65 results about "Truth value" patented technology

Provided in the embodiments of the present application are a large-model performance assessment method and a related device. The method comprises: acquiring structured text description of a test material, wherein the structured text description comprises information of the test material in a plurality of dimensions; inputting the structured text description and a test question into a large language model, so as to acquire an evaluation true value; inputting the test material and the test question into a large model under test, so as to acquire an answer under test of the test question; and inputting the evaluation true value, the test question and the answer under test into the large language model, so as to acquire an assessment result for the answer under test.

A computer-implemented method for facilitating reasoning under conditions of uncertainty includes receiving input including a set of logic formulas, a set of intervals representing lower and upper bounds on the truth values of the formulas in the set of logic formulas, and a query formula. The logic formulas can be converted into a logical credal network (LCN) representation and a factor graph representation of the LCN representation can be created. The method can output a probability interval [l, u] such that l≤P(q)≤u, where P(q) represents a query for a given probability interval.

A tailored interactive language learning system that teaches an individualized set of vocabulary words to users through interactive avatars and stories. The interaction is modeled through probabilistic rules in a semantic network and neural network having objects and relations. Dialog and narration is generated dynamically based on the state of the interactive story model using phrasal rewrite rules and neural network implementiung a four-valued logic system in which truth values of the objects and relations are encoded as true, false, defined, and undefined in a single memory array.

Systems, methods, apparatuses, and computer program products for verifying positioning accuracy. A method may include sending, by a test equipment, a request to measure position coordinates to a device, receiving, by the test equipment, a model reasoning including at least one position coordinate from the device, and determining, by the test equipment, whether a difference between the model reasoning and at least one ground truth value is within a threshold for a defined number of samples, wherein the at least one ground truth value comprises at least one known position coordinate of the test point.

The invention discloses a question and answer method, a training method of a question and answer large model, related equipment and a program product, and adopts a retrieval enhancement generation scheme based on the large model, and answer content and knowledge reference sources can be generated at the same time. The adopted large model is trained through reinforcement learning in advance, and in order to improve the correctness and factuality of knowledge reference sources generated by the large model, a reward function in the reinforcement learning process is determined based on reference consistency and / or fact consistency. The reference consistency is used for encouraging the knowledge reference source generated by the model to keep consistent with the knowledge reference source in the truth value label, and the fact consistency is used for encouraging the answer content generated by the model to keep consistent with the semantics of the knowledge fragment corresponding to the generated knowledge reference source. By performing reinforcement learning training on the large model according to the reward function, the accuracy and reliability of the generated content of the large model can be improved, and the illusion problem of the large model can be effectively relieved.

An abduction apparatus 1 includes: a probability calculation unit 2 configured to calculate, with respect to each of candidate hypotheses generated using observation information and knowledge information, a probability that the candidate hypothesis is an explanation regarding the observation information; a closed world assumption probability calculation unit 3 configured to calculate, with respect to the candidate hypotheses, a closed world assumption probability that the candidate hypothesis is an explanation regarding a first-order predicate logic literal to which a new truth value is determined as a result of assuming a closed world assumption; and a solution hypothesis determination unit 4 configured to determine a solution hypothesis that is a best explanation regarding the observation information from the candidate hypotheses using the probability and the closed world assumption probability.

The invention relates to an input adaptive precision Cordic algorithm implementation method and device. The method comprises the following steps: obtaining truth values of input x and y and comparing the truth values; performing most significant bit estimation on the truth value with the larger truth value, and obtaining a corresponding shifting mode; shifting the truth values of the input x and y based on the queried shifting mode; and inputting the complemented input x and y into the Cordic operation unit. According to the invention, the spare bit width in the input data is fully utilized to reduce or avoid the occurrence of error iteration, so that the occurrence of error iteration can be reduced to the greatest extent and the accuracy of the output result can be improved.

