Pith Number

pith:K6E2MM5D

pith:2026:K6E2MM5DZE7AANNQEGZHTOD7SM

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Teaching and Evaluating LLMs to Reason About Polymer Design Related Tasks

Benjamin Hsiao, Dikshya Mohanty, Mohammad Saqib Hasan, Niranjan Balasubramanian, Size Zheng, Syed Mostofa Monsur

Small language models trained on PolyBench match or beat larger models on polymer design reasoning tasks.

arxiv:2601.16312 v2 · 2026-01-22 · cs.CL · cs.AI

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Record completeness

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4 Citations open

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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

small language models (SLMs) with 7B to 14B parameters, trained on PolyBench, outperform similar-sized models and remain competitive with closed-source frontier LLMs on PolyBench's test dataset, while demonstrating performance gains on external polymer benchmarks.

C2weakest assumption

The tasks in PolyBench and the underlying knowledge base of 13 million data points accurately represent the knowledge and reasoning demands of real-world polymer design without major gaps, biases, or inaccuracies from the experimental and synthetic sources.

C3one line summary

Small 7B-14B parameter language models trained on the new PolyBench dataset for polymer design tasks outperform similar-sized models and compete with large frontier LLMs while improving on external benchmarks.

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-17T23:39:00.199888Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

5789a633a3c93e0035b021b279b87f93019e84449256715f416c0bebda3274fe

Aliases

arxiv: 2601.16312 · arxiv_version: 2601.16312v2 · doi: 10.48550/arxiv.2601.16312 · pith_short_12: K6E2MM5DZE7A · pith_short_16: K6E2MM5DZE7AANNQ · pith_short_8: K6E2MM5D

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/K6E2MM5DZE7AANNQEGZHTOD7SM \
  | 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: 5789a633a3c93e0035b021b279b87f93019e84449256715f416c0bebda3274fe

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "67d42ed87e302305fc5f7a16d7d99301ce1c15dbaa41f7aaddf44b6b7bd6a9d3",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-01-22T20:39:18Z",
    "title_canon_sha256": "690891f005264361c851591daaa8434dba4a55cccd41566ee0e0daa257756ebb"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2601.16312",
    "kind": "arxiv",
    "version": 2
  }
}