---
title: "CoNLL 2023 — accepted papers — Elamur Research"
description: "CoNLL 2023 — accepted papers: 4 papers in the Elamur Research library (Singapore), with our summaries, ranked by citations."
canonical: "https://research.elamur.ai/free/en/venues/conll/2023/"
---
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# CoNLL 2023 — accepted papers

CoNLL 2023 is the 2023 edition of the Conference on Computational Natural Language Learning (CoNLL), held in Singapore, December 2023 (publisher: Association for Computational Linguistics). The ACL Anthology lists 72 papers of it; our library holds 4 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

📍 [Singapore](https://md.research.elamur.ai/free/en/countries/singapore/) · 🗓 December 2023

[**72** papers in the proceedings](#all) · [**4** works in our library](https://md.research.elamur.ai/free/en/venues/conll/2023/#works) · [**242** citations of these works](https://md.research.elamur.ai/free/en/venues/conll/2023/#works)

## Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. **[Med-HALT: Medical Domain Hallucination Test for Large Language Models](https://md.research.elamur.ai/free/en/papers/pal-2023-med-halt-medical-domain-hallucination/)**Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu*144 citations · our summary*
2. **[Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora ↗](https://aclanthology.org/2023.conll-babylm.1/)**Alex Warstadt, Aaron Mueller, Leshem Choshen et al.*69 citations*
3. **[Theory of Mind in Large Language Models: Examining Performance of 11 State-of-the-Art models vs. Children Aged 7-10 on Advanced Tests ↗](https://aclanthology.org/2023.conll-1.25/)**Max van Duijn, Bram van Dijk, Tom Kouwenhoven et al.*23 citations*
4. **[Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty ↗](https://aclanthology.org/2023.conll-babylm.24/)**Inar Timiryasov, Jean-Loup Tastet*21 citations*
5. **[Future Lens: Anticipating Subsequent Tokens from a Single Hidden State ↗](https://aclanthology.org/2023.conll-1.37/)**Koyena Pal, Jiuding Sun, Andrew Yuan et al.*9 citations*
6. **[Not all layers are equally as important: Every Layer Counts BERT ↗](https://aclanthology.org/2023.conll-babylm.20/)**Lucas Georges Gabriel Charpentier, David Samuel*8 citations*
7. **[Pre-training LLMs using human-like development data corpus ↗](https://aclanthology.org/2023.conll-babylm.30/)**Khushi Bhardwaj, Raj Sanjay Shah, Sashank Varma*7 citations*
8. **[Towards Better Evaluation of Instruction-Following: A Case-Study in Summarization ↗](https://aclanthology.org/2023.conll-1.16/)**Ondrej Skopek, Rahul Aralikatte, Sian Gooding et al.*7 citations*
9. **[Exploring Transformers as Compact, Data-efficient Language Models ↗](https://aclanthology.org/2023.conll-1.35/)**Clayton Fields, Casey Kennington*6 citations*
10. **[Can Language Models Be Tricked by Language Illusions? Easier with Syntax, Harder with Semantics ↗](https://aclanthology.org/2023.conll-1.1/)**Yuhan Zhang, Edward Gibson, Forrest Davis*5 citations*

## All accepted papers (72)

The most cited first; 4 with our summary link to their page here, the others to the original.

