Signals 4 · free daily AI digest

Patient-specific rubric-based evaluation of large language models across longitudinal cancer care

Paper recorded by Signals 4 on 2026-10-26 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-26 on arXiv · recorded by Signals 4 on 2026-10-27

Category: cs.AI · 人工智能 · first seen 2026-10-27

Abstract

Large language models (LLMs) show promise in specialty medicine, yet existing evaluations largely focus on isolated clinical encounters rather than tracking how clinical responsibilities evolve across a longitudinal care pathway. Here we introduce NPC-RubricBench, a phase-aware benchmark for evaluating multistage clinical reasoning across the cancer care continuum, using nasopharyngeal carcinoma a

Read on arXiv →

#144 most recent of 960 cs.AI papers we have recorded · ↑ newer: Learning Force-Reactive Humanoid Loco-Manipulation · ↓ older: I-HITL: Inalienable Human-in-the-Loop
Cite this page: Patient-specific rubric-based evaluation of large language models across longitudinal cancer care: the #144 most recent of 960 cs.AI papers we have recorded (as of 2026-10-26). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/patient-specific-rubric-based-evaluation-of-large-language-models-across-longitu.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
Related: More cs.AI papers · arXiv signals · All papers · Today in AI
Get 4 AI signals a day by email — free.
Subscribe free → See all plans →
Get 4 AI signals a day by email — free
All models · All repos · By company · Daily editions