Detailed information about the 100 most recent patent applications.
| Application Number | Title | Filing Date | Disposal Date | Disposition | Time (months) | Office Actions | Restrictions | Interview | Appeal |
|---|---|---|---|---|---|---|---|---|---|
| 18885745 | END-TO-END SYSTEMS AND METHODS FOR CONSTRUCT SCORING | September 2024 | January 2026 | Allow | 16 | 3 | 0 | Yes | No |
| 18791863 | MULTILINGUAL EVENT CAUSALITY IDENTIFICATION METHOD AND SYSTEM BASED ON META-LEARNING WITH KNOWLEDGE | August 2024 | October 2025 | Abandon | 14 | 2 | 0 | No | No |
| 17599301 | A SYSTEM FOR MAPPING A NEURAL NETWORK ARCHITECTURE ONTO A COMPUTING CORE AND A METHOD OF MAPPING A NEURAL NETWORK ARCHITECTURE ONTO A COMPUTING CORE | September 2021 | March 2026 | Abandon | 54 | 2 | 0 | No | No |
| 17479856 | SYSTEMS AND METHODS FOR AUTOMATING DATA SCIENCE MACHINE LEARNING ANALYTICAL WORKFLOWS | September 2021 | December 2024 | Abandon | 38 | 1 | 0 | No | No |
| 17404470 | SITE CHARACTERIZATION FOR AGRICULTURE | August 2021 | July 2025 | Abandon | 47 | 1 | 0 | No | No |
| 17387736 | ULTRA LARGE LANGUAGE MODELS AS AI AGENT CONTROLLERS FOR IMPROVED AI AGENT PERFORMANCE IN AN ENVIRONMENT | July 2021 | December 2025 | Abandon | 52 | 2 | 0 | No | No |
| 17414596 | "System, Method, and Program for Precision Quantization of Neural Network Parameters" | June 2021 | March 2026 | Abandon | 57 | 4 | 0 | Yes | No |
| 17337998 | INTELLIGENTLY MODIFYING DIGITAL CALENDARS UTILIZING A GRAPH NEURAL NETWORK AND REINFORCEMENT LEARNING | June 2021 | October 2025 | Allow | 53 | 3 | 0 | Yes | No |
| 17299263 | SYSTEM, METHOD AND NETWORK NODE FOR GENERATING AT LEAST ONE CLASSIFICATION BASED ON MACHINE LEARNING TECHNIQUES | June 2021 | April 2025 | Abandon | 46 | 1 | 0 | No | No |
| 17231128 | DATA PROCESSING DEVICE, HUMAN-MACHINE INTERFACE SYSTEM INCLUDING THE DEVICE, VEHICLE INCLUDING THE SYSTEM, METHOD FOR EVALUATING USER DISCOMFORT, AND COMPUTER-READABLE MEDIUM FOR CARRYING OUT THE METHOD | April 2021 | February 2026 | Abandon | 58 | 4 | 0 | Yes | No |
| 17220158 | NEURAL NETWORK SEARCH METHOD AND RELATED APPARATUS | April 2021 | October 2025 | Abandon | 55 | 2 | 0 | No | No |
| 17217777 | APPARATUS FOR INSTRUCTION GENERATION FOR ARTIFICIAL INTELLIGENCE PROCESSOR AND OPTIMIZATION METHOD THEREOF | March 2021 | December 2025 | Abandon | 57 | 3 | 0 | No | No |
| 17153673 | MACHINE LEARNING TECHNIQUES FOR ASSOCIATING NETWORK ADDRESSES WITH INFORMATION OBJECT ACCESS LOCATIONS | January 2021 | February 2026 | Allow | 60 | 3 | 0 | No | No |
| 17261462 | COMPUTE-IN-MEMORY ARCHITECTURE FOR NEURAL NETWORKS | January 2021 | June 2025 | Abandon | 53 | 2 | 0 | No | No |
| 17261140 | INTEGRATED SYSTEM FOR MACHINE LEARNING ANALYSIS OF BIOLOGICAL, ENVIRONMENTAL, AND EMOTIONAL DATA | January 2021 | October 2025 | Abandon | 57 | 3 | 0 | Yes | No |
| 17079918 | ELECTRONIC DEVICE AND A METHOD FOR CONTROLLING A CONFIGURATION PARAMETER FOR AN ELECTRONIC DEVICE | October 2020 | May 2025 | Abandon | 54 | 3 | 0 | No | No |
No appeal data available for this record. This may indicate that no appeals have been filed or decided for applications in this dataset.
Examiner YI, HYUNGJUN B works in Art Unit 2146 and has examined 14 patent applications in our dataset. With an allowance rate of 14.3%, this examiner allows applications at a lower rate than most examiners at the USPTO. Applications typically reach final disposition in approximately 54 months.
Examiner YI, HYUNGJUN B's allowance rate of 14.3% places them in the 2% percentile among all USPTO examiners. This examiner is less likely to allow applications than most examiners at the USPTO.
On average, applications examined by YI, HYUNGJUN B receive 2.43 office actions before reaching final disposition. This places the examiner in the 70% percentile for office actions issued. This examiner issues a slightly above-average number of office actions.
The median time to disposition (half-life) for applications examined by YI, HYUNGJUN B is 54 months. This places the examiner in the 2% percentile for prosecution speed. Applications take longer to reach final disposition with this examiner compared to most others.
Conducting an examiner interview provides a +15.0% benefit to allowance rate for applications examined by YI, HYUNGJUN B. This interview benefit is in the 54% percentile among all examiners. Recommendation: Interviews provide an above-average benefit with this examiner and are worth considering.
When applicants file an RCE with this examiner, 14.3% of applications are subsequently allowed. This success rate is in the 10% percentile among all examiners. Strategic Insight: RCEs show lower effectiveness with this examiner compared to others. Consider whether a continuation application might be more strategic, especially if you need to add new matter or significantly broaden claims.
This examiner enters after-final amendments leading to allowance in 0.0% of cases where such amendments are filed. This entry rate is in the 1% percentile among all examiners. Strategic Recommendation: This examiner rarely enters after-final amendments compared to other examiners. You should generally plan to file an RCE or appeal rather than relying on after-final amendment entry. Per MPEP § 714.12, primary examiners have discretion in entering after-final amendments, and this examiner exercises that discretion conservatively.
Examiner's Amendments: This examiner makes examiner's amendments in 0.0% of allowed cases (in the 11% percentile). This examiner rarely makes examiner's amendments compared to other examiners. You should expect to make all necessary claim amendments yourself through formal amendment practice.
Quayle Actions: This examiner issues Ex Parte Quayle actions in 0.0% of allowed cases (in the 11% percentile). This examiner rarely issues Quayle actions compared to other examiners. Allowances typically come directly without a separate action for formal matters.
Based on the statistical analysis of this examiner's prosecution patterns, here are tailored strategic recommendations:
Not Legal Advice: The information provided in this report is for informational purposes only and does not constitute legal advice. You should consult with a qualified patent attorney or agent for advice specific to your situation.
No Guarantees: We do not provide any guarantees as to the accuracy, completeness, or timeliness of the statistics presented above. Patent prosecution statistics are derived from publicly available USPTO data and are subject to data quality limitations, processing errors, and changes in USPTO practices over time.
Limitation of Liability: Under no circumstances will IronCrow AI be liable for any outcome, decision, or action resulting from your reliance on the statistics, analysis, or recommendations presented in this report. Past prosecution patterns do not guarantee future results.
Use at Your Own Risk: While we strive to provide accurate and useful prosecution statistics, you should independently verify any information that is material to your prosecution strategy and use your professional judgment in all patent prosecution matters.