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pith:QWHABWM5

pith:2026:QWHABWM5WU2ONX3LANLUMMT6G5
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Self-Consistency from Only Two Samples: CoT-PoT Ensembling for Efficient LLM Reasoning

Majd Hawasly, Md Rizwan Parvez, Mohammad Raza, Raman Saparkhan

CoT-PoT ensembling cuts the samples needed for LLM self-consistency by 9.3 times while raising accuracy.

arxiv:2604.17433 v2 · 2026-04-19 · cs.CL · cs.AI · cs.LG

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Claims

C1strongest claim

CoT-PoT ensembling not only improves overall accuracy, but also drastically reduces the number of samples required for SC by a factor of 9.3x. In particular, the majority of tasks (78.6%) can be addressed with only two samples, which has not been possible with any prior SC methods.

C2weakest assumption

The assumption that Chain-of-Thought and Program-of-Thought outputs are sufficiently complementary and that their agreement reliably indicates correctness without needing many more samples or introducing new error modes; this is implicit in the early-stopping and ensembling strategies described.

C3one line summary

CoT-PoT ensembling achieves self-consistency accuracy in LLMs with only two samples for 78.6% of tasks, reducing computation by 9.3x compared to standard methods.

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First computed 2026-06-08T01:04:05.108686Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

858e00d99db534e6df6b035746327e3753e2c8efbcd59aafd69fe45a91df95c5

Aliases

arxiv: 2604.17433 · arxiv_version: 2604.17433v2 · doi: 10.48550/arxiv.2604.17433 · pith_short_12: QWHABWM5WU2O · pith_short_16: QWHABWM5WU2ONX3L · pith_short_8: QWHABWM5
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/QWHABWM5WU2ONX3LANLUMMT6G5 \
  | 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: 858e00d99db534e6df6b035746327e3753e2c8efbcd59aafd69fe45a91df95c5
Canonical record JSON
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