📰 CoNLL 2023: all accepted papers

72 papers · the most cited first · ← CoNLL 2023

1. Med-HALT: Medical Domain Hallucination Test for Large Language ModelsAnkit Pal, Logesh Kumar Umapathi, Malaikannan Sankarasubbu144 citations · our summary
2. Findings of the BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora ↗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 ↗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 ↗Inar Timiryasov, Jean-Loup Tastet21 citations
5. Future Lens: Anticipating Subsequent Tokens from a Single Hidden State ↗Koyena Pal, Jiuding Sun, Andrew Yuan et al.9 citations
6. Not all layers are equally as important: Every Layer Counts BERT ↗Lucas Georges Gabriel Charpentier, David Samuel8 citations
7. Pre-training LLMs using human-like development data corpus ↗Khushi Bhardwaj, Raj Sanjay Shah, Sashank Varma7 citations
8. Towards Better Evaluation of Instruction-Following: A Case-Study in Summarization ↗Ondrej Skopek, Rahul Aralikatte, Sian Gooding et al.7 citations
9. Exploring Transformers as Compact, Data-efficient Language Models ↗Clayton Fields, Casey Kennington6 citations
10. Can Language Models Be Tricked by Language Illusions? Easier with Syntax, Harder with Semantics ↗Yuhan Zhang, Edward Gibson, Forrest Davis5 citations
11. Large GPT-like Models are Bad Babies: A Closer Look at the Relationship between Linguistic Competence and Psycholinguistic Measures ↗Julius Steuer, Marius Mosbach, Dietrich Klakow5 citations
12. Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning ↗Lucas Weber, Elia Bruni, Dieuwke Hupkes5 citations
13. Humans and language models diverge when predicting repeating text ↗Aditya Vaidya, Javier Turek, Alexander Huth4 citations
14. ToMChallenges: A Principle-Guided Dataset and Diverse Evaluation Tasks for Exploring Theory of Mind ↗Xiaomeng Ma, Lingyu Gao, Qihui Xu4 citations
15. WhisBERT: Multimodal Text-Audio Language Modeling on 100M Words ↗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 ↗David Samuel3 citations
17. Tiny Language Models Enriched with Multimodal Knowledge from Multiplex Networks ↗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 ↗Bram van Dijk, Max van Duijn, Suzan Verberne et al.2 citations
19. Cross-Document Event Coreference Resolution: Instruct Humans or Instruct GPT? ↗Jin Zhao, Nianwen Xue, Bonan Min2 citations
20. Enhancing Code-mixed Text Generation Using Synthetic Data Filtering in Neural Machine Translation ↗Dama Sravani, Radhika Mamidi2 citations
21. How Fragile is Relation Extraction under Entity Replacements? ↗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 ↗Urban Knupleš, Diego Frassinelli, Sabine Schulte im Walde2 citations
23. JaSPICE: Automatic Evaluation Metric Using Predicate-Argument Structures for Image Captioning Models ↗Yuiga Wada, Kanta Kaneda, Komei Sugiura2 citations
24. PSST! Prosodic Speech Segmentation with Transformers ↗Nathan Roll, Calbert Graham, Simon Todd2 citations
25. REFER: An End-to-end Rationale Extraction Framework for Explanation Regularization ↗Mohammad Reza Ghasemi Madani, Pasquale Minervini2 citations
26. Strategies to Improve Low-Resource Agglutinative Languages Morphological Inflection ↗Gulinigeer Abudouwaili, Wayit Ablez, Kahaerjiang Abiderexiti et al.2 citations
27. Syntactic Inductive Bias in Transformer Language Models: Especially Helpful for Low-Resource Languages? ↗Luke Gessler, Nathan Schneider2 citations
28. The Validity of Evaluation Results: Assessing Concurrence Across Compositionality Benchmarks ↗Kaiser Sun, Adina Williams, Dieuwke Hupkes2 citations
29. Towards more Human-like Language Models based on Contextualizer Pretraining StrategyChenghao Xiao, G Thomas Hudson, Noura Al Moubayed2 citations · our summary
30. A surprisal oracle for active curriculum language modeling ↗Xudong Hong, Sharid Loáiciga, Asad Sayeed1 citation
31. Acquiring Linguistic Knowledge from Multimodal InputTheodor Amariucai, Alexander Scott Warstadt1 citation · our summary
32. Alignment via Mutual Information ↗Shinjini Ghosh, Yoon Kim, Ramon Fernandez Astudillo et al.1 citation
33. ArchBERT: Bi-Modal Understanding of Neural Architectures and Natural Languages ↗Mohammad Akbari, Saeed Ranjbar Alvar, Behnam Kamranian et al.1 citation
34. Baby's CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models ↗Zheyu Zhang, Han Yang, Bolei Ma et al.1 citation
35. BabyStories: Can Reinforcement Learning Teach Baby Language Models to Write Better Stories? ↗Xingmeng Zhao, Tongnian Wang, Sheri Osborn et al.1 citation
36. Better Together: Jointly Using Masked Latent Semantic Modeling and Masked Language Modeling for Sample Efficient Pre-training ↗Gábor Berend1 citation
37. Byte-ranked Curriculum Learning for BabyLM Strict-small Shared Task 2023 ↗Justin DeBenedetto1 citation
