MULTI-MODAL PROGRAM INFERENCE
    1.
    发明公开

    公开(公告)号:US20230176829A1

    公开(公告)日:2023-06-08

    申请号:US17544502

    申请日:2021-12-07

    CPC classification number: G06F8/33 G06F40/40 G06F8/38 G06F40/30 G06F8/10

    Abstract: Embodiments use a multi-modal approach to generate software programs that match a solution program description. The solution program description may include natural language, input-output examples, partial source code, desired operators, or other hints. Some embodiments use optimized prompts to a pre-trained language model to obtain initial candidate programs. Maximal program components are extracted and then recombined variously using component-based synthesis. Beam search reduces a solution program search space by discarding some candidates from a given synthesis iteration. Relevance metrics, string similarity metrics, operator frequency distributions, token rareness scores, and other optimizations may be employed. By virtue of optimizations and the multi-modal approach, a solution program may be obtained after fewer iterations than by use of a language model alone. The multi-modal approach is domain agnostic, as illustrated by examples using regular expression and cascading style sheet selector domain specific languages.

    SYSTEM AND METHOD FOR FAST CONSTRAINT DISCOVERY ON RELATIONAL DATA

    公开(公告)号:US20240176802A1

    公开(公告)日:2024-05-30

    申请号:US18060500

    申请日:2022-11-30

    CPC classification number: G06F16/284 G06F16/2246

    Abstract: Example aspects include techniques for improved constraint discovery on relational data. These techniques may include constructing a first layer of a lattice using a first plurality of candidate denial constraints (DC) each having a first number of predicates. In addition, the techniques may include performing a tree-based verification process on the first layer of the lattice to determine one or more verified DCs confirmed to be DCs and a plurality of unverified DCs that are not confirmed to be DCs. Further, the techniques may include presenting, via a graphical user interface (GUI), DC information based on the one or more verified DC, and generating, for construction of a second layer of the lattice to be evaluated via the tree-based verification process, a second plurality of candidate DCs by combining the plurality of unverified DCs.

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