Structural Priming in Language Models: Insights from Lexical and Frequency-Based Factors
Language models exhibit structural priming effects that can be explained by inverse frequency effects, such as prime surprisal and verb preference, as well as lexical dependence between prime and target.
Computational Analysis of Character Representation Shifts Across Online Fan Communities: A Case Study of Harry Potter
Online fan communities, such as fanfiction and forums, collaboratively reconstruct and renegotiate narrative elements like characters, leading to divergent representations from the original source material.
Sense-Specific Pitch Contours of Monosyllabic Words in Conversational Taiwan Mandarin
The realization of pitch contours of monosyllabic words in spontaneous Taiwan Mandarin speech is co-determined by tonal context, word identity, and word sense.
Multilingual Probing of Syntactic Representations in Pretrained Language Models
Pretrained multilingual language models do not encode abstract cross-linguistic syntactic structures, but rather rely on shallow language-specific cues.
A Quantitative and Typological Study of Early Slavic Participle Clauses and Their Competition with Finite Temporal Clauses
Early Slavic participle clauses (conjunct participles and dative absolutes) compete with finite temporal clauses (jegda-clauses) in the expression of temporal relations and discourse organization, with the choice between these constructions being motivated by factors such as information structure, discourse relations, and cross-linguistic typological patterns.
Maximizing Phylogenetic Signal in Cognate Data: Integrating Synonyms through Probabilistic Character Matrices
Cognate data with synonyms can be effectively represented using probabilistic character matrices to maximize the phylogenetic signal during maximum likelihood tree inference.
Modeling Orthographic and Lexical Variation Across Occitan Dialects
Large multilingual language models can effectively represent orthographic and lexical variation across Occitan dialects without the need for extensive data normalization.
Explainable Machine Learning Approaches for Geolinguistic Authorship Profiling in Forensic Linguistics: A Case Study
Explainable machine learning approaches can provide valuable insights for geolinguistic authorship profiling in forensic linguistics, complementing traditional qualitative methods.
Evaluating Large Language Model Performance on Part-of-Speech Tagging for Indigenous and Low-resource Brazilian Languages
Large Language Models perform poorly on part-of-speech tagging for indigenous and low-resource Brazilian languages compared to high-resource languages, but language adaptation can improve cross-lingual transfer performance.
Exploring Morphological Means of Expressing Temporal Subordination in Latin American and Caribbean Languages
Morphological means of expressing generic temporal subordination ('when'-clauses) are prevalent in many Latin American and Caribbean languages, posing challenges for token-based typological approaches. This study incorporates character n-gram analysis to capture such morphological markers alongside lexical subordinators, generating probabilistic semantic maps that reveal systematic cross-linguistic variation in the region.
© 2024 by Linnk AI