Prosecution Insights
Last updated: April 19, 2026
Application No. 18/591,337

DETECTING AND SELECTIVELY BUFFERING MARKUP INSTRUCTION CANDIDATES IN A STREAMED LANGUAGE MODEL OUTPUT

Non-Final OA §103
Filed
Feb 29, 2024
Examiner
PASHA, ATHAR N
Art Unit
2657
Tech Center
2600 — Communications
Assignee
Shopify Inc.
OA Round
1 (Non-Final)
90%
Grant Probability
Favorable
1-2
OA Rounds
2y 8m
To Grant
99%
With Interview

Examiner Intelligence

Grants 90% — above average
90%
Career Allow Rate
138 granted / 154 resolved
+27.6% vs TC avg
Strong +17% interview lift
Without
With
+17.0%
Interview Lift
resolved cases with interview
Typical timeline
2y 8m
Avg Prosecution
18 currently pending
Career history
172
Total Applications
across all art units

Statute-Specific Performance

§101
21.9%
-18.1% vs TC avg
§103
49.4%
+9.4% vs TC avg
§102
16.9%
-23.1% vs TC avg
§112
5.2%
-34.8% vs TC avg
Black line = Tech Center average estimate • Based on career data from 154 resolved cases

Office Action

§103
Notice of Pre-AIA or AIA Status The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . Claim Rejections - 35 USC § 103 In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status. The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action: A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made. The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows: 1. Determining the scope and contents of the prior art. 2. Ascertaining the differences between the prior art and the claims at issue. 3. Resolving the level of ordinary skill in the pertinent art. 4. Considering objective evidence present in the application indicating obviousness or nonobviousness. Claims 1, 2, 3, 12, 13, 14, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu (US 20120232904 A1) in further view of Chen (US 20190303136 A1) and Rudolph (US 20110119573 A1) With respect to claims 1, 12 and 20 Zhu teaches (claim 1) A computer-implemented method comprising: (claim 12) A computing system comprising: processing circuity ([0072] Although these modules are illustrated as separate components in FIG. 7, these components may be embodied as a single component performing the different operations, such as a microprocessor.); and memory comprising instructions (Although these modules are illustrated as separate components in FIG. 7, these components may be embodied as a single component performing the different operations, such as a microprocessor.) executed by the processing circuitry whereby the computing system is operable to: receiving a stream of symbols from a language model (Zhu ¶ [0074] The named entity word detecting module 200 determines a named entity word recognized incorrectly in the recognition result according to the named entity vocabulary mark-up information, marks up the named entity word recognized incorrectly in the recognition result, and outputs the recognition result to the user correcting module 300 and a display (not shown), ¶ [0077] Referring to FIG. 8, the continuous speech recognizing module includes a feature extracting submodule 101, a decoder 102, a named entity mark-up dictionary 103, an acoustical model 104, and a class-based language model 105.); and streaming the received stream of symbols as output, the output is caused to be rendered on a display ([0074] The named entity word detecting module 200 determines a named entity word recognized incorrectly in the recognition result according to the named entity vocabulary mark-up information, marks up the named entity word recognized incorrectly in the recognition result, and outputs the recognition result to the user correcting module 300 and a display (not shown) [streaming].), the streaming of the symbols as output comprises: detecting a markup sequence in the received stream of symbols ([0074] The named entity word detecting module 200 determines a named entity word recognized incorrectly in the recognition result according to the named entity vocabulary mark-up information, marks up the named entity word recognized incorrectly in the recognition result, and outputs the recognition result to the user correcting module 300 and a display (not shown).)); Zhu does not explicitly disclose however Chen teaches (claim 20 )A non-transitory computer readable medium comprising instructions executable by processing circuitry of a computing system whereby the computing system is operable to (Chen ¶[0022]A computer readable storage medium, as used herein, is not to be construed as being transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission media (e.g., light pulses passing through a fiber-optic cable), or electrical signals transmitted through a wire) responsive to detecting the markup sequence, pausing the streaming of the symbols as output and instead streaming the received stream of symbols to a buffer (Chen ¶ [0020] In decision block 360, software globalization module 300 determined whether or not an entry exists in a local cache for the internationalization key. If so, in block 370, software globalization module 300 retrieves a corresponding textual resource from the cache. Otherwise, in block 380 software globalization module 300 transmits the internationalization key and the locale setting to a remote server in response to which in block 390, the software globalization module 300 receives the corresponding textual resource. In decision block 400, the software globalization module 300 determines if additional markup remains to be parsed. If so, the process repeats through block 330. Otherwise, in block 410 the software globalization module 300 directs the Web browser to render the markup with the retrieved textual resource.) detecting a further markup sequence in the received stream of symbols (Chen ¶ [0020] In decision block 360, software globalization module 300 determined whether or not an entry exists in a local cache for the internationalization key. If so, in block 370, software globalization module 300 retrieves a corresponding textual resource from the cache. Otherwise, in block 380 software globalization module 300 transmits the internationalization key and the locale setting to a remote server in response to which in block 390, the software globalization module 300 receives the corresponding textual resource. In decision block 400, the software globalization module 300 determines if additional markup remains to be parsed. If so, the process repeats through block 330. Otherwise, in block 410 the software globalization