38. CLIMB – Curriculum Learning for Infant-inspired Model Building ↗Richard Diehl Martinez, Zébulon Goriely, Hope McGovern et al.1 citation
39. Can training neural language models on a curriculum with developmentally plausible data improve alignment with human reading behavior? ↗Aryaman Chobey, Oliver Smith, Anzi Wang et al.1 citation
40. ChapGTP, ILLC's Attempt at Raising a BabyLM: Improving Data Efficiency by Automatic Task Formation ↗Jaap Jumelet, Michael Hanna, Marianne de Heer Kloots et al.1 citation
41. CogMemLM: Human-Like Memory Mechanisms Improve Performance and Cognitive Plausibility of LLMs ↗Lukas Thoma, Ivonne Weyers, Erion Çano et al.1 citation
42. GPT-wee: How Small Can a Small Language Model Really Get? ↗Bastian Bunzeck, Sina Zarrieß1 citation
43. Grammar induction pretraining for language modeling in low resource contexts ↗Xuanda Chen, Eva Portelance1 citation
44. HNC: Leveraging Hard Negative Captions towards Models with Fine-Grained Visual-Linguistic Comprehension Capabilities ↗Esra Dönmez, Pascal Tilli, Hsiu-Yu Yang et al.1 citation
45. Implications of Annotation Artifacts in Edge Probing Test Datasets ↗Sagnik Ray Choudhury, Jushaan Kalra1 citation
46. Increasing The Performance of Cognitively Inspired Data-Efficient Language Models via Implicit Structure Building ↗Omar Momen, David Arps, Laura Kallmeyer1 citation
47. Lil-Bevo: Explorations of Strategies for Training Language Models in More Humanlike Ways ↗Venkata S Govindarajan, Juan Diego Rodriguez, Kaj Bostrom et al.1 citation
48. Mini Minds: Exploring Bebeshka and Zlata Baby Models ↗Irina Proskurina, Guillaume Metzler, Julien Velcin1 citation
49. Mmi01 at The BabyLM Challenge: Linguistically Motivated Curriculum Learning for Pretraining in Low-Resource Settings ↗Maggie Mi1 citation
50. On the effect of curriculum learning with developmental data for grammar acquisition ↗Mattia Opper, J. Morrison, N. Siddharth1 citation
51. Optimizing GPT-2 Pretraining on BabyLM Corpus with Difficulty-based Sentence Reordering ↗Nasim Borazjanizadeh1 citation
52. Penn & BGU BabyBERTa+ for Strict-Small BabyLM Challenge ↗Yahan Yang, Elior Sulem, Insup Lee et al.1 citation
53. Structural Ambiguity and its Disambiguation in Language Model Based Parsers: the Case of Dutch Clause Relativization ↗Gijs Wijnholds, Michael Moortgat1 citation
54. The Impact of Familiarity on Naming Variation: A Study on Object Naming in Mandarin Chinese ↗Yunke He, Xixian Liao, Jialing Liang et al.1 citation
55. The Zipfian Challenge: Learning the statistical fingerprint of natural languages ↗Christian Bentz1 citation
56. ToddlerBERTa: Exploiting BabyBERTa for Grammar Learning and Language Understanding ↗Ömer Veysel Çağatan1 citation
57. Too Much Information: Keeping Training Simple for BabyLMs ↗Lukas Edman, Lisa Bylinina1 citation
58. A Block Metropolis-Hastings Sampler for Controllable Energy-based Text Generation ↗Jarad Forristal, Fatemehsadat Mireshghallah, Greg Durrett et al.
59. A Comparative Study on Textual Saliency of Styles from Eye Tracking, Annotations, and Language Models ↗Karin de Langis, Dongyeop Kang
60. A Minimal Approach for Natural Language Action Space in Text-based Games ↗Dongwon Ryu, Meng Fang, Gholamreza Haffari et al.
61. Attribution and Alignment: Effects of Local Context Repetition on Utterance Production and Comprehension in Dialogue ↗Aron Molnar, Jaap Jumelet, Mario Giulianelli et al.
62. BabyLM Challenge: Curriculum learning based on sentence complexity approximating language acquisitionMiyu Oba, Akari Haga, Akiyo Fukatsu et al.our summary
63. Challenging the “One Single Vector per Token” Assumption ↗Mathieu Dehouck
64. McGill BabyLM Shared Task Submission: The Effects of Data Formatting and Structural Biases ↗Ziling Cheng, Rahul Aralikatte, Ian Porada et al.
65. MuLER: Detailed and Scalable Reference-based Evaluation ↗Taelin Karidi, Leshem Choshen, Gal Patel et al.
66. On the Effects of Structural Modeling for Neural Semantic Parsing ↗Xiang Zhang, Shizhu He, Kang Liu et al.
67. On the utility of enhancing BERT syntactic bias with Token Reordering Pretraining ↗Yassir El Mesbahi, Atif Mahmud, Abbas Ghaddar et al.
68. PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments ↗Daiki Asami, Saku Sugawara
69. Quantifying Information of Tokens for Simple and Flexible Simultaneous Machine Translation ↗DongHyun Lee, Minkyung Park, Byung-Jun Lee
70. Quirk or Palmer: A Comparative Study of Modal Verb Frameworks with Annotated Datasets ↗Risako Owan, Maria Gini, Dongyeop Kang
71. Revising with a Backward Glance: Regressions and Skips during Reading as Cognitive Signals for Revision Policies in Incremental Processing ↗Brielen Madureira, Pelin Çelikkol, David Schlangen
72. Tree-shape Uncertainty for Analyzing the Inherent Branching Bias of Unsupervised Parsing Models ↗Taiga Ishii, Yusuke Miyao

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