Please enter the search related information in the fields below. Partial information works, e.g. "SP-21" in the "tdoc" field lists all TSG SA documents from 2021. Regular expressions mostly work in all fields (e.g. "2[34].501" in the "Spec" field lists all documents related to 23.501 and 24.501. Capitalization is disregarded, i.e. "3GPP" gives the same results as "3gpp".
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| tdoc | Title | Type / Revs | Source | Spec / CR | S/WID | Release | Meeting | Status | Links |
|---|---|---|---|---|---|---|---|---|---|
| S5-243521 | TR 28.858 v0.0.0 (skeleton) Study on AI/ML management phase 2 | draft TR | NEC, Intel | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] | |
| S5-243522 | Draft TR 28.858 v0.1.0: Study on AI/ML management phase 2 | draft TR | NEC, Intel | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] | |
| S5-243528 | Rel-19 pCR TR28.858 Update R19 continuation use cases.docx |
pCR revised to S5-244598 |
Nokia | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243529 | Rel-19 pCR TR28.858 Conclude R19 continuation use cases |
pCR revised to S5-244600 |
Nokia | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243564 | Collection of runtime performance KPIs for ML models |
pCR revised to S5-244617 |
AT&T | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243565 | Network Management actions in response to an underperforming ML algorithm used in a live network |
pCR revised to S5-244618 |
AT&T | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243673 | pCR 28.858 Add use case for management of consumer-triggered Federated Learning | pCR | China Mobile | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
not treated | [WTS] [JSN] |
| S5-243674 | Rel-19 pCR TR28.858 Add use case of performance monitoring | pCR | China Mobile | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
not treated | [WTS] [JSN] |
| S5-243675 | Rel-19 pCR TR28.858 Add use case of AI emulation |
pCR revised to S5-244601 |
China Mobile | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243706 | pCR TR 28.858 Sustainability of AI-ML |
pCR revised to S5-244606 |
Huawei, Deutsche Telekom, Telecom Italia | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243731 | pCR TR 28.858 clause structure | pCR | NEC, Intel | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] |
| S5-243821 | TR28.858 add RAG use case in AIML Inference | pCR | Nokia, Nokia Shanghai Bell, China Unicom | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] |
| S5-243858 | pCR TR 28.858 Add Potential Requirements and Possible Solution for Sustainable AIML |
pCR revised to S5-244603 |
ZTE Corporation | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243859 | pCR TR 28.858 Add Use Case for Management of Vertical Federated Learning | pCR | ZTE Corporation | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
not treated | [WTS] [JSN] |
| S5-243860 | pCR TR 28.858 Add Possible Solution for Management of Vertical Federated Learning | pCR | ZTE Corporation | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
not treated | [WTS] [JSN] |
| S5-243861 | pCR TR 28.858 Add Use Case and Requirements for ML Model Transfer |
pCR revised to S5-244607 |
ZTE Corporation | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243873 | pCR TR 28.858 add scope |
pCR revised to S5-244592 |
NEC, Intel | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243876 | pCR TR 28.858 add overview |
pCR revised to S5-244593 |
NEC, Intel | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243879 | pCR TR 28.858 Add use case for management of Federated Learning |
pCR revised to S5-244817 |
Intel, ZTE, Nokia, China Mobile, NEC, HUAWEI | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243880 | pCR TR 28.858 Add possible solution for management of Federated Learning | pCR | Intel, ZTE, Nokia, China Mobile, NEC, HUAWEI | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
not treated | [WTS] [JSN] |
| S5-243881 | pCR TR 28.858 Update the UC and requirements for pre-training |
pCR revised to S5-244637 |
Intel, NEC | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243938 | DP on potential gaps in Inference management in TS 28.105 |
discussion revised to S5-244597 |
Nokia | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] | |
| S5-243939 | Rel-19 pCR TR28.858 R19 Support for efficient re-training |
pCR revised to S5-244602 |
Nokia | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243945 | Rel-19 pCR TR 28.858 Enhance the ML model loading use case and solution |
pCR revised to S5-244599 |
Huawei | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243946 | Rel-19 pCR TR 28.858 Add concept of new learning techniques | pCR | Huawei | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] |
| S5-243947 | Rel-19 pCR TR 28.858 Add concept of Generative AI |
pCR revised to S5-244828 |
Huawei | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243948 | Rel-19 pCR TR 28.858 add use cases, requirements for reinforcement learning management |
pCR revised to S5-244634 |
