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combining blotto networks and voter models to simulate voter behavior in response to competitive
election
swing voters
combining blotto networks and voter models to simulate voter behavior in response to competitive election spending
we first show that this compositionality can be systematically described by a probabilistic
generative
encoding models
we first show that this compositionality can be systematically described by a probabilistic generative model
chronic diseases frequently co-occur in patterns that are unlikely to
arise
comorbidity networks
chronic diseases frequently co-occur in patterns that are unlikely to arise by chance a phenomenon known as multimorbidity
we present a statistical framework that establishes an accelerating star formation scenario for
dense
stellar population
we present a statistical framework that establishes an accelerating star formation scenario for dense clumps using atlasgal and almagal samples
in particular for dense graphs with non-negative real weights we provide the first nearly work-efficient
strongly
strongly polynomial
in particular for dense graphs with non-negative real weights we provide the first nearly work-efficient strongly polynomial algorithm with sublinear depth
the results expose limitations in current llms capacity for representation alignment highlighting the need for further research on robust alignment between
language
vision-language models
the results expose limitations in current llms capacity for representation alignment highlighting the need for further research on robust alignment between language and internal agent representations
these results highlight the significant room for improving the mathematical reasoning in
current
large language models llms
these results highlight the significant room for improving the mathematical reasoning in current llms
we use the database constructed in wasleske baldassare 2024 which contains dwarf galaxies that were selected as
active
active galactic
we use the database constructed in wasleske baldassare 2024 which contains dwarf galaxies that were selected as active galaxies by optical spectroscopy infrared colors x-ray brightness and photometric variability
the average responded probability that our
vacuum
vacuum metastable
the average responded probability that our vacuum is metastable was 45
our study addresses the challenges inherent in calculating mixed fermion-boson systems and explores the potential of quantum
computing
open quantum
our study addresses the challenges inherent in calculating mixed fermion-boson systems and explores the potential of quantum computing to advance their analysis
it is setup for quantum communication and quantum-assured time transfer and can establish satellite
communication
optical communication
it is setup for quantum communication and quantum-assured time transfer and can establish satellite communication links within ten minutes of arriving on site day or night
7 db at spopo output evidencing the robustness and versatility of this platform for stable pulsed squeezed-light
generation
nonlinear optical
7 db at spopo output evidencing the robustness and versatility of this platform for stable pulsed squeezed-light generation and advanced quantum optical applications
experimental results confirm superior performance
compared
multi-object tracking
experimental results confirm superior performance compared to state-of-the-art trackers
through numerical simulations and theoretical analysis we discuss the conditions under which variation in how individuals experience environmental selection can naturally promote
evolutionary
evolutionary dynamics
through numerical simulations and theoretical analysis we discuss the conditions under which variation in how individuals experience environmental selection can naturally promote evolutionary strategies that generalize across environments and anticipate novel challenges
this formulation leads to a point to set type of optimization problem which relaxes the requirement on controllability of the system
compared
predictive control
this formulation leads to a point to set type of optimization problem which relaxes the requirement on controllability of the system compared to the classic lap framework
approximate nearest neighbor ann search and
approximate
-approximation algorithm
approximate nearest neighbor ann search and approximate kernel density estimation a-kde are fundamental problems at the core of modern machine learning with broad applications in data analysis information systems and large-scale decision making
quantum enhanced dark-matter search with entangled fock
states
open quantum
quantum enhanced dark-matter search with entangled fock states in high-quality cavities
large language models llms excel at general tasks but underperform in specialized
domains
large language
large language models llms excel at general tasks but underperform in specialized domains like economics and psychology which require deep principled understanding
dyck edit distance measures how far a parenthesis string is from a well-parenthesized expression while tree
edit
edit distance
dyck edit distance measures how far a parenthesis string is from a well-parenthesized expression while tree edit distance quantifies the minimum number of node insertions deletions and substitutions required to transform one rooted ordered labeled tree into another
our work incorporates state-of-the-art innovations in all key aspects of the fault-tolerant quantum
computing
quantum algorithm
our work incorporates state-of-the-art innovations in all key aspects of the fault-tolerant quantum computing ftqc stack to show how quantum computers could realistically and practically tackle co _2 utilization for green energy production
