Language Comprehension Research Articles

Integration of web scraping, fine-tuning, and data enrichment in a continuous monitoring context via large language model operations

This paper presents and discusses a framework that leverages large-scale language models (LLMs) for data enrichment and continuous monitoring emphasizing its essential role in optimizing the performance of deployed models. It introduces a comprehensive large language model operations (LLMOps) methodology based on continuous monitoring and continuous improvement of the data, the primary determinant of the model, in order to optimize the prediction of a given phenomenon. To this end, first we examine the use of real-time web scraping using tools such as Kafka and Spark Streaming for data acquisition and processing. In addition, we explore the integration of LLMOps for complete lifecycle management of machine learning models. Focusing on continuous monitoring and improvement, we highlight the importance of this approach for ensuring optimal performance of deployed models based on data and machine learning (ML) model monitoring. We also illustrate this methodology through a case study based on real data from several real estate listing sites, demonstrating how MLflow can be integrated into an LLMOps pipeline to guarantee complete development traceability, proactive detection of performance degradations and effective model lifecycle management.

Do local coherence effects exist in English reduced relative clauses?

For decades, a major underlying assumption behind theories of sentence comprehension has been that the parser only entertains analyses that are grammatically consistent with all words encountered in the sentence so far. A dramatic challenge to this self-consistency assumption came from two self-paced reading experiments in English (Tabor et al. 2004). Using a syntactic and a syntactic–semantic manipulation, Tabor et al. (2004) found that participants read a string of words more slowly if the string could locally form a grammatical structure that is ungrammatical given the preceding words. In the years since, such local coherence effects, and in particular syntactic local coherence effects, have generated much debate about the nature of human sentence parsing, and have become a central explanandum for psycholinguistic theories. Despite this attention, to our knowledge no one has directly attempted to replicate the claimed effects. Here, we present a large-sample replication attempt using the original Tabor et al. (2004) syntactic and syntactic–semantic local coherence design using two methods (self-paced reading and bidirectional self-paced reading). A Bayes factor analysis shows evidence against a large, immediate effect of syntactic local coherence in reading, and only anecdotal evidence for a syntactic–semantic local coherence effect, but only in bidirectional self-paced reading. In this paradigm, there are also large effects of local coherence on rereading, which may be due to error recovery mechanisms, and which do not affect all participants. Our results suggest that the original effect sizes, especially for the much-debated early syntactic local coherence effect, are likely to be overestimates due to low power in the original Tabor et al. (2004) study. An important implication for psycholinguistic theory is that the challenge to self-consistency posed by local coherence effects is not as strong as previously believed.

Natural Language Processing (NLP) in Artificial Intelligence

Natural language processing (NLP) which is a branch of Artificial Intelligence (AI) has experienced significant improvement in the recent past to allow machines to language comprehend and generate. They consist of uses like machine translation, sentiment analysis, chatbots, and virtual assistants, which form a cornerstone part of life. However, even with these advances, NLP still has numerous critical difficulties that affect its proficiency and usefulness in applying the systems. Some of the major problems include one language may mean different things to different people; every situation requires different approaches; and finally people from different cultures and languages will pose a significant problem. This paper presents evidence of lexical, syntactic, and semantic ambiguities that complicate the language understanding process. Besides that, NLP models are not able to comprehend the flow of human’s dialogues which is important factor of the communication. The problem of language diversity in human dialogue makes it even more challenging to develop NLP since over 7,000 languages are characterized by unique structures and expressions. With the recent development in Machine learning, and deep learning, these challenges have been well addressed. Pretrained transformer models like BERT and GPT have greatly enriched the field’s tech arsenal, since language comprehension and Boolean modernity loops very difficult to model and tackle. This journal provides a comprehensive look at these issues presents current technologies and examines new trends pertaining to NLP. Lastly, it brings focus on way ethical concerns like bias are paramount in making current NLP systems neutral. Looking forward more advances are expected in NLP which has the prospective of further improvement of interaction between human and computer.

Dynamic reorganization of task-related network interactions in post-stroke aphasia recovery.

