178 results about "Sentence generation" patented technology

A method includes preparing a base model using an input model pretrained on at least three languages different from each other and a base vocabulary including words corresponding to two languages among the at least three languages, where the preparing the base model includes constraining the input model to the words included in the base vocabulary; training the base model using a first enhanced training dataset generated from public data, to generate a text summarization model; training the base model using a second enhanced training dataset generated from the first enhanced training dataset, to generate a text generation model; and training the base model using a third enhanced training dataset that is generated using the second enhanced training dataset and the text summarization model, to generate a next sentence generation model.

The invention discloses a method for generating statements from natural languages to SQL (Structured Query Language) based on a large language model agent. The method comprises the following steps of: constructing an LLM (Logical Language Model) guide table mode index for a target database; obtaining a user natural language question and extracting a keyword; searching in an LLM guidance table mode index according to the keyword, and screening related data tables; splicing the table mode information and the keywords of the related data table into a user natural language problem, and constructing an enhanced cue word; based on the large language model intelligent agent, generating SQL statements according to the enhanced cue words and verifying the SQL statements, if the SQL statements succeed in verification, obtaining the required SQL statements, and if the SQL statements fail in verification, performing iterative closed-loop correction on the generated SQL statements through an SQL statement closed-loop correction workflow; if the corrected SQL statement is successfully verified, the required SQL statement is obtained, and if the corrected SQL statement fails and the number of times of correction reaches a threshold value, the suggestions that the natural language problem of the user has defects and is modified are output. According to the method, the accuracy and success rate of SQL statement generation can be improved.

The embodiment of the invention provides a data analysis method and system based on retrieval enhancement, and the method can obtain query information in a natural language text form, and retrieves enhancement information in a current domain knowledge base according to the query information, the enhanced information comprises one or more combinations of data definition language annotations, query engine grammar documents, business statement cases and custom domain indexes. And inputting the query information and the enhanced information into a statement generation model, and generating a query statement based on a retrieval result of the statement generation model. And executing the query statement through the database query engine, and obtaining the target data from the database. According to the method, semantic mapping of table names or fields can be established by constructing data definition language statements with annotations and query statement question and answer pairs, and the efficiency and accuracy of natural language query are improved.

The invention relates to the technical field of retrieval enhancement generation, and discloses a retrieval enhancement generation method based on a reflection mark, which comprises the following steps of: judging whether an answer question needs to be retrieved or not through a large language model, if so, searching a document related to the question, and disassembling the document into a plurality of sentences; generating a reflection mark for each sentence through the large language model, evaluating whether the retrieved document is related to the question and supports question answering, sorting all the sentences according to the reflection marks, and selecting the first Top K sentences from the plurality of sentences as reference contexts of the large language model for question answering by adopting a TOP K algorithm; whether the answer question still needs to be retrieved or not is judged based on the reference context through the large language model, and if yes, the step of obtaining the reference context is repeated until the target large language model considers that retrieval does not need to be conducted again; and the big language model is considered not to need to be retrieved in the reference context target big language model, and the question is answered.

One or more systems, devices, computer program products and / or computer-implemented methods of use provided herein relate to self-reward guided autoregressive sampling for large language models (LLMs). The system can comprise a processor that can execute computer executable components stored in a memory, where the computer executable components can comprise at least one self-reward model. The at least one self-reward model can generate a score for a sentence generated by an LLM, where the score can be based on one or more tokens comprised in the sentence and an attribute associated with the at least one self-reward model. The at least one self-reward model can further alter a text generation process employed by the LLM to generate the sentence, such that respective sampling probabilities of respective tokens comprised in a vocabulary employed by the LLM to generate a new token can be updated by the LLM based on the score.

Automatically generating sentences that a user can say to invoke a set of defined actions performed by a virtual assistant are disclosed. A sentence is received and keywords are extracted from the sentence. Based on the keywords, additional sentences are generated. A classifier model is applied to the generated sentences to determine a sentence that satisfies a threshold. In the situation a sentence satisfies the threshold, an intent associated with the classifier model can be invoked. In the situation the sentences fail to satisfy the classifier model, the virtual assistant can attempt to interpret the received sentence according to the most likely intent by invoking a sentence generation model fine-tuned for a particular domain, generate additional sentences with a high probability of having the same intent and fulfill the specific action defined by the intent.

