Prosecution Insights
Last updated: April 19, 2026
Application No. 18/265,513

Systems and Methods for Knowledge Distillation Using Artificial Intelligence

Non-Final OA §102§103§112
Filed
Jun 06, 2023
Examiner
SHAW, PETER C
Art Unit
2493
Tech Center
2400 — Computer Networks
Assignee
Northwestern University
OA Round
1 (Non-Final)
76%
Grant Probability
Favorable
1-2
OA Rounds
3y 5m
To Grant
99%
With Interview

Examiner Intelligence

Grants 76% — above average
76%
Career Allow Rate
422 granted / 553 resolved
+18.3% vs TC avg
Strong +36% interview lift
Without
With
+35.7%
Interview Lift
resolved cases with interview
Typical timeline
3y 5m
Avg Prosecution
46 currently pending
Career history
599
Total Applications
across all art units

Statute-Specific Performance

§101
11.2%
-28.8% vs TC avg
§103
55.7%
+15.7% vs TC avg
§102
13.9%
-26.1% vs TC avg
§112
12.7%
-27.3% vs TC avg
Black line = Tech Center average estimate • Based on career data from 553 resolved cases

Office Action

§102 §103 §112
DETAILED ACTION Claims 1-20 are pending in this action. 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 . Information Disclosure Statement The information disclosure statement (IDS) submitted on 6/6/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Claim Objections Claim 1 is objected to because of the following informalities: Line 6 of claim 1, reads “a machine learning models”. Examiner believes the “s” should be removed from models like in claims 8 and 15. Appropriate correction is required. 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. Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. As per independent claim 1 at lines 9-11, it is unclear from the claim language whether “the content sections”, “the summary data” or the overall “arrangement of the summary data” are based on the co-citations. Examiner suggests rewording the limitation or including a clarifying wherein clause. Also, in line 10 of claim 1, the summary data was defined to be from the abstracts of the related papers not the related papers themselves. Both these issues render the claim indefinite. The same issues are present in the other two independent claims, 8 and 15. The dependent claims are rejected based on their dependency on the independent claims. 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. (a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention. Claims 1, 5-8, 12-15 and 18-20 are rejected under 35 U.S.C. 102(a)(1) and 102(a)(2) as being anticipated by Conrad et al. (WO-2010141477-A2) [hereinafter “Conrad”]. As per claim 1, Conrad teaches a computer-implemented method for summarizing research papers, comprising: obtaining seed data indicating a reference paper (Page 15, para. 6, seed legal document with identifier and metadata); determining a set of related papers based on the seed data, wherein each paper in the set of related papers comprises an abstract (Page 15, para. 6, determining a number of similar cases – each with head notes see Page 12, para. 4); generating, using a machine learning models, summary data for the abstract of each paper in the set of related papers (Page 14, para. 1-3, generating data from each headnote including topics and legal issues – these are interpreted to be a type of summary data); generating one or more content sections based on the summary data for each paper in the set of related papers, wherein each content section comprises an arrangement of the summary data of the set of related papers (Page 2, para. 3, merging headnotes into clusters and into topics using various similarity features) determined based on co-citations with the reference paper (Page 15, para. 6, using co-citation feature to determine clusters and topics for merging); and generating a summary paper comprising the one or more content section (Page 16, para. 4, creating a label with description of legal topics from a clustered group). As per claim 5, Conrad teaches computer-implemented method of claim 1, further comprising determining the one or more content sections based on one or more science of science measures (Examiner Note: citations and co-citations are indicated in the specification as being examples of “science of science measures” see [0021], [0045] and [0051] of instant specification) (Conrad; Page 16, para. 4, using feature vectors in a ranked fashion to create a merged topic, wherein the feature vectors are created using citations and co-citations see Page 15, para. 6). As per claim 6, Conrad teaches the computer-implemented method of claim 1, wherein the set of related papers is determined based on topic similarity with a topic indicated in the seed data (Page 5, para. 2, related documents determined based on topic similarity with each document associated with the topic). As per claim 7, Conrad computer-implemented method of claim 1, wherein the summary data comprises a human-readable set of statements (Page 16, para. 4 and 5, merged topics and labels are human-readable statements that represent summary data regarding a legal document and/or a cluster of legal documents). As per claim 8, the substance of the claimed invention is identical or substantially similar to that of claim 1. Accordingly, this claim is rejected under the same rationale. As per claim 12, the substance of the claimed invention is identical or substantially similar to that of claim 5. Accordingly, this claim is rejected under the same rationale. As per claim 13, the substance of the claimed invention is identical or substantially similar to that of claim 6. Accordingly, this claim is rejected under the same rationale. As per claim 14, the substance of the claimed invention is identical or substantially similar to that of claim 7. Accordingly, this claim is rejected under the same rationale. As per claim 15, the substance of the claimed invention is identical or substantially similar to that of claim 1. Accordingly, this claim is rejected under the same rationale. As per claim 18, the substance of the claimed invention is identical or substantially similar to that of claim 5. Accordingly, this claim is rejected under the same rationale. As per claim 19, the substance of the claimed invention is identical or substantially similar to that of claim 6. Accordingly, this claim is rejected under the same rationale. As per claim 20, the substance of the claimed invention is identical or substantially similar to that of claim 7. Accordingly, this claim is rejected under the same rationale. 