490 citations · 1k across the 74 of their papers we have counts for
22 papers · 1 filter
Infinite Ends from Finite Samples: Open-Ended Goal Inference as Top-Down Bayesian Filtering of Bottom-Up Proposals
Tan Zhi-Xuan, Gloria Kang, Vikash Mansinghka +1
The space of human goals is tremendously vast; and yet, from just a few moments of watching a scene or reading a story, we seem to spontaneously infer a range of plausible motivati…
Pragmatic Instruction Following and Goal Assistance via Cooperative Language-Guided Inverse Planning
Tan Zhi-Xuan, Lance Ying, Vikash Mansinghka +1
People often give instructions whose meaning is ambiguous without further context, expecting that their actions or goals will disambiguate their intentions. How can we build assist…
Grounding Language about Belief in a Bayesian Theory-of-Mind
Lance Ying, Tan Zhi-Xuan, Lionel Wong +2
Despite the fact that beliefs are mental states that cannot be directly observed, humans talk about each others' beliefs on a regular basis, often using rich compositional language…
Inferring the Goals of Communicating Agents from Actions and Instructions
Lance Ying, Tan Zhi-Xuan, Vikash Mansinghka +1
When humans cooperate, they frequently coordinate their activity through both verbal communication and non-verbal actions, using this information to infer a shared goal and plan. H…
Sequential Monte Carlo Steering of Large Language Models using Probabilistic Programs
Alexander K. Lew, Tan Zhi-Xuan, Gabriel Grand +1
Even after fine-tuning and reinforcement learning, large language models (LLMs) can be difficult, if not impossible, to control reliably with prompts alone. We propose a new infere…
Abstract Interpretation for Generalized Heuristic Search in Model-Based Planning
Tan Zhi-Xuan, Joshua B. Tenenbaum, Vikash K. Mansinghka
Domain-general model-based planners often derive their generality by constructing search heuristics through the relaxation or abstraction of symbolic world models. We illustrate ho…