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cs.SE2026
Making Embodied AI Reliable: A Community Agenda from Testing to Formal Verification
Xi Zheng, Dulanga Weerakoon, Yintong Huo +8
Embodied AI systems are increasingly deployed in open-world environments, yet ensuring their reliability remains a fundamental challenge. Drawing on discussions from the AAAI'26 Br…
cs.AI2026
Evaluating Counterfactual Explanation Methods on Incomplete Inputs
Francesco Leofante, Daniel Neider, Mustafa Yalçıner
Existing algorithms for generating Counterfactual Explanations (CXs) for Machine Learning (ML) typically assume fully specified inputs. However, real-world data often contains miss…
cs.LG2026
Reinforcement Learning with Symbolic Reward Machines
Thomas Krug, Daniel Neider
Reward Machines (RMs) are an established mechanism in Reinforcement Learning (RL) to represent and learn sparse, temporally extended tasks with non-Markovian rewards. RMs rely on h…