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Found 3 papers, 2 papers with code
Can LLMs perform structured graph reasoning?
We highlight various limitations, biases and properties of LLMs through this benchmarking process, such as an inverse relation to the average degrees of freedom of traversal per node in graphs, the overall negative impact of k-shot prompting on graph reasoning tasks, and a positive response bias which prevents LLMs from identifying the absence of a valid solution.
Advancing Perception in Artificial Intelligence through Principles of Cognitive Science
In this review paper, we focus on the cognitive functions of perception, which is the process of taking signals from one's surroundings as input, and processing them to understand the environment.
STUPD: A Synthetic Dataset for Spatial and Temporal Relation Reasoning
In addition to spatial relations, we also propose 50K visual depictions across 10 temporal relations, consisting of videos depicting event/time-point interactions.