module 300 directs the Web browser to render the markup with the retrieved textual resource.); and responsive to detecting the further markup sequence in the received stream of symbols: causing the symbols in the buffer to be rendered (Chen ¶ [0020] In decision block 360, software globalization module 300 determined whether or not an entry exists in a local cache for the internationalization key. If so, in block 370, software globalization module 300 retrieves a corresponding textual resource from the cache. Otherwise, in block 380 software globalization module 300 transmits the internationalization key and the locale setting to a remote server in response to which in block 390, the software globalization module 300 receives the corresponding textual resource. In decision block 400, the software globalization module 300 determines if additional markup remains to be parsed. If so, the process repeats through block 330. Otherwise, in block 410 the software globalization module 300 directs the Web browser to render the markup with the retrieved textual resource.); and It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify receipts of symbols of Zhu to include the buffering of Chen in order to steam symbol output efficiently. None of Zhu and Chen explicitly disclose however Rudolph teaches resuming streaming the received stream of symbols as output (Rudolph ¶ [0054] This process is repeated for all visible lines.). It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify receipts of symbols of Zhu in view of the buffering of Chen to include repetition of Rudolph in order to improve rendered text quality ([0042], Rudolph) With respect to claims 2 and 13 Chen further teaches wherein the markup sequence and further markup sequence denote a markup instruction Chen ¶ [0020] In decision block 360, software globalization module 300 determined whether or not an entry exists in a local cache for the internationalization key. If so, in block 370, software globalization module 300 retrieves [instruction] a corresponding textual resource from the cache). With respect to claims 3 and 14 Chen further teaches wherein, responsive to the denoted markup instruction, the symbols in the buffer are caused to be rendered based on the markup instruction (Chen ¶ [0020] In decision block 360, software globalization module 300 determined whether or not an entry exists in a local cache for the internationalization key. If so, in block 370, software globalization module 300 retrieves a corresponding textual resource from the cache. Otherwise, in block 380 software globalization module 300 transmits the internationalization key and the locale setting to a remote server in response to which in block 390, the software globalization module 300 receives the corresponding textual resource. In decision block 400, the software globalization module 300 determines if additional markup remains to be parsed. If so, the process repeats through block 330. Otherwise, in block 410 the software globalization module 300 directs the Web browser to render the markup with the retrieved textual resource.)). Claims 4, 8, 15, 19 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu , Chen, and Rudolph in further view of Ku (US 20100235910 A1) With respect to claims 4 and 15 Zhu, Chen and Rudolph don’t explicitly disclose however Ku teaches wherein the markup sequence and further markup sequence denote a false detection of a markup instruction (Ku ¶ [0074] As illustrated in FIG. 4, a false code detection window according to an exemplary embodiment of the present invention may display HTML tag types set to be checked 1, a list of web pages or HTML tags set to be collected 2, a pattern application list 3, a false code list 4, and so on.). It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify receipts of symbols of Zhu in view of the buffering of Chen in view of repetition of Rudolph to include false detection of Ku in order to manage system stability ([0012], Ku) With respect to claims 8 and 19 Zhu, Chen and Rudolph don’t explicitly disclose however Ku teaches wherein the markup instruction is from a markup language comprising one of the group consisting of: HTML; XML; and Chat Markup Language (Ku ¶ [0074] As illustrated in FIG. 4, a false code detection window according to an exemplary embodiment of the present invention may display HTML tag types set to be checked 1, a list of web pages or HTML tags set to be collected 2, a pattern application list 3, a false code list 4, and so on.). It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify receipts of symbols of Zhu in view of the buffering of Chen in view of repetition of Rudolph to include false detection of Ku in order to manage system stability ([0012], Ku) Claims 5 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu , Chen, Rudolph and Ku in further view of Kaushik (US 20150012809 A1) With respect to claims 5 and 16 Zhu, Chen, Rudolph and Ku don’t explicitly disclose, however Kaushik teaches wherein, responsive to the false detection of the markup instruction, the symbols in the buffer are caused to be rendered without the markup instruction (Kaushik ¶ [0031] The browser does not understand how to interpret these application-specific objects. Without translation, the browser may ignore this code or display an error to the user.) It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify receipts of symbols of Zhu in view of the buffering of Chen in view of repetition of Rudolph in view of false detection of Ku to include rendering without markup of Kaushik in order to render content dynamically and efficiently. Claims 6 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu , Chen, and Rudolph in further view of Jain (US 20250131185 A1) With respect to claims 6 and 17 Zhu, Chen and Rudolph don’t explicitly disclose however Jain teaches wherein the Language Model is a Large Language Model (0034] To address the limitations of current RPA systems, methods of the present disclosure implement an AI-based RPA system (also referred to as ‘system’ and interchangeably used herein) that uses LLMs coupled with deep-learning based image understanding. It integrates vision capabilities with natural language processing techniques to adapt to changes in the graphical user interface (GUI) and automatically generate navigation workflows for handling of one or more associated field types of an application form using one or more screenshots