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by explicitly retaining the quantum coherence of the coupled electron-phonon-photon dynamics our model describes a two-stage buildup of entanglement - first between signal and idler photons and subsequently between idler
photons
quantum dot
by explicitly retaining the quantum coherence of the coupled electron-phonon-photon dynamics our model describes a two-stage buildup of entanglement - first between signal and idler photons and subsequently between idler photons mediated by material coherence
bi-isotropic effects on hybrid surface polaritons in
bilayer
phonon polaritons
bi-isotropic effects on hybrid surface polaritons in bilayer configurations
the european space agency esa and the european space resources innovation centre esric created the space resources challenge to invite researchers and companies to propose innovative solutions for multi-robot
systems
robotic systems
the european space agency esa and the european space resources innovation centre esric created the space resources challenge to invite researchers and companies to propose innovative solutions for multi-robot systems mrs space prospection
results show that deep industrial decarbonization is technically feasible led by electrification but
competitiveness
electricity demand
results show that deep industrial decarbonization is technically feasible led by electrification but competitiveness depends strongly on policy choices
this work introduces steervlm a lightweight steering module designed to guide vision-language models
vlms
autonomous driving
this work introduces steervlm a lightweight steering module designed to guide vision-language models vlms towards outputs that better adhere to desired instructions
we focus on an important safety problem that is already challenging for
humans
ai systems
we focus on an important safety problem that is already challenging for humans fact-verification of ai outputs
strong kantorovich duality for quantum optimal transport with generic cost and
optimal
quantum advantage
strong kantorovich duality for quantum optimal transport with generic cost and optimal couplings on quantum bits
we show here that in models equipped with a learning rule inferred from neurobiological data spurious overlaps collectively reduce the mean synaptic inputs to
neurons
artificial neural
we show here that in models equipped with a learning rule inferred from neurobiological data spurious overlaps collectively reduce the mean synaptic inputs to neurons and that this mean reduction causes in turn an increase in storage capacity through a sparsening of network activity
modulating the free-electron wave function with light brings new opportunities to create attosecond electron pulse trains to probe the
quantum
quantum emitters
modulating the free-electron wave function with light brings new opportunities to create attosecond electron pulse trains to probe the quantum coherence of systems with significantly improved spatial resolution and to generate classical and non-classical states of light with wide tunability
while this approach has advantages such as independence from appearance the
existing
existing methods
while this approach has advantages such as independence from appearance the existing methods may break down under real-world conditions
reinforcement learning rl is widely used to produce robust robotic manipulation
policies
motion planning
reinforcement learning rl is widely used to produce robust robotic manipulation policies but fine-tuning vision-language-action vla models with rl can be unstable due to inaccurate value estimates and sparse supervision at intermediate steps
for fluorescence-based readout we selectively couple one of the t center spin-conserving transitions to a single-mode
photonic
photonic crystal
for fluorescence-based readout we selectively couple one of the t center spin-conserving transitions to a single-mode photonic cavity exploiting the enhancement of the fluorescence emission and cyclicity
furthermore real-world experiments confirm that the
robot
robotic manipulation
furthermore real-world experiments confirm that the robot can safely pass through narrow passages while maintaining rapid planning performance
approximating human preferences using a multi-judge
learned
preference optimization
approximating human preferences using a multi-judge learned system
to address these limitations we introduce roboos-next a unified memory-based framework for lifelong scalable and robust
multi-robot
multi-robot collaboration
to address these limitations we introduce roboos-next a unified memory-based framework for lifelong scalable and robust multi-robot collaboration
however the up-to-date runtime estimates for utility-scale applications on certain quantum
hardware
quantum algorithm
however the up-to-date runtime estimates for utility-scale applications on certain quantum hardware systems are in the order of years rendering quantum computations impractical
the core of pisac lies in deriving a closed-form safety bound that explicitly links
isac
communication isac
the core of pisac lies in deriving a closed-form safety bound that explicitly links isac transmit power to sensing uncertainty based on the cram er-rao bound and occupancy inflation principles
dynamic spatial treatment effects and network fragility theory and
