World models (WMs) simulate the transition dynamics of environments, enabling agents to plan over the consequences of their actions. In text-based environments, fine-tuning a Language Model (LM) to serve as a WM has emerged as a dominant paradigm. However, despite the widespread success of non-parametric approaches suc...
Dhananjay Ashok, Shantanu Agarwal, Vivek Datla et al.· 0 citations
GameBoyWorlds is introduced, a testbed for agentic self-improvement in video games and it is shown that contemporary approaches to self-improvement are lacking, with world modelling and autonomous skill discovery failing, and a novel strategy that uses curiosity-based exploration to write guides achieving only partial...
Dhananjay Ashok, Adam Shen, A. Feng et al.· 0 citations
The PAU (Python API Understanding) benchmark is introduced, where models are provided with black-box, API-level access to code snippets, and inspiration is taken from the Asymmetric Actor Critic paradigm, frequently used in robot learning, to post-train models for interactive code understanding.
Dhananjay Ashok, Jesse Thomason, Jonathan May· 0 citations
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