we construct a non-parametric framework by generating large ensembles of randomized
sfhs
host galaxy
we construct a non-parametric framework by generating large ensembles of randomized sfhs for each galaxy in the sample
this improvement allows the inverse optimal safe control to inherit the standard
gain
inverse optimal
this improvement allows the inverse optimal safe control to inherit the standard gain margin of 1 2 inf without requiring prior knowledge of whether f x or u0 acts safely on the safety boundary while simultaneously ensuring global asymptotic stability of the resulting safe set
fast high-fidelity baseband reset of a latched state for quantum dot
qubit
qubit readout
fast high-fidelity baseband reset of a latched state for quantum dot qubit readout
to enhance efficiency we further develop vimogen-light a distilled variant that eliminates video
generation
video generation
to enhance efficiency we further develop vimogen-light a distilled variant that eliminates video generation dependencies while preserving strong generalization
the same framework applies broadly to continuously tunable phase-gradient optics including varifocal metalenses parfocal zoom
metalenses
refractive index
the same framework applies broadly to continuously tunable phase-gradient optics including varifocal metalenses parfocal zoom metalenses tunable axicons and related dynamic focusing elements
this work advances this vision by identifying the fundamental principles of human ai collaboration within
uncertainty
uncertainty quantification
this work advances this vision by identifying the fundamental principles of human ai collaboration within uncertainty quantification a key component of reliable decision making
we explain these capacities via a computational
cognitive
artificial intelligence
we explain these capacities via a computational cognitive model that we call the intuitive gamer
our findings thus interpret linear relational decoding in transformer
language
language models
our findings thus interpret linear relational decoding in transformer language models as primarily property-based rather than relation-specific
adaptive channel estimation and quantized feedback for ris assisted optical
wireless
wireless communication
adaptive channel estimation and quantized feedback for ris assisted optical wireless communication systems
we investigate the chemical content of 22 well-studied massive protostars from the sofia massive soma star formation survey aiming to identify correlations between
chemical
star clusters
we investigate the chemical content of 22 well-studied massive protostars from the sofia massive soma star formation survey aiming to identify correlations between chemical and physical parameters
first we formally define multiclass local calibration and
establish
local calibration
first we formally define multiclass local calibration and establish its relationship with strong calibration
our system enables users to interact seamlessly with real-world objects using natural gaze fixation from a first-person perspective while providing
augmented
augmented reality
our system enables users to interact seamlessly with real-world objects using natural gaze fixation from a first-person perspective while providing augmented visual cues to confirm intent and leveraging a pretrained vision model and robotic arm for intent recognition and object manipulation
here we introduce a photoelectrical spin readout scheme that detects
spin
spin readout
here we introduce a photoelectrical spin readout scheme that detects spin information stored long-term as trapped electrical charges
spiral features appear across stellar populations of different ages confirming their density-wave nature and producing coherent spirals in both metallicity and mean stellar age distributions-consistent with recent gaia observations of the
milky
massive galaxies
spiral features appear across stellar populations of different ages confirming their density-wave nature and producing coherent spirals in both metallicity and mean stellar age distributions-consistent with recent gaia observations of the milky way
a popular opinion is that much of the contextual influences arise from feedback from higher visual areas whose neurons have larger
receptive
receptive fields
a popular opinion is that much of the contextual influences arise from feedback from higher visual areas whose neurons have larger receptive fields
vacuum decay posits that the universe s apparent
vacuum
vacuum decay
vacuum decay posits that the universe s apparent vacuum is metastable and could transition to a lower-energy state
to address this issue we propose the adaptive
trajectory
motion planning
to address this issue we propose the adaptive trajectory refinement algorithm which consists of two main stages
jetson orin nano remains challenging due to high computational demands especially in real-world scenarios where power latency and
computational
physical computing
jetson orin nano remains challenging due to high computational demands especially in real-world scenarios where power latency and computational resources are critical
we empirically demonstrate that these human mobility network localities are rigorous geometric entities that map directly to geographic localities revealing that human
mobility
travel information
we empirically demonstrate that these human mobility network localities are rigorous geometric entities that map directly to geographic localities revealing that human mobility networks lie on manifolds of dimension 5
machine unlearning mu aims to remove the influence of certain data points from a
trained
continual learning
machine unlearning mu aims to remove the influence of certain data points from a trained model without costly retraining