associated with the application form. By utilizing vision techniques, the system identifies and locates screen elements, while a HyperText Markup Language (HTML) source code (in the case where the application form is a web application form) provides information about the type of these elements. A pre-trained large language model such as GPT-3 is then employed to generate navigation workflows based on this information. This navigation workflow is then executed using a scripting engine to complete the assigned task). It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify receipts of symbols of Zhu in view of the buffering of Chen in view of repetition of Rudolph to include LLM of Jain in order to achieve advanced language understanding and generation capabilities ([0032], Jain). Claims 7 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu , Chen, and Rudolph in further view of Lu (US 20190042549 A1) With respect to claims 7 and 18 Zhu, Chen and Rudolph don’t explicitly disclose however Lu teaches wherein the markup instruction is from a Markdown markup language (Lu ¶[0011] The above aspect and any possible implementation mode further provide an implementation mode: the lightweight markup language comprises Markdown markup language, Textile markup language or reStructured markup language.) It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify receipts of symbols of Zhu in view of the buffering of Chen in view of repetition of Rudolph to include markdown of Lu in order to provide efficiency and reliability ([0004], Lu). Claims 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Zhu , Chen, and Rudolph in further view of Springer (US 20240333779 A1) With respect to claim 9 Zhu, Chen and Rudolph don’t explicitly disclose however Springer teaches further comprising: before detecting the further markup sequence, causing to be rendered on a display that buffering is occurring (Springer ¶ [0072] The GUI 700 could be output to the user device 404A (or the first user device 504) of the first conference participant at a first time. The first conference participant may have a peripheral device 708, such as a headset visible in the user tile 702A. The first conference participant may transmit (e.g., from the user device 404A) an indication to the peripheral device 708 to temporarily buffer a portion of media content of the video conference. When buffering is complete, the GUI 700 may display a message 710 indicating buffering is complete and requesting input from the first conference participant to complete the transition (“Yes” or “No”).). It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify receipts of symbols of Zhu in view of the buffering of Chen in view of repetition of Rudolph to include messaging of Springer in order to provide real-time alignment between users and devices ([0016], Springer). With respect to claim 10 Zhu, Chen and Rudolph don’t explicitly disclose however Springer teaches wherein receiving the stream and streaming the received stream of symbols are implemented through the use of a stateful stream processor coupled with a buffer (Springer ¶ 0086] Some implementations may include an apparatus that includes a memory and a processor configured to execute instructions stored in the memory to transmit, from a first user device connected to a video conference and associated with a conference participant, an indication to a peripheral device to buffer a portion of media content of the video conference; and perform, within the video conference, a transition of the conference participant from the first user device to a second user device connected to the video conference including causing the peripheral device to relay the portion of the media content during the transition. In some implementations, the processor is further configured to execute instructions stored in the memory to determine the second user device using a machine learning model. In some implementations, the processor is further configured to execute instructions stored in the memory to buffer the portion of the media content by storing less than a ten seconds of the media content received by the first user device in a micro-buffer of the peripheral device.). It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify receipts of symbols of Zhu in view of the buffering of Chen in view of repetition of Rudolph to include messaging of Springer in order to provide real-time alignment between users and devices ([0016], Springer). Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Zhu , Chen, Rudolph and Springer in further view of Parekh (US 20010052910 A1) With respect to claim 11 Zhu, Chen and Rudolph, Springer don’t explicitly disclose however Parekh teaches wherein the received stream of symbols is parsed by the stateful stream processor which updates a buffer based on whether the sequence in the received stream of symbols currently being parsed is a candidate for a markup instruction ( Parekh ¶ 0063] In another preferred embodiment of the present invention, the programmer employs conventional HTML scripting styles to help the screen template generator software tool delimit each HTML command. In an alternate embodiment of the present invention, the screen template generator software tool can have a level of browser intelligence so as to recognize when an HTML command ends. Conventional browsers sometimes recognize here a command ends, even without a terminating tag, because the browser recognizes which markup tags are valid within a particular command. When the browser sees a new tag that is not a valid markup within the current command, it assumes that the current command has terminated.). It would have been obvious to one of ordinary skill in the art prior to the effective filing date of the invention to modify receipts of symbols of Zhu in view of the buffering of Chen in view of repetition of Rudolph in view of messaging of Springer to include markup candidates of Parekh in order to improve efficiency and make system less error-prone ([0007], Parekh). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to ATHAR N PASHA whose telephone number is (408)918-7675. The examiner can normally be reached Monday-Thursday Alternate Fridays, 7:30-4:30 PT. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Daniel Washburn can be reached on (571)272-5551. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /ATHAR N PASHA/ Primary Examiner, Art Unit 2657
Read full office action

