Title
Topic
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Reframing disability as ‘a property of both humans and machines’
Laura Forlano, professor of art and design and communication studies, has a new article titled “Living Intimately with Machines: Can AI Be Disabled?” Forlano proposes to take seriously the idea that we can “understand disability to be a property of both humans and machines.”
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‘Do Multi-Document Summarization Models Synthesize?’
“Multi-document summarization entails producing concise synopses of collections of inputs. For some applications, the synopsis should accurately synthesize inputs with respect to a key property or aspect. … In this paper we ask: To what extent do modern multi-document summarization models implicitly perform this type of synthesis? To assess this we perform a suite of experiments that probe the degree to which conditional generation models trained for summarization using standard methods yield outputs that appropriately synthesize inputs.” Read the paper and see the full list of authors in ArXiv.
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Foregrounding care in the co-creation of urban spaces: How to find ‘liveable urban futures’
This article asks, “Can participatory engagements in the form of more-than-human co-creation be a generative form of socially and ecologically-just and critical urban placemaking?” It goes on to explore “three interrelated examples of critical urban placemaking in the arts, interrogating how we might design for liveable urban futures as matters of care.” In foregrounding care, the authors explore “co-creation” practices that are “responsive and dynamic rather than prescriptive… [and that] “can transform the status quo, rather than merely reproduce it.” Read “Care-full co-curation: critical urban placemaking for more-than-human futures” and see the full list of authors in City: Analysis of Urban Change,…
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‘Explaining Dataset Changes for Semantic Data Versioning with Explain-Da-V (Technical Report)’
“In multi-user environments in which data science and analysis is collaborative, multiple versions of the same datasets are generated. While managing and storing data versions has received some attention in the research literature, the semantic nature of such changes has remained under-explored. In this work, we introduce \texttt{Explain-Da-V}, a framework aiming to explain changes between two given dataset versions.” Read the paper and see the full list of authors in ArXiv.
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‘Thought Bubbles: A Proxy into Players’ Mental Model Development’
“Studying mental models has recently received more attention, aiming to understand the cognitive aspects of human-computer interaction. However, there is not enough research on the elicitation of mental models in complex dynamic systems. We present Thought Bubbles as an approach for eliciting mental models and an avenue for understanding players’ mental model development in interactive virtual environments.” Read the paper and see the full list of authors at ArXiv.
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‘A Bias-Variance-Privacy Trilemma for Statistical Estimation’
“The canonical algorithm for differentially private mean estimation is to first clip the samples to a bounded range and then add noise to their empirical mean. Clipping controls the sensitivity and, hence, the variance of the noise that we add for privacy. But clipping also introduces statistical bias. We prove that this tradeoff is inherent: no algorithm can simultaneously have low bias, low variance, and low privacy loss for arbitrary distributions.” Read the paper and see the full list of authors in ArXiv.
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‘Making Reconstruction-Based Method Great Again for Video Anomaly Detection’
“Anomaly detection in videos is a significant yet challenging problem. Previous approaches based on deep neural networks employ either reconstruction-based or prediction-based approaches. … existing reconstruction-based methods 1) rely on old-fashioned convolutional autoencoders and are poor at modeling temporal dependency; 2) are prone to overfit the training samples, leading to indistinguishable reconstruction errors. … To address such issues, firstly, we get inspiration from transformer and propose Spatio-Temporal Auto-Trans-Encoder, dubbed as STATE, as a new autoencoder model for enhanced consecutive frame reconstruction.” Find the paper and the full list of authors in ArXiv.
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Re-evaluating ESG reporting: The missing human factor
Researchers from the Center for the Future of Higher Education and Talent Strategy have produced a new report that details the importance of human capital and its measurement in Environmental, Social, and Governance reporting.
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‘Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning’
“Off-policy learning from multistep returns is crucial for sample-efficient reinforcement learning, but counteracting off-policy bias without exacerbating variance is challenging. Classically, off-policy bias is corrected in a per-decision manner. … Many off-policy algorithms rely on this mechanism, along with differing protocols for cutting the IS ratios to combat the variance of the IS estimator. Unfortunately, once a trace has been fully cut, the effect cannot be reversed. … In this paper, we propose a multistep operator that can express both per-decision and trajectory-aware methods.” Read the paper and see the full list of authors in ArXiv.
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‘HoLA Robots: Mitigating Plan-Deviation Attacks in Multi-Robot Systems’
“Emerging multi-robot systems rely on cooperation between humans and robots, with robots following automatically generated motion plans to service application-level tasks. Given the safety requirements associated with operating in proximity to humans and expensive infrastructure, it is important to understand and mitigate the security vulnerabilities of such systems. … We focus on centralized systems, where a *central entity* (CE) is responsible for determining and transmitting the motion plans to the robots, which report their location as they move following the plan.” Read the paper and see the full list of authors in ArXiv.
