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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 07/29/2025 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
35 U.S.C. 101 requires that a claimed invention must fall within one of the four eligible categories of invention (i.e. process, machine, manufacture, or composition of matter) and must not be directed to subject matter encompassing a judicially recognized exception as interpreted by the courts. MPEP 2106. The four eligible categories of invention include: (1) process which is an act, or a series of acts or steps, (2) machine which is an concrete thing, consisting of parts, or of certain devices and combination of devices, (3) manufacture which is an article produced from raw or prepared materials by giving to these materials new forms, qualities, properties, or combinations, whether by hand labor or by machinery, and (4) composition of matter which is all compositions of two or more substances and all composite articles, whether they be the results of chemical union, or of mechanical mixture, or whether they be gases, fluids, powders or solids. MPEP 2106(I).
Claim 11 is rejected under 35 U.S.C. 101 as not falling within one of the four statutory categories of invention because the broadest reasonable interpretation of the instant claims in light of the specification encompasses transitory signals. But, transitory signals are not within one of the four statutory categories (i.e. non-statutory subject matter). See MPEP 2106(I). However, claims directed toward a non-transitory computer readable medium may qualify as a manufacture and make the claim patent-eligible subject matter. MPEP 2106(I). Therefore, amending the claims to recite a “non-transitory computer-readable medium” would resolve this issue.
Claim Rejections - 35 USC § 102
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 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 1 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Yu et al (“Self-Chained Image-Language Model for Video Localization and Question Answering”, see IDS filed 07/29/2025).
As per claim 1, Yu discloses a computer-implemented method, comprising: receiving, by a conditioned resampler model (figure 1: Self-Chained Video Localization-Answering (SeViLa)): video features of multiple video frames of a video processed by a visual encoder (page 2: first paragraph: forward chain “chooses the important language-aware video key frames via the localization prompt”; the localizer in forward chain includes a frozen image encoder, which is the claimed “visual encoder”; the “visual features” are the claimed “video features”, see section 3.1); and token embeddings for a specified task (page 4: footnote: each key frame is inserted with a frame ID token with a specific video language task by the forward chain’s localizer and answerer BLIP-2); generating, by the conditioned resampler model in response to the video features and token embeddings provided an input, conditioned resampler embeddings according to the specified task (figure 3: the “keyframe pseudo-labels” generated by Answerer for refining in Reverse Chain in response to the keyframe features and embedded keyframe ID tokens); providing the conditioned resampler embeddings to a large language model as input (section 3.1: a frozen large language model is used in BLIP-2); and generating, by the large language model in response to the conditioned resampler embeddings, a text response to the specified task (Figure 3 & section 3.2: “pseudo labels” in response to the “options” are the claimed “text response” to a “specified task”).
As per claim 2, Yu discloses providing as input to the large language model and with the conditioned resampler embeddings, data defining the specified task; and wherein the text response to the specified task generated by the large language model is generated in response to the conditioned resampler embeddings and the data defining the specified task (as explained above, a frozen large language model is included in BLIP-2 in section 3.1 and use to define various image-language tasks).
As per claim 3, Yu discloses wherein the data defining the specified task is a text prompt (see section 3.2 for localization prompt).
As per claim 4, Yu discloses wherein: the video features include temporal encodings based on the relative times of the video frames in the video (see section 3.2 for video temporal localization).
As per claim 5, Yu discloses wherein: the token embeddings for the specified task are prefixed with a learnable token specifying a task the conditioned resampler model is to solve and concatenated with a set of learnable query vectors (see figure 2 for “learnable query q”).
As per claim 8, Yu discloses wherein the conditioned resampler embeddings comprise a fixed length that is independent of the length of the video (section 3.1: fixe-length visual features).
As per claim 9, Yu discloses wherein the conditioned resampler model is a text-conditioned resampler model that is trained, in part, on embeddings from text that defined a task condition (section 3.1: the SeViLA “project query embeddings into the LLM’s dimensionwith image-to-text pre-training” for “video language tasks”).
As per claim 10, see explanation in claim 1, The examiner notes Yu’s system is a computer-like system.
As per claim 11, see explanation in claim 1. The examiner notes Yu’s system is a computer-like system, which inherently includes a non-transitory computer-readable medium.
Allowable Subject Matter
Claims 6-7 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.
Claims 12-20 are allowed.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TOM Y LU whose telephone number is (571)272-7393. The examiner can normally be reached Monday - Friday, 9AM - 5PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella can be reached at (571) 272 - 7778. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TOM Y LU/ Primary Examiner, Art Unit 2667
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