---
title: "Who cites Rafael Mosquera — 279 papers of our library"
description: "279 papers of the Elamur Research library cite the works of Rafael Mosquera, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/rafael-mosquera/cited-by/"
---
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# Who cites Rafael Mosquera

281 citations of their works from 279 papers of our library (of the 149,439 whose bibliographies we read) · 77 with a page here, the most cited first · [← Rafael Mosquera](https://md.research.elamur.ai/free/en/authors/rafael-mosquera/)

1. **[DataComp-LM: In search of the next generation of training sets for language models](https://md.research.elamur.ai/free/en/papers/li-2024-datacomp-lm-search-next-generation/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jeffrey Li, Alex Fang, Georgios Smyrnis, et al.*2024 · 191 citations*
2. **[ELEPHANT: Measuring and understanding social sycophancy in LLMs](https://md.research.elamur.ai/free/en/papers/cheng-2025-elephant-measuring-understanding-social-sycophancy/) [Science](https://md.research.elamur.ai/free/en/venues/science/)**Myra Cheng, Sunny Yu, Cinoo Lee, et al.*2025 · 188 citations*
3. [**AI Alignment: A Comprehensive Survey arXiv:2310.19852**Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.*2023 · 173 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-ai-alignment-comprehensive-survey/)
4. **[SciMON: Scientific Inspiration Machines Optimized for Novelty](https://md.research.elamur.ai/free/en/papers/wang-2023-scimon-scientific-inspiration-machines/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Qingyun Wang, Doug Downey, Heng Ji, et al.*2023 · 131 citations*
5. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
6. **[Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art](https://md.research.elamur.ai/free/en/papers/liu-2025-culturally-aware-adapted-nlp-taxonomy/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Chen Cecilia Liu, Iryna Gurevych, Anna Korhonen*2025 · 90 citations*
7. **[Apertus: Democratizing Open and Compliant LLMs for Global Language Environments](https://md.research.elamur.ai/free/en/papers/cano-2026-apertus-democratizing-open-compliant-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Alejandro Hernández-Cano, Alexander Hägele, Allen Hao Huang, et al.*2026 · 68 citations*
8. **[Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration](https://md.research.elamur.ai/free/en/papers/feng-2024-modular-pluralism-pluralistic-alignment-multi/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shangbin Feng, Taylor Sorensen, Yuhan Liu, et al.*2024 · 68 citations*
9. **[Language Models Learn Rare Phenomena from Less Rare Phenomena: The Case of the Missing AANNs](https://md.research.elamur.ai/free/en/papers/misra-2024-language-models-learn-rare-phenomena/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Kanishka Misra, Kyle Mahowald*2024 · 55 citations*
10. **[Benchmarking Distributional Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/meister-2025-benchmarking-distributional-alignment-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nicole Meister, Carlos Guestrin, Tatsunori Hashimoto*2025 · 35 citations*
11. **[Culture is Not Trivia: Sociocultural Theory for Cultural NLP](https://md.research.elamur.ai/free/en/papers/zhou-2025-culture-is-not-trivia-sociocultural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Naitian Zhou, David Bamman, Isaac L. Bleaman*2025 · 33 citations*
12. **[Language Model Fine-Tuning on Scaled Survey Data for Predicting Distributions of Public Opinions](https://md.research.elamur.ai/free/en/papers/suh-2025-language-model-fine-tuning-scaled/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Joseph Suh, Erfan Jahanparast, Suhong Moon, et al.*2025 · 28 citations*
13. **[The State of Multilingual LLM Safety Research: From Measuring The Language Gap To Mitigating It](https://md.research.elamur.ai/free/en/papers/yong-2025-state-multilingual-llm-safety-research/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zheng Xin Yong, Beyza Ermis, Marzieh Fadaee, et al.*2025 · 25 citations*
14. [**Language Model Alignment in Multilingual Trolley Problems arXiv:2407.02273**Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-language-model-alignment-multilingual-trolley/)
15. **[What is the Role of Small Models in the LLM Era: A Survey](https://md.research.elamur.ai/free/en/papers/chen-2024-role-small-models-llm-era/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Lihu Chen, Gael Varoquaux*2024 · 23 citations*
16. **[Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions](https://md.research.elamur.ai/free/en/papers/orlikowski-2025-beyond-demographics-fine-tuning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Matthias Orlikowski, Jiaxin Pei, Paul Röttger, et al.*2025 · 22 citations*