a convex reformulation for speed planning of a vehicle under the travel
time
optimal control
a convex reformulation for speed planning of a vehicle under the travel time and energy consumption objectives
it also leads to the first non-trivial strongly
polynomial
polynomial time
it also leads to the first non-trivial strongly polynomial dynamic algorithm for minimum mean cycle
this paper provides a nonparametric framework for
causal
causal effects
this paper provides a nonparametric framework for causal inference with categorical outcomes under binary treatment and binary instrument settings
recalling previously experienced movements is essential for a range of activities including sports music and rehabilitation yet little is known about the accuracy and decay of proprioceptive
working
working memory
recalling previously experienced movements is essential for a range of activities including sports music and rehabilitation yet little is known about the accuracy and decay of proprioceptive working memory
our results show that removing coreference
resolution
coreference resolution
our results show that removing coreference resolution results in a 28
that is surprising as this framework is naturally suited for hierarchical control applications in general and
autonomous
autonomous driving
that is surprising as this framework is naturally suited for hierarchical control applications in general and autonomous driving tasks in specific
we propose a framework for assessing lm reasoning efficiency through the lens of logic programming introducing a simple method to align proofs written in natural language -- as generated by an lm -- with shortest proofs found by executing the
logic
mathematical reasoning
we propose a framework for assessing lm reasoning efficiency through the lens of logic programming introducing a simple method to align proofs written in natural language -- as generated by an lm -- with shortest proofs found by executing the logic program
instead in this paper we flexibly derive robust precoding algorithms from given data using
reinforcement
reinforcement learning
instead in this paper we flexibly derive robust precoding algorithms from given data using reinforcement learning
this paper introduces cypress crop yield prediction via regression on prithvi s encoder for satellite sensing a
deep
deep network
this paper introduces cypress crop yield prediction via regression on prithvi s encoder for satellite sensing a deep learning model designed for high-resolution intra-field canola yield prediction
scribe combines domain-specific tools with a self-reflective inference
pipeline
thinking traces
scribe combines domain-specific tools with a self-reflective inference pipeline that supports iterative reasoning tool use and error recovery
our benchmark results reflect general improvements of recommender systems on the public
datasets
preference optimization
our benchmark results reflect general improvements of recommender systems on the public datasets with variable individual performances
we further extend these analyses to two broad families of activation functions and deep
feedforward
recurrent neural networks
we further extend these analyses to two broad families of activation functions and deep feedforward architectures demonstrating that abstract representations naturally arise in all these scenarios
understanding how the human brain progresses from
processing
cognitive neuroscience
understanding how the human brain progresses from processing simple linguistic inputs to performing high-level reasoning is a fundamental challenge in neuroscience
dinosaur photonic crystal cavity interfaces for color center coupling to
triangular
photonic crystal
dinosaur photonic crystal cavity interfaces for color center coupling to triangular nanostructures
in this work we utilize proximal causal inference framework for learning optimal dynamic
treatment
treatment regimes
in this work we utilize proximal causal inference framework for learning optimal dynamic treatment regimes when the unconfoundedness assumption fails
accurate angle-of-arrival aoa estimation is essential for next-generation wireless
communication
channel estimation
accurate angle-of-arrival aoa estimation is essential for next-generation wireless communication systems to enable reliable beamforming high-precision localization and integrated sensing
prompt estimation from prototypes for federated
prompt
prompt tuning
prompt estimation from prototypes for federated prompt tuning of vision transformers
in difference-in-differences did settings with categorical outcomes such as voting occupation or major choices
treatments
treatment effect boundaries
in difference-in-differences did settings with categorical outcomes such as voting occupation or major choices treatments often affect both total counts e
optical variability is a key observational probe for studying the accretion dynamics and central engine physics of active
galactic
galactic nuclei
optical variability is a key observational probe for studying the accretion dynamics and central engine physics of active galactic nuclei agns
a world model is an internal model that simulates how the
world
world models
a world model is an internal model that simulates how the world evolves
prior research examined how llms alter user views yet little work extended beyond one-way influence to address how user input can affect
llm
llm responses
prior research examined how llms alter user views yet little work extended beyond one-way influence to address how user input can affect llm responses and how such bi-directional influence manifests throughout the multi-turn conversations
our key innovation lies in superseding the gradient descent
