The reviewed record of science sign in
Pith
Pith Number

pith:W7HUX3ZE

pith:2021:W7HUX3ZEAPLD5ZGDW3P7DG23WO
not attested not anchored not stored refs resolved

Bridge Data: Boosting Generalization of Robotic Skills with Cross-Domain Datasets

Bernadette Bucher, Chelsea Finn, Frederik Ebert, Georgios Georgakis, Karl Schmeckpeper, Kostas Daniilidis, Sergey Levine, Yanlai Yang

A shared multi-task multi-domain robot dataset doubles success rates for new tasks in new environments when added to just 50 demonstrations.

arxiv:2109.13396 v1 · 2021-09-27 · cs.RO · cs.AI

Open paper page JSON Open Graph Bundle Merged state Verified badge What is a Pith Number?
Add to your LaTeX paper 
\usepackage{pith}
\pithnumber{W7HUX3ZEAPLD5ZGDW3P7DG23WO}

Prints a linked badge after your title and injects PDF metadata. Compiles on arXiv. Learn more · Embed verified badge

Record completeness

1 Bitcoin timestamp
2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
✓ Portable graph bundle live · download bundle · merged state
The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

jointly training with the proposed dataset and 50 demonstrations of a never-before-seen task in a new domain on average leads to a 2x improvement in success rate compared to using target domain data alone

C2weakest assumption

That the collected tasks and domains are representative enough that cross-domain data produces positive transfer rather than interference for arbitrary new tasks and environments.

C3one line summary

A large multi-task multi-domain robot dataset combined with 50 new demonstrations yields 2x higher success rates on never-before-seen tasks in new domains.

References

28 extracted · 28 resolved · 2 Pith anchors

[1] Imagenet classifica- tion with deep convolutional neural networks 2012
[2] BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding 2018 · arXiv:1810.04805
[3] Imagenet: A large-scale hierarchical image database 2009
[4] Gradient surgery for multi-task learning 2001
[5] Mt-opt: Continuous multi-task robotic reinforcement learning at scale 2021

Formal links

2 machine-checked theorem links

Cited by

53 papers in Pith

FlowDPG: Deterministic Policy Gradient on Flow Matching Policies for Real-World Manipulation
ZeroDex: Zero-Shot Long-Horizon Dexterous Manipulation via Multi-View 3D-Grounded VLM Reasoning
Mem-World: Memory-Augmented Action-Conditioned World Models for Persistent Robot Manipulation
RoboTacDex: A Dexterous Visual-Tactile-Action Dataset for Humanoid Manipulation
SAFE-Pruner: Semantic Attention-Guided Future-Aware Token Pruning for Efficient Vision-Language-Action Manipulation
Receipt and verification
First computed 2026-07-05T03:18:02.296857Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

b7cf4bef2403d63ee4c3b6dff19b5bb392960124d2610daa45682ef6293801f8

Aliases

arxiv: 2109.13396 · arxiv_version: 2109.13396v1 · doi: 10.48550/arxiv.2109.13396 · pith_short_12: W7HUX3ZEAPLD · pith_short_16: W7HUX3ZEAPLD5ZGD · pith_short_8: W7HUX3ZE
Agent API
Resolver JSON Graph JSON Events JSON Schema Signing key
Verify this Pith Number yourself 
curl -sH 'Accept: application/ld+json' https://pith.science/pith/W7HUX3ZEAPLD5ZGDW3P7DG23WO \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: b7cf4bef2403d63ee4c3b6dff19b5bb392960124d2610daa45682ef6293801f8
Canonical record JSON 
{
  "metadata": {
    "abstract_canon_sha256": "d64a0c5131cb832077a8388f095a6403844f9cc0e1337b66058bbb17f28f9942",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2021-09-27T23:42:12Z",
    "title_canon_sha256": "77553db0d2eb8301edb63c8be3ac05770fc7f85bfd9e98af11142622cb1e35e7"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2109.13396",
    "kind": "arxiv",
    "version": 1
  }
}