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pith:2026:5MYS7Y3PLFIZRWA5GUVQGS7USA
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GraphWalker: Patient Analogy Meets Information Gain for Clinical Reasoning with Large Language Models

Hongxin Ding, Jiaran Gao, Jinyang Zhang, Junfeng Zhao, Liantao Ma, Weibin Liao, Xinke Jiang, Yasha Wang, Yue Fang, Yuxin Guo, Zhibang Yang

GraphWalker selects in-context demonstrations for EHR reasoning by building graphs that combine patient clinical data with LLM estimates of information gain, then using cohort discovery and lazy greedy search to reduce redundancy and local-

arxiv:2604.06684 v2 · 2026-04-08 · cs.LG

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4 Citations open
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Claims

C1strongest claim

GraphWalker consistently outperforms state-of-the-art ICL baselines, yielding substantial improvements in clinical reasoning performance.

C2weakest assumption

That jointly modeling patient clinical information and LLM-estimated information gain via graphs, combined with cohort discovery and lazy greedy search, will reliably overcome perspective limitation, cohort awareness, and information aggregation issues on real EHR data without introducing new selection biases or overfitting to the tested benchmarks.

C3one line summary

GraphWalker improves LLM clinical reasoning on EHRs by graph-guided selection of in-context examples that jointly uses data similarity and model signals, plus cohort-level structure and greedy aggregation to reduce redundancy.

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First computed 2026-06-08T01:04:04.473430Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

eb312fe36f595198d81d352b034bf4901ec386e1b4a4d2e367e1bb3b46e844dd

Aliases

arxiv: 2604.06684 · arxiv_version: 2604.06684v2 · doi: 10.48550/arxiv.2604.06684 · pith_short_12: 5MYS7Y3PLFIZ · pith_short_16: 5MYS7Y3PLFIZRWA5 · pith_short_8: 5MYS7Y3P
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/5MYS7Y3PLFIZRWA5GUVQGS7USA \
  | 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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    "submitted_at": "2026-04-08T04:59:49Z",
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