Who cites «TinyStories: How Small Can Language Models Be and Still Speak Coherent English?»

158 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

A Unified Assessment of the Poverty of the Stimulus Argument for Neural Language Models — 2026 · arXiv:2602.09992
BabyBabelLM: A Multilingual Benchmark of Developmentally Plausible Training Data — 2026 · Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
Evaluating Small Decoder-Only Language Models for Grammar Correction and Text Simplification — 2026 · arXiv:2601.03874
Gaperon: A Peppered English-French Generative Language Model Suite — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
HSS-Synth: Humanities and Social Sciences Data Synthesis for LLMs — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
Making Synthetic Questions More Child-Directed: Prompting and Sampling Effects — 2026 · Proceedings of the 1st Workshop on Computational Developmental Linguistics (CDL)
Memorization, Emergence, and Explaining Reversal Failures: A Controlled Study of Relational Semantics in LLMs — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Nepali Legal Expertise through Generative and Extractive Pre-trained Transformers (NepLEGiT) — 2026 · arXiv:2609.16010
SteuerLLM: Local specialized large language model for German tax law analysis — 2026 · arXiv:2602.11081 · Scientific Reports, Volume 16, 2026
AQuilt: Weaving Logic and Self-Inspection into Low-Cost, High-Relevance Data Synthesis for Specialist LLMs — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Batch-wise Convergent Pre-training: Step-by-Step Learning Inspired by Child Language Development — 2025 · Proceedings of the First BabyLM Workshop
CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation — 2025 · Transactions of the Association for Computational Linguistics
Contrastive Decoding for Synthetic Data Generation in Low-Resource Language Modeling — 2025 · Proceedings of the First BabyLM Workshop
CurLL: A Developmental Framework to Evaluate Continual Learning in Language Models — 2025 · Proceedings of the First BabyLM Workshop
Decoding Dark Matter: Specialized Sparse Autoencoders for Interpreting Rare Concepts in Foundation Models — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
Demystifying Synthetic Data in LLM Pre-training: A Systematic Study of Scaling Laws, Benefits, and Pitfalls — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Do Construction Distributions Shape Formal Language Learning In German BabyLMs? — 2025 · Proceedings of the 29th Conference on Computational Natural Language Learning
Evaluating Synthetic Data Generation from User Generated Text — 2025 · Computational Linguistics
FastDraft: How to Train Your Draft — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Igniting Creative Writing in Small Language Models: LLM-as-a-Judge versus Multi-Agent Refined Rewards — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Know Your RAG: Dataset Taxonomy and Generation Strategies for Evaluating RAG Systems — 2025 · Proceedings of the 31st International Conference on Computational Linguistics: Industry Track
Language Modeling by Language Models — 2025 · arXiv:2506.20249
MetaSynth: Meta-Prompting-Driven Agentic Scaffolds for Diverse Synthetic Data Generation — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
Multilingual Language Model Pretraining using Machine-translated Data — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
Nemotron-CC: Transforming Common Crawl into a Refined Long-Horizon Pretraining Dataset — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Once Upon a Time: Interactive Learning for Storytelling with Small Language Models — 2025 · Proceedings of the First BabyLM Workshop
Pico: A Modular Framework for Hypothesis-Driven Small Language Model Research — 2025 · arXiv:2509.16413
RecombiText: Compositional Data Augmentation for Enhancing LLM Pre-Training Datasets in Low-Resource Scenarios — 2025 · Proceedings of the First BabyLM Workshop
Sample-Efficient Language Modeling with Linear Attention and Lightweight Enhancements — 2025 · Proceedings of the First BabyLM Workshop
Small Language Models can Outperform Humans in Short Creative Writing: A Study Comparing SLMs with Humans and LLMs — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
SpeechWeave: Diverse Multilingual Synthetic Text & Audio Data Generation Pipeline for Training Text to Speech Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 6: Industry Track)
Syntriever: How to Train Your Retriever with Synthetic Data from LLMs — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
TinyServe: Query-Aware Cache Selection for Efficient LLM Serving — 2025 · arXiv:2509.12211
Too Late to Train, Too Early To Use? A Study on Necessity and Viability of Low-Resource Bengali LLMs — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
Unifying Mixture of Experts and Multi-Head Latent Attention for Efficient Language Models — 2025 · Proceedings of the First BabyLM Workshop
A Comprehensive Survey of Small Language Models in the Era of Large Language Models: Techniques, Enhancements, Applications, Collaboration with LLMs, and Trustworthiness — 2024 · arXiv:2411.03350
A Glitch in the Matrix? Locating and Detecting Language Model Grounding with Fakepedia — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Arabic Automatic Story Generation with Large Language Models — 2024 · Proceedings of the Second Arabic Natural Language Processing Conference
BERTtime Stories: Investigating the Role of Synthetic Story Data in Language Pre-training — 2024 · The 2nd BabyLM Challenge at the 28th Conference on Computational Natural Language Learning
CUTE: Measuring LLMs'' Understanding of Their Tokens — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
DataNarrative: Automated Data-Driven Storytelling with Visualizations and Texts — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
DecorateLM: Data Engineering through Corpus Rating, Tagging, and Editing with Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Emergent Abilities in Reduced-Scale Generative Language Models — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
