Datasets:

cjc0013
/

ArxivFusedWithPatents

The pipeline is fully deterministic from ingest through release and is designed to run end-to-end without manual curation or mid-run intervention. All artifacts, cluster assignments, and release decisions are derived from the same run.

This is not a curated dataset. It is a large-scale fused technical corpus that has been deterministically analyzed and quality-gated to isolate the portion that behaves like a semantic clustering dataset.

Key Stats

Total labeled rows: 9,063,272
Raw clusters (pre-filter): 422
Release clusters (post-filter): 147
Retained rows: 3,881,329
Retention rate: 42.82%
Shards: 91 (labels / embeddings / chunks)
Size: ~20+ GB compressed

Pipeline Summary

The dataset was produced by a staged, resumable pipeline with Postgres acting as a control plane.

Core stages

Ingest and normalize fused patent + arXiv text
Chunk-level embedding
Embedding clustering
Shard-level processing with persistent state
Reducer-tree merge into global clusters
Global assignment + BM25 artifact generation
Deterministic inspection and release gating

System Design

The pipeline is built to operate under real constraints (long runtimes, memory pressure, interruptions), not ideal notebook conditions.

Control plane (Postgres)

Task leasing and discovery
Heartbeats and worker liveness
Stage state tracking (not-ready / running / done / failed)
Reducer-tree coordination and staged unblocking

Failure-aware execution

Distinguishes between:
- true OOM
- bad allocation
- killed process
- general memory pressure
Descending batch ladder (deterministic step-down on failure)
Proactive downshifting based on resource pressure
Resumable state across interruptions

Reducer-tree merge

Progressive level-by-level reduction
Final stage unblocked only after upstream completion
Prevents global merge bottlenecks
Avoids downstream fan-out gaps

Deterministic Quality Gating

The raw clustering output was not treated as valid by default.

A full deterministic inspection pass across all 422 clusters produced:

147 coherent clusters
107 mixed clusters
168 metadata-heavy clusters

Filtering decision

For the release dataset:

Kept: coherent clusters only
Dropped: mixed + metadata-heavy clusters

This was done without:

re-embedding
hand labeling
manual cluster editing
modifying the original run

All decisions are reproducible from pipeline outputs.

Metadata Leakage

A large portion of clusters were dominated by ingestion or wrapper fields such as:

source_file
record_hash
raw_meta_json
authors_parsed
published_date
similar structural tokens

These are not errors in the source data, but they degrade semantic clustering if left unfiltered.

Explicit detection and removal of these clusters is a core part of the release process.

Dataset Structure

The release package includes filtered artifacts aligned to the retained clusters:

labels/ — cluster assignments
chunks/ — source text chunks
embeddings/ — embedding vectors
microclusters/ — original microcluster outputs (for provenance)
global/ — cluster summaries, BM25 artifacts, reference data

All components are consistent with the same filtered subset.

What This Dataset Is

A deterministically derived technical clustering dataset
A fused patent + research corpus with broad technical coverage
A quality-gated subset of a larger clustering run
A reproducible artifact tied to a single pipeline execution

What This Dataset Is Not

Not manually curated
Not hand-labeled
Not cleaned via ad-hoc scripts
Not a “perfect” semantic dataset
Not independent from its pipeline (the pipeline defines it)

Example Cluster Themes

Cluster naming was derived deterministically from top terms. Example themes include:

wireless communication systems
semiconductor substrates and layers
chemical compounds and formulations
neural networks and data processing
vehicle control systems
signal processing and circuits

Intended Use

Retrieval / RAG experiments
Technical topic clustering
Cross-domain similarity analysis
Large-scale embedding evaluation
Downstream filtering / refinement pipelines

Notes

This dataset represents the release-grade subset of the full run. The original unfiltered output (422 clusters) is intentionally not presented as the primary artifact.