The present invention discloses a crowdsourcing labeling truth value reasoning method, device and storage device. The method is specifically as follows: construct a data set corresponding to each crowdsourcing worker; for a worker, if the worker has annotated a target instance, calculate the distance between each instance in the data set corresponding to the worker and the target instance, otherwise directly set the worker's labeling quality on the target instance to 0; sort the distance between each instance and the target instance, and find the K neighbor instances with the closest distance to the instance in the data set; use the K neighbor instances to measure the deviation and variance of the worker on the target instance; linearly combine the deviation and variance as the worker's labeling quality w on the target instance ir ; Repeat the above steps until the marking quality of all crowdsourcing workers on the target instance is estimated; select the marking of the worker with the highest marking quality from all workers as the inferred marking of the target instance. The beneficial effects of the present invention are: simple and easy to implement, high marking quality, and solve the problem of low performance of the truth value reasoning method.

The embodiment of the present application discloses a logic circuit truth table determination method, device and electronic equipment, relates to the technical field of electronic circuits, and can quickly extract the truth table of a logic circuit. The method comprises the following steps: based on a first group of input truth values in an input truth value list, input ports of a logic circuit described by a netlist are valued; the input truth value list is generated in advance according to the input ports of the logic circuit described by the netlist; based on the valuation of the input ports, the level value of the output ports of the logic circuit described by the netlist is calculated; it is judged whether the output ports have level values calculated; if the output ports have level values calculated, the calculated level value of the output ports is taken as the output truth value corresponding to the first group of input truth values. The present application is suitable for extracting the truth table of a logic circuit.

This application discloses a method and related apparatus for grading math problems, relating to the field of artificial intelligence technology. This application converts user responses in natural language into proof skeleton data in a pre-defined formal language, and uses a compiler of the pre-defined formal language as a deterministic oracle. By capturing compilation feedback signals, it determines the final evaluation result of the reasoning validity of the problem-solving process. By using the compiler's strict execution of substitution probability prediction, it provides deterministic logical truth values ​​for fuzzy natural language reasoning. Therefore, it can improve the reliability of the evaluation of the reasoning validity of students' problem-solving process.

The invention belongs to the technical field of knowledge questions and answers, and discloses a large model question and answer method and device based on a logic expression and a knowledge graph. The method comprises the steps of extracting a to-be-queried question from a text input by a user by using a large language model; inputting a to-be-queried question into the trained logic extraction and conversion module to generate a true value expression; inputting the truth value expression into the knowledge graph for query to obtain an effective truth value expression and a corresponding query result; and inputting the effective true value expression, the query result and the to-be-queried question into the large language model to generate a final answer. Through a small-scale large language model, questions and answers with high credibility and good interpretability can be provided for users.

The invention relates to a MC / DC coverage rate determination method and device based on a virtual machine and terminal equipment. The method comprises the following steps: analyzing an application source code file to obtain all conditional statements and conditional information, and sorting and simplifying the conditional statements and the conditional information to obtain an independent conditional list and corresponding conditional statement information; analyzing the executable target code file to obtain the address of the conditional statement and the symbol table information of the application program; adding an MC / DC coverage rate recording task in a virtual machine running environment, reading the address of each conditional statement by the task, calculating the truth value of each independent conditional simple logic expression and the truth value of the whole conditional judgment expression when the virtual machine runs to the address, and recording the coverage rate of each conditional statement; recording a file name, a function name, a line number, a judgment expression and a current execution truth value list result of the current statement into a specific file; and analyzing the record file after the operation of the virtual machine is finished, and calculating to obtain the MC / DC coverage rate of the conditional statements in the execution process and the MC / DC coverage rate of all conditional statements in the source code file of the application program.

A cause-effect graph generation device according to one aspect of the present disclosure comprises: a requirement analysis unit that uses a specification in which a requirement relating to a development target is described in natural language as input and uses a large language model to generate a condition relating to business logic represented by the specification and a truth table representing a relationship between the authenticity of the condition and the authenticity of results related to the business logic; a logical expression generation unit that uses the condition and the truth table as input and uses the large language model to generate, for each of the results, a logical expression which derives the results from the condition; and a cause-effect graph generation unit that uses the logical expression as input to generate a cause-effect graph which visualizes a relationship between the condition and the results.

