pith:2WVDHOSV
Graph of States: Solving Abductive Tasks with Large Language Models
Graph of States uses a causal graph and state machine to guide LLMs through reliable abductive reasoning.
arxiv:2603.21250 v2 · 2026-03-22 · cs.AI
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\pithnumber{2WVDHOSVEUUYFOMW5F73ZXKO36}
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Record completeness
Claims
GoS significantly outperforms all baselines, providing a robust solution for complex abductive tasks.
That grounding multi-agent LLM collaboration in a causal graph and state machine will reliably prevent Evidence Fabrication, Context Drift, Failed Backtracking, and Early Stopping without introducing new failure modes.
GoS structures LLM reasoning with belief-state graphs and state machines to enable reliable abductive inference, outperforming baselines on two real-world datasets.
Formal links
Receipt and verification
| First computed | 2026-05-17T23:39:15.705113Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
d5aa33ba55252982b996e97fbcdd4edf91f030e93bdb9f8d690c777929feca8b
Aliases
· · · · ·Agent API
Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/2WVDHOSVEUUYFOMW5F73ZXKO36 \
| 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: d5aa33ba55252982b996e97fbcdd4edf91f030e93bdb9f8d690c777929feca8b
Canonical record JSON
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