[Submitted on 18 Sep 2026]
Title:Comedic Fool's Gold: Reward Exploits and Countermeasures in Conversational Humor
View a PDF of the paper titled Comedic Fool's Gold: Reward Exploits and Countermeasures in Conversational Humor, by Sam Larson
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Abstract:We investigate automated rewards for training language models in conversational humor, focusing on reward exploits and countermeasures. Two approaches aim to capture understandable surprise and predicted audience amusement. Controlled tests show that an embedding-based surprise reward accepts word-shuffled replies as readily as witty ones. A fluency filter detects the shuffles, but the combined reward also rejects some witty replies and fails further validation. An audience model's predicted laughter is instead vulnerable to laughter cues in either speaker's messages. Normalizing these cues across speakers blocks the covered attacks, although unmatched expressions remain exploitable. Three reinforcement-learning runs evaluate training with successive reward revisions. The final run improves the combined evaluation score by 0.0903 and reduces zero-score sessions by 40%, but its humor-specific improvement remains below our preregistered target. These findings illustrate a broader challenge for automated reward design: countermeasures must block exploitable shortcuts while preserving the behavior the reward was intended to encourage.
Comments: 11 pages, 3 figures, 4 tables
Subjects:
Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Machine Learning (cs.LG)
Cite as: arXiv:2610.00197 [cs.AI]
(or arXiv:2610.00197v1 [cs.AI] for this version)
https://doi.org/10.48550/arXiv.2610.00197
arXiv-issued DOI via DataCite (pending registration)
Submission history
From: Samuel Larson [view email] [v1] Fri, 18 Sep 2026 20:14:09 UTC (56 KB)
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