The disclosed embodiments relate to a method and apparatus for constructing a distance truth library, a method and apparatus for detecting high-precision maps, an electronic device, and a storage medium, wherein the method for constructing the distance truth library comprises: obtaining map data, the map data being collected along the entire road by a collection device that meets set accuracy conditions; performing semantic segmentation based on the map data to obtain at least two first map elements; obtaining the distance truth value between two first map elements that are within an accuracy benchmark range among the at least two first map elements; and constructing a distance truth library based on the distance truth value between the two first map elements that are within the accuracy benchmark range. The disclosed embodiments can cause the distance truth library to include the distance truth value between any two first map elements that are within the accuracy benchmark range on the entire road section, thereby improving the accuracy of the map accuracy assessment when the map accuracy of the high-precision map is subsequently detected based on the distance truth library.

The invention discloses a formal verification method and system in an industrial control system. The method comprises the following steps: determining a target business entity corresponding to an operation object in a current message in the industrial control system; obtaining at least one target rule corresponding to the target business entity from a verification rule base; executing a logic verification operation on the operand value in the current message based on each target rule; if the judgment result of the logic verification operation shows that the target rule is violated, a safety response action is triggered; wherein the execution process of the logic verification operation comprises the following steps of: generating an instantaneous atomic proposition truth value corresponding to an operation value in a current message; obtaining truth values of other atomic propositions in the target rule from the system state cache to obtain a historical atomic proposition truth value; combining the instantaneous atomic proposition truth value and the historical atomic proposition truth value to obtain an atomic proposition truth value vector of the current message; and obtaining a judgment result corresponding to the true value vector of the atomic proposition, and defending logic attacks which utilize legal instructions but violate the technological process.

The invention relates to a dense crowd counting method based on a language guidance network, and the method comprises the following steps: S1, carrying out the conversion of a lattice diagram of a crowd tag, and making a truth value density map tag which is used for highlighting a foreground region and a background region; s2, migrating the CLIP visual language model to a counting task, and constructing a loss function used for enhancing the sample boundary clearness for the CLIP visual language model; s3, saving the model training overhead under the condition of not losing the counting precision through a multi-level quantity prompt algorithm, and realizing fine-grained counting; and S4, mapping the prediction density map to obtain the predicted number of people of the picture. The method is beneficial for efficiently and accurately distinguishing the foreground and the background of the image so as to accurately obtain the specific number of people of the crowd.

The present disclosure relates to a task planning method and device based on a large language model, an electronic device, a storage medium and a computer program product. The method comprises: for each task in a plurality of robot tasks, randomly sampling target parameters from a parameter set corresponding to the task; generating a target task instruction in natural language form based on the target parameters; constructing a structured step true value sequence corresponding to the target task instruction; inputting the target task instruction into a pre-trained large language model; comparing a structured step prediction sequence with the structured step true value sequence; and based on the comparison result, evaluating the inference performance of the large language model. In this way, since the present disclosure can automatically and quantitatively evaluate the structured inference ability of the large language model under fixed task constraints, the adverse effects of human factors on the inference performance evaluation of the large language model caused by relying on artificial labeling or subjective judgment can be effectively avoided.

The invention belongs to the technical field of batch SQL query, and particularly discloses a query optimization method and system based on a key truth value path table and set merger, and the method comprises the following steps: constructing parameter data and a data dictionary required by SQL query conditions according to a value space; analyzing the SQL statement, and generating and analyzing an SQL syntax tree; executing set query to obtain a query hit result set Sh of all parameter combinations; traversing query hit records in the query hit result set Sh, and reversely deducing query parameters; and packaging a query mapping result according to a query number parameter combination corresponding to the reverse hit record. By adopting the technical scheme, on the basis of the key truth value path table and set merging, the large-scale data volume is optimized, and the combined Cartesian product batch SQL query tasks are generated.

Provided in the embodiments of the present application are a large-model performance assessment method and a related device. The method comprises: acquiring structured text description of a test material, wherein the structured text description comprises information of the test material in a plurality of dimensions; inputting the structured text description and a test question into a large language model, so as to acquire an evaluation true value; inputting the test material and the test question into a large model under test, so as to acquire an answer under test of the test question; and inputting the evaluation true value, the test question and the answer under test into the large language model, so as to acquire an assessment result for the answer under test.

