Can the Berkeleyan Idealist Resist Spinozist Panpsychism?

We argue that prevailing definitions of Berkeley’s idealism fail to rule out a nearby Spinozist rival view that we call ‘mind-body identity panpsychism.’ Since Berkeley certainly does not agree with Spinoza on this issue, we call for more care in defining Berkeley’s view. After we propose our own definition of Berkeley’s idealism, we survey two Berkeleyan strategies to block the mind-body identity panpsychist and establish his idealism. We argue that Berkeley should follow Leibniz and further develop his account of the mind’s unity. Unity—not activity—is the best way for Berkeley to establish his view at the expense of his panpsychist competitors

Stronger Baselines for Trustable Results in Neural Machine Translation

Interest in neural machine translation has grown rapidly as its effectiveness has been demonstrated across language and data scenarios. New research regularly introduces architectural and algorithmic improvements that lead to significant gains over "vanilla" NMT implementations. However, these new techniques are rarely evaluated in the context of previously published techniques, specifically those that are widely used in state-of-theart production and shared-task systems. As a result, it is often difficult to determine whether improvements from research will carry over to systems deployed for real-world use. In this work, we recommend three specific methods that are relatively easy to implement and result in much stronger experimental systems. Beyond reporting significantly higher BLEU scores, we conduct an in-depth analysis of where improvements originate and what inherent weaknesses of basic NMT models are being addressed. We then compare the relative gains afforded by several other techniques proposed in the literature when starting with vanilla systems versus our stronger baselines, showing that experimental conclusions may change depending on the baseline chosen. This indicates that choosing a strong baseline is crucial for reporting reliable experimental results.Comment: To appear at the Workshop on Neural Machine Translation (WNMT

Multimodal interactions in insect navigation

Animals travelling through the world receive input from multiple sensory modalities that could be important for the guidance of their journeys. Given the availability of a rich array of cues, from idiothetic information to input from sky compasses and visual information through to olfactory and other cues (e.g. gustatory, magnetic, anemotactic or thermal) it is no surprise to see multimodality in most aspects of navigation. In this review, we present the current knowledge of multimodal cue use during orientation and navigation in insects. Multimodal cue use is adapted to a species’ sensory ecology and shapes navigation behaviour both during the learning of environmental cues and when performing complex foraging journeys. The simultaneous use of multiple cues is beneficial because it provides redundant navigational information, and in general, multimodality increases robustness, accuracy and overall foraging success. We use examples from sensorimotor behaviours in mosquitoes and flies as well as from large scale navigation in ants, bees and insects that migrate seasonally over large distances, asking at each stage how multiple cues are combined behaviourally and what insects gain from using different modalities