EdmondValar/robotics-papers-vecdb
Robotics Papers Vector Database Semantic search over 63,381 academic papers from 30 conference-year combinations in robotics, CV, and ML. Contents Embeddings: BAAI/bge-m3 (1024 dimensions) via SiliconFlow Conferences: CoRL, CVPR, ECCV, ICCV, ICLR, ICML, ICRA, IROS, NeurIPS, RSS, WACV (2023-2026) Fields: title, abstract, author, conference, year, arxiv, github, citations, keywords Format: LanceDB (compacted, single fragment) Usage… See the full description on the dataset page: https://huggingface.co/datasets/EdmondValar/robotics-papers-vecdb.
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Robotics Papers Vector Database
Semantic search over 63,381 academic papers from 30 conference-year combinations in robotics, CV, and ML.
Contents
- Embeddings: BAAI/bge-m3 (1024 dimensions) via SiliconFlow
- Conferences: CoRL, CVPR, ECCV, ICCV, ICLR, ICML, ICRA, IROS, NeurIPS, RSS, WACV (2023-2026)
- Fields: title, abstract, author, conference, year, arxiv, github, citations, keywords
- Format: LanceDB (compacted, single fragment)
Usage
Remote query (no download needed)
import lancedb
db = lancedb.connect("hf://datasets/Litian2002/robotics-papers-vecdb/lancedb")
table = db.open_table("papers")
print(f"Papers: {table.count_rows()}")
# Semantic search (requires embedding your query first)
# See the companion repo for the full search pipelineLocal usage
git clone https://huggingface.co/datasets/Litian2002/robotics-papers-vecdb
# or use huggingface_hub to downloadWith vec-db CLI
# Clone the tool repo
git clone <vec-db-repo-url>
cd vec-db
VECDB_LANCE_DIR=/path/to/downloaded/lancedb npx tsx src/cli.ts search "robot grasping"