1. **[Med-HALT: Medical Domain Hallucination Test for Large Language Models](https://md.research.elamur.ai/free/en/papers/pal-2023-med-halt-medical-domain-hallucination/)**Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu*144 citations · our summary*
2. **[Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora ↗](https://aclanthology.org/2023.conll-babylm.1/)**Alex Warstadt, Aaron Mueller, Leshem Choshen et al.*69 citations*
3. **[Theory of Mind in Large Language Models: Examining Performance of 11 State-of-the-Art models vs. Children Aged 7-10 on Advanced Tests ↗](https://aclanthology.org/2023.conll-1.25/)**Max van Duijn, Bram van Dijk, Tom Kouwenhoven et al.*23 citations*
4. **[Baby Llama: knowledge distillation from an ensemble of teachers trained on a small dataset with no performance penalty ↗](https://aclanthology.org/2023.conll-babylm.24/)**Inar Timiryasov, Jean-Loup Tastet*21 citations*
5. **[Future Lens: Anticipating Subsequent Tokens from a Single Hidden State ↗](https://aclanthology.org/2023.conll-1.37/)**Koyena Pal, Jiuding Sun, Andrew Yuan et al.*9 citations*
6. **[Not all layers are equally as important: Every Layer Counts BERT ↗](https://aclanthology.org/2023.conll-babylm.20/)**Lucas Georges Gabriel Charpentier, David Samuel*8 citations*
7. **[Pre-training LLMs using human-like development data corpus ↗](https://aclanthology.org/2023.conll-babylm.30/)**Khushi Bhardwaj, Raj Sanjay Shah, Sashank Varma*7 citations*
8. **[Towards Better Evaluation of Instruction-Following: A Case-Study in Summarization ↗](https://aclanthology.org/2023.conll-1.16/)**Ondrej Skopek, Rahul Aralikatte, Sian Gooding et al.*7 citations*
9. **[Exploring Transformers as Compact, Data-efficient Language Models ↗](https://aclanthology.org/2023.conll-1.35/)**Clayton Fields, Casey Kennington*6 citations*
10. **[Can Language Models Be Tricked by Language Illusions? Easier with Syntax, Harder with Semantics ↗](https://aclanthology.org/2023.conll-1.1/)**Yuhan Zhang, Edward Gibson, Forrest Davis*5 citations*
11. **[Large GPT-like Models are Bad Babies: A Closer Look at the Relationship between Linguistic Competence and Psycholinguistic Measures ↗](https://aclanthology.org/2023.conll-babylm.12/)**Julius Steuer, Marius Mosbach, Dietrich Klakow*5 citations*
12. **[Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning ↗](https://aclanthology.org/2023.conll-1.20/)**Lucas Weber, Elia Bruni, Dieuwke Hupkes*5 citations*
13. **[Humans and language models diverge when predicting repeating text ↗](https://aclanthology.org/2023.conll-1.5/)**Aditya Vaidya, Javier Turek, Alexander Huth*4 citations*
14. **[ToMChallenges: A Principle-Guided Dataset and Diverse Evaluation Tasks for Exploring Theory of Mind ↗](https://aclanthology.org/2023.conll-1.2/)**Xiaomeng Ma, Lingyu Gao, Qihui Xu*4 citations*
15. **[WhisBERT: Multimodal Text-Audio Language Modeling on 100M Words ↗](https://aclanthology.org/2023.conll-babylm.21/)**Lukas Wolf, Klemen Kotar, Greta Tuckute et al.*4 citations*
16. **[Mean BERTs make erratic language teachers: the effectiveness of latent bootstrapping in low-resource settings ↗](https://aclanthology.org/2023.conll-babylm.19/)**David Samuel*3 citations*
17. **[Tiny Language Models Enriched with Multimodal Knowledge from Multiplex Networks ↗](https://aclanthology.org/2023.conll-babylm.3/)**Clayton Fields, Osama Natouf, Andrew McMains et al.*3 citations*
18. **[ChiSCor: A Corpus of Freely-Told Fantasy Stories by Dutch Children for Computational Linguistics and Cognitive Science ↗](https://aclanthology.org/2023.conll-1.23/)**Bram van Dijk, Max van Duijn, Suzan Verberne et al.*2 citations*
19. **[Cross-Document Event Coreference Resolution: Instruct Humans or Instruct GPT? ↗](https://aclanthology.org/2023.conll-1.38/)**Jin Zhao, Nianwen Xue, Bonan Min*2 citations*
20. **[Enhancing Code-mixed Text Generation Using Synthetic Data Filtering in Neural Machine Translation ↗](https://aclanthology.org/2023.conll-1.15/)**Dama Sravani, Radhika Mamidi*2 citations*
21. **[How Fragile is Relation Extraction under Entity Replacements? ↗](https://aclanthology.org/2023.conll-1.27/)**Yiwei Wang, Bryan Hooi, Fei Wang et al.*2 citations*
22. **[Investigating the Nature of Disagreements on Mid-Scale Ratings: A Case Study on the Abstractness-Concreteness Continuum ↗](https://aclanthology.org/2023.conll-1.6/)**Urban Knupleš, Diego Frassinelli, Sabine Schulte im Walde*2 citations*
23. **[JaSPICE: Automatic Evaluation Metric Using Predicate-Argument Structures for Image Captioning Models ↗](https://aclanthology.org/2023.conll-1.28/)**Yuiga Wada, Kanta Kaneda, Komei Sugiura*2 citations*
24. **[PSST! Prosodic Speech Segmentation with Transformers ↗](https://aclanthology.org/2023.conll-1.31/)**Nathan Roll, Calbert Graham, Simon Todd*2 citations*
25. **[REFER: An End-to-end Rationale Extraction Framework for Explanation Regularization ↗](https://aclanthology.org/2023.conll-1.40/)**Mohammad Reza Ghasemi Madani, Pasquale Minervini*2 citations*

