The Two Word Test as a semantic benchmark for large language models Scientific Reports

(1) The marginal probability distribution p(w, z|α, β) is acquired by integrating the latent variables θ and φ. (2) The posterior probability distribution p(z| w, α, β) is sampled to gain the sample set of p(z| w, α, β). Despite the current limitations discussed above, the tool developed here demonstrates clear advantages and superiority to immunostaining for disease quantification in pancreatic pre-cancers.

The following Table 1 shows the twenty most frequent tokens and their counts prior to any transformations. As the objective for training involves numerous rows on both the input and output layers, the update equations must be similarly adjusted27. Our society is increasingly embracing the power of artificial intelligence (AI) and machine learning (ML) to make recommendations, serve customers, ensure safety, diagnose disease and more. These technologies have the potential to improve efficiency, yet they are far from perfect. You can foun additiona information about ai customer service and artificial intelligence and NLP. This fall, an additional $175,000 grant was received to support the retention and success of faculty across the three cluster hire cohorts.

Media bias estimation by word embedding

Therefore, this study introduced the concept of semantic characterization of microstates. The microstate sequence encapsulates a wealth of physiological and pathological information, intricately mirrored by the variability and randomness inherent in different states and subsequences within the microstate sequence, which is the theoretical basis for using this method. The mean probability of Topic 2 of articles, split by gender and political orientation.

However, it has been reported with normally developing Spanish 12 year old children45 where, like our data, the amplitude of words primed with a related prime was greater than words primed with an unrelated prime. Fernandez et al.45 attribute their results to the deployment of attention in highly constraining contexts, and suggest that this result is similar to other language tasks where such a pattern exists. This is a likely explanation for our results, as our design would have encouraged the use of attention and strategies. Notably, we used a relatively slow prime duration where such strategies are found46,47. The use of attention with such strategies may have also been in resource competition with other aspects of word processing that require attention, which is likely to be everything after the orthographic lexicon, including sublexical processing37. Our task, which required participants to generate a pronunciation, would thus have used attention, and when difficult words were read aloud (i.e., the inconsistent ones) they may have used a greater amount of attention than consistent words.

Latent Semantic Analysis: intuition, math, implementation

According to IBM, semantic analysis has saved 50% of the company’s time on the information gathering process. The assignment of the word pairs to either the test or restudy condition was counterbalanced by creating two matched sets of pairs with 15 related and 15 unrelated pairs. Words were always presented in the forward order (i.e. cue was always presented before the target).

As with the other forecasting models, we implemented an expanding window approach to generate our predictions. Specifically, we started with an initial subset of data to train the neural network and make a first prediction for the next period. The training set window was subsequently expanded by including the next observation, and the process was repeated recursively. Computational methods have been recognized as unable to understand human communication and language in all its richness and complexity41. Aligned with contemporary approaches to semantic analysis39,42, we have integrated computational methods with traditional techniques to analyze online text.

More than 8 million event records and 1.2 million news articles are collected to conduct this study. The findings indicate that media bias is highly regional and sensitive to popular events at the time, such as the Russia-Ukraine conflict. Furthermore, the results reveal some notable phenomena of media bias among multiple U.S. news outlets. While they exhibit diverse biases on different topics, some stereotypes are common, such as gender bias. This framework will be instrumental in helping people have a clearer insight into media bias and then fight against it to create a more fair and objective news environment. In this work, we propose an automated media bias analysis framework that enables us to uncover media bias on a large scale.

However, traditional LDA is faced with some defects such as the empirical selection of topic quantity, which results in the algorithm performance degradation. Given the Danish disinclination to support legal directives aimed at gender equality, the August 2022 implementation of the ChatGPT App EU directive on parental care represents a potentially important sociocultural inflection point. Media representations of the parental leave reform provide both a window into trends in attitudes and thoughts over time (see “culturomics”17), but also stand to shape public opinion18.

