Aiming at the problem of insufficient recognition of implicit variants by existing Chinese sensitive text detection methods,this paper proposes the IPKE-MoE framework,which consists of three parts,namely,a sensitive w...Aiming at the problem of insufficient recognition of implicit variants by existing Chinese sensitive text detection methods,this paper proposes the IPKE-MoE framework,which consists of three parts,namely,a sensitive word variant extraction framework,a sensitive word variant knowledge enhancement layer and a mixture-of-experts(MoE)classification layer.First,sensitive word variants are precisely extracted through dynamic iterative prompt templates and the context-aware capabilities of Large Language Models(LLMs).Next,the extracted variants are used to construct a knowledge enhancement layer for sensitive word variants based on RoCBert models.Specifically,after locating variants via n-gram algorithms,variant types are mapped to embedding vectors and fused with original word vectors.Finally,a mixture-of-experts(MoE)classification layer is designed(sensitive word,sentiment,and semantic experts),which decouples the relationship between sensitiveword existence and text toxicity throughmultiple experts.This framework effectively combines the comprehension ability of Large Language Models(LLMs)with the discriminative ability of smaller models.Our two experiments demonstrate that the sensitive word variant extraction framework based on dynamically iterated prompt templates outperforms other baseline prompt templates.TheRoCBert models incorporating the sensitive word variant knowledge enhancement layer and a mixture-of-experts(MoE)classification layer achieve superior classification performance compared to other baselines.展开更多
Automatically answer math word problems is a challenging task in artificial intelligence.Previous solvers constructed mathematical expressions in sequence or binary tree.However,these approaches may suffer from the fo...Automatically answer math word problems is a challenging task in artificial intelligence.Previous solvers constructed mathematical expressions in sequence or binary tree.However,these approaches may suffer from the following issues:Models relying on such structures exhibit fixed-order reasoning(e.g.,left-to-right),limiting flexibility and increasing error susceptibility;prior models rely on autoregressive reasoning in a single pass,accumulating minor errors(e.g.,incorrect math symbols)during generation,resulting in reduced accuracy.To address the above issues,we emulate the human“check and modify”process in reasoning and propose a unified M-tree self-correction solver(UTSCSolver)by iterative inference with self-correction mechanism.First,we use an iterative,non-autoregressive process for generating mathematical expressions,free from fixed generation orders to handle complex and diverse problems.Additionally,we design a self-correction mechanism based on alternating execution between a generator and a discriminator.This module iteratively detects and rectifies errors in generated expressions,leveraging previous iteration information for subsequent generation guidance.Experimental results show that our UTSC-Solver outperforms traditional models in accuracy on two popular datasets,while it improves the interpretability of mathematical reasoning.展开更多
Linking words,also called transition words,are quite useful in English expressions.Linking words are not the same as conjunctions,although some conjunctions can function as linking words.Here's a clear explanation...Linking words,also called transition words,are quite useful in English expressions.Linking words are not the same as conjunctions,although some conjunctions can function as linking words.Here's a clear explanation for English learners,followed by a wellorganized passage on the functions of linking words in writing and communication.展开更多
Term is a kind of limited language symbols,usually presented in a specific language or text and used to communicate and express ideas.With the globalization of economy,international trade has become more frequent,and ...Term is a kind of limited language symbols,usually presented in a specific language or text and used to communicate and express ideas.With the globalization of economy,international trade has become more frequent,and chemical products have gradually become the hotspot of international import and export transactions,so the Chinese translation of the names of chemical products has become more important,and accurate translation can better promote the development of the domestic chemical industry and its dialogue and exchange with the international chemical industry.In this paper,we first explore the Chinese translation strategies of the semi-technical words in chemistry,and then investigate the translation strategies for technical words,subdividing the technical words into compounds,derivatives,and acronyms,with a view to providing ideas and references for translations of relevant texts.展开更多
Memetics is a theory based on biology that explains cultural transmission.Memes are the basic units of cultural transmission.Culture-loaded words refer to unique vocabulary and idioms within a certain culture,reflecti...Memetics is a theory based on biology that explains cultural transmission.Memes are the basic units of cultural transmission.Culture-loaded words refer to unique vocabulary and idioms within a certain culture,reflecting the history,society,and lifestyles of different countries and ethnicities.Due to significant cultural differences between the Western world and China,translating culture-loaded words poses an unavoidable challenge for translators.This paper uses memetics as its theoretical foundation,classifies cultures according to Nida’s categories,and analyzes the application of memetics in the English translation of culture-loaded words through examples.展开更多
Words are like magic.They can lift you up,or they can knock you down.They are the most powerful tool we have.When I was in Grade 7,I performed badly in a math test.