Post-stroke aphasia is a network disorder characterized by language impairments and aberrant network activation. While patients with post-stroke aphasia recover over time, the dynamics of the underlying changes in the brain remain elusive. Neuroimaging work demonstrated that language recovery is a heterogeneous process, characterized by varying activation levels in several regions of the left-hemispheric language network and the domain-general bilateral multiple-demand network. Crucially, this activation seems to depend on the time elapsed since stroke and the lesion location. Yet, beyond task-related brain activation, the degree and nature of interactions between regions of the language and the multiple-demand network are not well understood. In this longitudinal functional neuroimaging study, we characterized task-related functional interactions between regions of the language and the multiple-demand network during language processing. We hypothesized that interactions between language regions and between language and multiple-demand regions should change over time and depend on lesion location. We compared changes in effective connectivity in patients with left-hemispheric frontal or temporo-parietal stroke (n=17 per group) and healthy controls (n=17) with Dynamic Causal Modelling. All patients repeatedly underwent an auditory sentence comprehension paradigm during functional neuroimaging in the acute (≤ 1 week), subacute (1-2 weeks), and chronic (> 6 months) phases after stroke. We found overall increased task-related connectivity from regions of the multiple-demand to the language network across patients, resembling the principal pattern of task-related interactions in controls. Early facilitation from multiple-demand to language regions correlated with later language improvement across both groups. Crucially, recruitment of specific connections from regions of the multiple-demand to language network depended on lesion location and changed over time. In the chronic phase, patients with frontal stroke showed facilitatory modulation from the right dorsolateral prefrontal cortex, while patients with temporo-parietal stroke integrated the supplementary motor area/dorsal anterior cingulate cortex. Besides this across-network reorganization, facilitatory connectivity between regions of the language network emerged in all patients in the subacute phase. Additionally, patients with frontal stroke showed facilitatory influences from the right lesion homologue to the remaining undamaged left inferior frontal cortex in the acute phase. Collectively, we provide first evidence that functional interactions of regions within and across the language and the multiple-demand network facilitate aphasia recovery. The identified dynamic reorganization principles over the time course of recovery may inform the future use of personalized treatment protocols with neurostimulation in aphasia rehabilitation. These protocols should be tailored to the individual lesion location and recovery phase.

Assessing sign language comprehension in adults with intellectual disability and deafness.

Language comprehension is an essential component of human development that is associated not only with expressive language development and knowledge acquisition, but also with social inclusion, mental health, and quality of life. For deaf and hard-of-hearing adults with intellectual disability, there is a paucity of measures of receptive sign language skills, although these are a prerequisite for individualized planning and evaluation of intervention. Assessments require materials and procedures that are accurate, feasible, and suitable for low levels of functioning. We adapted measures of English-language comprehension in young children-a direct assessment and a caregiver questionnaire-into Austrian Sign Language and to the target group of adults with intellectual disability and used them with a non-preselected sample of 67 deaf and hard-of-hearing adults with intellectual disability living in therapeutic communities specifically for deaf and hard-of-hearing people with multiple disabilities in Austria. Findings for both assessments demonstrate their construct validity, excellent internal consistency, and a large symmetrical distribution over the referential age range. Acceptance by the deaf and hard-of-hearing individuals and the caregivers and time-efficient administration suggest high practicability. We recommend further implementation in clinical practice, albeit with cautious interpretation of the results, and the inclusion of the instruments in research on intellectual disability and deafness.

The Parallel Architecture—application and explanatory power for neurolinguistic research