17. **[Can Language Models Reason about Individualistic Human Values and Preferences?](https://md.research.elamur.ai/free/en/papers/jiang-2025-can-language-models-reason-about/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liwei Jiang, Taylor Sorensen, Sydney Levine, et al.*2025 · 21 citations*
18. **[The AI Gap: How Socioeconomic Status Affects Language Technology Interactions](https://md.research.elamur.ai/free/en/papers/bassignana-2025-ai-gap-how-socioeconomic-status/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Elisa Bassignana, Amanda Cercas Curry, Dirk Hovy*2025 · 20 citations*
19. **[Is Child-Directed Speech Effective Training Data for Language Models?](https://md.research.elamur.ai/free/en/papers/feng-2024-is-child-directed-speech-effective/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Steven Y. Feng, Noah D. Goodman, Michael C. Frank*2024 · 18 citations*
20. **[IssueBench: Millions of Realistic Prompts for Measuring Issue Bias in LLM Writing Assistance](https://md.research.elamur.ai/free/en/papers/rottger-2026-issuebench-millions-realistic-prompts-measuring/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Paul Röttger, Musashi Hinck, Valentin Hofmann, et al.*2026 · 16 citations*
21. **[JuStRank: Benchmarking LLM Judges for System Ranking](https://md.research.elamur.ai/free/en/papers/gera-2025-justrank-benchmarking-llm-judges-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ariel Gera, Odellia Boni, Yotam Perlitz, et al.*2025 · 15 citations*
22. **[Value Profiles for Encoding Human Variation](https://md.research.elamur.ai/free/en/papers/sorensen-2025-value-profiles-encoding-human-variation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Taylor Sorensen, Pushkar Mishra, Roma Patel, et al.*2025 · 15 citations*
23. **[When One LLM Drools, Multi-LLM Collaboration Rules](https://md.research.elamur.ai/free/en/papers/feng-2026-when-one-llm-drools-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.*2026 · 14 citations*
24. **[Do Construction Distributions Shape Formal Language Learning In German BabyLMs?](https://md.research.elamur.ai/free/en/papers/bunzeck-2025-do-construction-distributions-shape-formal/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Bastian Bunzeck, Daniel Duran, Sina Zarrieß*2025 · 13 citations*
25. **[DevBench: A multimodal developmental benchmark for language learning](https://md.research.elamur.ai/free/en/papers/tan-2024-devbench-multimodal-developmental-benchmark-language/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Alvin Wei Ming Tan, Sunny Yu, Bria Long, et al.*2024 · 13 citations*
26. **[Latent Inter-User Difference Modeling for LLM Personalization](https://md.research.elamur.ai/free/en/papers/qiu-2025-latent-inter-user-difference-modeling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yilun Qiu, Tianhao Shi, Xiaoyan Zhao, et al.*2025 · 12 citations*
27. **[Whose Boat Does it Float? Improving Personalization in Preference Tuning via Inferred User Personas](https://md.research.elamur.ai/free/en/papers/balepur-2025-whose-boat-does-it-float/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nishant Balepur, Vishakh Padmakumar, Fumeng Yang, et al.*2025 · 12 citations*
28. **[Cognitive Plausibility in Natural Language Processing](https://md.research.elamur.ai/free/en/papers/matusevych-2024-cognitive-plausibility-natural-language-processing/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Yevgen Matusevych*2024 · 12 citations*
29. **[Can Language Models Learn Typologically Implausible Languages?](https://md.research.elamur.ai/free/en/papers/xu-2026-can-language-models-learn-typologically/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tianyang Xu, Tatsuki Kuribayashi, Yohei Oseki, et al.*2026 · 10 citations*
30. **[Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic Biases](https://md.research.elamur.ai/free/en/papers/hu-2025-between-circuits-chomsky-pre-pretraining/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael Y. Hu, Jackson Petty, Chuan Shi, et al.*2025 · 9 citations*
31. [**Language Models Fail to Introspect About Their Knowledge of Language arXiv:2503.07513**Siyuan Song, Jennifer Hu, Kyle Mahowald*2025 · 9 citations*](https://md.research.elamur.ai/free/en/papers/song-2025-language-models-fail-introspect-about/)
32. **[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*
33. **[Anything Goes? A Crosslinguistic Study of (Im)possible Language Learning in LMs](https://md.research.elamur.ai/free/en/papers/yang-2025-anything-goes-crosslinguistic-study-im/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiulin Yang, Tatsuya Aoyama, Yuekun Yao, et al.*2025 · 8 citations*
