Summary Report of the 6th Cloud Intelligence / AIOps Workshop 2025
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The International Workshop on Cloud Intelligence / AIOps is a forum for researchers, scientists, engineers, and practitioners to share and learn AI/ML powered DevOps solutions for cloud services. The workshop was inaugurated at AAAI'20 and has been hosted at ICSE, MLSys, and ASPLOS conferences with intention to bring technical leaders in AI, Software Engineering, and Systems together to tackle challenges in design, building, and operating cloud service. The 6th International workshop on Cloud Intelligence / AIOps was successfully hosted as an in-person event in conjunction with the 47th International Conference of Software Engineering (ICSE'25) on May 3rd, 2025 at Ottawa, Canada. The workshop received 10 submitted papers, from which 6 papers were accepted including 5 technical papers and 1 project showcase.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it