Various linguistic models have been developed to systematize language processes and provide a structured framework for understanding the complex network of language production and reception. However, these models have often been developed in isolation from neurolinguistic research, which continues to provide new insights into the mental processes involved in language production and comprehension. Conversely, neurolinguists often neglect the potential benefits of incorporating contemporary linguistic models into their research, although these models could help interpret specific findings and make complex concepts more accessible to readers. This paper evaluates the utility of Jackendoff's Parallel Architecture as a generic framework for explaining language acquisition. It also explores the potential for incorporating neurolinguistic findings by mapping its components onto specific neural structures, functions, and processes within the brain. To this end, we reviewed findings from a range of neurolinguistic studies on language acquisition and tested how their results could be represented using the Parallel Architecture. Our results indicate that the framework is generally well-suited to illustrate many language processes and to explain how language systems are built. However, to increase its explanatory power, it would be beneficial to add other linguistic and non-linguistic structures, or to signal that there is the option of adding such structures (e.g., prosody or pragmatics) for explaining the processes of initiating language acquisition or non-typical language acquisition. It is also possible to focus on fewer structures to show very specific interactions or zoom in on chosen structures and substructures to outline processes in more detail. Since the Parallel Architecture is a framework of linguistic structures for modeling language processes rather than a model of specific linguistic processes per se, it is open to new connections and elements, and therefore open to adaptations and extensions as indicated by new findings in neuro- or psycholinguistics.

The Impacts of Watching Videos on Improving Tertiary-Level Students’ English Language Speaking Skill

With the advancement of technology, video-based learning has become a dynamic tool for language learning that provides real-world language input via multimodal resources. This research aims to identify the impacts of watching videos on improving tertiary-level students’ English language speaking skill, focusing on vocabulary, comprehension, motivation, pronunciation, grammar, fluency, confidence, participation, and overall speaking skill. Despite the growing use of videos in language learning, there is a notable gap in the literature regarding their specific impacts on improving speaking skill at the tertiary level. Limited studies have explored the direct impacts of watching videos on improving speaking skill. This research addresses this gap by identifying how watching videos affects speaking skill and assessing students' perceptions about the impacts of watching videos on improving English language speaking skill. This research design was quantitative, and a questionnaire was used for data collection. The participants were twenty-eight non-native English-speaking students of the sophomore class of the English Language and Literature Department, Faculty of Languages and Literature, Kandahar University. The findings revealed that watching videos significantly improved vocabulary, comprehension, motivation, pronunciation, grammar, fluency, confidence, participation, and overall English language speaking skill. The results of this research have important implications for educators and curriculum designers, highlighting the impacts of watching videos to create engaging and effective language learning opportunities.

Noisy-channel language comprehension in aphasia: A Bayesian mixture modeling approach.

Individuals with "agrammatic" receptive aphasia have long been known to rely on semantic plausibility rather than syntactic cues when interpreting sentences. In contrast to early interpretations of this pattern as indicative of a deficit in syntactic knowledge, a recent proposal views agrammatic comprehension as a case of "noisy-channel" language processing with an increased expectation of noise in the input relative to healthy adults. Here, we investigate the nature of the noise model in aphasia and whether it is adapted to the statistics of the environment. We first replicate findings that a) healthy adults (N = 40) make inferences about the intended meaning of a sentence by weighing the prior probability of an intended sentence against the likelihood of a noise corruption and b) their estimate of the probability of noise increases when there are more errors in the input (manipulated via exposure sentences). We then extend prior findings that adults with chronic post-stroke aphasia (N = 28) and healthy age-matched adults (N = 19) similarly engage in noisy-channel inference during comprehension. We use a hierarchical latent mixture modeling approach to account for the fact that rates of guessing are likely to differ between healthy controls and individuals with aphasia and capture individual differences in the tendency to make inferences. We show that individuals with aphasia are more likely than healthy controls to draw noisy-channel inferences when interpreting semantically implausible sentences, even when group differences in the tendency to guess are accounted for. While healthy adults rapidly adapt their inference rates to an increase in noise in their input, whether individuals with aphasia do the same remains equivocal. Further investigation of comprehension through a noisy-channel lens holds promise for a parsimonious understanding of language processing in aphasia and may suggest potential avenues for treatment.

The Predictive Processing of Number Information in L1 and L2 Arabic Speakers

Prior research has shown that people can predict the syntactic features of an upcoming word during sentence comprehension. However, evidence for morphosyntactic predictive processing has been limited to gender or case marking in a small subset of Indo-European languages. In the current study, we implemented the eye-tracking visual world paradigm to investigate whether L1 (n = 18) and L2 (n = 40) Arabic speakers could extract number information from singular-marked verbs to anticipate the next noun. In a between-subject design, L1 and L2 speakers heard the singular verb in the simple past form (Exp 1) and the progressive past form (Exp 2). The effect of L2 proficiency (measured using a C-test and a receptive vocabulary test) on number prediction was also examined. L1 Arabic speakers showed earlier and stronger number prediction effects regardless of verb aspect. In contrast, L2 speakers exhibited delayed (Exp 1) or limited (Exp 2) prediction, suggesting a mediating role for verb aspect. Increased L2 proficiency did not influence anticipatory eye-movements during the verb region, and only emerged as significant during the noun region. These results confirm and extend earlier research on L1 and L2 number predictive processing.

