Discovering Dialog Structure Graph for Coherent Dialog Generation

AbstractThe causal compatibility question asks whether a given causal structure graph — possibly involving latent variables — constitutes a genuinely plausible causal explanation for a given probability distribution over the graph’s observed categorical variables. Algorithms predicated on merely necessary constraints for causal compatibility typically suffer from false negatives, i.e. they admit incompatible distributions as apparently compatible with the given graph. In 10.1515/jci-2017-0020, one of us introduced the inflation technique for formulating useful relaxations of the causal compatibility problem in terms of linear programming. In this work, we develop a formal hierarchy of such causal compatibility relaxations. We prove that inflation is asymptotically tight, i.e., that the hierarchy converges to a zero-error test for causal compatibility. In this sense, the inflation technique fulfills a longstanding desideratum in the field of causal inference. We quantify the rate of convergence by showing that any distribution which passes the nth-order inflation test must be $\begin{array}{} \displaystyle {O}{\left(n^{{{-}{1}}/{2}}\right)} \end{array}$-close in Euclidean norm to some distribution genuinely compatible with the given causal structure. Furthermore, we show that for many causal structures, the (unrelaxed) causal compatibility problem is faithfully formulated already by either the first or second order inflation test.

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Shape Neutral Analysis of Graph-based Data-structures

Theory and Practice of Logic Programming ◽

10.1017/s147106841800025x ◽

2018 ◽

Vol 18 (3-4) ◽

pp. 470-483 ◽

Cited By ~ 1

Author(s):

GREGORY J. DUCK ◽

JOXAN JAFFAR ◽

ROLAND H. C. YAP

Keyword(s):

Data Structure ◽

Data Structures ◽

Program Analysis ◽

Constraint Handling ◽

C Programs ◽

Wide Range ◽

Target Program ◽

Target Data ◽

Structure Graph ◽

Structure Properties

AbstractMalformed data-structures can lead to runtime errors such as arbitrary memory access or corruption. Despite this, reasoning over data-structure properties for low-level heap manipulating programs remains challenging. In this paper we present a constraint-based program analysis that checks data-structure integrity, w.r.t. given target data-structure properties, as the heap is manipulated by the program. Our approach is to automatically generate a solver for properties using the type definitions from the target program. The generated solver is implemented using a Constraint Handling Rules (CHR) extension of built-in heap, integer and equality solvers. A key property of our program analysis is that the target data-structure properties are shape neutral, i.e., the analysis does not check for properties relating to a given data-structure graph shape, such as doubly-linked-lists versus trees. Nevertheless, the analysis can detect errors in a wide range of data-structure manipulating programs, including those that use lists, trees, DAGs, graphs, etc. We present an implementation that uses the Satisfiability Modulo Constraint Handling Rules (SMCHR) system. Experimental results show that our approach works well for real-world C programs.

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Modeling Transitivity in Local Structure Graph Models

Sankhya A ◽

10.1007/s13171-021-00264-1 ◽

2021 ◽

Author(s):

Emily Casleton ◽

Daniel J. Nordman ◽

Mark S. Kaiser

Keyword(s):

Local Structure ◽

Graph Models ◽

Structure Graph

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Design for Product Variety: Key to Product Line Structuring

Volume 2: 11th Biennial Conference on Reliability, Stress Analysis, and Failure Prevention; 7th International Conference on Design Theory and Methodology; JSME Symposium on Design and Production; Mechanical Design Education and History; Computer-Integrated Concurrent Design Conference ◽

10.1115/detc1995-0183 ◽

1995 ◽

Author(s):

Kosuke Ishii ◽

Cheryl Juengel ◽

C. Fritz Eubanks

Keyword(s):

