DETAILED 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 .
This action is in response to the communication filed on January 28, .
Claims 1-20 are pending in this action.
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.
Claim(s) 1, 4-5, 8, 11-12, 15, 17-18 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Hu et al. (RADAR: Robust AI-Text detection via adversarial Learning).
As per claim 1, Hu discloses, a computer-implemented method for detecting artificial intelligence (AI) generated text (fig. 1), comprising:
generating a corpus of artificial intelligence (AI) generated documents with a large language model and a corpus of human-written documents using identified prompts (Section 3. RADAR: Methodology and Algorithms);
estimating text distributions of human-written text and AI-generated text from the corpus of Al generated documents and the corpus of human-written documents using token statistics (Section 3.1 Training Paraphraser via Clipped PPO with Entropy Penalty);
estimating a detection distribution of Al generated documents from a target corpus with maximum likelihood estimation using the text distributions (Section 3.1 Training Paraphraser via Clipped PPO with Entropy Penalty; equation 1); and
generating detection flags for the Al generated documents from the target corpus based on the detection distribution (Fig. 1, description at Page 2).
As per claim 4, Hu discloses, wherein estimating the detection distribution further comprises estimating the maximum likelihood by computing log likelihoods of a mixture distribution of a corpus (equation 1).
As per claim 5, Hu discloses, wherein estimating the detection distribution further comprises verifying performance accuracy by comparing an estimated detection distribution with known distributions of AI-generated text and human- written text (Section 3.1 Training Paraphraser via Clipped PPO with Entropy Penalty).
As per claims 8, 11-12, 15, and 17-18, they are analyzed and thus rejected for the same reasons set forth in the rejections of claims 1 and 4-5, because the corresponding claims have similar limitations.
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(s) 2, 9, and 16 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu et al. as applied to claims 1, 8, and 15 above, and further in view of Galle et al. (US 2023/0109734).
As per claim 2, 9, and 16, Hu does not explicitly disclose, but Galle discloses, wherein generating the detection flags further comprises inserting detection flags for news articles in a news outlet website for AI-generated text containing false information Paragraphs 0058-0060).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hu by including identifying fake news articles as taught by Galle for the advantage of exactly discriminating machine-generated fake news and notifying.
Claim(s) 3 and 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu et al. in view of Galle et al. as applied to claims 2 and 9 above, and further in view of Murphy et al. (US 2025/0111050).
As per claims 3 and 10, Hu in view of Galle do not disclose, but Murphy discloses, wherein generating the detection flags further comprises generating code snippets for the detection flags in the news outlet website (Paragraphs 0047-0048).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hu in view of Galle by including generating code snippets for the detection flags as taught by Murphy for the advantage of the platform may initiate security actions based on the match (Abstract).
Claim(s) 6-7, 13-14, and 19-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Hu et al. as applied to claims 1, 8, and 15 above, and further in view of Guberman (US 2024/0086431).
As per claims 6, 13, and 19, Hu does not explicitly disclose, but Gubman discloses, wherein estimating the text distributions further comprises estimating token occurrence based on the occurrences of tokens within a document for all documents within a corpus (Abstract).
As per claims 7, 14, and 20, Hu does not explicitly disclose, but Gubman discloses, wherein estimating the text distributions further comprises estimating a token frequency distribution based on the frequency of sampled tokens in the documents (Abstract).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention to modify the invention of Hu by including estimating the text distributions and estimating a token frequency distribution based on the frequency of sampled tokens in the documents as taught by Gubeman for the advantage of intelligent editing of legal documents (Abstract).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Bitton et al. (US 2024/0296288) discloses, methods and systems for determining whether a text was produced by a human or by artificial intelligence.
Knudson et al. (US 11,593,569) discloses, enhanced input for text analytics.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Abul K. Azad whose telephone number is (571) 272-7599. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Bhavesh Mehta, can be reached at (571) 272-7453.
Any response to this action should be mailed to:
Commissioner for Patents
P.O. Box 1450
Alexandria, VA 22313-1450
Or faxed to: (571) 273-8300.
Hand-delivered responses should be brought to 401 Dulany Street, Alexandria, VA-22314 (Customer Service Window).
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August 13, 2026
/ABUL K AZAD/Primary Examiner, Art Unit 2656
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