Prosecution Insights
Last updated: April 19, 2026
Application No. 18/676,330

OPTIMIZATION OF GENERATIVE AI SUMMARIZATION

Non-Final OA §101§103§112
Filed
May 28, 2024
Examiner
WONG, LINDA
Art Unit
2655
Tech Center
2600 — Communications
Assignee
Oracle International Corporation
OA Round
1 (Non-Final)
85%
Grant Probability
Favorable
1-2
OA Rounds
3y 0m
To Grant
99%
With Interview

Examiner Intelligence

Grants 85% — above average
85%
Career Allow Rate
602 granted / 709 resolved
+22.9% vs TC avg
Strong +16% interview lift
Without
With
+15.5%
Interview Lift
resolved cases with interview
Typical timeline
3y 0m
Avg Prosecution
17 currently pending
Career history
726
Total Applications
across all art units

Statute-Specific Performance

§101
7.2%
-32.8% vs TC avg
§103
44.5%
+4.5% vs TC avg
§102
22.3%
-17.7% vs TC avg
§112
16.5%
-23.5% vs TC avg
Black line = Tech Center average estimate • Based on career data from 709 resolved cases

Office Action

§101 §103 §112
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 . Drawings The drawings were received on 5/28/2024. These drawings are accepted. Claim Objections Claims 7,15 are objected to because of the following informalities: Claims 7,15 recites “said each subset” in “in response to inputting the second prompt …”. The highlighted portion is a fragment. Is “said each subset” referring to “the subset of the set of smaller cluster summaries” input into the fourth language model? Appropriate correction is required. Claim Rejections - 35 USC § 101 35 U.S.C. 101 reads as follows: Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title. Claims 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea in the form of a mental process without significantly more. The claim(s) recite(s) clustering embeddings of portions of text, cluster summaries of the clusters and a final summary based on the cluster summaries. Such is directed towards actions performed by a human being mentally using pen and paper to take text portions and generate embeddings such as a vector or list of characteristics of the text portions, clustering or grouping such embeddings, summarizing the clusters and generating a summary based on the cluster summaries. The limitations additionally recites using language models, such as a first language model, a second language model and one or more computing devices. Such recitation is merely directed towards generic device performing the abstract idea. This judicial exception is not integrated into a practical application because the recited claimed language is merely directed towards the judicial exception without positively recited language integrating the abstract idea into practical application. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the recited claimed language is merely directed towards the judicial exception without positively recited language indicating significantly more than the abstract idea. Claims 2-8 recite language adding to the judicial exception, but does not include positively recited language indicating significantly more than the abstract idea and/or integrating the abstract idea into practical application. Claims 9-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea in the form of a mental process without significantly more. The claim(s) recite(s) clustering embeddings of portions of text, cluster summaries of the clusters and a final summary based on the cluster summaries. Such is directed towards actions performed by a human being mentally using pen and paper to take text portions and generate embeddings such as a vector or list of characteristics of the text portions, clustering or grouping such embeddings, summarizing the clusters and generating a summary based on the cluster summaries. The limitations additionally recites using language models, such as a first language model, a second language model and “one or more non-transitory storage media storing instructions which, when executed by one or more computing devices”. Such recitation is merely directed towards generic device performing the abstract idea. This judicial exception is not integrated into a practical application because the recited claimed language is merely directed towards the judicial exception without positively recited language integrating the abstract idea into practical application. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the recited claimed language is merely directed towards the judicial exception without positively recited language indicating significantly more than the abstract idea. Claims 10-16 recite language adding to the judicial exception, but does not include positively recited language indicating significantly more than the abstract idea and/or integrating the abstract idea into practical application. Claims 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea in the form of a mental process without significantly more. The claim(s) recite(s) clustering embeddings of portions of text, cluster summaries of the clusters and a final summary based on the cluster summaries. Such is directed towards actions performed by a human being mentally using pen and paper to take text portions and generate embeddings such as a vector or list of characteristics of the text portions, clustering or grouping such embeddings, summarizing the clusters and generating a summary based on the cluster summaries. The limitations additionally recites using language models, such as a first language model, a second language model, one or more computing devices and “one or more non-transitory storage media storing instructions which, when executed by the one or more computing devices”. Such recitation is merely directed towards generic device performing the abstract idea. This judicial exception is not integrated into a practical application because the recited claimed language is merely directed towards the judicial exception without positively recited language integrating the abstract idea into practical application. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the recited claimed language is merely directed towards the judicial exception without positively recited language indicating significantly more than the abstract idea. Claims 18-20 recite language adding to the judicial exception, but does not include positively recited language indicating significantly more than the abstract idea and/or integrating the abstract idea into practical application. Claim Rejections - 35 USC § 112 The following is a quotation of 35 U.S.C. 112(b): (b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention. The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph: The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention. Claim 2 recites the limitation "the embeddings" in claim 1. There is insufficient antecedent basis for this limitation in the claim. Claim 10 recites the limitation "the embeddings" in claim 9. There is insufficient antecedent basis for this limitation in the claim. Claim 18 recites the limitation "the embeddings" in claim 17. There is insufficient antecedent basis for this limitation in the claim. 