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Dawn Lawrie

Dawn Lawrie has 4 papers in our library, in 2024–2026, most of them on Language models & pretraining, Multilingual & cross-lingual NLP, Information retrieval & search; often with Benjamin Van Durme, Orion Weller, Daniel Khashabi.

4 papers in our library · 2024–2026

OpenAlex · ORCID · Wikidata · h-index 26 · 174 works · 2,573 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 183 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #6225

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.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

 Works by year

2020s

 Papers

The most cited first (OpenAlex and our library).

  1. mmBERT: A Modern Multilingual Encoder with Annealed Language Learning (2025 · 59 citations)
    Multilingual encoder-only models have seen little progress in recent years, and XLM-R remains the default choice despite being more than six years old.
  2. “According to . . . “: Prompting Language Models Improves Quoting from Pre-Training Data (2024 · 46 citations)
    Large language models often invent facts even though they were trained on reliable text. The authors test whether a simple cue in the prompt, such as "According to Wikipedia", can make a model reproduce more material it memorized during pre-training. To measure this, they introduce QUIP-Score (Quoted Information…
  3. FollowIR: Evaluating and Teaching Information Retrieval Models to Follow Instructions (2025 · 40 citations)
    Neural retrievers are built on language models that can obey elaborate prompts, yet almost no retrieval system lets users attach detailed instructions to a query.
  4. Query Decomposition for RAG: Balancing Exploration-Exploitation (2026 · 2 citations)
    In RAG, complex requests are often split into sub-queries. Pulling a fixed number of documents for each one, however, floods the generator with irrelevant text and can overflow the context window. Petcu et al. treat the choice of which sub-query to read from, and how far down its ranked list to go, as a multi-armed…

All works

7 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. mmBERT: A Modern Multilingual Encoder with Annealed Language LearningarXiv:2509.06888Marc Marone, Orion Weller, William Fleshman, et al.2025 · 59 citations
  2. Transfer Learning Approaches for Building Cross-Language Dense Retrieval Models ↗ECIR 2022 · no summary yetSuraj Nair et al.2022 · 51 citations
  3. CLERC: A Dataset for U. S. Legal Case Retrieval and Retrieval-Augmented Analysis Generation ↗Findings of the Association for Computational Linguistics: NAACL 2025 · no summary yetAbe Bohan Hou et al.2025 · 29 citations
  4. CLERC: A Dataset for Legal Case Retrieval and Retrieval-Augmented Analysis Generation ↗arXiv:2406.17186 · no summary yetAbe Bohan Hou et al.2024 · 21 citations

 Co-authors here

12 of 14 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 183 times (of the 149,439 papers whose bibliographies we read); 50 citing papers with a page here →.

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