: | The proposed framework outperforms closed-source models and closed-sourced models on three out of four benchmarks and performs comparable to the larger and more expensive closed-Source model GPT-4 on two benchmarks. |
MiST: a Large-Scale Annotated Resource and Neural Models for Functions of Modal Verbs in English Scientific Text (2022.findings-emnlp)
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| Challenge: | modal verbs are used for hedges, but they may also denote abilities and restrictions in scientific texts . modals are often used for hedging, but prior work on this topic has been limited . |
| Approach: | They propose a dataset that contains 3737 modal instances in five scientific domains . they evaluate a set of competitive neural architectures to model the distinctions in MIST . |
| Outcome: | The proposed dataset contains 3737 modal instances in five scientific domains . leveraging non-scientific data is of limited benefit for modeling the distinctions in MIST . |
Texts or Images? A Fine-grained Analysis on the Effectiveness of Input Representations and Models for Table Question Answering (2025.findings-acl)
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| Challenge: | Existing studies on table question answering use either serialized text or images . lack of controlled setups limits fine-grained distinctions between these approaches. |
| Approach: | They propose a method selecting table representations dynamically and compare their performance to previous studies. |
| Outcome: | The proposed method improves performance 10% compared to using both representations indiscriminately. |
Table Question Answering in the Era of Large Language Models: A Comprehensive Survey of Tasks, Methods, and Evaluation (2026.acl-long)
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| Challenge: | Table Question Answering (TQA) aims to answer natural language questions using tabular data. |
| Approach: | They propose a systematic overview of TQA research using large language models and summarize available benchmarks based on task features. |
| Outcome: | The proposed framework provides a comprehensive overview of the current state of the art in the field of Table Question Answering. |
AnnoCTR: A Dataset for Detecting and Linking Entities, Tactics, and Techniques in Cyber Threat Reports (2024.lrec-main)
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Lukas Lange, Marc Müller, Ghazaleh Haratinezhad Torbati, Dragan Milchevski, Patrick Grau, Subhash Chandra Pujari, Annemarie Friedrich
| Challenge: | Abstract: Natural language processing can help with managing large amounts of unstructured information. |
| Approach: | They propose to annotate a CC-BY-SA-licensed dataset of cyber threat reports . they use named entities, temporal expressions, and cybersecurity-specific concepts . |
| Outcome: | The proposed dataset annotates reports with named entities, temporal expressions, and cybersecurity-specific concepts including implicitly mentioned techniques and tactics. |
Is the Answer in the Text? Challenging ChatGPT with Evidence Retrieval from Instructive Text (2023.findings-emnlp)
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| Challenge: | Generative language models have recently shown remarkable success in generating answers to questions in a given textual context, but they suffer from hallucination, wrongly cite evidence, and spread misleading information. |
| Approach: | They propose a benchmark to evaluate an annotated WikiHow article and use it to retrieve answers to questions from trustworthy texts. |
| Outcome: | The proposed model can retrieve answers to lexically varied and open-ended questions from trustworthy instructive texts. |
LGAR: Zero-Shot LLM-Guided Neural Ranking for Abstract Screening in Systematic Literature Reviews (2025.findings-acl)
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| Challenge: | Existing methods for abstract screening focus on binary classification settings; existing question answering (QA) based ranking approaches suffer from error propagation. |
| Approach: | They propose a systematic literature review (SLR) method that uses large language models to evaluate the SLR's inclusion and exclusion criteria. |
| Outcome: | The proposed method outperforms existing question answering (QA) based methods by 5-10 pp. in mean precision. |
A Survey of Methods for Addressing Class Imbalance in Deep-Learning Based Natural Language Processing (2023.eacl-main)
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| Challenge: | Developing methods to improve model performance in imbalanced data settings has been an active area for decades . |
| Approach: | They propose to use sampling, data augmentation, choice of loss function, staged learning, or model design to address class imbalance in NLP. |
| Outcome: | The proposed approaches are evaluated on a variety of NLP tasks or in the computer vision community. |
Three Real-World Datasets and Neural Computational Models for Classification Tasks in Patent Landscaping (2022.emnlp-main)
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| Challenge: | Patent Landscaping is one of the central tasks of intellectual property management and involves selecting and grouping patents according to user-defined technical or application-oriented criteria. |
| Approach: | They propose to use a novel model that takes into account textual information from the patents’ full texts as well as embeddings created based on the patent’s CPC labels. |
| Outcome: | The proposed model takes into account textual information from the patents’ full texts as well as embeddings created based on the patent’s CPC labels. |
FREB-TQA: A Fine-Grained Robustness Evaluation Benchmark for Table Question Answering (2024.naacl-long)
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| Challenge: | Existing benchmarks for Table Question Answering lack robustness . current systems generate inconsistent responses by performing coarse-grained changes in tables and questions. |
| Approach: | They formalize three major desiderata for a fine-grained evaluation of robustness of TQA systems . they aim to evaluate TQA responses on the content of relevant cells rather than on biases . |
| Outcome: | The proposed benchmarks show that state-of-the-art TQA systems fail in three aspects . the benchmarks are released publicly and are expected to improve over time . |
The SOFC-Exp Corpus and Neural Approaches to Information Extraction in the Materials Science Domain (2020.acl-main)
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Annemarie Friedrich, Heike Adel, Federico Tomazic, Johannes Hingerl, Renou Benteau, Anika Marusczyk, Lukas Lange
| Challenge: | Using BERT embeddings leads to large performance gains, but with increasing task complexity, adding a recurrent neural network seems beneficial. |
| Approach: | They propose an annotation scheme for marking information on publications related to solid oxide fuel cells . they propose to use a recurrent neural network to solve a variety of tasks . |
| Outcome: | The proposed scheme is based on a corpus of 45 open-access scholarly articles and a neural network for a variety of tasks. |