To efficiently conduct interviews.SOLUTION: An information processing device comprises a text generation unit and an output unit. The text generation unit generates response texts to user utterances and question texts for asking the user preset interview items using a text generation model for generating responses to the input texts on the basis of expert knowledge related to an interview subject and interview knowledge related to interviewing skills. The output unit outputs the response texts and question texts generated by the text generation unit to the user.SELECTED DRAWING: Figure 2

The present invention generates, with a minimum effort by a worker, a question sentence to be inputted to a generative AI device and acquires an NC program which realizes a desired operation of an industrial machine.　This program creation assistance device assists in creating a numerical control program which causes an industrial machine to operate. The program creation assistance device comprises: a machine information acquisition unit which acquires machine information regarding the industrial machine; a question sentence generation unit which acquires operation information regarding desired operation contents of the industrial machine, and generates a question sentence for a generative AI device by combining the operation information with the machine information acquired by the machine information acquisition unit; a transmission unit which transmits, to the generative AI device, the question sentence generated by the question sentence generation unit; a reception unit which receives a first response result from the generative AI device; and a presentation unit which presents the first response result.

To compare information transmission in an unspecified field with information extracted from another information source.SOLUTION: A non-transitory computer-readable recording medium storing a program for operating a computer, the program causing a processor of the computer to execute: receiving designation of a text; and extracting, from an information source available to an artificial intelligence system, at least one source text including a description similar to a designated text that is the designated text. Generating a prompt including an instruction to output information about the source sentence and an instruction to compare the extracted source sentence with a specified sentence, and presenting, to a user, the information about the source sentence and a result of the comparison between the specified sentence and the source sentence, based on an answer obtained from a large scale language model provided by an artificial intelligence system by inputting the prompt to the large scale language model.SELECTED DRAWING: Figure 10

The invention belongs to the crossing field of artificial intelligence and barrier-free assistance technology, and particularly discloses a sign language translation method and device based on a large language model.The method is applied to a terminal and comprises the steps that key points are extracted from sign language video frames; based on the coordinates, types and global indexes of the key points in the sign language video frames, obtaining fusion features through feature fusion; based on the fusion features corresponding to the sign language video frames in the frame window, time sequence modeling and classification are carried out, and a word prediction result of the frame window is obtained; a sliding window voting and deduplication mode is adopted, the candidate word sequence is preprocessed, a preprocessed word sequence is obtained, and the candidate word sequence is formed by connecting word prediction results of all frame windows in series according to a time sequence; based on the preprocessed word sequence, word error correction and statement generation are carried out by calling a large language model, and a sign language translation result is generated. According to the invention, sign language video translation can be realized for the terminal, and the accuracy and fluency of the translation result can be guaranteed.

The invention discloses a structured query statement generation method and device, equipment and a storage medium, belongs to the field of data processing, and can accurately generate SQL statements according to natural statements. The method comprises the steps of obtaining a to-be-generated statement, and determining intention information in the to-be-generated statement; based on a preset sub-graph determination rule, determining a first sub-graph structure corresponding to the intention information in a preset database graph structure, the database graph structure being formed based on a plurality of first graph nodes and an association relationship between the first graph nodes, and the first graph nodes being determined based on structure information of a plurality of associated databases; a plurality of preset second graph structures are obtained, the second graph structures with the structural similarity with the first sub-graph structures larger than a first threshold value are determined as third graph structures, and different second graph structures are generated based on different types of preset SQL statements; and determining statement generation parameters in the first sub-graph structure based on the third graph structure, so as to generate a target SQL statement based on the statement generation parameters.

The invention discloses a prompting method and system for enhancing the implicit reasoning ability of a large language model, and the method comprises the steps: receiving an original context, and generating a forward reasoning problem and a backward reasoning problem based on the sentence of the original context; the forward reasoning problem and the backward reasoning problem are screened, problems which are related to original context semantics and have logic values are reserved, and an intermediate reasoning problem set used for auxiliary reasoning is generated; combining the intermediate reasoning problem set with the original task input, and constructing an enhancement prompt; and inputting the enhancement prompt into the large language model and obtaining an answer. According to the method, a potential causal logic chain is complemented for the model, so that explicit and implicit information can be fused more sufficiently, the reasoning accuracy and robustness are improved, and the implicit information identification capability is enhanced; and the reasoning ability can be enhanced only by prompting the project without retraining or fine tuning of the model.

The application provides a power industry science and technology front and application article personalized recommendation method and system, a storage medium and an electronic device, and relates to the field of personalized recommendation.In the application, the related field coefficient is used to screen sentences related to the personalized knowledge graph in the article to be recommended, and a new text after information filtering is generated; the title of the article to be recommended and the new text are used as the input of the BERT model, the title representation and the sentence representation are obtained respectively, the attention mechanism at the sentence level is introduced, the attention weight of the title representation to each sentence representation is obtained, the weighted sentence representation is obtained, and finally the classifier is input.The application uses the constructed personalized knowledge graph to screen sentences, preliminarily filters out irrelevant information, introduces the sentence-level attention model, filters the preliminarily screened sentences again, greatly reduces the interference of information irrelevant to the theme, and improves the performance of the classification model, so that the personalized recommendation result with high accuracy is quickly generated.