step
deep learning
our key innovation lies in superseding the gradient descent step with a learnable sigmoid-based operator which inherently enforces non-negativity and boundedness by transforming traditional subtractive updates into multiplicative ones
quadratic truncated random return in distributional lqr positive definiteness
density
truncated random
quadratic truncated random return in distributional lqr positive definiteness density and log-concavity
remarkably however we show that if the system is stabilizable then using this as prior knowledge leads to necessary and sufficient conditions that are weaker than those for
data-driven
data-driven stabilization
remarkably however we show that if the system is stabilizable then using this as prior knowledge leads to necessary and sufficient conditions that are weaker than those for data-driven stabilization without prior knowledge
debiased machine learning typically requires estimation of the
riesz
machine learning
debiased machine learning typically requires estimation of the riesz representer and the regression function
automating the co-design of a robot s morphology and control is a long-standing challenge due to the vast design
space
multi-robot collaboration
automating the co-design of a robot s morphology and control is a long-standing challenge due to the vast design space and the tight coupling between body and behavior
however droplets no longer rebounded at higher weber numbers and
remained
weber numbers
however droplets no longer rebounded at higher weber numbers and remained deposited
we find that despite surfacing errors different
language
large language models llms
we find that despite surfacing errors different language models learn interchangeable representations of numbers that are systematic highly accurate and universal across their hidden states and the types of input contexts
the integrated system effectively addresses challenges
real-time
real-world applications
the integrated system effectively addresses challenges real-time quality assurance
specifically if a quantum walk algorithm designed with the known technique solves the maximum matching problem using o
n
query complexity
specifically if a quantum walk algorithm designed with the known technique solves the maximum matching problem using o n 2- epsilon queries with any constant epsilon 0 and if the underlying classical random walk is independent of an input graph then the guaranteed time complexity is larger than any polynomial of n
infected individuals in some epidemics can remain
asymptomatic
viral replication
infected individuals in some epidemics can remain asymptomatic while still carrying and transmitting the infection
this paper introduces a benchmark combobench evaluating llms capability to translate semantic actions into vr device manipulation sequences across 262 scenarios from four popular
vr
physical virtual
this paper introduces a benchmark combobench evaluating llms capability to translate semantic actions into vr device manipulation sequences across 262 scenarios from four popular vr games half-life alyx into the radius moss book ii and vivecraft
this result shows that even under relaxed assumptions quantum
theory
quantum networks
this result shows that even under relaxed assumptions quantum theory resists reconciliation with classical notions of absolute events reinforcing the foundational significance of wigner s friend-type paradoxes in timelike scenarios
those models give structure to expectations around walking behavior of
groups
human mobility
those models give structure to expectations around walking behavior of groups from pedestrian walking independently to the emergence of a collective intention where group members tended to maintain bounded distance between each other
this paper introduces a stochastic optimal control framework to address these issues
simultaneously
inverse optimal issf
this paper introduces a stochastic optimal control framework to address these issues simultaneously without excessively conservative approximations
these applications have motivated a growing demand for
compact
integrated photonics
these applications have motivated a growing demand for compact reconfigurable vortex arrays with tunable topological charge yet integrating these functionalities into nanophotonic platforms remains elusive
unsupervised learning is therefore a natural approach for exploring the design of
biological
artificial neural
unsupervised learning is therefore a natural approach for exploring the design of biological neural networks and their computations
this work introduces steervlm a lightweight steering module designed to guide vision-language models
vlms
vision transformers
this work introduces steervlm a lightweight steering module designed to guide vision-language models vlms towards outputs that better adhere to desired instructions
ai-powered approaches specifically large language models llms natural
language
ai agents
ai-powered approaches specifically large language models llms natural language processing nlp and generative ai offer transformative solutions and reduce inefficiencies
spiral self-play incremental racing algorithm for learning in
multi-drone
multi-drone racing
spiral self-play incremental racing algorithm for learning in multi-drone competitions
our results suggest that fishing pressure in tandem with
climate
climate change
our results suggest that fishing pressure in tandem with climate change substantially reduces ecosystem resilience highlighting the importance of sustainable harvest strategies in a changing climate
during training text tokens in each image-caption pair are masked at a randomly chosen ratio and a decoder conditioned on
visual
vision-language models vlms
