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The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →63 simple patent families and 86 published records on binary neural network weight binarization, led by Samsung Electronics at 6.3% of families.
86 published records collapse into 63 simple (DOCDB) families; the difference is the same invention filed in more than one country. In force = 37 of 86 records still granted and maintained at the data cut-off; the rest are pending, withdrawn, refused or lapsed.
This page reports every record returned by a search for binary neural network and binarized neural network filings that combine a binarization or one-bit term with the word weight. The search string sets no date limit, so the set spans whatever filing dates the matching records carry, not a fixed window chosen for this page. In total it returns 86 published records, which de-duplicate to 63 simple patent families once the same invention filed in multiple countries is collapsed to one.
63 families is a small pool. The figures below describe what this particular search returned, who filed, which IPC classes came up, and where documents were filed, and should be read as a starting point for further search rather than a settled map of the field.
Ordered by volume only, not by importance or claim strength. Counted in simple (DOCDB) patent families, so one invention filed in several countries counts once. Names come from Patsnap's standardised assignee field as recorded on each document; subsidiaries and group companies are not merged. The icon before each name is read from the name itself (words such as University, Institute or Ltd); the data carries no organisation-type field, so treat it as a reading aid rather than a classification. 2 rows in this table share the name ELECTRONICS (ELECTRONICS & TELECOMM RES INST, SAMSUNG ELECTRONICS CO LTD). They are left as separate rows, so the largest-filer figure above is per legal entity, not per group. Rows that look related still cannot be added together: one family can name several of them. Counted one by one, those rows between them cover more than the largest single row does, so the largest single row is not necessarily the largest filer in this field. How much those rows cover together is not something this dataset can say: one family can name several of them, so their counts cannot be added. Every ranking statement on this page is per individual filer row, never per group. Filings held by named individuals rather than organisations are removed where they can be identified; that identification is not exhaustive, so an individually held filing can still appear below. Either way those filings stay inside the totals above. This table shows the top 30 of the 57 filers returned for this search; the data endpoint returns at most 100 entities, so even that 57 is not the complete set of filers. A single family can name more than one filer, so these counts overlap and do not add up to the total.
Pick a task. Every answer cites the patents behind it.
Two views of the same 63 families: how publication dates line up over time, and which IPC subclasses the records carry.
Filing counts run from 5 records in 2017 to a peak of 12 in both 2022 and 2023, with 4 recorded for 2026. Records from 2022 onward are still filling in as later publications arrive, so the recent end of this line understates eventual totals and should not be read as a drop-off.
Counted in published records by earliest filing year, not de-duplicated into families. A filing is counted in the year it was filed, but it only becomes visible after it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. 2022 onwards are therefore still filling in and are shaded; no growth figure on this page uses them. Because this series counts documents rather than inventions, a rise can mean more inventions or the same inventions filed in more countries; this dataset cannot separate the two.
G06N (computing based on AI models) appears on 60 of the 63 families, 95.2% of the set. No other subclass returned here clears 15% of the families, and because a family can carry more than one class, the shares shown add up to more than 100%.
Shares are the percentage of the 63 patent families in scope. One patent family can carry several IPC classes, so the shares add up to more than 100%.
This page is one run against one query. Ask Eureka your own question about binary neural network weight binarization quantization patent landscape and every answer comes back with the patent numbers behind it.
Try EurekaIn a method of training a binarized neural network (BNN), a binarized weight set is generated by applying a clipping function to a weight set. Output data is generated by sequentially performing a forward computation on the binarized neural network based on input data and the binarized weight set. A gradient of the weight set is generated by sequentially performing a backward computation on the binarized neural network based on loss calculated from the output data. The binarized neural network is trained by updating the weight set based on the gradient of the weight set and changing a range of the clipping function.This is the first record returned under the database's default ordering, not a most-cited, newest or broadest filing. It is shown to illustrate what a record in this set looks like, not as representative of the field.


Selected as the first record the search returns under the database default order, then shown in full. It is not ranked by citations, claim breadth or commercial importance, and it is not a judgement about which filing in this space matters most.
When you want the answer in the next five minutes.
The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →When it has to run inside your own pipeline.
Patent search, landscape analysis and assignee resolution as MCP tools. Drop them into any agent framework, or call REST directly.