In implementations of systems for generating templates using structure-based matching, a computing device implements a template system to receive input data describing a set of digital design elements. The template system represents the input data as a sentence in a design structure language that describes structural relationships between design elements included in the set of digital design elements. An input template embedding is generated based on the sentence in the design structure language. The template system generates a digital template that includes the set of digital design elements for display in a user interface based on the input template embedding.

In a fault cause identification support device, an error message acquisition means acquires an error message from an IT system. A configuration information acquisition means acquires configuration information of the IT system. A device state acquisition means acquires state information of each of devices forming the IT system based on the error message and the configuration information. A question sentence generation means generates a first question sentence including the error message, the configuration information, the state information, and an instruction sentence for instructing analysis of an error cause. A response means inputs the first question sentence to a large-scale language model and acquire one or more candidates of the error cause as an answer. Thus, the fault cause identification support device capable of supporting in identifying a cause of a fault in the IT system is provided.

A factuality verification apparatus includes an input module configured to receive a written document, a filtering module configured to filter an untargeted sentence, which does not correspond to a target for factuality verification, a selection module configured to respectively divide a plurality of individual facts of one sentence into different sentences to generate atomic sentences respectively corresponding to the plurality of individual facts and select a core atomic sentence corresponding to a sentence including the fact-related content associated with the subject among the atomic sentences, and a verification module configured to perform factuality verification on whether the core atomic sentence is true or not, through comparison of the core atomic sentence and an evidence document capable of checking whether content of the core atomic sentence is true or false.

The invention discloses a statement generation method, which comprises the following steps of: receiving load characteristic information and database mode information, and obtaining characteristic parameters according to the load characteristic information and the database mode information; determining the statement type of the generated statement according to the feature parameters; and calculating a state transition probability according to the load feature information. In the embodiment of the invention, the load type required by the user can be determined according to the database mode information and the load feature information, and the SQL statement of the load of the determined type is generated according to the load feature information. The styles of the SQL statements of the load generated by the method are more, so that the styles of the SQL statements of the load are enriched, and the load generation mobility is improved.

The application relates to an artificial intelligence-based sentence generation model updating method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: obtaining a query sentence triggered by an object identifier, generating a plurality of candidate sentences associated with the query sentence through a sentence generation model; selecting a candidate sentence selected through the object identifier as a positive sample, and selecting a candidate sentence not selected as a negative sample; respectively extracting features of the positive sample and the negative sample to obtain semantic representations corresponding to the positive sample and the negative sample; constructing a contrast loss function between the positive sample and the negative sample based on the semantic representations of the positive sample and the negative sample; and updating and training the sentence generation model through the contrast loss function until a stop condition is reached, thereby obtaining an updated sentence generation model. The method can improve the accuracy of the generalization result of the sentence generation model in generating a result associated with the query sentence.

This application proposes a social text enhancement method based on multimodal retrieval and keyword extraction, comprising: S1, extracting keywords from sample sentences of different categories using a category keyword extraction algorithm; S2, training a sentence generation model using an RNN model combined with a self-attention mechanism, and controlling the sentence generation direction of the generation model according to the keywords of the corresponding categories of the training samples; S3, inputting the original sentence into the generation model to generate a first generated sentence with text enhancement; S4, based on a multimodal retrieval algorithm, determining whether the first generated sentence contains keywords from the keyword file; if so, finding the keyword to be replaced in the first generated sentence, and retrieving synonyms of the keyword to be replaced for replacement, thereby generating multiple second generated sentences with data enhancement. This application has the effect of controlling the generation direction and number of generated sentences of the generation model.

The invention relates to an information processing system, an information processing method, and a non-transitory storage medium. An information processing system described in this disclosure includes a memory storing instructions and at least one processor configured to execute the instructions. The at least one processor is configured to execute the instruction to acquire input information for input into a sentence generation model, acquire output information generated by inputting the input information into the sentence generation model, and generate the sentence. The input information and the output information are compared to identify a portion of the output information that recommends user inspection, and a display is caused to display the output information in correspondence with the portion that recommends user inspection.

The application discloses a kind of based on big language model's graph database query processing system and method, the system includes entity extraction module, for the query problem of acquisition is added given first hint, sent into big language model and carries out entity extraction;Entity alignment module, by the second hint obtained guide big language model will extract entity and the entity in graph database are aligned;Sentence generation module, according to alignment result, generates query sentence;Data return module, the generated query sentence is sent into graph database, and feedback data is returned;Report generation module, feedback data and query problem are substituted into the third hint of construction, generate new input hint, and the input hint is used as constraint, is transmitted to big language model;Its effect is: by hint, the associated information in graph database is fed to big model, realizes not to fine-tune for big model supplement knowledge, allow longer text input, generate more accurate reply.

