[Model Submission] Nexus-Pilot
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- Dominant language
- Python
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Description
Model Name
Nexus-Pilot
Model Overview
Nexus-Pilot is an experimental prompt-layered conversational agent designed to explore structured proposal generation and meta-evaluation using a proprietary large language model (100B+ scale). It does not rely on fine-tuning, and instead uses a multi-stage prompt chaining mechanism (Intent → Suggestion → Evaluation).
- OpenAI Chat API-compatible
- Single-turn and multi-turn capable
- All outputs are generated through prompt logic, not architectural modifications
Model Type
Proprietary LLM (not fine-tuned, prompt-engineered only)
Training Data
Not disclosed. The underlying LLM is private and does not share architecture or data provenance. No public datasets are used directly in inference.
Intended Use
Evaluation of proposal-generation strategies in multi-turn conversational settings. Academic and commercial R&D contexts.
Limitations
- The agent does not contain domain-specific optimization.
- All behaviors are prompt-driven; factuality and consistency may vary depending on the prompt chain.
License
Apache 2.0 (for the prompt agent wrapper code)
Source Code
https://github.com/nexus-core-jp/nexus-pilot
Contact
@nexus-core-jp
Notes
This model does not reveal its backend structure intentionally. It is designed for interface-level evaluation, and the LLM provider is not disclosed.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
The issue provides model metadata and a source repository but names no FastChat file, test, or entry point to update. First identify how FastChat records submitted models and where this model should be registered; done means the submission is represented according to that project’s existing model records and checks pass.
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Assessment
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100