Huawei | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-243949 | Rel-19 pCR TR 28.858 add possible solutions for reinforcement learning management | pCR | Huawei | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] |
| S5-244057 | pCR TR 28.858 Add Potential Requirements and Possible Solution for Management of Reinforcement Learning | pCR | ZTE Corporation | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
merged | [WTS] [JSN] |
| S5-244120 | Rel-19 pCR TR 28.858 Update use case of Sustainable AI/ML and add new potential requirements and solutions | pCR | China Unicom, ZTE | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
merged | [WTS] [JSN] |
| S5-244162 | Standardization of Federated Learning in 3GPP SA5 |
discussion revised to S5-244608 |
Ericsson-LG Co., LTD | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] | |
| S5-244210 | Rel-19 pCR 28.858 Reinforcement Learning addition | pCR | Samsung R&D Institute UK | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
merged | [WTS] [JSN] |
| S5-244212 | Rel-19 pCR 28.858 Generative AI | pCR | Samsung R&D Institute UK | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] |
| S5-244238 | Rel-19 pCR TR 28.858 Add Potential Solution for Pre-training |
pCR revised to S5-244616 |
China Mobile, ZTE | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244240 | Rel-19 pCR TR 28.858 Add use case for ML Fine-tuning |
pCR revised to S5-244609 |
China Mobile, China Unicom, Verizon, Intel, NEC, CATT, Nokia, Nokia Shanghai Bell, ZTE, HUAWEI | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244241 | Rel-19 pCR TR 28.858 Add use case for ML Incremental Pre-training |
pCR revised to S5-244638 |
China Mobile, ZTE | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244242 | Rel-19 pCR TR 28.858 Add Potential Solution for Fine-tuning |
pCR revised to S5-244615 |
China Mobile, ZTE | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244247 | Rel-19 pCR TR 28.858 Add solution for ML model confidence threshold |
pCR revised to S5-244826 |
Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244256 | Rel-19 pCR TR 28.858 Add possible solutions on ML entity distributed training management |
pCR revised to S5-245274 |
CATT | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
not treated | [WTS] [JSN] |
| S5-244257 | Rel-19 pCR TR 28.858 Add use case on ML entity distributed training |
pCR revised to S5-244619 |
CATT | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244290 | Rel-19 pCR TR 28.858 Add evaluation for training data statistical properties |
pCR revised to S5-244595 |
Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244295 | Rel-19 pCR TR28.858 Add requirements and solution for management of Reinforcement Learning | pCR | Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
merged | [WTS] [JSN] |
| S5-244299 | Rel-19 pCR TR28.858 Add use case and requirements for ML fallback management |
pCR revised to S5-244594 |
Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244319 | Rel-19 pCR TR 28.858 ML explainability | pCR | Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
not treated | [WTS] [JSN] |
| S5-244334 | Rel-19 pCR TR 28.858 Add requirements and solution for ML model training energy consumption |
pCR revised to S5-244604 |
Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244342 | Rel-19 pCR TR 28.858 Add use case, requirements and solution for AIML inference energy consumption |
pCR revised to S5-244605 |
Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244349 | Rel-19 pCR TR 28.858 AIML inference energy consumption-based ML model update | pCR | Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] |
| S5-244407 | Rel-19 pCR TR28.858 Add solution for ML model training for multiple contexts |
pCR revised to S5-244596 |
Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
revised | [WTS] [JSN] |
| S5-244558 | Draft TR 28.858 | draft TR | NEC | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] | |
| S5-244591 | DP for TR 28.858 clause structure | discussion | NEC, Intel | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] | |
| S5-244592 | pCR TR 28.858 add scope |
pCR revision of S5-243873 |
NEC, Intel | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244593 | pCR TR 28.858 add overview and list of references |
pCR revision of S5-243876 |
NEC, Intel | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244594 | Rel-19 pCR TR28.858 Add use case and requirements for ML fallback management |
pCR revision of S5-244299 |
Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244595 | Rel-19 pCR TR 28.858 Add evaluation for training data statistical properties |
pCR revision of S5-244290 |
Nokia Hungary, Verizon, Ericsson | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244596 | Rel-19 pCR TR28.858 Add solution for ML model training for multiple contexts |
pCR revision of S5-244407 |
Nokia Hungary, Ericsson | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244597 | DP on potential gaps in Inference management in TS 28.105 |
discussion revision of S5-243938 |
Nokia | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] | |
| S5-244598 | Rel-19 pCR TR28.858 Update R19 continuation use cases |
pCR revision of S5-243528 |
