Pith Number

pith:XBEJZENZ

pith:2026:XBEJZENZKFYYM2QOCNI5V63AOS

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Exploring Lightweight Large Language Models for Court View Generation

Kun Zeng, Nanli Zeng, Tianyong Hao, Zhitian Hou, Zhixiong Chao

Lightweight LLMs under 2 billion parameters generate court views from case facts and support charge prediction with competitive results against DNNs.

arxiv:2605.16770 v1 · 2026-05-16 · cs.CL · cs.AI

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\pithnumber{XBEJZENZKFYYM2QOCNI5V63AOS}

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2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications 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

Experimental results provide new insights into the trade-offs between model architecture, model size, and the influence between different tasks, highlighting the potential of lightweight LLMs in judicial AI applications.

C2weakest assumption

That training on a mixed dataset from multiple sources and evaluating on individual test sets produces fair, generalizable comparisons without significant domain shift or distribution mismatch biasing the architecture and size effects.

C3one line summary

Lightweight LLMs are benchmarked for court view generation and charge prediction across architectures, sizes, DNN comparisons, and task ordering on three datasets using the new CVGEvalKit framework.

References

22 extracted · 22 resolved · 5 Pith anchors

[1] arXiv preprint arXiv:2509.09969 , year=

[2] 2024 International Joint Conference on Neural Networks (IJCNN) , pages= 2024

[3] 2024 International Joint Conference on Neural Networks (IJCNN) , pages= 2024

[4] 2024 International Joint Conference on Neural Networks (IJCNN) , pages= 2024

[5] Interpretable Charge Predictions for Criminal Cases: Learning to Generate Court Views from Fact Descriptions · arXiv:1802.08504

Receipt and verification

First computed	2026-05-20T00:03:21.050047Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

b8489c91b95171866a0e1351dafb6074875adb91ac9c042577a5778cc8ebb068

Aliases

arxiv: 2605.16770 · arxiv_version: 2605.16770v1 · doi: 10.48550/arxiv.2605.16770 · pith_short_12: XBEJZENZKFYY · pith_short_16: XBEJZENZKFYYM2QO · pith_short_8: XBEJZENZ

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Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/XBEJZENZKFYYM2QOCNI5V63AOS \
  | 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: b8489c91b95171866a0e1351dafb6074875adb91ac9c042577a5778cc8ebb068

Canonical record JSON

{
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    "abstract_canon_sha256": "9b03b1fad8d7d1605a205e230fd31d2c7a7d56543fe7ca23a8fe4d1f6ac0e536",
    "cross_cats_sorted": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.CL",
    "submitted_at": "2026-05-16T02:44:32Z",
    "title_canon_sha256": "dea59d1b818dfa16b43ada94cc95b2c81b22d22c39a484b5484fd26120dd7d21"
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  "source": {
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    "kind": "arxiv",
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