Profiling Cognitive and Social Functioning in a Small Cohort with Malan Syndrome

Background/Objectives: Malan syndrome (MALNS) is an ultra-rare genetic disorder caused by aberrations in the NFIX gene, located at chromosome 19p13.2. Key features of MALNS include general overgrowth, a typical facial gestalt, muscle–skeletal abnormalities, speech difficulties and intellectual disability. Additionally, MALNS frequently presents with autism-like behaviour and social challenges. However, characterisation of the cognitive profile of MALNS, including social perception skills, is limited. Methods: Six children and adolescents with MALNS, whose clinical and emotional–behavioural features had been described in previous studies, were assessed by means of a single, co-normed neuropsychological battery covering multiple cognitive domains. Results: Consistent with their intellectual disability, performance was generally weak across all neuropsychological subtests. Nonetheless, memory for faces, visual attention and contextual (non-verbal) theory of mind emerged as relative strengths of the profile, both at group and individual levels. Conversely, tasks requiring verbal reasoning and language comprehension, such as comprehension of instructions and verbal theory of mind, represented weaknesses for all participants. Conclusions: These findings provide a further characterisation of cognitive and social functioning in MALNS, which can inform future research as well as clinical practice and rehabilitation

Scientific Large Language Models: A Survey on Biological & Chemical Domains

Large Language Models (LLMs) have emerged as a transformative power in enhancing natural language comprehension, representing a significant stride toward artificial general intelligence. The application of LLMs extends beyond conventional linguistic boundaries, encompassing specialized linguistic systems developed within various scientific disciplines. This growing interest has led to the advent of scientific LLMs, a novel subclass specifically engineered for facilitating scientific discovery. As a burgeoning area in the community of AI for Science, scientific LLMs warrant comprehensive exploration. However, a systematic and up-to-date survey introducing them is currently lacking. In this paper, we endeavor to methodically delineate the concept of “scientific language”, whilst providing a thorough review of the latest advancements in scientific LLMs. Given the expansive realm of scientific disciplines, our analysis adopts a focused lens, concentrating on the biological and chemical domains. This includes an in-depth examination of LLMs for textual knowledge, small molecules, macromolecular proteins, genomic sequences, and their combinations, analyzing them in terms of model architectures, capabilities, datasets, and evaluation. Finally, we critically examine the prevailing challenges and point out promising research directions along with the advances of LLMs. By offering a comprehensive overview of technical developments in this field, this survey aspires to be an invaluable resource for researchers navigating the intricate landscape of scientific LLMs.

Common and distinct ERP responses to violations of two different types of politeness maxims during sentence comprehension.

An ERP experiment was conducted to investigate the common and distinct neurocognitive mechanisms underlying the on-line processing of two types of politeness maxims (self-depreciation and other-elevation) and the individual differences during sentence reading. Electroencephalograms were recorded while participants read sentences containing pragmatically appropriate or inappropriate honorific or humble terms. When collapsing all participants' data, inappropriate humble and honorific terms elicited N400 and P600 effects, respectively, which could reflect semantic processing costs and rechecking processes, respectively. More importantly, communication abilities modulated N400 and late negativity effects for appropriateness for humble but not honorific terms. In contrast, perspective-taking and emphatic concern modulated N400 and late positivity effects, respectively, for honorific but not humble terms. Moreover, some commonness of the appropriateness effect modulation by individual variables was also observed. These results are discussed in terms of the commonness and individuality of neurocognitive mechanisms underlying the processing of different politeness maxims during sentence comprehension.