1.The price of a desk is 10 times the price of a chair.The desk costs 288 yuan more than the chair.How much does one desk and one chair cost?2.A and B start from two different places and walk toward each other.After 4...1.The price of a desk is 10 times the price of a chair.The desk costs 288 yuan more than the chair.How much does one desk and one chair cost?2.A and B start from two different places and walk toward each other.After 4 hours,they meet at a point that is 4 kilometres away from the midpoint between their starting points.A walks faster than B.How many more kilometres per hour does A walk than B?展开更多
The current study investigated how language context and word frequency influenced vowel perception of Chinese-Japanese cognates among Chinese learners of Japanese.Focusing on orthographic cognates,participants perform...The current study investigated how language context and word frequency influenced vowel perception of Chinese-Japanese cognates among Chinese learners of Japanese.Focusing on orthographic cognates,participants performed a vowel detection task on cognates,manipulating language context and target language(Chinese vs.Japanese),as well as word frequency(high vs.low).We measured reaction times,perceptual sensitivity,and response criterion.For high-frequency words,consistent language contexts facilitated faster vowel detection in both languages.However,in low-frequency conditions,participants showed higher perceptual sensitivity to Chinese targets and more conservative response criteria for Japanese targets,regardless of context.These findings revealed the complex interplay between word frequency,language dominance,and context in cross-language processing.Our study contributed to the understanding of vowel perception in languages with shared orthography but distinct phonological systems,offering insights for models of cross-language cognition and second language education.Furthermore,it highlighted the importance of considering both word frequency and language-specific features in cross-language studies.展开更多
In the wave of internet culture,short videos have become an indispensable medium for social communication.The metaphorical hot words contained within them serve as a unique linguistic phenomenon that leads topics and ...In the wave of internet culture,short videos have become an indispensable medium for social communication.The metaphorical hot words contained within them serve as a unique linguistic phenomenon that leads topics and focuses attention,greatly enriching the expressive layers and rhetorical charm of short videos,and significantly enhancing the video’s theme orientation and emotional identification.This research aims to explore the relationship between the use of metaphorical Internet buzzwords in short videos and the thematic and emotional orientation.The study adopts a combination of qualitative and quantitative methods,taking 10 videos with over 10,000 likes posted by a well-known blogger on Xiaohongshu in 2024 as the research object,transcribing the text,forming research corpora,and conducting multi-dimensional cognitive analysis on them.The study shows that about half of short videos contain metaphorical hot words.Different types of metaphorical hot words can trigger different emotional reactions from fans,especially humorous metaphorical hot words that can stimulate fans’emotional identification and resonance.In addition,in terms of fan participation,videos using metaphorical hot words tend to attract more fan attention than those that do not:these videos not only attract more fans to watch and like,but also trigger more comments and sharing behaviors.In summary,short videos cleverly use metaphors to create internet hot words,significantly enhancing the video’s thematic guidance and emotional resonance,manifested in creating popular topics,clarifying guiding themes,enhancing content attractiveness,and stimulating strong emotional identification,thereby promoting interactive behaviors such as likes and shares.These findings provide a reference for research in related fields such as metaphor,communication studies,and sociology.展开更多
基金funded by the National Natural Science Foundation of China(Grant No.62441212)the Major Project of the Natural Science Foundation of Inner Mongolia(Grant No.2025ZD008).
文摘Aiming at the problem of insufficient recognition of implicit variants by existing Chinese sensitive text detection methods,this paper proposes the IPKE-MoE framework,which consists of three parts,namely,a sensitive word variant extraction framework,a sensitive word variant knowledge enhancement layer and a mixture-of-experts(MoE)classification layer.First,sensitive word variants are precisely extracted through dynamic iterative prompt templates and the context-aware capabilities of Large Language Models(LLMs).Next,the extracted variants are used to construct a knowledge enhancement layer for sensitive word variants based on RoCBert models.Specifically,after locating variants via n-gram algorithms,variant types are mapped to embedding vectors and fused with original word vectors.Finally,a mixture-of-experts(MoE)classification layer is designed(sensitive word,sentiment,and semantic experts),which decouples the relationship between sensitiveword existence and text toxicity throughmultiple experts.This framework effectively combines the comprehension ability of Large Language Models(LLMs)with the discriminative ability of smaller models.Our two experiments demonstrate that the sensitive word variant extraction framework based on dynamically iterated prompt templates outperforms other baseline prompt templates.TheRoCBert models incorporating the sensitive word variant knowledge enhancement layer and a mixture-of-experts(MoE)classification layer achieve superior classification performance compared to other baselines.
基金supported by the National Natural Science Foundation of China(62106244)the Fundamental Research Funds for the Central Universities(WK2150110021)the University Synergy Innovation Program of Anhui Province(GXXT-2022-042).
