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Beyond the limitations of any imaginable mechanism: large language models and psycholinguistics

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arxiv 2303.00077 v1 pith:MJBWIVAB submitted 2023-02-28 cs.CL cs.AI

classification cs.CLcs.AI
keywords languagemodelslargepsycholinguisticstheyanimalbasisbecause
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Large language models are not detailed models of human linguistic processing. They are, however, extremely successful at their primary task: providing a model for language. For this reason and because there are no animal models for language, large language models are important in psycholinguistics: they are useful as a practical tool, as an illustrative comparative, and philosophically, as a basis for recasting the relationship between language and thought.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Multi-granular Training Strategies for Robust Multi-hop Reasoning Over Noisy and Heterogeneous Knowledge Sources

    cs.CL 2025-02 reject novelty 2.0 of 10

    AMKOR is described as a state-of-the-art multi-hop QA system, but the paper provides no reproducible evidence and the reported numbers appear unverifiable.

  2. Generalization of Medical Large Language Models through Cross-Domain Weak Supervision

    cs.CL 2025-02 reject novelty 2.0 of 10

    A claimed curriculum-based fine-tuning framework for medical LLMs reports better question answering and response generation, but lacks reproducible evidence.

  3. Weak Supervision Dynamic KL-Weighted Diffusion Models Guided by Large Language Models

    cs.CL 2025-02 reject novelty 2.0 of 10

    A vague proposal for LLM-guided diffusion with dynamic KL weighting, backed by unsupported FID/IS tables.

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