Papers by Aya Meltzer-Asscher
Large Language Models for Psycholinguistic Plausibility Pretesting (2024.findings-eacl)
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| Challenge: | Psycholinguists typically use language models to create controlled materials . plausibility judgments are often based on coarse-grained judgements, but fine-grounded ones do not . |
| Approach: | They investigate whether Language Models can be used to generate plausibility judgments . they find that plausible judgements from LMs are highly related to human judgements - whereas other LM models are not . |
| Outcome: | The proposed language models can generate plausibility judgments from human evaluators . the proposed models do not provide satisfactory discriminative power . |
When the LM misunderstood the human chuckled: Analyzing garden path effects in humans and language models (2025.acl-long)
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| Challenge: | Modern Large Language Models (LLMs) have shown human-like abilities in many language tasks, sparking interest in comparing LLMs’ and humans’ language processing. |
| Approach: | They propose to answer two questions: 1. What makes garden-path sentences hard for humans? 2. Do the same reasons make garden- path sentences hard? |
| Outcome: | The proposed models show that humans struggle with specific syntactic complexities, with some models showing high correlation with human comprehension. |
Comparing human and language models sentence processing difficulties on complex structures (2026.acl-long)
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| Challenge: | Large language models (LLMs) that converse with humans are a reality, but do LLMs experience human-like processing difficulties? |
| Approach: | They systematically compare human and LLM sentence comprehension across seven challenging linguistic structures. |
| Outcome: | The proposed model achieves near perfect accuracy on non-GP structures, but struggles on GP structures. |