Prosecution Insights
Last updated: October 01, 2026
Application No. 18/819,054

HANDLING COMPLEX STRUCTURES FOR SENTENCE PARAPHRASING UTILIZING A LANGUAGE MODEL

Non-Final OA §102§103
Filed
Aug 29, 2024
Examiner
BLOOMQUIST, KEITH D
Art Unit
2171
Tech Center
2100 — Computer Architecture & Software
Assignee
Adobe Inc.
OA Round
1 (Non-Final)
63%
Grant Probability
Moderate
1-2
OA Rounds
11m
Est. Remaining
81%
With Interview

Examiner Intelligence

Grants 63% of resolved cases
63%
Career Allowance Rate
455 granted / 722 resolved
+8.0% vs TC avg
Strong +18% interview lift
Without
With
+18.4%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
40 currently pending
Career history
770
Total Applications
across all art units

Statute-Specific Performance

§101
8.2%
-31.8% vs TC avg
§103
62.3%
+22.3% vs TC avg
§102
19.0%
-21.0% vs TC avg
§112
7.9%
-32.1% vs TC avg
Black line = Tech Center average estimate • Based on career data from 722 resolved cases

Office Action

§102 §103
DETAILED ACTION This action is responsive to the application filed 8/29/2024. Claims 1-20 are pending. Claim Rejections - 35 USC § 102 The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action: A person shall be entitled to a patent unless – (a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention. Claims 16 and 18 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Rajendran, et al., U.S. PGPUB No. 2018/0267960 (“Rajendran”). With regard to Claim 16, Rajendran teaches a computer-implemented method comprising: determining a template-based caption describing a data chart according to an insight template ([0022] describes that a processor generates insights by mapping statistical data with one or more predefined narratives); performing a step for generating an augmented insight describing the data chart in natural language phrases ([0022] describes that natural language processing can be used to generate a contextual summary of the chart using the one or more generated insights); and providing the augmented insight for display on a client device ([0033] describes that the contextual summaries can be presented to an end user). With regard to Claim 18, Rajendran teaches providing the augmented insight for display comprises providing an insight interface depicting the data chart and the augmented insight together. [0035] and Table 1 show that insights are displayed explaining a chart, where the chart is displayed as shown in Fig. 2B. Claim Rejections - 35 USC § 103 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. Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Rajendran, in view of Liu, et al., U.S. PGPUB No. 2024/0346254 (“Liu”). With regard to Claim 17, Rajendran, in view of Liu teaches comparing a placeholder insight generated by a natural language model to a distilled placeholder insight generated by a distilled insight model; and modifying parameters of the distilled insight model based on comparing the placeholder insight to the distilled placeholder insight. Rajendran teaches a natural language generation task for insights, as described above. Liu teaches at [0029]-[0032] that a language generation system can receive inputs and learn a policy used to generate a natural language output. The natural language output can be provided to a large language model, which can assess aspects of the generated output. The large language model can fine tune the language generation system in order that the natural language system can more closely mimic the output of the large language model, as also described at [0052]. [0035] describes that the language generation system can utilize a domain-specific small language model. It would have been obvious to one of ordinary skill in the art at the time this application was filed to modify Rajendran to use a small language model trained as described in Liu. As describes at [0004] of Liu, a small language model provides advantages of lower resource consumption and greater adaptability, while the techniques described in the reference allow for also leveraging the benefits of large language models. Therefore, one of skill in the art would have sought the modification, to improve Rajendran by reducing resource consumption of natural language generation, while still retaining access to the power afforded by large language models. Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Rajendran, in view of Liu, and in view of Yang, et al., U.S. PGPUB No. 2021/0097425 (“Yang”). With regard to Claim 19, Yang teaches generating a modified training caption from a template-based training caption by replacing an entity name with a placeholder name; and generating, utilizing an insight model to process the modified training caption, a distilled placeholder insight using the placeholder name. [0036]-[0037] describes that insight templates used for generating narrative insights include user-generated data. Templates include text as well as placeholders, meaning users can generate the template data and use a placeholder in place of a particular entity. Liu teaches using a distilled model for natural language generation at [0029]-[0032]. It would have been obvious to one of ordinary skill in the art at the time this application was filed to combine Yang with Liu, to improve system functioning by enabling the use of small language models for insight generation. It would have been obvious to one of ordinary skill in the art at the time this application was filed to combine Yang and Liu with Rajendran, to improve system functioning by enabling better user control over the narrative generation by template authoring, as well as by reducing resource consumption of natural language generation. Allowable Subject Matter Claims 1-15 are allowable over the prior art. Claim 20 is objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEITH D BLOOMQUIST whose telephone number is (571)270-7718. The examiner can normally be reached M-F, 8:30-5 PM. 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, Kieu Vu can be reached at 571-272-4057. 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. /KEITH D BLOOMQUIST/Primary Examiner, Art Unit 2171 7/10/2026
Read full office action

Prosecution Timeline

Aug 29, 2024
Application Filed
Jul 14, 2026
Non-Final Rejection mailed — §102, §103
Sep 14, 2026
Interview Requested

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
63%
Grant Probability
81%
With Interview (+18.4%)
3y 0m (~11m remaining)
Median Time to Grant
Low
PTA Risk
Based on 722 resolved cases by this examiner. Grant probability derived from career allowance rate.

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