---
title: "BabyLM Workshop 2025 — all accepted papers"
description: "All 41 papers of BabyLM Workshop 2025, the most cited first; those with our summary link to it."
canonical: "https://research.elamur.ai/free/en/venues/babylm/2025/papers/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/venues/babylm/2025/papers/)

[home](https://md.research.elamur.ai/free/en/) / [venues](https://md.research.elamur.ai/free/en/venues/) / [BabyLM Workshop](https://md.research.elamur.ai/free/en/venues/babylm/) / [2025](https://md.research.elamur.ai/free/en/venues/babylm/2025/) / papers

# BabyLM Workshop 2025: all accepted papers

41 papers · the most cited first · [← BabyLM Workshop 2025](https://md.research.elamur.ai/free/en/venues/babylm/2025/)

1. **[Findings of the Third BabyLM Challenge: Accelerating Language Modeling Research with Cognitively Plausible Data ↗](https://aclanthology.org/2025.babylm-main.28/)**Lucas Charpentier, Leshem Choshen, Ryan Cotterell et al.*2 citations*
2. **[Are BabyLMs Deaf to Gricean Maxims? A Pragmatic Evaluation of Sample-efficient Language Models](https://md.research.elamur.ai/free/en/papers/askari-2025-are-babylms-deaf-gricean-maxims/)**Raha Askari, Sina Zarrieß, Özge Alacam et al.*1 citation · our summary*
3. **[Dialogue Is Not Enough to Make a Communicative BabyLM (But Neither Is Developmentally Inspired Reinforcement Learning) ↗](https://aclanthology.org/2025.babylm-main.29/)**Francesca Padovani, Bastian Bunzeck, Manar Ali et al.*1 citation*
4. **[Influence-driven Curriculum Learning for Pre-training on Limited Data ↗](https://aclanthology.org/2025.babylm-main.26/)**Loris Schoenegger, Lukas Thoma, Terra Blevins et al.*1 citation*
5. **[Large Language Models and Children Have Different Learning Trajectories in Determiner Acquisition ↗](https://aclanthology.org/2025.babylm-main.8/)**Olivia La Fiandra, Nathalie Fernandez Echeverri, Patrick Shafto et al.*1 citation*
6. **[Mask and You Shall Receive: Optimizing Masked Language Modeling For Pretraining BabyLMs ↗](https://aclanthology.org/2025.babylm-main.31/)**Lukas Edman, Alexander Fraser*1 citation*
7. **[Once Upon a Time: Interactive Learning for Storytelling with Small Language Models ↗](https://aclanthology.org/2025.babylm-main.32/)**Jonas Mayer Martins, Ali Hamza Bashir, Muhammad Rehan Khalid et al.*1 citation*
8. **[Sample-Efficient Language Modeling with Linear Attention and Lightweight Enhancements ↗](https://aclanthology.org/2025.babylm-main.14/)**Patrick Haller, Jonas Golde, Alan Akbik*1 citation*
9. **[Teacher Demonstrations in a BabyLM's Zone of Proximal Development for Contingent Multi-Turn Interaction ↗](https://aclanthology.org/2025.babylm-main.25/)**Suchir Salhan, Hongyi Gu, Donya Rooein et al.*1 citation*
10. **[A Comparison of Elementary Baselines for BabyLM ↗](https://aclanthology.org/2025.babylm-main.16/)**Rareș Păpușoi, Sergiu Nisioi
11. **[A Morpheme-Aware Child-Inspired Language Model ↗](https://aclanthology.org/2025.babylm-main.21/)**Necva Bölücü, Burcu Can
12. **[Active Curriculum Language Modeling over a Hybrid Pre-training Method ↗](https://aclanthology.org/2025.babylm-main.34/)**Eleni Fysikoudi, Sharid Loáiciga, Asad B. Sayeed
13. **[BLiSS: Evaluating Bilingual Learner Competence in Second Language Small Language Models ↗](https://aclanthology.org/2025.babylm-main.13/)**Yuan Gao, Suchir Salhan, Andrew Caines et al.
14. **[Babies Learn to Look Ahead: Multi-Token Prediction in Small LMs](https://md.research.elamur.ai/free/en/papers/aynetdinov-2025-babies-learn-look-ahead-multi/)**Ansar Aynetdinov, Alan Akbik*our summary*
15. **[Batch-wise Convergent Pre-training: Step-by-Step Learning Inspired by Child Language Development](https://md.research.elamur.ai/free/en/papers/yoshida-2025-batch-wise-convergent-pre-training/)**Ko Yoshida, Daiki Shiono, Kai Sato et al.*our summary*
16. **[Beyond Repetition: Text Simplification and Curriculum Learning for Data-Constrained Pretraining ↗](https://aclanthology.org/2025.babylm-main.19/)**Matthew Theodore Roque, Dan John Velasco
17. **[BitMar: Low-Bit Multimodal Fusion with Episodic Memory for Edge Devices](https://md.research.elamur.ai/free/en/papers/aman-2025-bitmar-low-bit-multimodal-fusion/)**Euhid Aman, Esteban Carlin, Hsing-Kuo Kenneth Pao et al.*our summary*
18. **[CLASS-IT: Conversational and Lecture-Aligned Small-Scale Instruction Tuning for BabyLMs ↗](https://aclanthology.org/2025.babylm-main.30/)**Luca Capone, Alessandro Bondielli, Alessandro Lenci