Nokia | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244599 | Rel-19 pCR TR 28.858 Enhance the ML model loading use case and solution |
pCR revision of S5-243945 |
Huawei | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244600 | Rel-19 pCR TR28.858 Conclude R19 continuation use cases |
pCR revision of S5-243529 |
Nokia | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244601 | Rel-19 pCR TR28.858 Add use case of AI emulation |
pCR revision of S5-243675 |
China Mobile | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244602 | Rel-19 pCR TR28.858 R19 Support for efficient re-training |
pCR revision of S5-243939 |
Nokia | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] |
| S5-244603 | pCR TR 28.858 Add Potential Requirements and Possible Solution for Sustainable AIML |
pCR revision of S5-243858 |
ZTE Corporation | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] |
| S5-244604 | Rel-19 pCR TR 28.858 Add requirements and solution for ML model training energy consumption |
pCR revision of S5-244334 |
Nokia, China Unicom, ZTE, Verizon, Ericsson, NEC | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244605 | Rel-19 pCR TR 28.858 Add use case, requirements and solution for AIML inference energy consumption |
pCR revision of S5-244342 |
Nokia Hungary, ZTE, Verizon, Ericsson, NEC | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244606 | pCR TR 28.858 Sustainability of AI-ML |
pCR revision of S5-243706 |
Huawei, DeuHuawei, Deutsche Telekom, Telecom Italia, Ericsson, Nokia | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244607 | pCR TR 28.858 Add Use Case and Requirements for ML Model Transfer |
pCR revision of S5-243861 |
ZTE Corporation, NEC, Ericsson | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244608 | Standardization of Federated Learning in 3GPP SA5 |
discussion revision of S5-244162 |
Ericsson-LG Co., LTD, NEC | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
endorsed | [WTS] [JSN] | |
| S5-244609 | Rel-19 pCR TR 28.858 Add use case for ML Fine-tuning |
pCR revision of S5-244240 |
China Mobile, China Unicom, Verizon, Intel, NEC, CATT, Nokia, Nokia Shanghai Bell, ZTE, HUAWEI, Ericsson | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244615 | Rel-19 pCR TR 28.858 Add Potential Solution for Fine-tuning |
pCR revision of S5-244242 |
China mobile, ZTE Corporation, NEC, Nokia, Nokia Shanghai Bell | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244616 | Rel-19 pCR TR 28.858 Add Potential Solution for Pre-training |
pCR revision of S5-244238 |
China Mobile, ZTE Corporation, NEC, Nokia, Nokia Shanghai Bell | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244617 | Collection of runtime performance KPIs for ML models |
pCR revision of S5-243564 |
AT&T | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244618 | Network Management actions in response to an underperforming ML algorithm used in a live network |
pCR revision of S5-243565 |
AT&T | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244619 | Rel-19 pCR TR 28.858 Add use case on ML entity distributed training |
pCR revision of S5-244257 |
CATT, Ericsson | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244634 | Rel-19 pCR TR 28.858 add use cases, requirements for reinforcement learning management |
pCR revision of S5-243948 |
Huawei, Samsung R&D Institute UK, Nokia, ZTE, Ericsson, NEC | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244635 | pCR TR 28.858 Add Potential Requirements and Possible Solution for Management of Reinforcement Learning | pCR | ZTE Corporation | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
withdrawn | [WTS] [JSN] |
| S5-244636 | Rel-19 pCR TR28.858 Add requirements and solution for management of Reinforcement Learning | pCR | Nokia Hungary | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
withdrawn | [WTS] [JSN] |
| S5-244637 | pCR TR 28.858 Update the UC and requirements for pre-training |
pCR revision of S5-243881 |
Intel, NEC | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244638 | Rel-19 pCR TR 28.858 Add use case for ML Incremental Pre-training |
pCR revision of S5-244241 |
China Mobile, ZTE | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] |
| S5-244639 | Rel-19 pCR 28.858 Generative AI | pCR | Samsung R&D Institute UK | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
withdrawn | [WTS] [JSN] |
| S5-244817 | pCR TR 28.858 Add use case for management of Federated Learning |
pCR revision of S5-243879 |
Intel, ZTE, Nokia, China Mobile, NEC, HUAWEI | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244826 | Rel-19 pCR TR 28.858 Add solution for ML model confidence threshold |
pCR revision of S5-244247 |
Nokia Hungary, Verizon | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
approved | [WTS] [JSN] |
| S5-244827 | TR28.858 add RAG use case in AIML Inference | pCR | Nokia, Nokia Shanghai Bell, China Unicom | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
withdrawn | [WTS] [JSN] |
| S5-244828 | Rel-19 pCR TR 28.858 Add concept of Generative AI |
pCR revision of S5-243947 |
Huawei | 28.858 0.1.0 | FS_AIML_MGT_Ph2 | Rel-19 |
S5-156 AI: 6.19.1 |
noted | [WTS] [JSN] |
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