Eyes on the Pupil Size: Pupillary Response During Sentence Processing in Aphasia

Eyes on the Pupil Size: Pupillary Response During Sentence Processing in Aphasia

Respektuje český zákonodárce princip subsidiarity trestní represe?

In this article the author expresses the conviction that it is necessary to continue to uphold the principle of subsidiarity of penal repression (other terms used are “the subsidiarity role of criminal law”, “the limitation of criminal law” or “the ultima ratio principle”), no matter how ambiguous the hitherto development of the Czech Republic’s criminal policy may have been. To assess the level of country’s criminal law repressiveness, we especially need to look at the scope of criminalization, i.e. the range of anti- social conduct against which the state applies criminal sanctions. Further elements to be considered are the severity of penal sanctions, the minimum age for criminal liability, the scope of circumstances excluding the illegality of an act, the conditions under which criminal liability of a person expires, the conditions under which criminal penalties are enforced, the rigor of procedural laws and above all the standard of fundamental human rights guarantees applicable during criminal proceedings. In the author’s view, the tendency towards more repression has prevailed in the draft of the new Czech Penal Code and is manifested mainly through the criminalization of acts that have so far not been considered criminal offences or have only very recently been introduced by amendment to the Penal Code (esp. by increasing the number of the “prematurely completed” offences and the abstract generally- endangering offences). Further, the draft includes longer prison terms and would introduce a lower age limit for criminal liability and more severe sanctions for particularly dangerous recidivists. The authors expresses serious doubts about this trend and points out its possible negative effects. In the final part the author speaks out for upholding the long-term objective of any modem criminal policy, which is to reintegrate offenders back into society instead of ostracizing them. The means to achieve this objective is the inclusion of offenders into the process of criminal prosecution and sentencing.

A Study on Pivot Sentences Acquisition of International Students based on Natural Language Processing Technologies

In the context of the rapid development of globalized education, the demand for Chinese language learning among international students continues to rise. As a special and complex sentence structure in Chinese, the acquisition of "pivot sentences" is of great importance. Traditional acquisition research methods often rely on manual annotation and empirical analysis, which are difficult to handle large-scale data and are subject to a high degree of subjectivity. With the rapid advancement of natural language processing (NLP) technologies, new opportunities have emerged for research in this field. This paper utilizes various techniques from NLP, such as pre-trained language models (e.g., BERT, GPT) and grammar error detection methods based on Bayesian classification algorithms, to automatically analyze the production of pivot sentences by international students. These technologies enable precise identification of grammatical errors, syntactic structure anomalies, and inappropriate word usage in serial verb constructions. By deeply exploring the underlying causes of error patterns, this research provides a comprehensive and systematic understanding of the acquisition process of pivot sentences by international students, offering strong support for targeted teaching and promoting the advancement of Chinese as a second language education to a new level.

Neural connectivity underlying core language functions.

Although many white matter tracts underlying language functions have been identified, even in aggregate they do not provide a sufficiently detailed and expansive picture to enable us to fully understand the computational processes that might underly language production and comprehension. We employed diffusion tensor tractography (DTT) with a tensor distribution model to more extensively explore the white matter tracts supporting core language functions. Our study was guided by hypotheses stemming largely from the aphasia literature. We employed high angular resolution diffusion imaging (HARDI) with a dual region of interest tractography approach. Our diffusion tensor distribution model uses a mixture of Wishart distributions to estimate the water molecule displacement probability functions on a voxel-by-voxel basis and to model crossing/branching fibers using a multicompartmental approach. We replicated the results of previously published studies of tracts underlying language function. Our study also yielded a number of novel findings: 1) extensive connectivity between Broca's region and the entirety of the middle and superior frontal gyri; 2) extensive interconnectivity between the four subcomponents of Broca's region, pars orbitalis, pars triangularis, pars opercularis, and the inferior precentral gyrus; 3) connectivity between the mid-superior temporal gyrus and the transverse gyrus; 4) connectivity between the mid-superior temporal gyrus, the transverse gyrus, and the planum temporale and the inferior and middle temporal gyri; and 5) connectivity between mid- and anterior superior temporal gyrus and all components of Broca's region. These results, which replicate the results of prior DTT studies, also considerably extend them and thereby provide a fuller picture of the structural basis of language function and the basis for a novel model of the neural network architecture of language function. This new model is entirely consistent with discoveries from the aphasia literature and with parallel distributed processing conceptualizations of language function.

