3 citations · 13 across the 16 of their papers we have counts for
17 papers
Sequential Contextual Fit Predicts Human Behavioural and Neural Dynamics Across Domains
Kun Sun, Rong Wang
Human perception, action and decision making unfold in sequences, but computational predictors are often domain-specific. This study computes and tests sequential contextual fit (S…
Contextual Semantic Relevance Tracks fMRI BOLD Responses During Naturalistic Speech Comprehension
Kun Sun, Rong Wang
Naturalistic language comprehension requires listeners to process both local probabilistic expectations and contextual semantic relations. This study tested whether contextual sema…
Contextual Semantic Relevance and Word Surprisal Predict N400 and P600 Dynamics During Naturalistic Reading
Kun Sun, Rong Wang
Word surprisal is a well-established computational predictor of human neural responses during language comprehension, but it remains less clear whether local semantic fit explains…
Prior over Evidence: Stereotype-Driven Diagnosis in LLM-Based L2 Pronunciation Feedback
Rong Wang, Kun Sun
Large language models are increasingly deployed for written pronunciation feedback in second-language (L2) English learning, under the assumption that their diagnoses are grounded…
Stop When Further Reasoning Won't Help: Attention-State Adaptive Generation in Reasoning Models
Jiakai Li, Ke Qin, Rongzheng Wang +4
By incorporating test-time compute scaling, large reasoning models (LRMs) can solve complex problems through explicit chain-of-thought (CoT) reasoning processes. However, they ofte…
Systematic Framework of Application Methods for Large Language Models in Language Sciences
Kun Sun, Rong Wang
Large Language Models (LLMs) are transforming language sciences. However, their widespread deployment currently suffers from methodological fragmentation and a lack of systematic s…
The fragility of "cultural tendencies" in LLMs
Kun Sun, Rong Wang
In a recent study, Lu, Song, and Zhang (2025) (LSZ) propose that large language models (LLMs), when prompted in different languages, display culturally specific tendencies. They re…
Dspy-based Neural-Symbolic Pipeline to Enhance Spatial Reasoning in LLMs
Rong Wang, Kun Sun, Jonas Kuhn
Large Language Models (LLMs) have demonstrated remarkable capabilities across various tasks, yet they often struggle with spatial reasoning. This paper presents a novel neural-symb…
The Roles of Contextual Semantic Relevance Metrics in Human Visual Processing
Kun Sun, Rong Wang
Semantic relevance metrics can capture both the inherent semantics of individual objects and their relationships to other elements within a visual scene. Numerous previous research…
A Novel Dependency Framework for Enhancing Discourse Data Analysis
Kun Sun, Rong Wang
The development of different theories of discourse structure has led to the establishment of discourse corpora based on these theories. However, the existence of discourse corpora…
Textual Similarity as a Key Metric in Machine Translation Quality Estimation
Kun Sun, Rong Wang
Machine Translation (MT) Quality Estimation (QE) assesses translation reliability without reference texts. This study introduces "textual similarity" as a new metric for QE, using…
Continuous Output Personality Detection Models via Mixed Strategy Training
Rong Wang, Kun Sun
The traditional personality models only yield binary results. This paper presents a novel approach for training personality detection models that produce continuous output values,…
Automatic Essay Multi-dimensional Scoring with Fine-tuning and Multiple Regression
Kun Sun, Rong Wang
Automated essay scoring (AES) involves predicting a score that reflects the writing quality of an essay. Most existing AES systems produce only a single overall score. However, use…
TIMIT Speaker Profiling: A Comparison of Multi-task learning and Single-task learning Approaches
Rong Wang, Kun Sun
This study employs deep learning techniques to explore four speaker profiling tasks on the TIMIT dataset, namely gender classification, accent classification, age estimation, and s…
Computational Sentence-level Metrics Predicting Human Sentence Comprehension
Kun Sun, Rong Wang
The majority of research in computational psycholinguistics has concentrated on the processing of words. This study introduces innovative methods for computing sentence-level metri…
Differential contributions of machine learning and statistical analysis to language and cognitive sciences
Kun Sun, Rong Wang
Data-driven approaches have revolutionized scientific research, with machine learning and statistical analysis being commonly used methodologies. Despite their widespread use, thes…
Comprehensive Reassessment of Large-Scale Evaluation Outcomes in LLMs: A Multifaceted Statistical Approach
Kun Sun, Rong Wang, Anders Søgaard
Amidst the rapid evolution of LLMs, the significance of evaluation in comprehending and propelling these models forward is increasingly paramount. Evaluations have revealed that fa…