Together, these layers aim to keep the system’s behavior within a , even as its competencies expand.
If you want, I can provide: a sample minimal inference pipeline (code) for ONNX/TensorRT, a quantization recipe, or a compact fine-tuning plan for a specific domain—tell me which. midv-615
| What I need to know | Why it matters | |----------------------|----------------| | (e.g., “MidV‑615: Emerging Trends in Virtual Reality for Healthcare”) | Determines the focus of the research questions, literature, and arguments. | | Paper type (research article, literature review, position paper, case study, etc.) | Guides the structure and the amount of original data vs. synthesis. | | Length / Word count (e.g., 2 500 words, 10‑page double‑spaced) | Affects how deep you can go into each section and how many sub‑headings you’ll need. | | Target audience / venue (undergraduate class, conference submission, journal, etc.) | Influences tone, level of technical detail, and citation style. | | Citation style (APA, IEEE, Chicago, etc.) | Determines formatting of references and in‑text citations. | | Key requirements (e.g., must include a methods section, need at least 8 peer‑reviewed sources) | Ensures we meet the assignment rubric. | | Deadline | Helps prioritize what to flesh out first. | Together, these layers aim to keep the system’s