Prosecution Insights
Last updated: July 17, 2026
Application No. 18/056,559

PRUNING COMPLEX DEEP LEARNING MODELS BASED ON PARENT PRUNING INFORMATION

Non-Final OA §101
Filed
Nov 17, 2022
Priority
Nov 18, 2021 — provisional 63/281,045
Examiner
HICKS, AUSTIN JAMES
Art Unit
2124
Tech Center
2100 — Computer Architecture & Software
Assignee
NVIDIA Corporation
OA Round
3 (Non-Final)
75%
Grant Probability
Favorable
3-4
OA Rounds
0m
Est. Remaining
99%
With Interview

Examiner Intelligence

Grants 75% — above average
75%
Career Allowance Rate
310 granted / 413 resolved
+20.1% vs TC avg
Strong +25% interview lift
Without
With
+25.2%
Interview Lift
resolved cases with interview
Typical timeline
3y 2m
Avg Prosecution
54 currently pending
Career history
467
Total Applications
across all art units

Statute-Specific Performance

§101
3.9%
-36.1% vs TC avg
§103
82.7%
+42.7% vs TC avg
§102
9.0%
-31.0% vs TC avg
§112
3.8%
-36.2% vs TC avg
Black line = Tech Center average estimate • Based on career data from 413 resolved cases

Office Action

§101
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 . Continued Examination Under 37 CFR 1.114 A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3/10/2026 has been entered. Response to Arguments Applicant's arguments filed 3/10/2026 have been fully considered but they are not persuasive. The 112 rejections are withdrawn due to amendments, thank you. Applicant argues, The analysis provided for Example 40, Claim 1, of the Subject Matter Eligibility Examples (Analysis), states that "The claim recites the combination of additional elements of collecting at least one of network delay, packet loss, or jitter relating to the network traffic passing through the network appliance, and collecting additional Netflow protocol data relating to the network traffic when the collected network delay, packet loss, or jitter is greater than the predefined threshold." Similarly, amended claim 1 recites "one or more processors executing iterations of a recursive graph traversal algorithm traversing one or more branches of a graph using memory access operations to evaluate one or more nodes of a plurality of nodes corresponding to a deep learning model for inclusion in one or more lists of one or more prunable parent nodes of one or more corresponding nodes of the graph," and "incorporating... the one or more prunable parent nodes of the first node that were determined during the first iteration into a list... wherein the traversing of the one or more branches is bypassed for the second iteration based at least on the one or more processors determining, using stored data corresponding to the first iteration, that the first iteration has occurred." Remarks 13. The difference is that Example 40 collects more data after a determination. Applicant’s claim 1 includes a node in a list when it determines to include a node into a list. Applicant’s claims don’t collect more data, or perform some other activity outside of the abstract idea of pruning a learning model. Therefore, the claims are not integrated into a practical application. Applicant argues, Similarly, amended claim 1 as a whole is directed to a particular improvement in generating pruning information for pruning deep learning models….amended claim 1 recites that "the traversing of the one or more branches is bypassed for the second iteration based at least on the one or more processors determining, using stored data corresponding to the first iteration, that the first iteration has occurred," thereby limiting collection of one or more additional prunable parent nodes and the corresponding "memory access operations to evaluate one or more nodes," which avoids excess memory traffic volume on the memory system and hindrance of memory and processing performance. Finally, the Analysis notes that the "collected data can then be used to analyze the cause of the abnormal condition," which "provides a specific improvement over prior systems, resulting in improved network monitoring. The claim as a whole integrates the mental process into a practical application.” Remarks 14. MPEP 2106.05(f) states, “instruction to apply the abstract idea using a generic computer do not render an abstract idea eligible.” The claim is not an improvement to computers or a technological field because the alleged improvement is directed towards the abstract idea of pruning. Executing the algorithm on a computer is a “mere instruction to apply an exception”, even where the claimed algorithm is an alleged improvement over other algorithms. 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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of a mental concept and mathematical relationship without significantly more. The claims recite determining two lists related to nodes, generating pruning information from the lists and then pruning a learning model based on the pruning information. This judicial exception is not integrated into a practical application because additional limitations directed to circuits, a computer and deploying the pruned model to a device merely link the abstract idea to computers. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional limitations are all directed to generic computer parts. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to Austin Hicks whose telephone number is (571)270-3377. The examiner can normally be reached Monday - Thursday 8-4 PST. 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, Mariela Reyes can be reached at (571) 270-1006. 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. /AUSTIN HICKS/Primary Examiner, Art Unit 2142
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Prosecution Timeline

Show 3 earlier events
Nov 21, 2025
Response Filed
Dec 10, 2025
Final Rejection mailed — §101
Mar 03, 2026
Interview Requested
Mar 09, 2026
Examiner Interview Summary
Mar 09, 2026
Applicant Interview (Telephonic)
Mar 10, 2026
Request for Continued Examination
Mar 15, 2026
Response after Non-Final Action
May 21, 2026
Non-Final Rejection mailed — §101 (current)

Precedent Cases

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

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Prosecution Projections

3-4
Expected OA Rounds
75%
Grant Probability
99%
With Interview (+25.2%)
3y 2m (~0m remaining)
Median Time to Grant
High
PTA Risk
Based on 413 resolved cases by this examiner. Grant probability derived from career allowance rate.

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