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pith:RGCV7AB6

pith:2026:RGCV7AB6DNP3HPOEX3I2HOWISI
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RouteProfile: Graph-Based Profiling for Cold-Start LLM Routing

Ge Liu, Haozhen Zhang, Hongji Pu, Jiaxuan You, Jingjun Xu, Tao Feng

Structured profiles for LLM capabilities outperform flat ones in routing tasks and improve generalization to new models.

arxiv:2605.00180 v2 · 2026-04-30 · cs.NI · cs.CL

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Claims

C1strongest claim

Through systematic evaluation across three representative routers under both standard and new-LLM generalization settings, we show that: (1) structured profiles consistently outperform flat ones; (2) query-level signals are more reliable than coarse domain-level signals; and (3) generalization to newly introduced models benefits most from structured profiles under trainable configurations.

C2weakest assumption

That evaluations on three routers and the chosen standard plus generalization settings are representative enough to elucidate the full design space and apply to other routing systems and LLMs.

C3one line summary

RouteProfile organizes LLM profile design into organizational form, representation type, aggregation depth, and learning configuration, with evaluations showing structured profiles outperform flat ones and aid generalization to new models.

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First computed 2026-05-28T01:04:41.192497Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

89855f803e1b5fb3bdc4bed1a3bac8923744fcd402c085a3165d3a5354309920

Aliases

arxiv: 2605.00180 · arxiv_version: 2605.00180v2 · doi: 10.48550/arxiv.2605.00180 · pith_short_12: RGCV7AB6DNP3 · pith_short_16: RGCV7AB6DNP3HPOE · pith_short_8: RGCV7AB6
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/RGCV7AB6DNP3HPOEX3I2HOWISI \
  | 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())"
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Canonical record JSON
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    "license": "http://creativecommons.org/licenses/by/4.0/",
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    "submitted_at": "2026-04-30T19:56:08Z",
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