activity
20122026
most citedChurch: a language for generative models

490 citations · 1k across the 74 of their papers we have counts for

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6 papers · 1 filter

cs.CL2025

Belief Attribution as Mental Explanation: The Role of Accuracy, Informativity, and Causality

Lance Ying, Almog Hillel, Ryan Truong +3

A key feature of human theory-of-mind is the ability to attribute beliefs to other agents as mentalistic explanations for their behavior. But given the wide variety of beliefs that…

cs.CL2025★ 2 cited

Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo

João Loula, Benjamin LeBrun, Li Du +12

A wide range of LM applications require generating text that conforms to syntactic or semantic constraints. Imposing such constraints can be naturally framed as probabilistic condi…

cs.CL2025

Self-Steering Language Models

Gabriel Grand, Joshua B. Tenenbaum, Vikash K. Mansinghka +2

While test-time reasoning enables language models (LMs) to tackle complex tasks, searching or planning in natural language can be slow, costly, and error-prone. But even when LMs s…

cs.CL2025★ 1 cited

Fast Controlled Generation from Language Models with Adaptive Weighted Rejection Sampling

Benjamin Lipkin, Benjamin LeBrun, Jacob Hoover Vigly +9

The dominant approach to generating from language models subject to some constraint is locally constrained decoding (LCD), incrementally sampling tokens at each time step such that…

cs.CL2024

Understanding Epistemic Language with a Language-augmented Bayesian Theory of Mind

Lance Ying, Tan Zhi-Xuan, Lionel Wong +2

How do people understand and evaluate claims about others' beliefs, even though these beliefs cannot be directly observed? In this paper, we introduce a cognitive model of epistemi…

cs.CL2023★ 38 cited

From Word Models to World Models: Translating from Natural Language to the Probabilistic Language of Thought

Lionel Wong, Gabriel Grand, Alexander K. Lew +4

How does language inform our downstream thinking? In particular, how do humans make meaning from language--and how can we leverage a theory of linguistic meaning to build machines…