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 (i.e., changing from AIA to pre-AIA ) 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. Claim(s) 1,2,9,10,17,18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Mattivi et al (US Publication No.: 20220215274) in view of Somech et al (US Publication No.: 20190005024). Claim 1, Mattivi et al discloses Identifying a plurality of portions of text data (Fig. 5, label 510. Paragraph 77 discloses receiving a multi-section document with content of the document organized into different sections. Fig. 5, label 515 selects a section of the document.); For each portion of the plurality of portions, generating an embedding based on said each portion (Fig. 5, label 520. Paragraph 78 discloses generate an embedding representation of the section selected at 515.); Based on a plurality of embeddings that are generated for the plurality of portions, generating a plurality of clusters of embeddings (Fig. 5, label 525. Paragraph 79 discloses assign a cluster to the section of the multi-section document at 525. Cluster assignment is determined based on per-type section cluster for the section as per process shown in Fig. 4. Fig. 4, label 430. Paragraph 69 discloses clustering of the embedding representations having similar semantic meaning together.); For each cluster of embeddings of the plurality of clusters of embeddings: Generating, by a first language model, a cluster summary based on portions, of the plurality of portions, that correspond to embeddings associated with said each cluster of embeddings (Fig. 4, label 440 generates a cluster summary for each cluster. Paragraph 72,73 discloses a document summarization machine learning model or first language model to generate a per-type section cluster summary.); Adding the cluster summary to a set of cluster summaries (Fig. 4, label 435-445 shows a loop for continuous cluster section and cluster summarization which indicates an adding of cluster summary to the set of cluster summaries when a cluster summary for a selected section subset for cluster is performed.); Generating, using a second model, a final summary based on the set of cluster summaries (Fig. 5, label 535 generates an inferred document where Fig. 7 shows an example of using the inferred document to generate a prediction or summary of relevant features with respect to the claim being likely subject to overpayment. Fig. 7, label 725, as the inferred document generated via Fig. 4,5. Fig. 7, label 730 and paragraph 90 discloses a machine learning model is used to generate the prediction or summary as indicated in paragraph 90.); Wherein the method is performed by one or more computing devices (Fig. 2 shows one or more computing devices). Mattivi et al discloses machine learning model as the second model in paragraph 90 and discloses the output or final summary or prediction includes relevant contract features along with a summary of each relevant section of the contract explaining its importance. (paragraph 90) Although Mattivi et al discloses a summary of relevant sections of the contract as part of the output from the machine learning model as per paragraph 90, Mattivi et al fails to disclose the machine learning model is a natural language model. Somech et al discloses natural language model generating summarization versions of the relevant portions of content using one or more natural language models (paragraph 9).It would be obvious to one skilled in the art before the effective filing date of the application to substitute one well known element of Mattivi et al’s machine learning model that generates summary of relevant sections of the contract with predictions with another well-known element of a natural language model to generate summary of relevant content as disclosed by Somech et al so to yield predictable results of outputting a summary. Claim 2, Mattivi et al discloses wherein the embeddings, associated with a first cluster of embeddings in the plurality of clusters of embeddings, upon which a first cluster summary is based is less than all embeddings that are associated with the first cluster embeddings (Paragraph 69 discloses clustering embeddings of similar semantic meaning together. Fig. 4, label 415,420,425 continuously generates embeddings for sections in the contract or text. Label 430 performs clustering. Since clustering is performed based on semantic similarity, this indicates embeddings generated for each section can be grouped together. As the embeddings are grouped or clustered together, the embeddings yet to be clustered can be less than embeddings already clustered.). Claim 9 recites similar limitations as claim 1 and is rejected on the same grounds as claim 1. Claim 10 recites similar limitations as claim 2 and is rejected on the same grounds as claim 2. Claim 17 recites similar limitations as claim 1 and is rejected on the same grounds as claim 1. In addition, Mattivi et al discloses one or more computing devices (Fig. 2); one or more non-transitory storage media storing instructions which, when executed by the one or more computing devices (Paragraph 55 discloses processing element as microprocessors executing instructions stored in media such as memory such as label 220, paragraph 56.) cause the performance of limitations similarly rejected in claim 1 (please see claim 1). Claim 18 recites similar limitations as claim 2 and is rejected on the same grounds as claim 2. Allowable Subject Matter Claims 3-8,11-16,19-20 are 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 LINDA WONG whose telephone number is (571)272-6044. The examiner can normally be reached 9-5. 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, Andrew C Flanders can be reached at 571-272-7516. 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. /LINDA WONG/Primary Examiner, Art Unit 2655
Read full office action

Prosecution Timeline

May 28, 2024
Application Filed
Feb 06, 2026
Non-Final Rejection — §101, §103, §112 (current)

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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
85%
Grant Probability
99%
With Interview (+15.5%)
3y 0m
Median Time to Grant
Low
PTA Risk
Based on 709 resolved cases by this examiner. Grant probability derived from career allow rate.

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