REDCap and KoBoToolbox as electronic data capture systems

Specifically, even though the most common authorship type remained sole authorship for these two decades, by following the universal trend of increasing co-authorship alongside the demise of sole authorship, this collaborative culture has been consistently reinforced. In fact, multi-authorship, which represents 40 to 45% of the entirety of articles published in the early 2000s, increased to about 70% in the 2020s. The most common collaborators with Asian researchers were American, English, and Australian scholars. Furthermore, international collaborations among the 13 target countries occurred often as well. To provide a more complete understanding of exactly how diverse and strong each country’s international impact was, Fig. 12 depicts the citation network of Asian ‘language and linguistics’ research, after excluding author- and country-level self-citations.

The BERT model for the computation of the encodings processes input vectors with a maximum of 512 tokens. As an additional step in our analysis, we conducted a forecasting exercise to examine the predictive capabilities of our new indicators in forecasting the Consumer Confidence Index. Our sample size is limited, which means that our analysis only serves as an indication of the potential of textual data to predict consumer confidence information. It is important to note that our findings should not be considered a final answer to the problem. Violin plot visualizing the distribution of change rates for the property factor of ANIMATE (YES/NO). In addition to that, we have several questions concerning the evolutionary dynamics of meanings, which can be retrieved from the phylogenetic comparative reconstruction.

The reason that the models’ Dice scores are lower than expected from successful models is because the models actually refined approximations in the experts’ annotations leading to discrepancies between prediction and annotation (Fig. 1b). Due to the limitations of the annotation method used, entire lesions (including empty lumina, mixed morphologies (Supplemental Fig. 2E), and ChatGPT additional negative space) were labeled as one type of tissue (i.e., ADM or dysplasia). The models, however, accurately differentiate between the tissue types within a lesion and avoid labeling lumina. Despite these results being biologically correct, they are different than the experts’ manual annotations, resulting in a negative impact on the measured Dice Coefficients.

PD-nMCI patients vs. HCs

Namely, there are sufficient semantic connections between customer requirements and training corpus. In the fine-tuning stage, full connection layers and a softmax layer are added to the output-end of BERT for fine-tuning training. The cross entropy loss function is utilized for back-propagation training and the accuracy is employed to demonstrate the model classification ability.

• Moreover, the current study does not involve the refinement of semantic analysis tools since the modification and improvement of language models require high technique level and a massive quantity of training materials.
• Moreover, context is equally important while processing the language, as it takes into account the environment of the sentence and then attributes the correct meaning to it.
• This is understandable, as economic cycles can be complex and difficult to understand without specialized training or experience.
• The question of whether translational language should be regarded as a distinctive language variant has since sparked considerable debate in the field of translation studies.
• The function descrTable was utilized for the description of the data and the generation of the table.

Similarly, Mohsen (2021) and Barrot et al. (2022) investigated how one topic of ‘language and linguistics’ research has been administered at a country level. In particular, the former study addressed the ‘applied linguistics’ research in Saudi Arabia in the past decade (2011–2020); the later executed a bibliometric study about ELT in the Philippines and is based on doctoral dissertations and master’s theses. As such, these regional studies were limited to only a few countries or to countries that were relatively inactive in terms of research (see section “Geographic distribution of ‘language and linguistics’ research in Asian countries”). Nor did the bibliometric analyses compare research trends across several countries, as the current study has intended.

Extended data

Phuong has built research-practice partnerships and award-winning programs focused on this framework to scale the adoption of equitable and anti-racist practices across multiple universities. Jacinda Abdul-Mutakabbir received a message from Skaggs School of Pharmacy and Pharmaceutical Sciences Division Head of Clinical Pharmacy Linda Awdishu. The interaction came with an invitation to apply to become part of the “Bridging Black Studies and STEM” recruitment.

This groups concepts into classes according to their cultural usage and how they cluster by colexification. In a way, it is circular to use a classification partly based on colexification for testing change rates retrieved from patterns of colexification. However, there are large discrepancies between the classes, which we believe depend on semantic properties, and the classification is clearly contributing to our understanding of these patterns, as we will see Section 3. The original semantics analysis data set was manually coded and retrieved from various sources, mostly dictionaries, but also fieldwork. This resulted in an uneven status of the data, where some languages and lexemes had more detail in their semantic information, whereas other languages were less informative. An important aim for the current project was to standardize the various polysemous meanings given by different lexemes, as well as to standardize these meanings to avoid unnecessary redundancy in the data.

