[logseq-plugin-git:commit] 2026-01-16T09:39:04.335Z

This commit is contained in:
2026-01-16 10:39:04 +01:00
parent 41561cfdf5
commit 9f083dc265
5 changed files with 9 additions and 9 deletions
+6
View File
@@ -237,4 +237,10 @@
todoist-project:: #✏️ PAPERS
todoist-due:: 2026-01-17
todoist-desc:: WebLink: [Outlook](https://outlook.office365.com/owa/?ItemID=AAMkADM1NGNiNjk0LTY0ZGUtNDgzOC04MDM5LWNhODNkYWNjNjU4YwBGAAAAAACT6qp78kRgRKuUMBdWEga%2FBwCOhWlC8F7PRKzlljZYZYQmAAAAAAEMAACOhWlC8F7PRKzlljZYZYQmAAiaRHodAAA%3D&exvsurl=1&viewmodel=ReadMessageItem) Email Content Summary: - Initial impression and feedback request on the draft. - Recognize lack of extensive data on case study part, no certifiable evidence available. - Suggestion to clarify the exploratory nature of data and possibly cut detailed parts accordingly. - Latex file hosted on Overleaf to be shared later. - Reference to using IEEE software standards; draft might need trimming or condensing. - Discussion about restructuring submission plans due to draft length. - Deep review and improved figures needed, specifically on asymmetry and traceability matrix analysis. - Deadline implied: review needed by weekend (from email dated 14 Jan 2026). Action Points Extracted: 1. Share Overleaf latex file. 2. Review draft for trimming or condensing. 3. Clarify exploratory nature of case study data. 4. Discuss and possibly revise submission plans based on draft length. 5. Revise and improve figures. 6. Analyze traceability matrix deeply. 7. Complete review by the weekend of 17 January 2026.
todoist-status:: ◼️
- [[2026-01-17]] Item shared with you: FSE2026-MachineUnlearning.drawio
todoist-id:: [6fmQrh84v35wwmrg](https://todoist.com/showTask?id=6fmQrh84v35wwmrg)
todoist-project:: #✏️ PAPERS
todoist-due:: 2026-01-17
todoist-desc:: ✉: https://s.diruscio.org/Qg0bc 📱: https://s.diruscio.org/k9ICr Sender: "Phuong Nguyen (via Google Drive)" <drive-shares-dm-noreply@google.com> Sent: Thu Jan 15 2026 15:32:35 GMT+0100 (Central European Standard Time) --- I've shared an item with you: FSE2026-MachineUnlearning.drawio https://drive.google.com/file/d/14NA2GwzfRVG2xi2krsIYLXZIMNXxrnmZ/view?usp=sharing&ts=6968fa83 It's not an attachment it's stored online. To open this item, just click the link above. Hi All, I shared with you the source of the figures for our FSE 2026 paper. ---
todoist-status:: ◼️