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The agent works the prompt against patents and technical literature, citing every source.
Run your analysis now →Filing growth compares 2021 (43 records) with 2024 (32) — a three-year span. 2024 is the most recent year we treat as complete: publication lags filing by roughly 18 months, so 2025 onwards are still filling in and any growth rate that ends there would understate the field. Top-5 share is the combined record count of the five largest assignees divided by all 1,327 records in scope (CR5), not by the ranked leaders only.
This dataset tracks patent activity where product quantization, vector compression and residual quantization intersect with practical concerns like codebook training, exact reranking, quantization error and distance approximation — the mechanics that make compressed vector representations usable for retrieval at scale. The corpus spans 1,327 records published between 2015 and mid-2026.
Much of the underlying technique originates in video and audio codec work, where lattice and trellis-coded quantization first solved the problem of compressing signals without losing the ability to compare them cheaply. That lineage still shows up strongly in the classification mix, even as the same math gets repurposed for embedding search and approximate nearest-neighbour retrieval.
Two views of the same 1,327 records: how filing activity has moved year over year, and which IPC subclasses the claims actually sit in.
Filings peaked in 2018 at 73 and have since drifted down, with 2021 at 43 and 2024 at 32 records — a -26% change over that three-year window. The 2025 and 2026 figures are undercounted because publication typically lags filing by around 18 months; they should not be read as a continued decline.
H04N (pictorial communication) appears in 41.8% of records and G10L (speech and audio) in 19.6%, confirming the field's roots in media codecs. G06F (13.2%) and H03M (12.6%) reflect the general data-processing and coding layers, while G06N (7.3%) marks the smaller but growing overlap with AI-model-based approaches. Because records can carry multiple IPC classes, these shares sum to well over 100% of the record total.
Shares are the percentage of the 1,327 records in scope. A patent 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 vector quantization for retrieval and every answer comes back with the patent numbers behind it.
Try EurekaA frequency divider circuit applies a variable division-ratio control signal alongside a residual quantization error signal to cancel phase error in the divided output, with both signals dithered to smooth the correction.Filed by Kaben Research Inc.; illustrates how residual quantization error terms surface even in circuit-level frequency-division work, well outside retrieval systems.


| # | Publication no. | Patent title | Citations |
|---|---|---|---|
| 1 | US5297170A | Lattice and trellis-coded quantization | 298 |
| 2 | US20100223237A1 | Lossless data compression and real-time decompression | 284 |
| 3 | US5490247A | Video subsystem for computer-based conferencing system | 275 |
| 4 | US5434913A | Audio subsystem for computer-based conferencing system | 262 |
| 5 | US5515296A | Scan path for encoding and decoding two-dimensional signals | 254 |
| 6 | US5488570A | Encoding and decoding video signals using adaptive filter switching criteria | 242 |
| 7 | US20040217956A1 | Method and system for processing, compressing, streaming, and interactive rendering of 3D color image data | 220 |
| 8 | US5684920A | Acoustic signal transform coding method and decoding method having a high efficiency envelope flattening meth… | 197 |
| 9 | US20040042549A1 | Architecture and method for fine granularity scalable video coding | 193 |
| 10 | US6125398A | Communications subsystem for computer-based conferencing system using both ISDN B channels for transmission | 192 |
Citation counts favour older filings simply because they have had more time to accumulate citations within this corpus — treat them as markers of foundational influence, not current relevance.
Each row carries its publication number; clicking a row searches Eureka by that number.
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 read-outs from the dataset that matter more than the raw counts on their own.
The five leading assignees combined account for 44.9% of all 1,327 records in scope, and the top 10 extend that to 57.6%. A ranked list of 100 companies exists below them, but the tail thins quickly — most of those 100 hold only a handful of families each.
Filings fell from 43 in 2021 to 32 in 2024, a -26% move over that span, continuing a slide from the 2018 peak of 73. Recent-year momentum data shows several of the largest historical filers posting zero or sharply reduced output in the latest tracked year, though 2025-2026 figures are still incomplete.
H04N (pictorial communication) and G10L (speech and audio) together touch the majority of records, meaning most active claim territory still frames quantization as a media-compression problem rather than a retrieval-system one. G06N's smaller 7.3% share marks where AI-model framing is starting to enter.
Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to vector quantization for retrieval, with the prior art for and against each one.
| Assignee | Co-assignee | Shared families |
|---|---|---|
| Huawei Technologies Co., Ltd. | GAO YANG | 6 |
| Fraunhofer Gesellschaft zur Forderung der angewandten Forschung e.V. | WIEGAND THOMAS | 4 |
| Fraunhofer Gesellschaft zur Forderung der angewandten Forschung e.V. | SCHWARZ HEIKO | 3 |
| Huawei Technologies Co., Ltd. | SYCHEV MAXIM BORISOVITCH | 3 |
| Fraunhofer Gesellschaft zur Forderung der angewandten Forschung e.V. | WINKEN MARTIN | 2 |
| Fraunhofer Gesellschaft zur Forderung der angewandten Forschung e.V. | HINZ TOBIAS | 2 |
| Qualcomm Inc. | YANG WEI | 2 |
| Qualcomm Inc. | WU LIANGMING | 2 |
Ten co-assignee pairs appear in the data, with the strongest linking a major Chinese electronics filer to an individual inventor at 6 shared records — a pattern typical of in-house inventor-assignee collaboration rather than cross-company joint filing.