The invention discloses a class-level object grabbing method based on an equivariant grabbing pose field. The method solves the problems that an existing method is low in reasoning speed, poor in pose generalization and the like. The invention provides an equivariant grabbing pose field which comprises four parts. Firstly, a grabbing pose field is constructed, object shape point cloud serves as a condition, class-level shape features are extracted through a neural network, and mapping from any input pose to an object feasible grabbing pose is learned. Secondly, training a grabbing pose field, quantifying a grabbing pose data set of an object by using L1 norm loss, and supervising the difference between a predicted pose and a grabbing pose true value; then, on the basis of reasoning of a grabbing pose field, grabbing pose prediction is used as guidance for updating a grabbing pose estimated value, and interpolation is carried out in the Lie algebra space; and finally, constructing a grabbing pose field to be equal, so that the network can be generalized to any object pose through the property of the construction instead of data enhancement.

Provided is a secret logical calculation device in a secret logical calculation system comprising three or more secret logical calculation devices for calculating ternary logic in a secret manner, wherein: a truth value of the ternary logic is expressed using two bits; the first bit x0 from between the two bits (x0, x1 used to represent the truth value of the ternary logic is a flag indicating whether the truth value is Undefined, and the second bit x1 represents a true / false value which is the truth value when the first bit x0 indicates that the truth value is not Undefined (however, when the first bit x0 indicates that the value is Undefined, the second bit (x0, x1) represents Undefined).

The invention discloses a method and a system for converting an RSML-e model into a Luter synchronous data stream language. The method is used for converting the RSML-e model into a Luter related type, a Boolean expression, an and-or table, a variable, a macro and a function. Type conversion processes undefined values by creating enumeration and structures. The Boolean expression conversion comprises truth value judgment, logical negation, pre-state reference and equivalence judgment. And constructing sub-expressions according to columns in the and-or table conversion, and using logic or connection. The variables are converted into a Luster node, and the ordinary variables and the input variables are used for processing initial values and conditions respectively. The macro and function are converted into nodes with input and return values, and the contained logic is converted into a Boolean expression. In the whole process, the mapping from the RSML-e logic to the Luter data stream is realized, so that the security attribute of the system can be verified by using a model detection tool, and the security of the system is improved.

Disclosed are a method and system for redundancy switch between two controllers for supplementary damping of a governor, relating to the technical field of control methods. The method includes acquiring a participation condition according to an output result, listing the participation condition in a truth value table and supplementing correlation logic; outputting the correlation logic as an image language, and simplifying the image language; and acquiring switch logic by a simplified image language, and transforming the switch logic into a programming language of the controller. A complex control relation can be decomposed in the disclosure, so that the difficulty can be reduced, and a correct and comprehensive control purpose can be achieved. Moreover, the method has universality.

The invention provides an information extraction method and system using a large model. The method comprises the following steps: extracting a plurality of schemes of attributes by using the large model; the large model converts each scheme into a corresponding code through a natural language algorithm; analyzing the webpage by using the large model, and extracting truth values of attributes; applying the code corresponding to each scheme to the webpage to obtain a value to be verified; comparing the value to be verified with the true value of the attribute, and filtering out incorrect schemes; according to the method, multiple schemes for extracting the attributes can be generated through the large model, corresponding codes are generated for each scheme for implementation, then the truth values of the attributes are extracted from the webpage through the large model to serve as references, incorrect schemes are filtered out, the efficiency, accuracy and robustness of information extraction can be improved, and manpower resources and time cost are saved.

The application discloses an automatic driving data set construction system and method, and belongs to the technical field of automatic driving; the system comprises a hardware and a data layer for collecting relevant data of a target scene and clock aligning the data; a perception and planning layer connected with the output end of the hardware and the data layer, for processing the aligned data, and outputting physically credible three-dimensional geometric true values, kinematic true values and expert planning trajectories; and a semantic cognition layer connected with the output end of the perception and planning layer, for key frame screening, fact dictionary construction and counterfactual reasoning, for converting numerical true values into cognitive annotation data, and obtaining an automatic driving data set, wherein the system is combined with the corresponding method to establish a three-in-one multi-paradigm unified architecture, which not only provides a high-precision three-dimensional geometric annotation for a modular model, and a closed-loop planning trajectory for an end-to-end model, but also innovatively introduces a counterfactual reasoning and hallucination suppression mechanism.

