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cs.CL2026
Bayesian Teaching Enables Probabilistic Reasoning in Large Language Models
Linlu Qiu, Fei Sha, Kelsey Allen +3
Large language models (LLMs) are increasingly used as agents that interact with users and with the world. To do so successfully, LLMs must construct representations of the world an…
cs.CL2024
A Systematic Comparison of Syllogistic Reasoning in Humans and Language Models
Tiwalayo Eisape, MH Tessler, Ishita Dasgupta +3
A central component of rational behavior is logical inference: the process of determining which conclusions follow from a set of premises. Psychologists have documented several way…
cs.CL2024
The Impact of Depth on Compositional Generalization in Transformer Language Models
Jackson Petty, Sjoerd van Steenkiste, Ishita Dasgupta +3
To process novel sentences, language models (LMs) must generalize compositionally -- combine familiar elements in new ways. What aspects of a model's structure promote compositiona…