Abstract: At least selectively utilizing a large language model (LLM) in generating a natural language (NL) based summary to be rendered in response to a query. In some implementations, in generating the NL based summary additional content is processed using the LLM. The additional content is in addition to query content of the query itself and, in generating the NL based summary, can be processed using the LLM and along with the query content—or even independent of the query content. Processing the additional content can, for example, mitigate occurrences of the NL based summary including inaccuracies and/or can mitigate occurrences of the NL based summary being over-specified and/or under-specified.

Abstract: At least selectively utilizing a large language model (LLM) in generating a natural language (NL) based summary to be rendered in response to a query. In some implementations, in generating the NL based summary additional content is processed using the LLM. The additional content is in addition to query content of the query itself and, in generating the NL based summary, can be processed using the LLM and along with the query content—or even independent of the query content. Processing the additional content can, for example, mitigate occurrences of the NL based summary including inaccuracies and/or can mitigate occurrences of the NL based summary being over-specified and/or under-specified.

Abstract: The present disclosure generally relates to methods and user interfaces for managing visual content at a computer system. In some embodiments, methods and user interfaces for managing visual content in media are described. In some embodiments, methods and user interfaces for managing visual indicators for visual content in media are described. In some embodiments, methods and user interfaces for inserting visual content in media are described. In some embodiments, methods and user interfaces for identifying visual content in media are described. In some embodiments, methods and user interfaces for translating visual content in media are described. In some embodiments, methods and user interfaces for translating visual content in media are described. In some embodiments, methods and user interfaces for managing user interface objects for visual content in media are described.

Abstract: Techniques for providing an enhanced search to generate a feed based on a user's interests are disclosed. In some embodiments, a system/process/computer program product for providing an enhanced search to generate a feed based on a user's interests includes receiving a plurality of interests associated with a user, searching online content including one or more websites (e.g., news or other content websites, social networking sites, and/or other online content) based on the plurality of interests associated with the user, receiving a plurality of web documents (e.g., links to websites, social networking sites, and other online content) based on the search for online content, ranking the plurality of web documents based on a document score and a user signal, and generating a content feed that includes at least a subset of the plurality of web documents based on the ranking.

Abstract: At least selectively utilizing a large language model (LLM) in generating a natural language (NL) based summary to be rendered in response to a query. In some implementations, in generating the NL based summary additional content is processed using the LLM. The additional content is in addition to query content of the query itself and, in generating the NL based summary, can be processed using the LLM and along with the query content—or even independent of the query content. Processing the additional content can, for example, mitigate occurrences of the NL based summary including inaccuracies and/or can mitigate occurrences of the NL based summary being over-specified and/or under-specified.

Abstract: Techniques for providing an enhanced search to generate a feed based on a user's interests are disclosed. In some embodiments, a system/process/computer program product for providing an enhanced search to generate a feed based on a user's interests includes receiving a plurality of interests associated with a user, searching online content including one or more websites (e.g., news or other content websites, social networking sites, and/or other online content) based on the plurality of interests associated with the user, receiving a plurality of web documents (e.g., links to websites, social networking sites, and other online content) based on the search for online content, ranking the plurality of web documents based on a document score and a user signal, and generating a content feed that includes at least a subset of the plurality of web documents based on the ranking.

Abstract: At least selectively utilizing a large language model (LLM) in generating a natural language (NL) based summary to be rendered in response to a query. In some implementations, in generating the NL based summary additional content is processed using the LLM. The additional content is in addition to query content of the query itself and, in generating the NL based summary, can be processed using the LLM and along with the query content—or even independent of the query content. Processing the additional content can, for example, mitigate occurrences of the NL based summary including inaccuracies and/or can mitigate occurrences of the NL based summary being over-specified and/or under-specified.

Abstract: At least selectively utilizing a large language model (LLM) in generating a natural language (NL) based summary to be rendered in response to a query. In some implementations, in generating the NL based summary additional content is processed using the LLM. The additional content is in addition to query content of the query itself and, in generating the NL based summary, can be processed using the LLM and along with the query content—or even independent of the query content. Processing the additional content can, for example, mitigate occurrences of the NL based summary including inaccuracies and/or can mitigate occurrences of the NL based summary being over-specified and/or under-specified.

