6 citations · 14 across the 12 of their papers we have counts for
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cs.CL2026
AutoHarness: improving LLM agents by automatically synthesizing a code harness
Xinghua Lou, Miguel Lázaro-Gredilla, Antoine Dedieu +3
Despite significant strides in language models in the last few years, when used as agents, such models often try to perform actions that are not just suboptimal for a given state,…
cs.LG2026
Joint Learning of Hierarchical Neural Options and Abstract World Model
Wasu Top Piriyakulkij, Wolfgang Lehrach, Kevin Ellis +1
Building agents that can perform new skills by composing existing skills is a long-standing goal of AI agent research. Towards this end, we investigate how to efficiently acquire a…