Search Results for author:
Found 8 papers, 2 papers with code
Multilingual Pretraining and Instruction Tuning Improve Cross-Lingual Knowledge Alignment, But Only Shallowly
In this paper, we propose CLiKA, a systematic framework to assess the cross-lingual knowledge alignment of LLMs in the Performance, Consistency and Conductivity levels, and explored the effect of multilingual pretraining and instruction tuning on the degree of alignment.
Measuring Meaning Composition in the Human Brain with Composition Scores from Large Language Models
Drawing on the key-value memory interpretation of transformer feed-forward network blocks, we introduce the Composition Score, a novel model-based metric designed to quantify the degree of meaning composition during sentence comprehension.
Roles of Scaling and Instruction Tuning in Language Perception: Model vs. Human Attention
Recent large language models (LLMs) have revealed strong abilities to understand natural language.
ACQ: Improving Generative Data-free Quantization Via Attention Correction
This is always ignored and restricts the quantization performance.
Quantifying Discourse Support for Omitted Pronouns
Pro-drop is commonly seen in many languages, but its discourse motivations have not been well characterized.
The Role of Syntax During Pronoun Resolution: Evidence from fMRI
The current study examined the role of syntactic structure during pronoun resolution.
Modeling Brain Activity Associated with Pronoun Resolution in English and Chinese
Typological differences between English and Chinese suggest stronger reliance on salience of the antecedent during pronoun resolution in Chinese.
Temporal Lobes as Combinatory Engines for both Form and Meaning
The relative contributions of meaning and form to sentence processing remains an outstanding issue across the language sciences.
