Abstract:In this (work in progress) paper, we present Bounded Pragmatic Listener (or BPL), a cognitively grounded Bayesian framework for modelling susceptibility to information disorder. BPL extends Rational Speech Act theory with three cognitively motivated bounds derived from the bounded rationality literature with a) a recursion depth bound (that emphasises working memory limits);b) a prior compression parameter (which is oriented at capturing information bottleneck); and c) an availability sample size (that operationalises importance sampling with saliency-weighted proposals). This allows us to test predictions about misinformation susceptibility, annotator disagreement, and the differential vulnerability to mis-, dis-, and mal-information as defined in the Information Disorder framework. We validate BPL on the LIAR and MultiFC benchmarks showcasing competitive veracity classification and experimental support for the depth-mismatch paradox.
| Comments: | work in progress |
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| Cite as: | arXiv:2605.09483 [cs.CL] |
| (or arXiv:2605.09483v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2605.09483 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Pranava Madhyastha [view email]
[v1]
Sun, 10 May 2026 11:37:40 UTC (36 KB)