The invention discloses a performance evaluation method and device for a language model, equipment, a medium and a product, and relates to the fields of data processing technologies, large model technologies and large language model technologies. The method comprises: for each question, obtaining a plurality of predicted answers to the question through a language model, the plurality of predicted answers each having a different answer form; the method also includes obtaining a plurality of true value answers for the question, the plurality of true value answers corresponding to different answer sources, respectively. The method further includes obtaining a plurality of comparison results based on a comparison between the plurality of predicted answers and the plurality of true value answers, the plurality of comparison results indicating differences between the plurality of predicted answers and the plurality of true value answers. The method further includes determining a plurality of comparison scores corresponding to the plurality of comparison results, and determining a performance score of the language model based on the plurality of comparison scores, the performance score indicating question and answer performance of the language model. In this way, the coverage of performance evaluation can be improved, and model tuning can be facilitated.

The invention relates to a method, particularly a computer-implemented method for determining a fatigue value of a person, the method comprising the steps of:i) displaying of:a) a first group (1) of symbols and a second group (2) of symbols,b) a selection rule (3) associating each of the symbols of the first group (1) of symbols to one symbol of the second group (2) of symbols,ii) highlighting one symbol (11) of the first group (1) of symbols,iii) receiving a user input from the person selecting one symbol (12) of the second group (2) of symbols,iv) determining a truth value based on the selected symbol (12) of the second group (2) of symbols, wherein the truth value assumes a true value if the selected symbol (12) is selected in accordance with the selection rule (3) and wherein the truth value takes on a false value if not, wherein the highlighted symbol (11) of the first group (1) of symbols is highlighted for a predetermined time based on a statistical response time of the person, and wherein if the user input is not received within the predetermined time in step iv), the method is set forth with step v) having the truth value set to the false value, or the method is set forth with step vi),v) storing the truth value on a non-transitory memory device,vi) changing the selection rule (3), such that each of the symbols of the first group (1) of symbols is associated anew to one symbol of the second group (2) of symbols,vii) changing the highlighted symbol (11) of the first group (1) of symbols,viii) repeating steps iii) to vii) at least once andix) based on at least some of the stored truth values, determining a fatigue value of the person.

The present invention relates to the technical field of crowdsourcing systems, and specifically to an anti-plagiarism iterative truth value discovery method based on lightweight homomorphic encryption. By adding the attribute of the working end weight in the truth value calculation process of the crowdsourcing task, the truth value is inferred according to the attribute of the working end weight to obtain a preliminary set of truth value answers, and whether the working end is the original author is determined based on the preliminary set of truth value answers. Based on the answer set of the original author, the plagiarist is determined by the similarity threshold, and the weight of the plagiarist is reduced. The next round of truth value calculation is performed according to the changed weight of the working end until the convergence criterion is met to output the final set of truth value answers. The crowdsourcing system can automatically monitor and automatically exclude plagiarism in the process of truth value calculation, thereby improving the accuracy of the final truth value result.

The invention relates to the technical field of water conservancy and hydropower engineering safety monitoring, and discloses a safety monitoring data abnormal value identification method based on a sliding window and morphological logic, and the method comprises the steps: processing an original data sequence through a window sliding at a fixed odd length, calculating a median and a median absolute deviation, and estimating a standard deviation; generating a dynamic upper and lower threshold sequence; comparing with a dead zone tolerance threshold value, converting into a logic vector, identifying a connected region with continuous truth values, and secondarily marking all data points in the region with the length exceeding the maximum allowable value as abnormal to obtain an abnormal value logic sequence; and performing linear interpolation processing on the data points marked as abnormal values in the abnormal value logic sequence to obtain a cleaned data sequence without abnormal values. According to the method, more than 95% of invalid data can be efficiently eliminated while the integrity of real signals is reserved, a high-reliability data basis is provided for data analysis and structural safety evaluation, and the method has important engineering application value.

System for causal-logical validation of AI output values, comprising an AI module and a logic validator, wherein the logic validator has access to an axiomatic reference database (Commons architecture).