Papers with object extraction

2 papers
Do BabyLMs Wanna Learn Wanna Contraction? On the Learnability without Language-Specific Bias (2026.findings-acl)

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Challenge: grammatical constraints on wanna contraction can be learned by artificial learners under cognitively plausible learning conditions.
Approach: They evaluate 24 BabyLMs from 2024 BabyLM Challenge and four standard models . they find that only encoder-based BabyLM models can capture wanna contraction .
Outcome: The proposed models show modest but meaningful sensitivity on large datasets and high-frequency wanna instances.
How Do Multilingual Language Models Remember Facts? (2025.findings-acl)

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Challenge: Prior research has focused on English monolingual models, but how these mechanisms generalize to non-English languages remains unexplored.
Approach: They analyze three multilingual LLMs to find out how they can generalize recall mechanisms . they find that subject enrichment is language-independent, object extraction is language dependent .
Outcome: The proposed model performs better in multilingual contexts than in English models . the model is more efficient in multi-lingual context, but it is more complex in multilinguistic models compared to English models.

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