pith. sign in
Pith Number

pith:YC2DF4WR

pith:2026:YC2DF4WR42EPUUAYW5SKMHLLSS
not attested not anchored not stored refs resolved

Distill: Uncovering the True Intent behind Human-Robot Communication

David Porfirio, Ting Li

Distill refines initial robot task specifications by removing steps, generalizing meanings, and relaxing order constraints to better match users' true intent.

arxiv:2605.14262 v1 · 2026-05-14 · cs.RO · cs.HC

Add to your LaTeX paper
\usepackage{pith}
\pithnumber{YC2DF4WR42EPUUAYW5SKMHLLSS}

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

We implemented Distill on a web interface and, through a crowdsourcing study, demonstrated its ability to elicit and refine user intent from initial task specifications.

C2weakest assumption

That the three operations of removing steps, generalizing meanings, and relaxing ordering constraints accurately uncover and preserve the user's true underlying intent without introducing distortions or requiring additional user feedback.

C3one line summary

Distill refines user task specifications for robots by pruning unnecessary steps, generalizing meanings, and relaxing order constraints, as demonstrated in a crowdsourcing study on a web interface.

References

66 extracted · 66 resolved · 1 Pith anchors

[1] [n. d.]. LimeZu. https://limezu.itch.io/. Accessed: 2026-04-25 2026
[2] Gopika Ajaykumar, Maureen Steele, and Chien-Ming Huang. 2021. A survey on end-user robot programming.ACM Computing Surveys (CSUR)54, 8 (2021), 1–36. doi:10.1145/3466819 2021 · doi:10.1145/3466819
[3] Sonya Alexandrova, Zachary Tatlock, and Maya Cakmak. 2015. RoboFlow: A flow-based visual programming language for mobile manipulation tasks. In2015 IEEE international conference on robotics and automa 2015 · doi:10.1109/icra.2015.7139973
[4] Bennett, Kori Inkpen, Jaime Teevan, Ruth Kikin-Gil, and Eric Horvitz 2019 · doi:10.1145/3290605.3300233
[5] Virginia Braun and Victoria Clarke. 2021. Thematic analysis: A practical guide. (2021) 2021

Formal links

2 machine-checked theorem links

Receipt and verification
First computed 2026-05-17T23:39:10.473718Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

c0b432f2d1e688fa5018b764a61d6b9490983a2520418fdc9c617314bd4baac1

Aliases

arxiv: 2605.14262 · arxiv_version: 2605.14262v1 · doi: 10.48550/arxiv.2605.14262 · pith_short_12: YC2DF4WR42EP · pith_short_16: YC2DF4WR42EPUUAY · pith_short_8: YC2DF4WR
Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/YC2DF4WR42EPUUAYW5SKMHLLSS \
  | 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: c0b432f2d1e688fa5018b764a61d6b9490983a2520418fdc9c617314bd4baac1
Canonical record JSON
{
  "metadata": {
    "abstract_canon_sha256": "e853514525568f2fac9131f95d7718417706c7bf5e8feafb8924ca7cf8c2a6a8",
    "cross_cats_sorted": [
      "cs.HC"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.RO",
    "submitted_at": "2026-05-14T02:05:49Z",
    "title_canon_sha256": "1e48279d5669a23e5640225cb25e0a60e8ad9fb010fbadd28d3208e086e7d668"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.14262",
    "kind": "arxiv",
    "version": 1
  }
}