34. [**Manipulating language models' training data to study syntactic constraint learning: the case of English passivization arXiv:2407.04593**Cara Su-Yi Leong, Tal Linzen*2024 · 8 citations*](https://md.research.elamur.ai/free/en/papers/leong-2024-manipulating-language-models-training-data/)
35. **[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*
36. **[IPA CHILDES & G2P+: Feature-Rich Resources for Cross-Lingual Phonology and Phonemic Language Modeling](https://md.research.elamur.ai/free/en/papers/goriely-2025-ipa-childes-g2p-feature-rich/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Zébulon Goriely, Paula Buttery*2025 · 6 citations*
37. **[Minimal Pair-Based Evaluation of Code-Switching](https://md.research.elamur.ai/free/en/papers/sterner-2025-minimal-pair-based-evaluation-code/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Igor Sterner, Simone Teufel*2025 · 6 citations*
38. **[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*
39. **[LLM Alignment for the Arabs: A Homogenous Culture or Diverse Ones](https://md.research.elamur.ai/free/en/papers/keleg-2025-llm-alignment-arabs-homogenous-culture/) [Workshop on Cross-Cultural Considerations in NLP](https://md.research.elamur.ai/free/en/venues/c3nlp/)**Amr Keleg*2025 · 5 citations*
40. **[Extending ASR Evaluation Resources for Modern Greek Dialects](https://md.research.elamur.ai/free/en/papers/tsoukala-2026-extending-asr-evaluation-resources-modern/) [Workshop on NLP for Similar Languages, Varieties and Dialects (VarDial)](https://md.research.elamur.ai/free/en/venues/vardial/)**Chara Tsoukala, Stavros Bompolas, Antigoni Margariti, et al.*2026 · 4 citations*
41. **[Language Statistics and False Belief Reasoning: Evidence from 41 Open-Weight LMs](https://md.research.elamur.ai/free/en/papers/trott-2026-language-statistics-false-belief-reasoning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sean Trott, Samuel M. Taylor, Cameron Robert Jones, et al.*2026 · 3 citations*
42. [**TafBERTa: Learning Grammatical Rules from Small-Scale Language Acquisition Data in Hebrew**Anita Gelboim, Elior Sulem*2025 · 3 citations*](https://md.research.elamur.ai/free/en/papers/gelboim-2025-tafberta-learning-grammatical-rules-small/)
43. **[Kenji-Endo: a BabyLM @EVALITA](https://md.research.elamur.ai/free/en/papers/scozzaro-2026-kenji-endo-babylm-evalita/) [Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop](https://md.research.elamur.ai/free/en/venues/evalita/)**Calogero Jerik Scozzaro, Matteo Rinaldi, Gianluca Mittone, et al.*2026 · 2 citations*
44. **[Using Curriculum Masking Based on Child Language Development to Train a Large Language Model with Limited Training Data](https://md.research.elamur.ai/free/en/papers/lucas-2024-curriculum-masking-based-child-language/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Evan Lucas, Dylan Gaines, Tagore Rao Kosireddy, et al.*2024 · 2 citations*
45. **[An Existence Proof for Neural Language Models That Can Explain Garden-Path Effects via Surprisal](https://md.research.elamur.ai/free/en/papers/yoshida-2026-existence-proof-neural-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ryo Yoshida, Shinnosuke Isono, Taiga Someya, et al.*2026 · 1 citation*
46. **[CuMA: Aligning LLMs with Sparse Cultural Values via Demographic-Aware Mixture of Adapters](https://md.research.elamur.ai/free/en/papers/sun-2026-cuma-aligning-llms-sparse-cultural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ao Sun, Xiaoyu Wang, Zhe Tan, et al.*2026 · 1 citation*
47. **[Do BabyLMs Wanna Learn Wanna Contraction? On the Learnability without Language-Specific Bias](https://md.research.elamur.ai/free/en/papers/noh-2026-do-babylms-wanna-learn-wanna/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kangsan Noh, Sanghoun Song*2026 · 1 citation*
48. **[Human-like Fleeting Memory Improves Language Learning but Impairs Reading Time Prediction in Transformer Language Models](https://md.research.elamur.ai/free/en/papers/thamma-2026-human-like-fleeting-memory-improves/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Abishek Thamma, Micha Heilbron*2026 · 1 citation*
49. **[Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions](https://md.research.elamur.ai/free/en/papers/scivetti-2026-language-models-learn-constructional-semantics/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Wesley Scivetti, Ethan Gotlieb Wilcox, Nathan Schneider, et al.*2026 · 1 citation*
50. **[P-Check: Advancing Personalized Reward Model via Learning to Generate Dynamic Checklist](https://md.research.elamur.ai/free/en/papers/seo-2026-p-check-advancing-personalized-reward/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kwangwook Seo, Dongha Lee*2026 · 1 citation*
