Pith Number

pith:3GM4RFGA

pith:2026:3GM4RFGAGFGAC5TWUXX5BHCWO4

not attested not anchored not stored refs pending

How to Guide Your Flow: Few-Step Alignment via Flow Map Reward Guidance

Jerry Y. Huang, Justin Lin, Kartik Nair, Nicholas M. Boffi, Sheel Shah

Reformulating guidance as deterministic optimal control lets the flow map steer trajectories to rewards in a single pass.

arxiv:2604.27147 v2 · 2026-04-29 · cs.LG · cs.AI

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\usepackage{pith}
\pithnumber{3GM4RFGAGFGAC5TWUXX5BHCWO4}

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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

FMRG matches or surpasses baselines across inverse problems, style transfer, human preferences, and VLM rewards with as few as 3 NFEs, giving at least an order-of-magnitude speedup in comparison to prior state of the art.

C2weakest assumption

The deterministic optimal control reformulation of the guidance problem remains accurate and useful when discretized to very few steps and when the flow map is applied directly without additional approximation error or training.

C3one line summary

FMRG is a training-free, single-trajectory guidance method for flow models derived from optimal control that achieves strong reward alignment with only 3 NFEs.

Cited by

2 papers in Pith

Flow Map Denoisers: Traversing the Distortion-Perception Plane for Inverse Problems

Diffusion-Based Posterior Sampling: A Feynman-Kac Analysis of Bias and Stability

Receipt and verification

First computed	2026-05-21T01:04:26.515890Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

d999c894c0314c017676a5efd09c56770643adcf68f4025a59e700f8b8a70935

Aliases

arxiv: 2604.27147 · arxiv_version: 2604.27147v2 · doi: 10.48550/arxiv.2604.27147 · pith_short_12: 3GM4RFGAGFGA · pith_short_16: 3GM4RFGAGFGAC5TW · pith_short_8: 3GM4RFGA

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/3GM4RFGAGFGAC5TWUXX5BHCWO4 \
  | 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: d999c894c0314c017676a5efd09c56770643adcf68f4025a59e700f8b8a70935

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "e5d90b16e5401c58e65b5807a6d45f1d2793580e11b4b4859aab0e6d9bceeefb",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-04-29T19:56:53Z",
    "title_canon_sha256": "3e507dbcf04cafc1041733300149f26b66da165b267a75b89b379adfd41b4525"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2604.27147",
    "kind": "arxiv",
    "version": 2
  }
}