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cs.AI2025
Structured Sparse Transition Matrices to Enable State Tracking in State-Space Models
Aleksandar TerziÄ, Nicolas Menet, Michael Hersche +2
Modern state-space models (SSMs) often utilize transition matrices which enable efficient computation but pose restrictions on the model's expressivity, as measured in terms of the…
cs.AI2025
Can Large Reasoning Models do Analogical Reasoning under Perceptual Uncertainty?
Giacomo Camposampiero, Michael Hersche, Roger Wattenhofer +2
This work presents a first evaluation of two state-of-the-art Large Reasoning Models (LRMs), OpenAI's o3-mini and DeepSeek R1, on analogical reasoning, focusing on well-established…
cs.AI2024
Towards Learning to Reason: Comparing LLMs with Neuro-Symbolic on Arithmetic Relations in Abstract Reasoning
Michael Hersche, Giacomo Camposampiero, Roger Wattenhofer +2
This work compares large language models (LLMs) and neuro-symbolic approaches in solving Raven's progressive matrices (RPM), a visual abstract reasoning test that involves the unde…