[See all 72 papers in CoNLL 2023 — accepted papers →](https://md.research.elamur.ai/free/en/venues/conll/2023/papers/)

## Papers with our summary in our library (4)

The most cited first (OpenAlex citations plus our library's).

1. **[Med-HALT: Medical Domain Hallucination Test for Large Language Models](https://md.research.elamur.ai/free/en/papers/pal-2023-med-halt-medical-domain-hallucination/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Ankit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu*2023 · 220 citations*
2. **[BabyLM Challenge: Curriculum learning based on sentence complexity approximating language acquisition](https://md.research.elamur.ai/free/en/papers/oba-2023-babylm-challenge-curriculum-learning-based/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Miyu Oba, Akari Haga, Akiyo Fukatsu, et al.*2023 · 9 citations*
3. **[Towards more Human-like Language Models based on Contextualizer Pretraining Strategy](https://md.research.elamur.ai/free/en/papers/xiao-2023-more-human-like-language-models/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Chenghao Xiao, G Thomas Hudson, Noura Al Moubayed*2023 · 7 citations*
4. **[Acquiring Linguistic Knowledge from Multimodal Input](https://md.research.elamur.ai/free/en/papers/amariucai-2023-acquiring-linguistic-knowledge-multimodal-input/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Theodor Amariucai, Alexander Scott Warstadt*2023 · 6 citations*

## Top topics

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

[Language models & pretraining (1)](https://md.research.elamur.ai/free/en/topics/language-models/) · [Psycholinguistics & language acquisition (1)](https://md.research.elamur.ai/free/en/topics/psycholinguistics/) · [Vision & language (1)](https://md.research.elamur.ai/free/en/topics/multimodal/)

## Fields

[Arts and Humanities (4)](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science (3)](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Medicine (1)](https://md.research.elamur.ai/free/en/shelves/medicine/)

## Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

[🧑‍🔬**Ankit Pal**1 work here · 220 citations](https://md.research.elamur.ai/free/en/authors/ankit-pal/) · [🧑‍🔬**Logesh Kumar Umapathi**1 work here · 220 citations](https://md.research.elamur.ai/free/en/authors/logesh-kumar-umapathi/) · [🧑‍🔬**Malaikannan Sankarasubbu**1 work here · 220 citations](https://md.research.elamur.ai/free/en/authors/malaikannan-sankarasubbu/) · [🧑‍🔬**Yohei Oseki**1 work here · 9 citations](https://md.research.elamur.ai/free/en/authors/yohei-oseki/)

## Top institutions

Institutions on the bylines of its works here, by the number of works.

[🎓**Durham University** Durham · United Kingdom 1 work here](https://md.research.elamur.ai/free/en/universities/durham-university/) · [🎓**ETH Zurich** Zurich · Switzerland 1 work here](https://md.research.elamur.ai/free/en/universities/eth-zurich/) · [🎓**The University of Tokyo** Tokyo · Japan 1 work here](https://md.research.elamur.ai/free/en/universities/the-university-of-tokyo/) · [🎓**Nara Institute of Science and Technology** Ikoma · Japan 1 work here](https://md.research.elamur.ai/free/en/universities/nara-institute-of-science-and-technology/)

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

- [← previous CoNLL 2022](https://md.research.elamur.ai/free/en/venues/conll/2022/)
- [next → CoNLL 2024](https://md.research.elamur.ai/free/en/venues/conll/2024/)
- [↑ back to CoNLL](https://md.research.elamur.ai/free/en/venues/conll/)