Browse MCP servers →Three figures from this dataset, reported with the unit each was counted in.
Samsung Electronics Co Ltd is named on 4 of the 63 simple patent families in scope, 6.3% of the total. This is the highest count of any single row in the listed filers; it does not establish claim scope, validity or commercial activity.
Of the 57 listed filers returned by this search, 54 hold 2 or fewer simple patent families each. Filer rows are not mutually exclusive, one family can name several filers, so these counts cannot be added into a combined share.
At the 2026-10-15 retrieval date, 37 of the 86 published records (43%) were granted and still in force. The remaining records are pending, withdrawn, refused, lapsed or not determinable, and that breakdown is not separated out here.
IPC subclass G06N (computing based on AI models) appears on 60 of the 63 simple patent families, 95.2% of the set. No other subclass returned by this search reaches 15% of the families, so the composition here is read through this single subclass.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to binary neural network weight binarization quantization patent landscape, with the prior art for and against each one.
This page is a starting point built from one search string. Refining the scope or reading individual claim sets is the next step for any decision that depends on it.
A family count or an abstract cannot tell you what a claim covers. Before concluding anything about freedom to operate, read the granted claim set for the specific records that matter to you.
Open a record in EurekaThis set is built from one combination of terms. Adjacent phrasing for binarization, quantization or ternary weights may surface records this string misses.
Rebuild the search in EurekaFiler rows in this list are not rolled up to corporate group, and they overlap because one family can name several filers. Verify any name you plan to rely on against the underlying record.
Review filers in EurekaA search combining binary/binarized neural network terms with binarization or one-bit weight language returns 86 published records, which de-duplicate to 63 simple patent families once the same invention filed in multiple countries is counted once. There is no date limit on the search, so this reflects every matching record regardless of filing date, not a fixed recent window. Because the search string is narrow, this figure should be read as what this particular query returns rather than a count of every related filing that exists.
Samsung Electronics Co Ltd is named on 4 of the 63 simple patent families in scope, 6.3% of the total, the highest count among the 57 listed filers this search returned. Two rows beginning with related-looking names, Electronics & Telecomm Res Inst and Samsung Electronics Co Ltd, are listed separately and are not added together here. Most of the listed filers, 54 of 57, hold 2 or fewer families each, so the distribution does not concentrate heavily on any single row.
In this dataset, weight binarization generally refers to converting the weight values of a neural network to a small discrete set, often two values, rather than retaining full floating-point precision, as seen in the sample record on parameterized weight clipping. Exactly what a given patent's claims require, the clipping method, the range adjustment, the training procedure, has to be read from the granted claim text itself, not inferred from a title or abstract. This page reports what the search returned, not a legal interpretation of any claim.
At the retrieval date of 2026-10-15, 37 of the 86 published records, 43%, were granted and still in force. The remaining records fall into pending, withdrawn, refused, lapsed or not-determinable categories that are not broken out individually on this page. Legal status changes continuously and reflects standing at one point in time, not a measure of the quality or value of any filing.
IPC subclass G06N, computing arrangements based on specific computational models, appears on 60 of the 63 simple patent families in scope, 95.2% of the set. No other subclass returned by this search reaches 15% of the families, so G06N accounts for most of what this dataset's technology composition shows. Because one family can carry more than one class, subclass shares in this dataset add up to more than 100% and should not be read as a partition of the set.
Go past this page: query the whole binary neural network weight binarization quantization patent landscape corpus yourself, in your own scope.
Every answer comes back with patent numbers you can open.
Search. Every figure on this page comes from one Patsnap search, run once and not edited afterwards. This is the exact search string:
TAC:(("binary neural network" OR "binarized neural network") AND (binariz* OR "one-bit") AND weight)
Reading the field codes: TAC searches the title, abstract and claims of each record, not the full description. The search string sets no date limit, so the scope is every matching record in the database regardless of when it was filed. It is not restricted to recent years. How this string was built matters for how far the counts can be pushed. It was generated in batch from a topic list rather than hand-crafted for this page, and the result set is not manually screened. A keyword search over title, abstract and claims both over-captures (unrelated filings that happen to use the same words) and under-captures (the same invention written in different words). This page cannot measure either effect, so read every figure here as what this particular string returned, not as what exists in the field. One subclass (G06N) carries 95.2% of the patent families, so this search returned a classification-tight set.
