2 citations · 4 across the 4 of their papers we have counts for
6 papers
Slaying the Hydra: Interaction-Aware Circuit Discovery in Language Models
Sankaran Vaidyanathan, Rafal Urbaniak, Emily Bunnapradist +2
Localizing behavior to individual components of a language model is a central goal of mechanistic interpretability. However, scoring components one at a time misses context-depende…
EMPIRIC: Experiment-Driven Learning of Residual World Models for Robot Planning
Yichao Liang, Amber Li, Dat Nguyen +13
A robot should be able to learn through experiments how unfamiliar objects behave and interact, then plan with that knowledge. It need not start from scratch: physics engines suppl…
Pact: A Choreographic Language for Agentic Ecosystems
Kiran Gopinathan, Jack Feser, Michelangelo Naim +2
Recent advances in large language models have led to the rise of software systems (i.e. agents) that execute with increasing autonomy on behalf of users in open, multi-party settin…
Benchmarking World-Model Learning with Environment-Level Queries
Archana Warrier, Dat Nguyen, Michelangelo Naim +8
World models are central to building AI agents capable of flexible reasoning and planning. Yet current evaluations (i) test only properties measurable from observed interactions, s…
Combining Induction and Transduction for Abstract Reasoning
Wen-Ding Li, Keya Hu, Carter Larsen +11
When learning an input-output mapping from very few examples, is it better to first infer a latent function that explains the examples, or is it better to directly predict new test…
Lyfe Agents: Generative agents for low-cost real-time social interactions
Zhao Kaiya, Michelangelo Naim, Jovana Kondic +5
Highly autonomous generative agents powered by large language models promise to simulate intricate social behaviors in virtual societies. However, achieving real-time interactions…