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. 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 2, 9 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Conrad in view of Quartey et al. (US PGPUB No. 2022/0019609) [hereinafter “Quartey”]. As per claim 2, Conrad teaches the computer-implemented method of claim 1. Conrad does not explicitly teach wherein the machine learning model comprises a transformer architecture. Quartey teaches wherein the machine learning model comprises a transformer architecture ([0040], generating summary data for a document and headnote using Google’s Text-to-Text Transfer Transformer). At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Conrad with the teachings of Quartey, wherein the machine learning model comprises a transformer architecture, to provide the latest and precise predictive models when generating summary data regarding a document. As per claim 9, the substance of the claimed invention is identical or substantially similar to that of claim 2. Accordingly, this claim is rejected under the same rationale. As per claim 16, the substance of the claimed invention is identical or substantially similar to that of claim 2. Accordingly, this claim is rejected under the same rationale. Claims 3 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Conrad in view of Tacchi et al. (US Patent No. 9,767,165) [hereinafter “Tacchi”]. As per clam 3, Conrad teaches the computer-implemented method of claim 1. Conrad does not explicitly teach wherein the one or more content sections are determined using a principal component analysis. Tacchi teaches wherein the machine learning model comprises a transformer architecture (Col. 4, lines 56-67, using principal component analysis for generating a feature vector for a document used to summarize the document). At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Conrad with the teachings of Tacchi, wherein the machine learning model comprises a transformer architecture, to provide the latest and precise predictive models when generating summary data regarding a document. As per claim 10, the substance of the claimed invention is identical or substantially similar to that of claim 3. Accordingly, this claim is rejected under the same rationale. Claims 4, 11 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Conrad and Tacchi in further view of Kreulen et al. (US Patent No. 6,862,586) [hereinafter “Kreulen”]. As per claim 4, the combination of Conrad and Tacchi teaches the computer-implemented method of claim 3. The combination of Conrad and Tacchi does not explicitly teach wherein the one or more content sections comprise a cluster of research papers in the set of related papers determined using k-means clustering. Kreulen teaches wherein the one or more content sections comprise a cluster of research papers in the set of related papers determined using k-means clustering (Col. 1, lines 50-60, using toric k-means clustering before summarizing documents). At the time of filing, it would have been obvious to one of ordinary skill in the art to combine Conrad and Tacchi with the teachings of Kreulen, wherein the one or more content sections comprise a cluster of research papers in the set of related papers determined using k-means clustering, to employ effective known techniques when processing documents for classification and summary. As per claim 11, the substance of the claimed invention is identical or substantially similar to that of claim 4. Accordingly, this claim is rejected under the same rationale. As per claim 17, the substance of the claimed invention is identical or substantially similar to that of claim 4. Accordingly, this claim is rejected under the same rationale. Conclusion The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Chen (US PGPUB No. 2011/0295903), Caid et al. (US Patent No. 7,251,637), Ronnewinkel et al. (US PGPUB No. 2004/0083232), Bali et al. ("Semantic Similarity Detection and Analysis For Text Documents," 2024 Second International Conference on Emerging Trends in Information Technology and Engineering (ICETITE), Vellore, India, 2024, pp. 1-9, doi: 10.1109/ic-ETITE58242.2024.10493834), Varga et al. ("Measuring Research Interest Similarity with Transition Probabilities," arXiv:2409.18240, September 26, 2024), Abuobieda et al. ("Differential evolution cluster-based text summarization methods," 2013 INTERNATIONAL CONFERENCE ON COMPUTING, ELECTRICAL AND ELECTRONIC ENGINEERING (ICCEEE), Khartoum, Sudan, 2013, pp. 244-248, doi: 10.1109/ICCEEE.2013.6633941) and Magara et al. ("A comparative analysis of text similarity measures and algorithms in research paper recommender systems," 2018 Conference on Information Communications Technology and Society (ICTAS), Durban, South Africa, 2018, pp. 1-5, doi: 10.1109/ICTAS.2018.8368766) all disclose various aspects of using predictive models to cluster and summarize documents and papers. Any inquiry concerning this communication or earlier communications from the examiner should be directed to PETER C SHAW whose telephone number is (571)270-7179. The examiner can normally be reached Max Flex. 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, Carl Colin can be reached at 571-272-3862. 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. /PETER C SHAW/Primary Examiner, Art Unit 2493 January 31, 2026
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Prosecution Timeline

Jun 06, 2023
Application Filed
Jan 31, 2026
Non-Final Rejection — §102, §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
76%
Grant Probability
99%
With Interview (+35.7%)
3y 5m
Median Time to Grant
Low
PTA Risk
Based on 553 resolved cases by this examiner. Grant probability derived from career allow rate.

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