19. **[Contrastive Decoding for Synthetic Data Generation in Low-Resource Language Modeling ↗](https://aclanthology.org/2025.babylm-main.2/)**Jannek Ulm, Kevin Du, Vésteinn Snæbjarnarson
20. **[CurLL: A Developmental Framework to Evaluate Continual Learning in Language Models ↗](https://aclanthology.org/2025.babylm-main.20/)**Pavan Kalyan Tankala, Shubhra Mishra, Satya Lokam et al.
21. **[Design and Analysis of few Million Parameter Transformer-based Language Models trained over a few Million Tokens Dataset ↗](https://aclanthology.org/2025.babylm-main.9/)**Yen-Che Hsiao, Abhishek Dutta
22. **[Do Syntactic Categories Help in Developmentally Motivated Curriculum Learning for Language Models? ↗](https://aclanthology.org/2025.babylm-main.22/)**Arzu Burcu Güven, Anna Rogers, Rob van der Goot
23. **[Exploring smaller batch sizes for a high-performing BabyLM model architecture ↗](https://aclanthology.org/2025.babylm-main.12/)**Sharid Loáiciga, Eleni Fysikoudi, Asad B. Sayeed
24. **[FORGETTER with forgetful hyperparameters and recurring sleeps can continue to learn beyond normal overtfitting limits ↗](https://aclanthology.org/2025.babylm-main.7/)**Yamamoto Rui, Keiji Miura
25. **[Linguistic Units as Tokens: Intrinsic and Extrinsic Evaluation with BabyLM ↗](https://aclanthology.org/2025.babylm-main.35/)**Achille Fusco, Maria Letizia Piccini Bianchessi, Tommaso Sgrizzi et al.
26. **[Looking to Learn: Token-wise Dynamic Gating for Low-Resource Vision-Language Modelling ↗](https://aclanthology.org/2025.babylm-main.15/)**Bianca-Mihaela Ganescu, Suchir Salhan, Andrew Caines et al.
27. **[Masked Diffusion Language Models with Frequency-Informed Training ↗](https://aclanthology.org/2025.babylm-main.38/)**Despoina Kosmopoulou, Efthymios Georgiou, Vaggelis Dorovatas et al.
28. **[MoEP: Modular Expert Paths for Sample-Efficient Language Modeling ↗](https://aclanthology.org/2025.babylm-main.39/)**Joonas Tapaninaho
29. **[Model Merging to Maintain Language-Only Performance in Developmentally Plausible Multimodal Models ↗](https://aclanthology.org/2025.babylm-main.5/)**Ece Takmaz, Lisa Bylinina, Jakub Dotlacil
30. **[Pretraining Language Models with LoRA and Artificial Languages ↗](https://aclanthology.org/2025.babylm-main.37/)**Nalin Kumar, Mateusz Lango, Ondrej Dusek
31. **[RecombiText: Compositional Data Augmentation for Enhancing LLM Pre-Training Datasets in Low-Resource Scenarios ↗](https://aclanthology.org/2025.babylm-main.40/)**Alexander Tampier, Lukas Thoma, Loris Schoenegger et al.
32. **[Rethinking the Role of Text Complexity in Language Model Pretraining ↗](https://aclanthology.org/2025.babylm-main.1/)**Dan John Velasco, Matthew Theodore Roque
33. **[Single layer tiny Co4 outpaces GPT-2 and GPT-BERT ↗](https://aclanthology.org/2025.babylm-main.24/)**Noor Ul Zain, Mohsin Raza Naseem, Ahsan Adeel
34. **[SlovakBabyLM: Replication of the BabyLM and Sample-efficient Pretraining for a Low-Resource Language ↗](https://aclanthology.org/2025.babylm-main.23/)**Ľuboš Kriš, Marek Suppa
35. **[TafBERTa: Learning Grammatical Rules from Small-Scale Language Acquisition Data in Hebrew](https://md.research.elamur.ai/free/en/papers/gelboim-2025-tafberta-learning-grammatical-rules-small/)**Anita Gelboim, Elior Sulem*our summary*
36. **[Two ways into the hall of mirrors: Language exposure and lossy memory drive cross-linguistic grammaticality illusions in language models ↗](https://aclanthology.org/2025.babylm-main.17/)**Kate McCurdy, Katharina Christian, Amelie Seyfried et al.
37. **[Understanding and Enhancing Mamba-Transformer Hybrids for Memory Recall and Language Modeling ↗](https://aclanthology.org/2025.babylm-main.27/)**Hyunji Lee, Wenhao Yu, Hongming Zhang et al.
38. **[Unifying Mixture of Experts and Multi-Head Latent Attention for Efficient Language Models ↗](https://aclanthology.org/2025.babylm-main.3/)**Sushant Mehta, Raj Dandekar, Rajat Dandekar et al.
39. **[What did you say? Generating Child-Directed Speech Questions to Train LLMs](https://md.research.elamur.ai/free/en/papers/poh-2025-what-did-you-say-generating/)**Whitney Poh, Michael Tombolini, Libby Barak*our summary*
40. **[What is the Best Sequence Length for BabyLM? ↗](https://aclanthology.org/2025.babylm-main.10/)**Suchir Salhan, Richard Diehl Martinez, Zébulon Goriely et al.
41. **[You are an LLM teaching a smaller model everything you know: Multi-task pretraining of language models with LLM-designed study plans ↗](https://aclanthology.org/2025.babylm-main.33/)**Wiktor Kamzela, Mateusz Lango, Ondrej Dusek
- [← back to](https://md.research.elamur.ai/free/en/venues/babylm/2025/) — BabyLM Workshop 2025