@inproceedings{mo-etal-2026-whats,
title = "What{'}s in a Name? Morphological Shortcuts by {LLM}s in Pharmacology",
author = "Mo, Kaijie and
Yang, Thomas and
Shaib, Chantal and
Yao, Qing and
Rudman, William and
Kouzy, Ramez and
Misra, Kanishka and
Wallace, Byron C and
Li, Junyi Jessy",
editor = "Lee, Hung-Yi and
Dev, Sunipa and
Li, Jessy and
Elliott, Desmond",
booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing",
month = oct,
year = "2026",
address = "Budapest, Hungary",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.emnlp-main.1646/",
pages = "37411--37434",
ISBN = "979-8-89176-459-0",
abstract = "The morphological form of a word can often give cues to its meaning, but purely relying on these mappings can lead to overgeneralization in high-stakes domains. In the medical domain, for instance, LLMs can confidently reason about fictitious drugs from their affixes alone (e.g., wugcillin) and generate plausible-looking clinical content. We present a behavioral and mechanistic study of LLM ``affix heuristics'' in pharmacology. Using fictitious drug names built from real affixes, we show that affix signals alone elicit class-level pharmacological responses. We introduce a framework for identifying whether a model{'}s drug semantics are driven mainly by the affix, the stem, or the drug name as a whole. Applied across 653 drugs, our framework reveals that models often induce drug meaning primarily through affix cues, yet rarely explicitly indicate this reliance, and sometimes incorrectly conflate properties among affix-sharing drugs. Activation patching across models further localizes this behavior to early-mid layers. These findings show that morphological shortcuts pose a subtle but measurable risk to safety."
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<abstract>The morphological form of a word can often give cues to its meaning, but purely relying on these mappings can lead to overgeneralization in high-stakes domains. In the medical domain, for instance, LLMs can confidently reason about fictitious drugs from their affixes alone (e.g., wugcillin) and generate plausible-looking clinical content. We present a behavioral and mechanistic study of LLM “affix heuristics” in pharmacology. Using fictitious drug names built from real affixes, we show that affix signals alone elicit class-level pharmacological responses. We introduce a framework for identifying whether a model’s drug semantics are driven mainly by the affix, the stem, or the drug name as a whole. Applied across 653 drugs, our framework reveals that models often induce drug meaning primarily through affix cues, yet rarely explicitly indicate this reliance, and sometimes incorrectly conflate properties among affix-sharing drugs. Activation patching across models further localizes this behavior to early-mid layers. These findings show that morphological shortcuts pose a subtle but measurable risk to safety.</abstract>
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%0 Conference Proceedings
%T What’s in a Name? Morphological Shortcuts by LLMs in Pharmacology
%A Mo, Kaijie
%A Yang, Thomas
%A Shaib, Chantal
%A Yao, Qing
%A Rudman, William
%A Kouzy, Ramez
%A Misra, Kanishka
%A Wallace, Byron C.
%A Li, Junyi Jessy
%Y Lee, Hung-Yi
%Y Dev, Sunipa
%Y Li, Jessy
%Y Elliott, Desmond
%S Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-459-0
%F mo-etal-2026-whats
%X The morphological form of a word can often give cues to its meaning, but purely relying on these mappings can lead to overgeneralization in high-stakes domains. In the medical domain, for instance, LLMs can confidently reason about fictitious drugs from their affixes alone (e.g., wugcillin) and generate plausible-looking clinical content. We present a behavioral and mechanistic study of LLM “affix heuristics” in pharmacology. Using fictitious drug names built from real affixes, we show that affix signals alone elicit class-level pharmacological responses. We introduce a framework for identifying whether a model’s drug semantics are driven mainly by the affix, the stem, or the drug name as a whole. Applied across 653 drugs, our framework reveals that models often induce drug meaning primarily through affix cues, yet rarely explicitly indicate this reliance, and sometimes incorrectly conflate properties among affix-sharing drugs. Activation patching across models further localizes this behavior to early-mid layers. These findings show that morphological shortcuts pose a subtle but measurable risk to safety.
%U https://aclanthology.org/2026.emnlp-main.1646/
%P 37411-37434
Markdown (Informal)
[What’s in a Name? Morphological Shortcuts by LLMs in Pharmacology](https://aclanthology.org/2026.emnlp-main.1646/) (Mo et al., EMNLP 2026)
ACL
- Kaijie Mo, Thomas Yang, Chantal Shaib, Qing Yao, William Rudman, Ramez Kouzy, Kanishka Misra, Byron C Wallace, and Junyi Jessy Li. 2026. What’s in a Name? Morphological Shortcuts by LLMs in Pharmacology. In Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing, pages 37411–37434, Budapest, Hungary. Association for Computational Linguistics.