An object of the system according to the embodiment is to realize a dialogue with the user by reproducing the voice and speech of the deceased.SOLUTION: A system includes a voice generation unit, a sentence generation unit, a storage unit, and an interaction unit. The voice generation part reproduces the voice of the deceased. The sentence generation part generates the speech of the deceased. The storage unit stores information on the deceased. The interaction unit realizes interaction with a user.SELECTED DRAWING: Figure 1

To provide an information processor, an information processing method and a program for suppressing labor and time for a store side to prepare publication information to be published on a contribution site.SOLUTION: The management server 10 configured by one or a plurality of information processing devices including an arithmetic device and a storage device includes an acquisition unit 11 that acquires post information corresponding to a specific store from a posting site that discloses post information posted for a predetermined store, an output unit 12 that outputs the post information corresponding to the specific store acquired from the posting site to be displayed, and a posting unit 13 that posts posting information including a sentence related to the specific store on an information disclosure page corresponding to the specific store prepared in the posting site. Then, the publication part transmits request information showing the request of the contents of the publication information to the sentence generation device, requests the generation of sentence information corresponding to the request information, acquires the sentence information generated by the sentence generation device, and publishes the publication information based on the sentence information on the information disclosure page.SELECTED DRAWING: Figure 2

This invention relates to the field of artificial intelligence technology, and more particularly to a method, apparatus, computer device, and medium for generating incorrect sentences for model training. The method maps the number of terms in the text to be processed to an adjustment quantity, samples target terms from the text to be processed, adjusts the target terms to obtain augmented text, occludes the text to be processed, inputs it into a reconstruction model to obtain reconstructed text, trains a generative model based on the text to be processed, the augmented text, and the reconstructed text, inputs real-time text into the trained generative model to obtain generated incorrect sentence text, processes the text to be processed using multiple data augmentation methods to obtain text containing rich error types as labels, trains an end-to-end generative model, allowing real-time text to be directly input into the trained generative model to obtain generated incorrect sentence text without frequent switching of data augmentation methods, greatly improving the efficiency of incorrect sentence generation while ensuring high quality.

An object of a system according to an embodiment is to generate an image in accordance with a user's request and to enable detailed partial correction.SOLUTION: A system includes a sentence generation AI, an image generation AI, a correction unit, and an interaction unit. The text generation AI supplements missing information based on an instruction from the user. The image generation AI generates an image based on the information complemented by the sentence generation AI. The correction unit corrects a part of the generated image. The interaction unit generates the entire image or modifies a part of the image while interacting with the user.SELECTED DRAWING: Figure 1

This wearable device may provide torque to a user who is exercising, obtain an indicator about the extent of burden on the body of the user on the basis of at least one of exercise information about exercise performance of the user, biometric information of the user, or setting information set so that the wearable device provides the torque, select a sentence to be used for voice generation of the wearable device on the basis of the indicator, generate a voice on the basis of the selected sentence, and provide the generated voice to the user.

This invention relates to a method and system for optimizing machine translation using a large language model, belonging to the field of machine translation technology. It includes: generating a corresponding first translation from a source sentence in a bilingual corpus; segmenting the source sentence into words, counting the frequency of easily misspelled words in each segment, and calculating the easily misspelled word score, obtaining an easily misspelled word set based on the score; calculating the semantic similarity between the sentence to be translated and multiple candidate examples, and calculating the quality scores of the multiple candidate examples; selecting the optimal k candidate examples from the multiple candidate examples based on semantic similarity and quality scores, and constructing them as prompt templates; obtaining training sentence pairs from the bilingual corpus based on the easily misspelled word scores to construct a training set; and using the training set and prompt templates to perform low-rank adaptive training on a large language model to obtain an optimized large language model. This invention not only improves translation quality but also enhances the interpretability of the translation process.

An object of a system according to an embodiment is to generate a natural sentence by utilizing personal data and conversation data of a user.SOLUTION: A system according to an embodiment includes a personal data collection unit, a conversation data collection unit, a prompt input unit, a sentence generation unit, and an output unit. The personal data collection unit collects personal data of a user. The conversation data collection unit collects daily conversation data of a user. The prompt input unit receives a prompt from a user. The sentence generation unit generates a sentence on the basis of the data collected by the personal data collection unit and the conversation data collection unit. The output unit provides the user with the sentence generated by the sentence generation unit.SELECTED DRAWING: Figure 1

The invention relates to the technical field of natural language processing, in particular to a statement generation method and device based on a large language model, equipment and a medium. In the embodiment of the invention, the large language model has the capability of classifying the text, and the classification capability can determine that the target text is classified so as to determine which target data tables need to be used for generating the SQL statement, and then the large language model is enabled to generate the SQL statement according to the target data tables; the SQL statement generation based on multiple data tables is realized, and the SQL statement generation accuracy is ensured.