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Mareike Hartmann

Mareike Hartmann has 3 papers in our library, in 2019–2024, most of them on Language models & pretraining, Evaluation & benchmarks, Code & programming languages; often with Ashish Sabharwal, Tushar Khot, Alexander Koller.

3 papers in our library · 2019–2024

OpenAlex · ORCID · h-index 10 · 34 works · 388 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 162 times in our library · 5 more in our library without a page yet · ⭐ Paper Stars ranking: #4612

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 more institutions on single bylines are not listed.

 Concepts, shelves and topics

Of its works in our library: the number of works on each and its rating among them.

 Works by year

2020s

2010s

 Papers

The most cited first (OpenAlex and our library).

  1. ADaPT: As-Needed Decomposition and Planning with Language Models (2024 · 85 citations)
    LLM agents for interactive tasks usually follow one of two patterns. Some choose one action at a time, like ReAct. Others draft a fixed list of sub-tasks up front and then run them (plan-and-execute). Both break down on complex tasks: a single sub-task that proves too hard can sink the whole attempt. ADaPT tackles…
  2. AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents (2024 · 73 citations)
    Agents that automate everyday digital chores, such as paying roommates or picking a playlist, must use several apps and write code that adapts to what they observe along the way.
  3. Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary Induction (2019 · 52 citations)
    The paper examines how far the MUSE benchmark for bilingual dictionary induction (BDI) can be trusted. This task is commonly used for the intrinsic evaluation of cross-lingual word embeddings. The MUSE dictionaries (110 language pairs) were generated automatically and were not cleaned manually. The authors worked…

All works

8 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. Lost in Evaluation: Misleading Benchmarks for Bilingual Dictionary InductionYova Kementchedjhieva, Mareike Hartmann, Anders SgaardEMNLP-IJCNLP 2019 (Hong Kong) · 52 citations
  2. A Danish FrameNet Lexicon and an Annotated Corpus Used for Training and Evaluating a Semantic Frame Classifier · original ↗ · no summary yet · Proceedings of the Eleventh International Conference on Language Resources and…Bolette Pedersen et al.2018 · 29 citations
  3. Adapting Multilingual LLMs to Low-Resource Languages with Knowledge Graphs via Adapters · original ↗ · no summary yet · arXiv:2407.01406 · 2024.kallm-1.7Daniil Gurgurov, Mareike Hartmann, Simon Ostermann2024 · 23 citations
  4. Why is unsupervised alignment of English embeddings from different algorithms so hard? · original ↗ · no summary yet · Proceedings of the 2018 Conference on Empirical Methods in Natural Language…Mareike Hartmann, Yova Kementchedjhieva, Anders Søgaard2018 · 14 citations
  5. Cross-domain German Medical Named Entity Recognition using a Pre-Trained Language Model and Unified Medical Semantic Types · original ↗ · no summary yet · Proceedings of the 5th Clinical Natural Language Processing WorkshopSiting Liang, Mareike Hartmann, Daniel Sonntag2023 · 6 citations
  6. Cross-lingual German Biomedical Information Extraction: from Zero-shot to Human-in-the-Loop · original ↗ · no summary yet · arXiv:2301.09908Siting Liang, Mareike Hartmann, Daniel Sonntag2023 · 3 citations

 Co-authors here

8 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 162 times (of the 141,840 papers whose bibliographies we read); 6 citing papers with a page here →.

Updated

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