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Paper from the Ocean Genome Legacy Center, ‘Greater Than pH 8: The pH Dependence of EDTA as a Preservative of High Molecular Weight DNA’
“Ethylenediaminetetraacetic acid (EDTA) is a divalent cation chelator and chemical preservative that has been shown to be the active ingredient of the popular DNA preservative DESS. EDTA may act to reduce DNA degradation during tissue storage by sequestering divalent cations that are required by nucleases naturally occurring in animal tissues. … Increasing the pH of EDTA-containing preservative solutions may improve their effectiveness as DNA preservatives.” Read “Greater Than pH 8: The pH Dependence of EDTA as a Preservative of High Molecular Weight DNA in Biological Samples” and find the full list of authors in PLOS ONE.
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‘Single-Pass Streaming Algorithms for Correlation Clustering’
“We study correlation clustering in the streaming setting. This problem has been studied extensively and numerous algorithms have been developed, most requiring multiple passes over the stream. … We present a single-pass algorithm that obtains a 5-approximation using O(n) space. The algorithm itself is extremely simple and has implications beyond the streaming setting (such as for dynamic and local computation algorithms). The approximation analysis, on the other hand, is delicate and in fact tight.” Read the paper and see the full list of authors in the Society for Industrial and Applied Mathematics.
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‘Dynamic Algorithms for Maximum Matching Size’
“We study fully dynamic algorithms for maximum matching. This is a well-studied problem, known to admit several update-time/approximation trade-offs. For instance, it is known how to maintain a 1/2-approximate matching in (poly log n) update time or a 2/3-approximate matching in O(√n) update time, where n is the number of vertices. … We show that when the goal is to maintain just the size of the matching (and not its edge-set), then these bounds can indeed be improved.” Read the paper and see the full list of authors in the Society for Industrial and Applied Mathematics.
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‘Decadal Application of WRF/Chem Under Future Climate and Emission Scenarios’
“This work presents new climate and emissions scenarios to investigate changes on future meteorology and air quality in the U.S. Here, we employ a dynamically downscaled Weather Research and Forecasting model coupled with chemistry (WRF/Chem) simulations that use two Intergovernmental Panel on Climate Change scenarios (i.e., A1B and B2) integrated with explicitly projected emissions from a novel Technology Driver Model (TDM).” Read “Decadal Application of WRF/Chem Under Future Climate and Emission Scenarios: Impacts of Technology-Driven Climate and Emission Changes on Regional Meteorology and Air Quality” and see the full list of authors in Atmosphere.
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‘Who Wants To Cooperate—And Why? Attitude and Perception of Crowd Workers in Online Labor Markets’
“Existing literature and studies predominantly focus on how crowdsource workers individually complete tasks and projects. Our study examines crowdsource workers’ willingness to work collaboratively. We report results from a survey of 122 workers on a leading online labor platform (Upwork) to examine crowd workers’ behavioral preferences for collaboration. … We then test if actual cooperative behavior matches with workers’ behavioral preferences through an incentivized social dilemma experiment. We find that respondents cooperate at a higher rate (85%) than reported in previous comparable studies (between 50-75%).” Read the paper and see the full list of authors in ArXiv.
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‘Interphase Chromosomes of the Aedes Aegypti Mosquito Are Liquid Crystalline and Can Sense Mechanical Cues’
In “Interphase chromosomes of the Aedes aegypti mosquito are liquid crystalline and can sense mechanical cues,” the authors observe “the three-dimensional architecture of the Aedes aegypti genome,” a species of mosquito. Their observations “[provide] a possible physical mechanism linking mechanical cues to gene regulation.” Find the paper and the full list of authors at Nature Communications.
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Building a better hologram: Just add noise
Researchers from Northeastern University, in collaboration with Nanjing University, have broken a “theoretical limit” in metasurface capacities—a.k.a. “holograms.” By introducing carefully engineered noise into Jones matrices, they have produced “the highest capacity reported for polarization multiplexing.” They demonstrate this raised capacity across “11 independent holographic images.” Read “Breaking the Limitation of Polarization Multiplexing in Optical Metasurfaces with Engineered Noise” and find the full list of authors at Science.
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‘Lineage-Mismatched Mitochondrial Replacement … Effectively Restores the Original Proteomic Landscape of Recipient Cells’
“Here an inducible mitochondrial depletion modelis used to study how cells lacking endogenous mitochondria respond, on a global protein expression level, to transplantation with lineage-mismatched (LM) mitochondria. It is shown that LM mitochondrial transplantation does not alter the proteomic profile in nonmitochondria–depleted recipient cells; however, enforced depletion of endogenous mitochondria results in dramatic changes in the proteomic landscape, which returns to the predepletion state following internalization of LM mitochondria.” Find “Lineage-Mismatched Mitochondrial Replacement in an Inducible Mitochondrial Depletion Model Effectively Restores the Original Proteomic Landscape of Recipient Cells” and the full list of authors in Advanced Biology.