Prosecution Timeline

Feb 29, 2024
Application Filed
Jan 10, 2026
Non-Final Rejection — §103 (current)

Precedent Cases

Applications granted by this same examiner with similar technology

Patent 12596882
COMPLIANCE DETECTION USING NATURAL LANGUAGE PROCESSING
2y 5m to grant Granted Apr 07, 2026
Patent 12586563
Method, System and Apparatus for Understanding and Generating Human Conversational Cues
2y 5m to grant Granted Mar 24, 2026
Patent 12579173
SYSTEMS AND METHODS FOR DYNAMICALLY PROVIDING INTELLIGENT RESPONSES
2y 5m to grant Granted Mar 17, 2026
Patent 12566921
GAZETTEER INTEGRATION FOR NEURAL NAMED ENTITY RECOGNITION
2y 5m to grant Granted Mar 03, 2026
Patent 12547844
INTELLIGENT MODEL SELECTION SYSTEM FOR STYLE-SPECIFIC DIGITAL CONTENT GENERATION
2y 5m to grant Granted Feb 10, 2026
Study what changed to get past this examiner. Based on 5 most recent grants.

AI Strategy Recommendation

Get an AI-powered prosecution strategy using examiner precedents, rejection analysis, and claim mapping.
Powered by AI — typically takes 5-10 seconds

Prosecution Projections

1-2
Expected OA Rounds
90%
Grant Probability
99%
With Interview (+17.0%)
2y 8m
Median Time to Grant
Low
PTA Risk
Based on 154 resolved cases by this examiner. Grant probability derived from career allow rate.

Sign in with your work email

Enter your email to receive a magic link. No password needed.

Personal email addresses (Gmail, Yahoo, etc.) are not accepted.

Free tier: 3 strategy analyses per month