EvoClaw Novelty Classifier (Meta-Control Layer)
Overview
Overstating novelty wastes months of work on a paper that will be rejected. This skill forces honest classification of the contribution type and innovation degree, then checks alignment with the target venue.
Core principle: Classify honestly, match realistically.
Violating the letter of this rule is violating the spirit of this rule.
The Iron Law
CLASSIFY NOVELTY HONESTLY. DO NOT OVERSTATE. VENUE MISMATCH IS CAUGHT HERE, NOT AT REVIEW TIME.
When This Runs
- After Phase 1 (literature review): Preliminary classification — is the proposed direction novel enough for the target venue?
- After Phase 3 (method design): Final classification — does the concrete method meet the novelty bar?
If classification downgrades between Phase 1 and Phase 3, WARN the user immediately.
Classification Flow
digraph novelty_classifier {
rankdir=TB;
start [label="Contribution\ndefined" shape=doublecircle];
type [label="Classify\ncontribution type" shape=box];
degree [label="Assess\ninnovation degree" shape=box];
check [label="Venue tier\nalignment?" shape=diamond];
pass [label="Aligned\nProceed" shape=box style=filled fillcolor="#d4edda"];
warn [label="Mismatch\nWARN user" shape=box style=filled fillcolor="#f8d7da"];
decide [label="User decides:\nadd depth / retarget / proceed" shape=diamond];
start -> type;
type -> degree;
degree -> check;
check -> pass [label="matches"];
check -> warn [label="insufficient"];
warn -> decide;
}
Step 1 — Contribution Type Classification
| Type | Description | Example |
|---|---|---|
| New Problem | First to formulate this problem | Defining few-shot learning |
| New Method | Novel algorithm or architecture | Transformer architecture |
| New Theory | Theoretical advance | PAC learning bounds |
| New Data/Benchmark | New dataset or evaluation standard | ImageNet |
| Engineering Integration | Combining existing techniques | Adding attention to existing model |
Classify the contribution into exactly one primary type. If it spans two, pick the stronger one and note the secondary.
Step 2 — Innovation Degree Assessment
| Degree | Definition |
|---|---|
| Foundational | Opens a new research direction |
| Significant improvement | Clear advance over SOTA with novel insight |
| Incremental improvement | Modest advance, refines existing approach |
| Combination/Engineering | Assembles known parts in new configuration |
Be precise. "Significant" requires a novel insight, not just better numbers.
Step 3 — Venue-Innovation Alignment Check
| Venue Tier | Minimum Innovation |
|---|---|
| A (NeurIPS/ICML/Nature) | New method with significant insight, or foundational |
| B (AAAI/IJCAI/domain top) | Significant improvement or meaningful combination with strong experiments |
| C (workshops/lower journals) | Incremental improvement with solid experiments |
Warning Rules
- Engineering Integration + Tier A target → WARN: "This may not have sufficient novelty for [venue]. Consider: (a) identify a deeper insight, (b) add theoretical analysis, (c) target Tier B venue."
- Incremental improvement + Tier A target → WARN with same options.
- Scale-up / backbone swap / hyperparameter tuning only → HARD WARNING: "This is not a research contribution. It is engineering. Redefine the contribution or kill the submission."
Warnings are presented to the user. The agent does not suppress them.
Red Flags — STOP
- Classifying engineering work as "novel method"
- Claiming foundational novelty without a new problem formulation
- Skipping this check to avoid uncomfortable results
- Upgrading classification between runs without new evidence
- Targeting Tier A with incremental work and no theoretical backing
Rationalization Prevention
| Excuse | Reality |
|---|---|
| "Our combination is novel" | Is the insight novel, or just the combination? Reviewers will ask. |
| "No one has done exactly this" | Exact novelty ≠ meaningful novelty. What new insight does it provide? |
| "The experiments will show it's better" | Better results from engineering ≠ scientific contribution. |
| "We can frame it as novel" | Framing doesn't survive peer review. Real novelty does. |
The Bottom Line
Honest classification now → correct venue targeting → accepted paper
Inflated classification now → months of work → desk rejection
Classify honestly. Match realistically. Correct course early.