51. **[What Exactly do Children Receive in Language Acquisition? A Case Study on CHILDES with Automated Detection of Filler-Gap Dependencies](https://md.research.elamur.ai/free/en/papers/zhou-2026-what-exactly-do-children-receive/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Zhenghao Zhou, William Dai, Maya Viswanathan, et al.*2026 · 1 citation*
52. **[When Do Language Models Endorse Limitations on Human Rights Principles?](https://md.research.elamur.ai/free/en/papers/samway-2026-when-do-language-models-endorse/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Keenan Samway, Miu Nicole Takagi, Rada Mihalcea, et al.*2026 · 1 citation*
53. **[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/) [BabyLM Workshop](https://md.research.elamur.ai/free/en/venues/babylm/)**Ansar Aynetdinov, Alan Akbik*2025 · 1 citation*
54. **[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/) [BabyLM Workshop](https://md.research.elamur.ai/free/en/venues/babylm/)**Ko Yoshida, Daiki Shiono, Kai Sato, et al.*2025 · 1 citation*
55. **[Dreaming Out Loud: A Self-Synthesis Approach For Training Vision-Language Models With Developmentally Plausible Data](https://md.research.elamur.ai/free/en/papers/alkhamissi-2024-dreaming-out-loud-self-synthesis/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Badr AlKhamissi, Yingtian Tang, Abdülkadir Gökce, et al.*2024 · 1 citation*
56. **[\textitOne Persona, \textitMany Cues, \textitDifferent Results: How Sociodemographic Cues Impact LLM Personalization](https://md.research.elamur.ai/free/en/papers/weeber-2026-textitone-persona-textitmany-cues-textitdifferent/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Franziska Weeber, Vera Neplenbroek, Jan Batzner, et al.*2026*
57. **[Bias Dynamics in BabyLMs: Towards a Compute-Efficient Sandbox for Democratising Pre-Training Debiasing](https://md.research.elamur.ai/free/en/papers/trhlik-2026-bias-dynamics-babylms-compute-efficient/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Filip Trhlík, Andrew Caines, Paula Buttery*2026*
58. **[Calibrating LLM Judges: Linear Probes for Fast and Reliable Uncertainty Estimation](https://md.research.elamur.ai/free/en/papers/radharapu-2026-calibrating-llm-judges-linear-probes/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bhaktipriya Radharapu, Eshika Saxena, Kenneth Li, et al.*2026*
59. **[Can a Remedy Find a Researcher? Exploring the Development of Semantic Knowledge in Italian BabyLMs](https://md.research.elamur.ai/free/en/papers/suozzi-2026-can-remedy-find-researcher-exploring/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Alice Suozzi, Luca Capone, Gianluca Lebani, et al.*2026*
60. **[Carefully Considering Culture: Analyzing LLM Alignment in Single- and Multi-Cultural Settings using Cultural Consensus Theory](https://md.research.elamur.ai/free/en/papers/pothugunta-2026-carefully-considering-culture-analyzing-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Krishna Pothugunta, John P. Lalor*2026*
61. **[Character-aware Transformers Learn an Irregular Morphological Pattern Yet None Generalize Like Humans](https://md.research.elamur.ai/free/en/papers/ramarao-2026-character-aware-transformers-learn-irregular/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Akhilesh Kakolu Ramarao, Kevin Tang, Dinah Baer-Henney*2026*
62. **[Child-directed speech facilitates production, not comprehension, in BabyLMs](https://md.research.elamur.ai/free/en/papers/bunzeck-2026-child-directed-speech-facilitates-production/) [Conference on Computational Natural Language Learning (CoNLL)](https://md.research.elamur.ai/free/en/venues/conll/)**Bastian Bunzeck, Sina Zarrieß*2026*
63. **[ChineseDevBench: A Chinese Developmental Benchmark for Language Development](https://md.research.elamur.ai/free/en/papers/wang-2026-chinesedevbench-chinese-developmental-benchmark-language/) [Workshop on Cognitive Modeling and Computational Linguistics (CMCL)](https://md.research.elamur.ai/free/en/venues/cmcl/)**Shaonan Wang, Yiwen Wu, Na Li, et al.*2026*
64. **[Computational Benchmarks for Egyptian Arabic Child Directed Speech](https://md.research.elamur.ai/free/en/papers/khalifa-2026-computational-benchmarks-egyptian-arabic-child/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Salam Khalifa, Abed Qaddoumi, Nizar Habash, et al.*2026*
65. **[CoopValue: Revealing LLM Value Preferences Through Multi-Agent Cooperation](https://md.research.elamur.ai/free/en/papers/tang-2026-coopvalue-revealing-llm-value-preferences/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zee Hen Tang, Mi-Yen Yeh*2026*
66. **[Evaluating Language Model Pluralism through In-the-wild Crowd Discussions](https://md.research.elamur.ai/free/en/papers/mundada-2026-evaluating-language-model-pluralism-through/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gagan Mundada, Rohan Surana, Nandhini Swaminathan, et al.*2026*
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