# The 23-Stage Pipeline

Click any stage to expand its description. Yellow badges mark gate stages that require quality checks before proceeding.

A

### Research Scoping

1

#### Topic Initialization

Define research topic, scope, and target conference
Takes a user-provided topic prompt and generates a structured research plan including target conference, research questions, and expected contributions. Emphasizes novelty and alignment with recent conference trends.
LLM
2

#### Problem Decomposition

Break research into sub-problems and objectives
Decomposes the research topic into concrete sub-problems, defines evaluation criteria, and identifies the key technical challenges to address.
LLM
B

### Literature Discovery

3

#### Search Strategy

Generate search queries and select paper sources
Generates targeted search queries from the research plan, selects which APIs to query (OpenAlex, Semantic Scholar, arXiv), and defines inclusion/exclusion criteria.
LLM
4

#### Literature Collect

Search OpenAlex, Semantic Scholar, and arXiv
Executes multi-source literature search with intelligent caching, circuit breakers, and rate limiting. Deduplicates results across sources and injects seminal papers from the seed library.
API
5

#### Literature Screen

Quality and relevance screening (Gate)
Gate Stage. LLM reviews each collected paper for relevance, quality, and domain match. Cross-domain false positives are explicitly rejected. Papers below threshold are filtered out.
Gate LLM
6

#### Knowledge Extract

Extract key insights and methodologies from papers
Extracts structured knowledge from screened papers: key contributions, methods, results, limitations, and open questions. Builds a knowledge graph for synthesis.
LLM
C

### Knowledge Synthesis

7

#### Synthesis

Gap analysis and research trend synthesis
Clusters extracted knowledge by topic, identifies research gaps, and synthesizes trends. Produces a structured literature review summary that informs hypothesis generation.
LLM
8

#### Hypothesis Generation

Generate testable research hypotheses
Generates novel, testable hypotheses that address gaps not covered by existing literature. Each hypothesis includes expected outcomes, evaluation metrics, and ablation dimensions.
LLM
D

### Experiment Design

9

#### Experiment Design

Methodology design and validation (Gate)
Gate Stage. Designs the complete experimental methodology: baselines, ablations, metrics, datasets, and statistical tests. Requires modern benchmarks and real datasets (CIFAR-10, etc.).
Gate LLM
10

#### Code Generation

Generate executable experiment code
Generates complete Python experiment code (main.py) with dataset loading, model definition, training loop, evaluation, and results output. Includes security validation, import checking, and code review.
LLM New
11

#### Resource Planning

Estimate compute budget and time allocation
Estimates GPU memory requirements, training time, and compute budget. Configures Docker sandbox resource limits and timeout values based on available hardware.
LLM
E

### Experiment Execution

12

#### Experiment Run

Execute experiments in Docker sandbox
Runs generated code inside an isolated Docker container with NVIDIA GPU passthrough. Captures stdout metrics, timing data, and exit codes. Pre-cached datasets available at /workspace/data.
Docker
13

#### Iterative Refinement

Fix errors and improve experiment code
If experiment fails or produces poor results, automatically diagnoses issues and generates refined code. Checks ablation effectiveness (>5% difference from baseline). Up to 3 refinement iterations.
LLM Docker New
F

### Analysis & Decision

14

#### Result Analysis

Statistical analysis of experiment outcomes
Parses experiment outputs, computes statistical significance, generates comparison charts, and produces structured results summaries. Detects result contradictions and null findings.
LLM
15

#### Research Decision

Pivot, refine, or proceed based on results
Evaluates experiment results and decides: Proceed (results support hypothesis), Refine (re-run with improvements), or Pivot (discard hypothesis, generate new one). Max 2 pivots to prevent infinite loops.
LLM
G

### Paper Writing

16

#### Paper Outline

Structure paper sections and arguments
Creates a detailed paper outline with section-by-section arguments, key claims, and figure placements. Follows conference template structure (abstract, intro, related work, method, experiments, conclusion).
LLM
17

#### Paper Draft

Write the full paper draft
Generates the complete paper in Markdown/LaTeX with structured writing rules: 150-200 word abstract, no number repetition across sections, proper citation of original papers for all discussed techniques.
LLM
18

#### Peer Review

Multi-agent simulated conference review
Multiple LLM reviewer personas evaluate the paper: one technical reviewer, one methodology expert, and one clarity/presentation reviewer. Each provides structured feedback with scores.
LLM
19

#### Paper Revision

Revise based on peer review feedback
Addresses reviewer comments systematically: fixes technical issues, improves writing clarity, adds missing comparisons, and strengthens the narrative. Produces a revised draft.
LLM New
H

### Finalization

20

#### Quality Gate

Final quality assessment (Gate)
Gate Stage. Comprehensive quality assessment scoring the paper on novelty, soundness, significance, clarity, and reproducibility. Papers below threshold are sent back for rewriting.
Gate LLM
21

#### Knowledge Archive

Archive findings to knowledge base
Stores research findings, methodology, and results in the persistent knowledge base for future reference and cross-project knowledge transfer. Non-critical: failure doesn't abort pipeline.
LLM
22

#### Export & Publish

Generate LaTeX PDF and final output
Converts the paper to conference-ready LaTeX, compiles to PDF, generates BibTeX bibliography, and produces the final output package (paper.pdf, main.tex, references.bib, charts/).
LaTeX
23

#### Citation Verify

Verify all citations against real databases
Verifies every cited paper exists in real academic databases. Checks DOI via CrossRef, title via OpenAlex, arXiv ID via arXiv API, and falls back to Semantic Scholar. Non-critical: failure doesn't abort pipeline.
API