Modeling complex narrative memory via sentence recognition: A marriage of distributional semantic models and an episodic model (MINERVA 2)

Lexical and Discourse Semantics in a Reading-time Corpus of English

Using LMs to Model the Effects of Context and Coreference during Sentence Comprehension

This work systematically vary the context window size of GPT-2 across four large-scale naturalistic English reading-time datasets and observes a U-shaped relationship, demonstrating that tracking long-range coreference relations is one important factor for the alignment between LM surprisal and human reading behavior.

Word Category-Specific Semantic Deficits in Mild Cognitive Impairment: A BERT Embedding Analysis of Picture Description Narratives.

PURPOSE Mild cognitive impairment (MCI), a transitional state between normal aging and dementia, is associated with subtle but systematic disruptions in semantic memory, yet the representational mechanisms underlying these changes remain poorly understood. Grounded in neuropsychological evidence that semantic vulnerabi...

Syntactic headedness aligns with visual narrative structure.

Recent research has highlighted how visual narrative sequences involve similar structures and processing as syntax in language, yet no work has asked whether these structures may interact with each other. Here we examine whether the syntactic word orders and/or headedness of languages influence the orders of particular...

Discourse Structure as an Interpretable Signal for Detecting Hallucinated Chain-of-Thought Reasoning in Large Language Models

This paper studies hallucinated CoT as a discourse-structural phenomenon, not only a factual one, and suggests that discourse structure provides an interpretable signal for detecting reasoning hallucinations and complements existing factuality and uncertainty-based hallucination detectors.

The Structural Sources of Verb Meanings Revisited: Large Language Models Display Syntactic Bootstrapping

The results show that models’ verb representations degrade more when the authors perturb word order, which removes syntactic information, than when they perturb co-occurrence among content words, which removes semantic information.