Event Causality Identification with Synthetic Control — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Experimenting with Legal AI Solutions: The Case of Question-Answering for Access to Justice — 2024 · arXiv:2409.07713
Findings of the Second BabyLM Challenge: Sample-Efficient Pretraining on Developmentally Plausible Corpora — 2024 · The 2nd BabyLM Challenge at the 28th Conference on Computational Natural Language Learning
From Tarzan to Tolkien: Controlling the Language Proficiency Level of LLMs for Content Generation — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
From fieldwork to linguistic theory: A tribute to Dan Everett — 2024 · edited-volume
HLSTransform: Energy-Efficient Llama 2 Inference on FPGAs Via High Level Synthesis — 2024 · arXiv:2405.00738
Improving Language Models Trained on Translated Data with Continual Pre-Training and Dictionary Learning Analysis — 2024 · Proceedings of the Second Arabic Natural Language Processing Conference
InFoBench: Evaluating Instruction Following Ability in Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
Is Child-Directed Speech Effective Training Data for Language Models? — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Is Training Data Quality or Quantity More Impactful to Small Language Model Performance? — 2024 · arXiv:2411.15821 · Commun. Comput. Inf. Sci. 2665 (2025) 75-87
Language Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the Missing AANNs — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Language Models as Models of Language — 2024 · arXiv:2408.07144
Latent Paraphrasing: Perturbation on Layers Improves Knowledge Injection in Language Models — 2024 · arXiv:2411.00686
MIND: Math Informed syNthetic Dialogues for Pretraining LLMs — 2024 · arXiv:2410.12881
Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures — 2024 · arXiv:2407.19580
MoPS: Modular Story Premise Synthesis for Open-Ended Automatic Story Generation — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
On LLMs-Driven Synthetic Data Generation, Curation, and Evaluation: A Survey — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
On the Diversity of Synthetic Data and its Impact on Training Large Language Models — 2024 · arXiv:2410.15226
OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset — 2024 · arXiv:2402.10176
Pretraining Language Models Using Translationese — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Reason from Fallacy: Enhancing Large Language Models'' Logical Reasoning through Logical Fallacy Understanding — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
Scaling Properties of Speech Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
Small Language Models Are Good Too: An Empirical Study of Zero-Shot Classification — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Small Language Models: Survey, Measurements, and Insights — 2024 · arXiv:2409.15790
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models — 2024 · arXiv:2412.02980
Synthetic continued pretraining — 2024 · arXiv:2409.07431
The Fourth Evaluation on Chinese Spatial Cognition — 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)
The Parrot Dilemma: Human-Labeled vs. LLM-augmented Data in Classification Tasks — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 2: Short Papers)
The Unreasonable Ineffectiveness of the Deeper Layers — 2024 · arXiv:2403.17887
Think Big, Generate Quick: LLM-to-SLM for Fast Autoregressive Decoding — 2024 · arXiv:2402.16844
Towards Pareto Optimal Throughput in Small Language Model Serving — 2024 · arXiv:2404.03353
WanJuan-CC: A Safe and High-Quality Open-sourced English Webtext Dataset — 2024 · arXiv:2402.19282
What Evidence Do Language Models Find Convincing? — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
What should Baby Models read? Exploring Sample-Efficient Data Composition on Model Performance — 2024 · The 2nd BabyLM Challenge at the 28th Conference on Computational Natural Language Learning
WhatIf: Leveraging Word Vectors for Small-Scale Data Augmentation — 2024 · The 2nd BabyLM Challenge at the 28th Conference on Computational Natural Language Learning
小規模言語モデルによる子供の過剰一般化のモデリング — 2024 · 言語処理学会第30回年次大会発表論文集 (NLP2024)
BabyStories: Can Reinforcement Learning Teach Baby Language Models to Write Better Stories? — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
Efficient RLHF: Reducing the Memory Usage of PPO — 2023 · arXiv:2309.00754
Exposing Attention Glitches with Flip-Flop Language Modeling — 2023 · arXiv:2306.00946
Gentopia: A Collaborative Platform for Tool-Augmented LLMs — 2023 · arXiv:2308.04030
Large GPT-like Models are Bad Babies: A Closer Look at the Relationship between Linguistic Competence and Psycholinguistic Measures — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models — 2023 · arXiv:2309.12284
Mini Minds: Exploring Bebeshka and Zlata Baby Models — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
Physics of Language Models: Part 3.1, Knowledge Storage and Extraction — 2023 · arXiv:2309.14316
Pretraining on the Test Set Is All You Need — 2023 · arXiv:2309.08632
Textbooks Are All You Need — 2023 · arXiv:2306.11644
Textbooks Are All You Need II: phi-1.5 technical report — 2023 · arXiv:2309.05463
The Quantization Model of Neural Scaling — 2023 · arXiv:2303.13506
TinyGSM: achieving >80% on GSM8k with small language models — 2023 · arXiv:2312.09241
ToddlerBERTa: Exploiting BabyBERTa for Grammar Learning and Language Understanding — 2023 · Proceedings of the BabyLM Challenge at the 27th Conference on Computational Natural Language Learning
``Fifty Shades of Bias'''': Normative Ratings of Gender Bias in GPT Generated English Text — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
alyafeai-2025-mole-metadata-extraction-validation-scientific
baker-2025-structural-inference-interpreting-small-language
bergeron-2024-blu-syntra-distinguish-synergies-trade
bian-2024-rule-or-story-which-is
brown-2025-pula-training-large-language-models

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