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The straightest line between two points: When your map’s incomplete
The authors of “Finding shortest and nearly shortest path nodes in large substantially incomplete networks by hyperbolic mapping” have determined that large, real-world networks “are not random but are organized according to latent-geometric rules.” This being the case, they argue that, when “mapped to points in latent hyperbolic spaces,” they can calculate shortest paths “along geodesic curves connecting endpoint nodes.” In other words, they can get from A to C, without knowing B’s location. Read “Finding shortest and nearly shortest path nodes in large substantially incomplete networks by hyperbolic mapping” and see the full list of authors in Nature Communications.
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How the ‘two ingredients of language’ come from different regions of the brain
The authors of “Phonetic Categorization Relies on Motor Simulation, But Combinatorial Phonological Computations Are Abstract” note two elements required in human language, categorization (identifying words as “distinct units”) and combination (distinguishing between units). The authors explore these mechanisms “using transcranial magnetic stimulation. [They] show that speech categorization engages the motor system. … In contrast, the combinatorial computation of syllable structure engages Broca’s area,” a region within the brain’s frontal lobe. They “conclude that the two ingredients of language—categorization and combination—are distinct functions in human brains.” Read their paper and see the full list of authors in Scientific Reports.
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‘Byzantine Resilience at Swarm Scale: A Decentralized Blocklist Protocol From Inter-Robot Accusations’
“The Weighted-Mean Subsequence Reduced (W-MSR) algorithm, the state-of-the-art method for Byzantine-resilient design of decentralized multi-robot systems, is based on discarding outliers received over Linear Consensus Protocol (LCP). Although W-MSR provides well-understood theoretical guarantees relating robust network connectivity to the convergence of the underlying consensus, the method comes with several limitations preventing its use at scale. … In this work, we propose a Decentralized Blocklist Protocol (DBP) based on inter-robot accusations.” Read the paper and see the full list of authors in ArXiv.
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‘Beating (1 – 1/e)-Approximation for Weighted Stochastic Matching’
“In the stochastic weighted matching problem, the goal is to find a large-weight matching of a graph when we are uncertain about the existence of its edges. In particular, each edge e has a known weight we but is realized independently with some probability pe. The algorithm may query an edge to see whether it is realized. We consider the well-studied query commit version of the problem, in which any queried edge that happens to be realized must be included in the solution.” Find the paper and the full list of authors at SIAM.
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‘Beating Greedy Matching in Sublinear Time’
“We study sublinear time algorithms for estimating the size of maximum matching in graphs. Our main result is a (½ + Ω(1))-approximation algorithm which can be implemented in O(n1+ε) time, where n is the number of vertices and the constant ε > 0 can be made arbitrarily small. The best known lower bound for the problem is Ω(n), which holds for any constant approximation.” Read the paper and see the full list of authors at the Society for Industrial and Applied Mathematics.
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‘Single-Pass Streaming Algorithms for Correlation Clustering’
“We study correlation clustering in the streaming setting. This problem has been studied extensively and numerous algorithms have been developed, most requiring multiple passes over the stream. For the important case of single-pass algorithms, recent work of Assadi and Wang [8] obtains a c-approximation using Õ(n) space where c > 105 is a constant and n is the number of vertices to be clustered. We present a single-pass algorithm that obtains a 5-approximation using O(n) space.” Read the paper and see the full list of authors at the Society for Industrial and Applied Mathematics.
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‘Dynamic Algorithms for Maximum Matching Size’
“We study fully dynamic algorithms for maximum matching. This is a well-studied problem, known to admit several update-time/approximation trade-offs. … It has been a long-standing open problem to determine whether either of these bounds can be improved. In this paper, we show that when the goal is to maintain just the size of the matching (and not its edge-set), then these bounds can indeed be improved.”
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‘Sublinear Algorithms for TSP via Path Covers’
“We study sublinear time algorithms for the traveling salesman problem (TSP). First, we focus on the closely related maximum path cover problem, which asks for a collection of vertex disjoint paths that include the maximum number of edges. Our analysis of the running time uses connections to parallel algorithms and is information-theoretically optimal up to poly log n factors. Additionally, we show that our approximation guarantees for path cover and (1,2)-TSP hit a natural barrier: We show better approximations require better sublinear time algorithms for the well-studied maximum matching problem.” Find the paper and full list of authors at ArXiv.
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Chowdhury awarded patent for intelligent wi-fi access points
Professor Kaushik Chowdhury received a patent for work on the “Method and apparatus for access point discovery in dense WiFi networks.” The abstract to the patent offers “Systems, devices, and methods for access point discovery in a wireless network,” which rely on phase shift methods “encoded into bits in selected ones of a plurality of subcarriers.”
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Rethinking the source: COVID-19 and global supply chains in 2023
In the wake of the COVID-19 pandemic, distinguished professor Nada Sanders tracks “three major shifts in how companies manage their supply chains.” According to her analysis, both customers and businesses will be impacted by the force of: 1) Bringing supply chains home, 2) investments in more technology, and 3) a shift from “just-in-time” thinking to “just-in-case” processes. The goal through all of these changes, Sanders writes, “is to ensure [that companies] can withstand disruptions and maintain business continuity.” To read more about these three forces and their potential impacts on the economy, see her article in The Conversation.