文摘Automatically answer math word problems is a challenging task in artificial intelligence.Previous solvers constructed mathematical expressions in sequence or binary tree.However,these approaches may suffer from the following issues:Models relying on such structures exhibit fixed-order reasoning(e.g.,left-to-right),limiting flexibility and increasing error susceptibility;prior models rely on autoregressive reasoning in a single pass,accumulating minor errors(e.g.,incorrect math symbols)during generation,resulting in reduced accuracy.To address the above issues,we emulate the human“check and modify”process in reasoning and propose a unified M-tree self-correction solver(UTSCSolver)by iterative inference with self-correction mechanism.First,we use an iterative,non-autoregressive process for generating mathematical expressions,free from fixed generation orders to handle complex and diverse problems.Additionally,we design a self-correction mechanism based on alternating execution between a generator and a discriminator.This module iteratively detects and rectifies errors in generated expressions,leveraging previous iteration information for subsequent generation guidance.Experimental results show that our UTSC-Solver outperforms traditional models in accuracy on two popular datasets,while it improves the interpretability of mathematical reasoning.
文摘Linking words,also called transition words,are quite useful in English expressions.Linking words are not the same as conjunctions,although some conjunctions can function as linking words.Here's a clear explanation for English learners,followed by a wellorganized passage on the functions of linking words in writing and communication.
基金USST Construction Project of English-Taught Courses for International Students in 2024USST Teaching Achievement Award(Postgraduate)Cultivation Project in 2024.
文摘Term is a kind of limited language symbols,usually presented in a specific language or text and used to communicate and express ideas.With the globalization of economy,international trade has become more frequent,and chemical products have gradually become the hotspot of international import and export transactions,so the Chinese translation of the names of chemical products has become more important,and accurate translation can better promote the development of the domestic chemical industry and its dialogue and exchange with the international chemical industry.In this paper,we first explore the Chinese translation strategies of the semi-technical words in chemistry,and then investigate the translation strategies for technical words,subdividing the technical words into compounds,derivatives,and acronyms,with a view to providing ideas and references for translations of relevant texts.
文摘Memetics is a theory based on biology that explains cultural transmission.Memes are the basic units of cultural transmission.Culture-loaded words refer to unique vocabulary and idioms within a certain culture,reflecting the history,society,and lifestyles of different countries and ethnicities.Due to significant cultural differences between the Western world and China,translating culture-loaded words poses an unavoidable challenge for translators.This paper uses memetics as its theoretical foundation,classifies cultures according to Nida’s categories,and analyzes the application of memetics in the English translation of culture-loaded words through examples.
文摘Words are like magic.They can lift you up,or they can knock you down.They are the most powerful tool we have.When I was in Grade 7,I performed badly in a math test.
文摘1.The price of a desk is 10 times the price of a chair.The desk costs 288 yuan more than the chair.How much does one desk and one chair cost?2.A and B start from two different places and walk toward each other.After 4 hours,they meet at a point that is 4 kilometres away from the midpoint between their starting points.A walks faster than B.How many more kilometres per hour does A walk than B?
文摘The current study investigated how language context and word frequency influenced vowel perception of Chinese-Japanese cognates among Chinese learners of Japanese.Focusing on orthographic cognates,participants performed a vowel detection task on cognates,manipulating language context and target language(Chinese vs.Japanese),as well as word frequency(high vs.low).We measured reaction times,perceptual sensitivity,and response criterion.For high-frequency words,consistent language contexts facilitated faster vowel detection in both languages.However,in low-frequency conditions,participants showed higher perceptual sensitivity to Chinese targets and more conservative response criteria for Japanese targets,regardless of context.These findings revealed the complex interplay between word frequency,language dominance,and context in cross-language processing.Our study contributed to the understanding of vowel perception in languages with shared orthography but distinct phonological systems,offering insights for models of cross-language cognition and second language education.Furthermore,it highlighted the importance of considering both word frequency and language-specific features in cross-language studies.
文摘In the wave of internet culture,short videos have become an indispensable medium for social communication.The metaphorical hot words contained within them serve as a unique linguistic phenomenon that leads topics and focuses attention,greatly enriching the expressive layers and rhetorical charm of short videos,and significantly enhancing the video’s theme orientation and emotional identification.This research aims to explore the relationship between the use of metaphorical Internet buzzwords in short videos and the thematic and emotional orientation.The study adopts a combination of qualitative and quantitative methods,taking 10 videos with over 10,000 likes posted by a well-known blogger on Xiaohongshu in 2024 as the research object,transcribing the text,forming research corpora,and conducting multi-dimensional cognitive analysis on them.The study shows that about half of short videos contain metaphorical hot words.Different types of metaphorical hot words can trigger different emotional reactions from fans,especially humorous metaphorical hot words that can stimulate fans’emotional identification and resonance.In addition,in terms of fan participation,videos using metaphorical hot words tend to attract more fan attention than those that do not:these videos not only attract more fans to watch and like,but also trigger more comments and sharing behaviors.In summary,short videos cleverly use metaphors to create internet hot words,significantly enhancing the video’s thematic guidance and emotional resonance,manifested in creating popular topics,clarifying guiding themes,enhancing content attractiveness,and stimulating strong emotional identification,thereby promoting interactive behaviors such as likes and shares.These findings provide a reference for research in related fields such as metaphor,communication studies,and sociology.