The meaning of sovereignty: Ukrainian and European views of Russia’s war on Ukraine

Among them, semantic features have the highest percentage, which suggests that semantic features contribute greatly to understanding and classifying SCZ. It also strongly suggests that semantic sequences may carry information inherent to the brain states of SCZ patients. Second, the quality features of microstate sequences also occupy an important position, which implies that the dual-template approach proposed in this paper is reasonable and reliable.

(1) An important consideration is the transferability of microstate templates between healthy individuals and SCZ patients, specifically, whether the same set of templates can effectively model EEG signals in both groups. Due to the similarity of microstates under different conditions, researchers typically model the EEG signals of healthy individuals and SCZ patients uniformly. Although this method can effectively reduce computational complexity, it overlooks the quality characteristics of microstate sequence. Even though the causal relations between social support and self-acceptance are unexplored for the limitations of cross-sectional design, the findings of the present study highlighted the significance of the symptom “SIA” (Self-acceptance). As previous research documented, self-acceptance and social support are internal and external protective factors of mental health, respectively (Huang et al., 2020).

You will also note that, based on dimensions, the multiplication of the 3 matrices (when V is transposed) will lead us back to the shape of our original matrix, the r dimension effectively disappearing. If we’re looking at foreign policy, we might see terms like “Middle East”, “EU”, “embassies”. For elections it might be “ballot”, “candidates”, “party”; and for reform we might see “bill”, “amendment” or “corruption”. So, if we plotted these topics and these terms in a different table, where the rows are the terms, we would see scores plotted for each term according to which topic it most strongly belonged. Naturally there will be terms that feature in all three documents (“prime minister”, “Parliament”, “decision”) and these terms will have scores across all 3 columns that reflect how much they belong to either category — the higher the number, the greater its affiliation to that topic. Suppose that we have some table of data, in this case text data, where each row is one document, and each column represents a term (which can be a word or a group of words, like “baker’s dozen” or “Downing Street”).

For semantic subsumption, verbs that serve as the roots of argument structures are evaluated based on their semantic depth, which is assessed through a textual entailment analysis based on WordNet. The identification of semantic similarity or distance between two words mainly relies on WordNet’s subsumption hierarchy (hyponymy and hypernymy) (Budanitsky & Hirst, 2006; Reshmi & Shreelekshmi, 2019). Therefore, each verb is compared with its root hypernym and the semantic distance between them can be interpreted as the explicitness of the verb.

• Jacinda Abdul-Mutakabbir received a message from Skaggs School of Pharmacy and Pharmaceutical Sciences Division Head of Clinical Pharmacy Linda Awdishu.
• For deep learning, sentiment analysis can be done with transformer models such as BERT, XLNet, and GPT3.
• Therefore, the customer requirements expression are satisfactory when they are consistent with the cognition of designers.
• Analysis on semantics, therefore, can be compared across the entire corpus despite similar concepts being represented by analogous phrases.

The results demonstrated that our target countries had indeed dominated the entire field of Asian ‘language and linguistics’ research from 2000 to 2021. For the given period, 41 Asian countries published 35,830 articles, and the scale of the publications constituted an 17% annual growth in productivity. In particular, the target countries published 85% of all papers in Asia, and the scale of the research originating from 28 other Asian countries has never actually surpassed that of the individual 13 target countries for the past 20 years. Thus, the current study paid attention mainly to the 30,515 articles published by these 13 countries. Table 4 lists the top 30 keywords, along with the countries that used the corresponding keywords most often, as well as the most frequent co-appearing keywords. According to the data, some Asian languages (‘Chinese,’ ‘Hebrew,’ ‘Hong Kong,’ ‘Japanese,’ ‘Cantonese’) and teaching and learning English (‘EFL,’ ‘EFL learners,’ ‘English’) were the most frequently explored topics.