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1. Viewpoint-independent face recognition via extrapolation in paper wasps

   https://doi.org/10.1242/jeb.247661  

   Tibbetts, Elizabeth A; Weise, Chloe; Pardo-Sanchez, Juanita; Vi, An Na (September 2024, Journal of Experimental Biology)

   ABSTRACT Visual recognition of three-dimensional signals, such as faces, is challenging because the signals appear different from different viewpoints. A flexible but cognitively challenging solution is viewpoint-independent recognition, where receivers identify signals from novel viewing angles. Here, we used same/different concept learning to test viewpoint-independent face recognition in Polistes fuscatus, a wasp that uses facial patterns to individually identify conspecifics. We found that wasps use extrapolation to identify novel views of conspecific faces. For example, wasps identify a pair of pictures of the same wasp as the ‘same’, even if the pictures are taken from different views (e.g. one face 0 deg rotation, one face 60 deg rotation). This result is notable because it provides the first evidence of view-invariant recognition via extrapolation in an invertebrate. The results suggest that viewpoint-independent recognition via extrapolation may be a widespread strategy to facilitate individual face recognition. 

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2. Geographic variation in individual face learning based on plasticity rather than local genetic adaptation in Polistes wasps

   https://doi.org/10.1093/beheco/arad100  

   Simons, Meagan; Green, Delbert A; Tibbetts, Elizabeth A (January 2024, Behavioral Ecology)

   While, Geoffrey (Ed.)

   Abstract Signals and receiver responses often vary across a species’ geographic range. Effective communication requires a match between signal and receiver response, so there is much interest in the developmental mechanisms that maintain this link. Two potential mechanisms are genetic covariance between signal and receiver response and plasticity where individuals adjust their phenotype based on their partner’s phenotype. Here, we test how plasticity contributes to geographic variation in individual face recognition in Polistes fuscatus wasps. Previous work has shown that P. fuscatus from Michigan, USA (MI) have variable facial patterns used for individual recognition, while P. fuscatus from central Pennsylvania, USA (PA) lack variable facial patterns and are unable to learn individual conspecifics. We experimentally altered rearing environment, so wasps were either reared with their own population or in a common garden with wasps from both populations. Then, we tested the wasps’ capacity to learn and remember individual conspecific faces. Consistent with previous work, MI wasps reared with MI wasps were adept at learning conspecific faces, while PA wasps reared with PA wasps were unable to learn conspecific faces. However, MI and PA wasps reared in a common garden developed similar, intermediate capacity for individual face learning. These results indicate that individual face learning in Polistes wasps is highly plastic and responsive to the social environment. Plasticity in receiver responses may be a common mechanism mediating geographic differences in non-sexual signaling systems and may play a role in maintaining links between signals and receiver responses in geographically variable communication systems. 

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3. Male recognition of conspecific female chemical cues in a diverse clade of freshwater fishes

   https://doi.org/10.1111/jfb.15600  

   Black, Taylor N; Rastogi, Aakriti; Saegert, Abby; Dib, Joseph; Moran, Rachel L (March 2024, Journal of Fish Biology)

   Abstract Where orangethroat darters (Etheostoma: Ceasia) and rainbow darters (Etheostoma caeruleum) co‐occur, males prefer conspecific over heterospecific females. The cues males use to identify conspecific females remain unclear. We conducted behavioral trials to ask whether chemical cues function in conspecific recognition. We found that males from three orangethroat darter species preferentially associate with female scent over a control. Our results support the use of olfaction in conspecific identification in the orangethroat clade and contribute to our understanding of signals that may facilitate species recognition and underlie the evolution of behavioral isolation. 

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4. Postural analysis reveals persistent changes in paper wasp foundress behavioral state after conspecific challenge

   https://doi.org/10.1002/ece3.10436  

   Legan, Andrew W; Vogt, Caleb C; Sheehan, Michael J (September 2023, Ecology and Evolution)

   Abstract Vigilant animals detect and respond to threats in the environment, often changing posture and movement patterns. Vigilance is modulated not only by predators but also by conspecific threats. In social animals, precisely how conspecific threats alter vigilance behavior over time is relevant to long‐standing hypotheses about social plasticity. We report persistent effects of a simulated conspecific challenge on behavior of wild northern paper wasp foundresses,Polistes fuscatus. During the founding phase of the colony cycle, conspecific wasps can usurp nests from the resident foundress, representing a severe threat. We used automated tracking to monitor the movement and posture ofP. fuscatusfoundresses in response to simulated intrusions. Wasps displayed increased movement, greater bilateral wing extension, and reduced antennal separation after the threat was removed. These changes were not observed after presentation with a wooden dowel. By rapidly adjusting individual behavior after fending off an intruder, paper wasp foundresses might invest in surveillance of potential threats, even when such threats are no longer immediately present. The prolonged vigilance‐like behavioral state observed here is relevant to plasticity of social recognition processes in paper wasps. 

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5. Bound-Tightened Densest Subgraph Discovery on GPU

   https://doi.org/10.1145/3802023  

   Manzoor, Wajid; Fan, Ke; Shaheer, Muhammad; Guo, Guimu (May 2026, Proceedings of the ACM on Management of Data)

   The densest subgraph discovery (DSD) problem is a fundamental task in graph mining with applications in social networks, bioinformatics, graph databases, and systems engineering. Given a graphG= (V, E) and an integerk? 2, the goal is to find a vertex subsetD?Vwhose induced subgraphG(D) maximizes thek-clique density, defined as the number ofk-cliques per vertex. Larger values ofkcapture higher-order connectivity patterns beyond edges, enabling the discovery of more cohesive structures. We present a GPU-accelerated framework that integrates a warp-levelk-clique enumeration algorithm along with clique-core–based pruning and edge pruning techniques to reduce the search space, followed by parallel connected component decomposition to split the pruned graph into independent smaller subproblems. The exact solution is then obtained by formulating DSD on each connected component as a maximum flow problem and solving it using a highly parallel vertex-centric push–relabel algorithm, enhanced with tight upper and lower density bounds and compact, GPU-friendly data structures. Experiments on a diverse set of real-world and synthetic graphs show substantial speedups over the state-of-the-art CPU implementation, while producing identical solutions. 

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