What is being counted. Two different units appear on this page and they are not interchangeable. The filer list and the technology split are counted in simple (DOCDB) patent families: one invention counts once however many countries it was filed in. The total, the jurisdiction split and the filing-year chart are counted in published records: the same invention counts once per publication. For this search that is 86 records and 63 families. Record counts reward filing in many jurisdictions; family counts do not. Shares are only ever taken against a denominator in the same unit, and each one names it.
Who the filers are. Names come from Patsnap's standardised assignee field, as recorded on the documents themselves. They are not rolled up to corporate group: a parent and its subsidiaries appear as separate entries, and a portfolio acquired from another company stays under the name on the document unless the assignment is reflected there. This list is meant to carry organisations, not people. Filings held by a named individual are identified by matching the assignee against the inventors on the same search, and, for names written in Chinese, Japanese or Korean characters, by the name carrying no organisational suffix; those are removed from the list. Neither test is exhaustive: the inventor list it matches against is itself capped, and a personal name written in Latin script with no organisational wording in it cannot be told apart from a short company name by rule. So an individually held filing can still appear in the list. Those filings stay inside every total and share on this page either way, so the listed entries can add up to less than the total. A record shown in full further down still names its assignee exactly as the patent office records it, including where that is a person: that name is how the record is identified and checked. What is left out of the ranking is people as ranked entries, not people as cited sources. The table shows the top 30 of the 57 filers returned, ordered by count alone; the data endpoint returns at most 100 entities, so even that 57 is not every filer. One patent family can name several filers and each is counted separately, so these rows are not slices of a divided whole: adding them together over-counts, and this page deliberately publishes no combined "top five" share for that reason. See every filer, individuals included
Dates. The year chart counts by earliest filing year, not publication year. A filing only becomes visible once it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. Measured across these pages, the year four back from today still holds only about 89% of its eventual count. 2022 onwards are therefore shaded on the chart as still filling in. The data behind this page was retrieved on 2026-10-15.
Legal status. "In force" counts documents whose legal status at retrieval was granted and maintained (37 of 86). Everything else is pending, withdrawn, refused, lapsed or not determinable, and those states are not broken out here because the underlying codes do not separate them cleanly. Legal status changes continuously and is reported per document, not per family. Get the status breakdown in Eureka
Classification. The technology split uses IPC subclasses (four characters, for example H01M). A single record usually carries several, so the shares add up to more than 100% and a record can appear in more than one bar. Subclass is a coarse grouping; it describes the field a record was classified into, not what the claims cover. Break the classes down to subgroup level
Who wrote the words. The tables, charts, counts, shares and patent numbers on this page are produced directly from the search result by a program; none of them are written or estimated by a language model. The surrounding prose, headings, FAQ answers and the answers in the question panel are drafted by a language model that is given those same figures and is not permitted to introduce others. Prose can still mis-describe a correct figure, so where the two disagree, the tables and charts are the record.
Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries limitations that apply to every figure above. Recent filings are under-counted, because an application is not public until roughly 18 months after filing and database loading adds further delay. The search string defines and constrains everything shown: records that use different terminology, or that sit outside the fields searched, are absent and cannot be counted. Applicant names, classification codes, legal-status codes and citation records are taken as recorded and may contain errors, duplicates, omissions or stale entries. Ordering by volume is not a measure of quality, scope, enforceability or commercial value, and a larger portfolio is not a stronger one. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, validity or infringement search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. No attorney-client relationship is created by it. Any patent, commercial, or strategic decision should be verified independently against the primary records and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
The question panel. The answers behind the suggested questions on this page were written when the page was generated, not in response to your click. The progress steps that play before an answer appears are an animation of how that analysis was done; nothing is being searched or computed at that moment. Typing your own question instead opens Patsnap Eureka, which does run it live.
Machine translation. Assignee and organisation names originally recorded in Chinese, Japanese or Korean have been rendered into English by an AI translation step so that the tables stay readable. These renderings are best-effort and may not match a company's registered English name; the original name is what the underlying patent record carries, and it is what any Eureka query launched from this page uses.
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