evidence
spatial treatment
dynamic spatial treatment effects and network fragility theory and evidence from european banking
a hierarchical architecture combining one orchestrator with three specialist agents uses the react pattern for iterative reasoning enabling dynamic coordination without hardcoded workflows while integrating google calendar for
context-aware
context engineering
a hierarchical architecture combining one orchestrator with three specialist agents uses the react pattern for iterative reasoning enabling dynamic coordination without hardcoded workflows while integrating google calendar for context-aware deadline extraction
the influence of the moving mass is described in body-frame and included as states in both an additional kinematic equation and as part of the coupled rigid-body kinetics of the
underwater
moving mass
the influence of the moving mass is described in body-frame and included as states in both an additional kinematic equation and as part of the coupled rigid-body kinetics of the underwater vehicle
reading radio from camera visually-grounded
lightweight
channel state information
reading radio from camera visually-grounded lightweight and interpretable rssi prediction
splitflow flow decomposition for inversion-free
text-to-image
image generation
splitflow flow decomposition for inversion-free text-to-image editing
these results demonstrate that assembly history rather than halo mass alone critically shapes the present-day kinematic and morphological
diversity
galaxy cgm
these results demonstrate that assembly history rather than halo mass alone critically shapes the present-day kinematic and morphological diversity of dwarf galaxies
to address the non-convex and temporally coupled optimization problem we propose a mixture-of-experts-augmented soft actor-critic moe-sac
algorithm
deep reinforcement learning
to address the non-convex and temporally coupled optimization problem we propose a mixture-of-experts-augmented soft actor-critic moe-sac algorithm that employs a sparse top-k gated mixture-of-shallow-experts architecture to represent multimodal policy distributions arising from the conflicting optimization objectives
more recently a new class of prefix queries was introduced together with reductions that among others transform a simple tradeoff for prefix-select
queries
query complexity
more recently a new class of prefix queries was introduced together with reductions that among others transform a simple tradeoff for prefix-select queries into a suffix array tradeoff matching state-of-the-art space and query-time bounds while achieving sublinear construction time
accurate estimation of motion information is crucial in
diverse
pose estimation
accurate estimation of motion information is crucial in diverse computational imaging and computer vision applications
this gives rise to a new family of explicitly constructed
graphs
regular graphs
this gives rise to a new family of explicitly constructed graphs which may have other applications
enhancing the reachability of variational quantum
algorithms
fault-tolerant quantum
enhancing the reachability of variational quantum algorithms via input-state design
those models give structure to expectations around walking behavior of groups from pedestrian walking independently to the emergence of a
collective
collective action
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
observed changes in exponential rates come from growing public awareness governmental restrictions and their later relaxation annual holidays seasonal variation emergence of new
viral
infectious individuals
observed changes in exponential rates come from growing public awareness governmental restrictions and their later relaxation annual holidays seasonal variation emergence of new viral variants and from mass vaccination
debiased machine learning typically requires estimation of the
riesz
riesz regression
debiased machine learning typically requires estimation of the riesz representer and the regression function
magnetic field-controlled thz modulation in uniaxial
anisotropic
magnetic anisotropy
magnetic field-controlled thz modulation in uniaxial anisotropic spin-valves emitters
this study addresses the critical challenge of preserving the intrinsic optical
characteristics
optical interference
this study addresses the critical challenge of preserving the intrinsic optical characteristics of 2d tmdcs during fib patterning
this manuscript revisits the essence of generative image fusion under the inspiration of human cognitive laws and proposes a novel infrared and visible image
fusion
vision transformers
this manuscript revisits the essence of generative image fusion under the inspiration of human cognitive laws and proposes a novel infrared and visible image fusion method termed hclfuse
5 nm schottky contacts that ultimately enabled
breakdown
breakdown voltage
5 nm schottky contacts that ultimately enabled breakdown voltage of 3
noisy payoffs can permit the stable co-existence of cooperators and defectors in the prisoner s dilemma for example as well as bistability in snowdrift games and stable limit cycles in rock-paper-scissors
games
game theory