Usefulness of Large Language Models (LLMs) for Student Feedback on H&P During Clerkship: Artificial Intelligence for Personalized Learning

Large Language Models (LLMs) notably GPT-4, demonstrate exceptional language generation and comprehension abilities, and they have potential uses in clinical practice, learning, and medical research. In this study, we explore practical use of Large Language Models (LLMs) in enhancing case-based learning in medical education. The study employes a designed mixed-methods approach, combining quantitative metrics with qualitative feedback from 100 medical students, providing comprehensive insights into both the technical performance and educational value of LLM-based feedback systems. Our results indicate that LLMs can enhance medical students’ History and Physical (H&P) skills by providing personalized insights, fostering critical thinking, and improving their abilities to analyze, diagnose, and present clinical cases. This study has surfaced significant insights into the potential benefits and limitations of integrating LLMs into medical education. Our findings show the positive impact of LLMs on enhancing personalized learning experiences, critical thinking, and the effectiveness of case-based learning aids and highlighting its limitations.

A beginner's guide to eye tracking for psycholinguistic studies of reading.

Eye tracking has been a popular methodology used to study the visual, cognitive, and linguistic processes underlying word recognition and sentence parsing during reading for several decades. However, the successful use of eye tracking requires researchers to make deliberate choices about how they apply this technique, and there is wide variability across labs and fields with respect to which choices are "standard." We aim to provide an easy-to-reference guideline that can help new researchers with their entrée into eye-tracking-while-reading research. Because the standards do - and should - vary from field to field or study to study as is appropriate for the research question, we do not set a rigid recipe for handling eye tracking data, but rather provide a conceptual framework within which researchers can make informed decisions about how to treat their data so that it is most informative for their research question. Therefore, this paper provides a description of eye movements in reading and an overview of psycholinguistic research on the topic, an overview of experiment design considerations, a description of the data processing pipeline and important choice points and implications, an overview of common dependent measures and their calculation, and a summary of resources for data analysis.

Exploring How Exposure to Pop Culture English Movies Enriches Vocabulary

EFL students frequently face challenges in understanding cultural references, idioms, and slang, which can hinder vocabulary acquisition and overall language comprehension. This issue raises important questions about the accessibility and effectiveness of various language learning tools for learners from diverse linguistic and cultural backgrounds. This study explored the impact of using pop culture English movies for vocabulary acquisition among EFL college students. A qualitative case study method was employed, involving 40 participants, with 10 students from each grade level completing a questionnaire and 10 participating in follow-up interviews. Data were collected through Likert-scale questionnaires to explore students’ perceptions and semi-structured interviews to investigate the strategies for learning vocabulary through movies. The results indicated that students generally found movies valuable for vocabulary acquisition, particularly enhancing their listening skills and contextual understanding. Most students reported increased confidence in using new vocabulary learned through movies. They employed various strategies, including note-taking, subtitles, and engaging in peer discussions. However, challenges such as difficulty understanding cultural references and the fast pace of dialogues were significant obstacles. Despite these, many students preferred learning vocabulary through movies over traditional classroom methods. The study concluded that pop culture English movies can be an effective tool for vocabulary acquisition, provided that students are guided in using appropriate learning strategies. Future research should focus on the long-term impact of movie-based learning on vocabulary retention and the potential benefits of different movie genres for language learning.

Ibn Tofail University Students’ Attitudes Towards Implementing English as a Medium of Instruction (EMI)

This study investigates Ibn Tofail Faculty of Science students’ attitudes towards implementing English as a medium of instruction (EMI). This research examines students’ language proficiency, educational backgrounds, and equity issues in a possible shift to EMI. Findings corroborate existing literature indicating strongly positive attitudes towards a possible shift to EMI but highlight disparities in linguistic readiness between public and high school graduates. This study underscores the need for a comprehensive language policy centred around fostering equity to ensure the success of any possible shift to EMI.