Paper

Same Patient, Different Words, Different Diagnosis? Evaluating Semantic Stability in Clinical LLMs

Unreadunread

AI summary

arXiv:2605. 30646v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used in clinical applications.

Reading status

Priority

About this paper

Authors: Mahdi Alkaeed, Adnan Qayyum, Nabeel Abo Kashreef, Muhammad Bilal, Junaid Qadir
Released: 2026-06-01 (1mo ago)
Topic: Related to current project
Relation to my work: Read next because Same Patient, Different Words, Different Diagnosis? Evaluating Semantic Stability in Clinical LLMs overlaps with clean result "LoRA persona trained on <A> alone emits <B> at 23.5% when a co-trained partner learns <A>...<B>, vs 0% control on Qwen2.5-7B-Instruct (MODERATE confidence)", clean result "Leakage rate is a usable signal for recovering trigger-shaped phrases on Gaperon-1125-1B without knowing the hidden trigger itself (MODERATE confidence)", clean result "Language-mismatch LoRA SFT on Qwen2.5-7B leaks the trained completion language into bystander directives the model was never trained on, absent under same-language SFT (LOW confidence)". Matching terms: strong, word, eval, source, line, rate, compare, does. Source: arxiv cs.CL (NLP).
arXiv: 2605.30646

Ask Claude about this paper

Posts a comment with @claude so the runner spins up a Claude Code session scoped to Same Patient, Different Words, Different Diagnosis? Evaluating Semantic Stability in Clinical LLMs. Replies appear in the conversation below.

Comments

No comments yet.

Related records

No links yet.