The leading assignees span consumer electronics, telecom infrastructure and standards-adjacent codec research, with the ranked field extending to 100 companies before the tail becomes sparse.
The top-ranked assignee holds 238 records, more than four times the count at fifth place (59). That gap suggests a deliberate, sustained filing programme rather than opportunistic patenting.
Record counts fall from 59 at fifth place to 20 at tenth, and the top 10 combined still represent 57.6% of all 1,327 records in scope. Below tenth place, the ranking spreads across many single- and low-digit filers.
Several of the largest historical assignees show zero filings or year-over-year declines of -75% to -100% in the latest tracked year. Given the roughly 18-month publication lag, this likely overstates any real slowdown, but it is a signal worth confirming rather than ignoring.
| Assignee | Recent year | YoY |
|---|---|---|
| Qualcomm Inc. | 1 | -75% |
| M&K Holdings Inc. | 0 | — |
| Fraunhofer Gesellschaft zur Forderung der angewandten Forschung e.V. | 0 | -100% |
| Huawei Technologies Co., Ltd. | 0 | -100% |
| LG Electronics Inc. | 0 | -100% |
| Dolby International AB | 0 | -100% |
| Mitsubishi Electric Corporation | 0 | — |
| Google LLC | 0 | -100% |
The dataset points to specific next steps depending on whether the goal is freedom-to-operate, competitive tracking or identifying open claim space.
With 57.6% of records held by the top 10 assignees, any new filing in codebook training or distance approximation should be checked against those portfolios first.
Explore assignee portfolios in Eureka →G06N's 7.3% share is small today but represents the branch most likely to grow as quantization techniques get reframed for embedding-based retrieval rather than media codecs.
Track emerging IPC shifts in Eureka →Recent-year momentum figures showing declines at major assignees are affected by publication lag; confirm with filing-date data before concluding the field is cooling.
Run a filing-date trend check in Eureka →In this dataset, vector quantization claims mostly originate in video and audio codec work, covering techniques like product quantization, residual quantization and codebook training that compress signal or vector data while preserving the ability to approximate distances between compressed representations. That same machinery is increasingly repurposed for retrieval systems, where compressed embedding vectors need to be compared quickly at query time. The IPC composition shows H04N and G10L still account for the largest shares of records, meaning most granted claim territory frames the problem as media compression rather than search infrastructure.
The ranking covers 100 companies, with a single leader holding 238 records — more than four times the count at fifth place, which sits at 59. The top 5 assignees together hold 44.9% of all 1,327 records in scope, and the top 10 extend that to 57.6%, so the field is genuinely concentrated at the top rather than evenly spread. Company names in the underlying data span consumer electronics, telecom equipment and codec-standards research organisations.
Filings peaked at 73 in 2018 and have since eased, with 2021 at 43 and 2024 at 32 — a -26% change over that three-year span, which is the most recent period reliable enough to compare. Figures for 2025 and 2026 look lower still, but publication typically lags actual filing by around 18 months, so those years are undercounted rather than necessarily reflecting reduced activity. A clearer read on the current trajectory will only be available once those years finish publishing.
The classification data shows dense claim coverage in pictorial and speech/audio compression (H04N at 41.8%, G10L at 19.6%) but comparatively thinner coverage in areas like cache-locality-aware index layouts, asymmetric distance computation tuned for retrieval query patterns, and residual quantization applied specifically to multi-vector retrieval rather than single-signal compression. These are areas where the underlying technique clearly applies but claim density is lower relative to the codec core, making them worth a closer prior-art check before filing rather than areas to avoid entirely.
US6944257B2 covers a frequency divider circuit that uses a residual quantization error signal to cancel phase error, assigned to Kaben Research Inc. and unrelated to embedding retrieval or search systems. It matters mainly as an example of how the term 'residual quantization error' recurs across very different engineering domains, from circuit design to media codecs to modern vector search, so a keyword-only prior art search can surface false-positive blocking concerns. Teams should confirm relevance by claim scope and application domain, not by search term overlap alone.
Go past this page: query the whole vector quantization for retrieval corpus yourself, in your own scope.
Every answer comes back with patent numbers you can open.
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 inherent limitations: recent filings (typically the most recent 18–24 months) are under-counted due to standard publication lag; counts may be reported at either a patent-family or a patent-record basis and are not always directly comparable; classification, applicant-name, and citation data may contain errors, duplicates, or omissions; and the underlying search query defines and constrains the scope shown. 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, or validity search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. Any patent, commercial, or strategic decision should be verified independently 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.
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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