Supply Chain ◽

Life Cycle ◽

Manufacturing Process ◽

Life Cycle Cost ◽

Manufacturing System ◽

Product Variety ◽

Product Line ◽

Customer Preference ◽

The Cost ◽

Structure Graph

Abstract This study develops a method to capture the broadest customer preference in a product line while minimizing the life-cycle cost of providing variety. The paper begins with an overview of product variety and its importance in overhead costs: supply chain, equipment and tooling, service, and recycling. After defining the product structure graph as a representation of variety, the paper introduces an approximate measure for the customer importance and life-cycle cost of product variety The cost measure utilizes the concept of late point identification which urges standardization early in the manufacturing process and differentiation at the end of the process. The variety importance-cost map allows engineers to identify cost drivers in the design of the product or the manufacturing system and seek improvements. The refrigerator door example illustrates the concept. On-going work seeks to validate and enhance the method with several companies from different industries.

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The Beauty of the Graphical Structure Graph

Software Development in Chemistry 5 ◽

10.1007/978-3-642-76325-0_25 ◽

1991 ◽

pp. 225-231

Author(s):

T. Cieplak

Keyword(s):

Graphical Structure ◽

Structure Graph

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Improved Image Description Via Embedded Object Structure Graph and Semantic Feature Matching

2018 IEEE International Symposium on Multimedia (ISM) ◽

10.1109/ism.2018.00021 ◽

2018 ◽

Cited By ~ 1

Author(s):

Li Ren ◽

Kien Hua

Keyword(s):

Feature Matching ◽

Semantic Feature ◽

Image Description ◽

Object Structure ◽

Structure Graph

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Test signal generation for service diagnosis based on local structural properties

International Journal of Applied Mathematics and Computer Science ◽

10.2478/v10006-012-0004-y ◽

2012 ◽

Vol 22 (1) ◽

pp. 55-65 ◽

Cited By ~ 4

Author(s):

Michael Ungermann ◽

Jan Lunze ◽

Dieter Schwarzmann

Keyword(s):

Structural Properties ◽

Test Signal ◽

Operating Conditions ◽

Signal Generation ◽

Theoretic Analysis ◽

New Approach ◽

Graph Theoretic ◽

Signal Selection ◽

Operating Points ◽

Structure Graph

Test signal generation for service diagnosis based on local structural propertiesThe paper presents a new approach to the generation of test signals used in service diagnosis. The tests make it possible to isolate faults, which are isolable only if the system is brought into specific operating points. The basis for the test signal selection is a structure graph that represents the couplings among the external and internal signals of the system and the fault signals. Graph-theoretic methods are used to identify edges that disappear under certain operating conditions and prevent a fault from changing the system behavior at this operating point. These operating conditions are identified by validuals, which are indicators obtained during the graph-theoretic analysis. The test generation method is illustrated by a process engineering example.

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Failure Analysis of Mechanical Systems Based on Function-Cum-Structure Approach

Volume 1: Advanced Energy Systems, Advanced Materials, Aerospace, Automation and Robotics, Noise Control and Acoustics, and Systems Engineering ◽

10.1115/esda2006-95726 ◽

2006 ◽

Author(s):

M. F. Wani

Keyword(s):

Failure Analysis ◽

Mechanical Systems ◽

Sliding Contact ◽

System Function ◽

Operational Parameters ◽

Structure Approach ◽

Critical Function ◽

Failure Function ◽

Structure Graph

This paper suggest failure analysis of mechanical systems using function cum structure approach. Operational parameters of system function are identified and their relationships are developed. The predicates, which comprise the components of the system and their properties as their attributes, i.e., type of connectivity (fixed or sliding contact) and functions (transmit torque, and transmit force etc.) represent the facts. The facts are modelled in terms of functional-cum-structure graph. By analysing interaction of a failure function i.e., function of a failed component in the graph with other functions, the failure cause-function is identified. The problem can either be solved by removing the cause-functions or by modifying the failure function. A critical function is also identified from function set on the basis of importance of a function. Appropriate parameters for in-situ design provision for condition monitoring of the system are also identified. The steps of the methodology are included and are illustrated by means of an example.

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