during training text tokens in each image-caption pair are masked at a randomly chosen ratio and a decoder conditioned on visual features is trained to reconstruct the original text
this research opens new avenues for enhancing the performance and reliability of autonomous
racing
multi-drone racing
this research opens new avenues for enhancing the performance and reliability of autonomous racing drones in increasingly complex and competitive scenarios
this work underscores the potential of cas as proactive human-machine interface hmi interventions demonstrating how natural language can support context-aware
interaction
human-ai interaction
this work underscores the potential of cas as proactive human-machine interface hmi interventions demonstrating how natural language can support context-aware interaction during automated driving
recent approaches to modeling such objects either rely on optimization-based
reconstruction
image reconstruction
recent approaches to modeling such objects either rely on optimization-based reconstruction pipelines that require dense-view supervision or on feed-forward generative models that produce coarse geometric approximations and often overlook surface texture
the localization of magnetic moments is robust even in non-equilateral
nanoflake
magnetic ground
the localization of magnetic moments is robust even in non-equilateral nanoflake geometries highlighting their intrinsic stability regardless of the high symmetry of the hosting structure
to address these limitations a brain-computer interface bci system is developed using a non-invasive electroencephalogram
eeg
electroencephalography eeg
to address these limitations a brain-computer interface bci system is developed using a non-invasive electroencephalogram eeg headband focuscalm to record brainwave activity under attentive and non-attentive states
the model outputs per-object recall probabilities that can drive interface adjustments when predicted
recall
object recall
the model outputs per-object recall probabilities that can drive interface adjustments when predicted recall falls
however the performance of all previous digital quantum simulations has been matched by classical methods and it has thus far remained unclear whether near-term intermediate-scale
quantum
quantum technologies
however the performance of all previous digital quantum simulations has been matched by classical methods and it has thus far remained unclear whether near-term intermediate-scale quantum hardware could offer any computational advantage in this area
using a simulation model based on the prisoner s dilemma and quantal response equilibrium we analyze how variations in these
learning
complex networks
using a simulation model based on the prisoner s dilemma and quantal response equilibrium we analyze how variations in these learning rates affect the emergence of large-scale network structures
in the deep-strong coupling dsc regime the
interaction
light-matter interactions
in the deep-strong coupling dsc regime the interaction between light and matter exceeds their bare frequencies leading to an effective decoupling
we describe how weak phase modulations applied to classical
coherent
coherent control
we describe how weak phase modulations applied to classical coherent light in specially modified linear interferometers can be used to perform primitive computational tasks
our method can also handle real-world constraints by restricting changes to immutable and categorical features such as age gender sex height and other related characteristics such as the
case
real-world datasets
our method can also handle real-world constraints by restricting changes to immutable and categorical features such as age gender sex height and other related characteristics such as the case for a health-based dataset
however discovering insights from this complex landscape is exploratory conceptually challenging and requires expertise in
social
social media
however discovering insights from this complex landscape is exploratory conceptually challenging and requires expertise in social media mining and visualization
this provides a flexible technology compensating limited collected brightnesses of single-photon sources as well as a thorough investigation of
single-photon
single photons
this provides a flexible technology compensating limited collected brightnesses of single-photon sources as well as a thorough investigation of single-photon statistics advantage scenarios over poisson-distributed statistics
the theoretical analysis presented in this work focuses on novel
convergence
convergence guarantees
the theoretical analysis presented in this work focuses on novel convergence estimates for the sga and lrsga methods including parameter bounds
bnlf performs late fusion by modelling the sentiment predictions from multiple
llms
large language models llms
bnlf performs late fusion by modelling the sentiment predictions from multiple llms as probabilistic nodes within a bayesian network
this paper develops a unified framework for identifying
spatial
spatial treatment
this paper develops a unified framework for identifying spatial and temporal boundaries of treatment effects in difference-in-differences designs
we show that the cavity reflection approach enables high-fidelity spin
readout
spin readout
we show that the cavity reflection approach enables high-fidelity spin readout even when the t center only has a modest cyclicity
our study contributes to the scheduling and combinatorial optimization literature with new heuristics discovered by leveraging the power of large
language
language models
our study contributes to the scheduling and combinatorial optimization literature with new heuristics discovered by leveraging the power of large language models llms