pith:6RVGS7X3
Render-of-Thought: Rendering Textual Chain-of-Thought as Images for Visual Latent Reasoning
Rendering chain-of-thought steps as images compresses reasoning tokens by 3-4x in language models.
arxiv:2601.14750 v4 · 2026-01-21 · cs.CL · cs.CV
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Claims
we introduce Render-of-Thought (RoT), the first framework to reify the reasoning chain by rendering textual steps into images, making the latent rationale explicit and traceable... achieves 3-4x token compression and substantial inference acceleration compared to explicit CoT... maintains competitive performance
leverage the vision encoders of existing Vision Language Models (VLMs) as semantic anchors to align the vision embeddings with the textual space without incurring additional pre-training overhead
RoT renders CoT reasoning text as images and aligns them via VLM vision encoders to achieve 3-4x token compression and faster inference with competitive accuracy.
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| First computed | 2026-06-02T01:04:15.471492Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
f46a697efb419bbb8c9ba24d889b5902c337566ac46983c39be9b829b5a2ff63
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· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/6RVGS7X3IGN3XDE3UJGYRG2ZAL \
| 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: f46a697efb419bbb8c9ba24d889b5902c337566ac46983c39be9b829b5a2ff63
Canonical record JSON
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