Abstract: At least selectively utilizing a large language model (LLM) in generating a natural language (NL) based summary to be rendered in response to a query. In some implementations, in generating the NL based summary additional content is processed using the LLM. The additional content is in addition to query content of the query itself and, in generating the NL based summary, can be processed using the LLM and along with the query content—or even independent of the query content. Processing the additional content can, for example, mitigate occurrences of the NL based summary including inaccuracies and/or can mitigate occurrences of the NL based summary being over-specified and/or under-specified.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for context scoring adjustments for candidate answer passages. In one aspect, a method includes scoring candidate answer passages. For each candidate answer passage, the system determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading to which the candidate answer passage is subordinate; determines a context score based, at least in part, on the heading vector; and adjusts answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score. The system then selects an answer passage from the candidate answer passages based on the adjusted answer scores.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for scoring candidate answer passages. In one aspect, a method includes receiving a query determined to be a question query that seeks an answer response and data identifying resources determined to be responsive to the query; for a subset of the resources: receiving candidate answer passages; determining, for each candidate answer passage, a query term match score that is a measure of similarity of the query terms to the candidate answer passage; determining, for each candidate answer passage, an answer term match score that is a measure of similarity of answer terms to the candidate answer passage; determining, for each candidate answer passage, a query dependent score based on the query term match score and the answer term match score; and generating an answer score that is a based on the query dependent score.

Abstract: One or more content examples associated with a content channel are received. One or more entities are determined based on the one or more content examples. One or more web documents are provided in a content feed based on the one or more determined entities.

Abstract: A nearest neighbor image embedding associated with an n-gram is determined. The nearest neighbor image embedding is associated with an image. One or more web documents associated with the n-gram and the image are provided in a content feed.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating candidate answer passages. In one aspect, a method includes receiving a query determined to be a question query data identifying resources determined to be responsive to the query; for each resource in a top-ranked subset of the resources: identifying a plurality of passage units in the resource; applying a set of passage unit selection criterion to the passage units, each passage unit selection criterion specifying a condition for inclusion of a passage unit in a candidate answer passage, wherein a first subset of passage unit selection criteria applies to structured content and a second subset of passage unit selection criteria applies to unstructured content; and generating, from passage units that satisfy the set of passage unit selection criterion, a set of candidate answer passages.

Abstract: Techniques for providing an enhanced search to generate a feed based on a user's interests are disclosed. In some embodiments, a system/process/computer program product for providing an enhanced search to generate a feed based on a user's interests includes receiving a plurality of interests associated with a user, searching online content including one or more websites (e.g., news or other content websites, social networking sites, and/or other online content) based on the plurality of interests associated with the user, receiving a plurality of web documents (e.g., links to websites, social networking sites, and other online content) based on the search for online content, ranking the plurality of web documents based on a document score and a user signal, and generating a content feed that includes at least a subset of the plurality of web documents based on the ranking.

Abstract: Techniques for enhanced search for generating a content feed are disclosed. In some embodiments, a system/process/computer program product for enhanced search for generating a content feed includes determining a plurality of interests for a user, wherein the user is associated with a user account; searching one or more websites based on the plurality of interests associated with the user; generating an index that includes a plurality of web documents and relationships between each of the plurality of web documents; and generating a content feed that includes at least a subset of the plurality of web documents based on a ranking, wherein the ranking is based on the plurality of interests associated with the user.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for context scoring adjustments for candidate answer passages. In one aspect, a method includes scoring candidate answer passages. For each candidate answer passage, the system determines a heading vector that describes a path in the heading hierarchy from the root heading to the respective heading to which the candidate answer passage is subordinate; determines a context score based, at least in part, on the heading vector; and adjusts answer score of the candidate answer passage at least in part by the context score to form an adjusted answer score. The system then selects an answer passage from the candidate answer passages based on the adjusted answer scores.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for scoring candidate answer passages. In one aspect, a method includes receiving a query determined to be a question query that seeks an answer response and data identifying resources determined to be responsive to the query; for a subset of the resources: receiving candidate answer passages; determining, for each candidate answer passage, a query term match score that is a measure of similarity of the query terms to the candidate answer passage; determining, for each candidate answer passage, an answer term match score that is a measure of similarity of answer terms to the candidate answer passage; determining, for each candidate answer passage, a query dependent score based on the query term match score and the answer term match score; and generating an answer score that is a based on the query dependent score.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for identifying implicit question queries. In one aspect, a method includes receiving a query in unstructured form, comparing terms of the query to query templates, determining, based on the comparison, a match of the query terms to a first query template, wherein the first query template is not determined to be indicative of a question query, determining, based on the first query template, a second query template, and determining that the query is an implicit question query in response to the second query template being indicative of a question queries.

Abstract: Methods, systems, and apparatus, including computer program products, for generating synthetic queries using seed queries and structural similarity between documents are described. In one aspect, a method includes identifying embedded coding fragments (e.g., HTML tag) from a structured document and a seed query; generating one or more query templates, each query template corresponding to at least one coding fragment, the query template including a generative rule to be used in generating candidate synthetic queries; generating the candidate synthetic queries by applying the query templates to other documents that are hosted on the same web site as the document; identifying terms that match structure of the query templates as candidate synthetic queries; measuring a performance for each of the candidate synthetic queries; and designating as synthetic queries the candidate synthetic queries that have performance measurements exceeding a performance threshold.