noisy payoffs can permit the stable co-existence of cooperators and defectors in the prisoner s dilemma for example as well as bistability in snowdrift games and stable limit cycles in rock-paper-scissors games -- dynamical phenomena that cannot occur in the absence of noise
these results provide quantitative guidance for allocating green-finance
resources
green finance
these results provide quantitative guidance for allocating green-finance resources elevating green-innovation efficiency and designing regionally coordinated mitigation policies
the dataset is carefully constructed with temporal splits comprehensive features and strict leakage prevention to support realistic and reproducible
machine
machine learning
the dataset is carefully constructed with temporal splits comprehensive features and strict leakage prevention to support realistic and reproducible machine learning evaluation
in task and motion planning high-level task
planning
mobile robots
in task and motion planning high-level task planning is done over an abstraction of the world to enable efficient search in long-horizon robotics problems
these results complement the straightforward observation that solution discovery for the studied problems is fixed-parameter tractable when the budget b is included in the parameter in particular parameterized by cliquewidth b where the cliquewidth of a graph is at most any of the studied parameters and provide a near-complete fixed-parameter tractability meta-theorems investigation for solution
discovery
solution discovery
these results complement the straightforward observation that solution discovery for the studied problems is fixed-parameter tractable when the budget b is included in the parameter in particular parameterized by cliquewidth b where the cliquewidth of a graph is at most any of the studied parameters and provide a near-complete fixed-parameter tractability meta-theorems investigation for solution discovery problems for mso- and fo-definable graph problems and structural parameters larger than cliquewidth
twin-field quantum key distribution protocols security and
open
quantum dot
twin-field quantum key distribution protocols security and open problems
we formulate the problem as the minimization of the total transmit power subject to signal-to-interference-plus-noise ratio sinr constraints for
communication
channel estimation
we formulate the problem as the minimization of the total transmit power subject to signal-to-interference-plus-noise ratio sinr constraints for communication users and mean-squared-error mse constraints for radar sensing
we formulate the problem as a markov decision
process
decision process
we formulate the problem as a markov decision process and analyze the structure of the optimal policy pi star for l 3 extending insights to arbitrary l
sites burned within the last five years supported fewer
species
ecological communities
sites burned within the last five years supported fewer species primarily dominated by generalists while mid- to late-successional sites exhibited greater richness and a higher proportion of specialists
these results establish arp as a robust and scalable approach for
coherent
coherent control
these results establish arp as a robust and scalable approach for coherent control in inas qd ensembles with potential applications for ultrafast and broadband optical communication in the thz spectral region
firstly our deep learning model predicts correspondence probabilities and reliabilities for every pair of a trajectory and
sensor
autonomous driving
firstly our deep learning model predicts correspondence probabilities and reliabilities for every pair of a trajectory and sensor measurements
geometric priors are incorporated into image annotations to constrain the vlm
action
vision-language models vlms
geometric priors are incorporated into image annotations to constrain the vlm action space and improve decision quality
we further evaluate a range of strategies for aligning
visual
multi-goal visual
we further evaluate a range of strategies for aligning visual representations and introduce a simple yet effective method that mitigates degradation and yields improved generalization to out-of-distribution ood scenarios
our results show that removing coreference
resolution
coreference resolution
our results show that removing coreference resolution results in a 28
we then propose novel estimators that are
asymptotically
asymptotic normality
we then propose novel estimators that are asymptotically efficient achieving this theoretical bound
compared with the local gaussian correlation network among positive tails and the conventional pearson correlation network the properties of the local gaussian
correlation
local gaussian correlation
compared with the local gaussian correlation network among positive tails and the conventional pearson correlation network the properties of the local gaussian correlation network among negative tails are more sensitive to the stock market risks
these findings suggest that resting-state eeg connectivity patterns can index stable
cognitive
working memory
these findings suggest that resting-state eeg connectivity patterns can index stable cognitive traits such as creativity
our results advance the understanding of transient dynamics across network structures and input types extend the existing theory to more general settings and provide practical guidance for optimizing
transient
transient dynamics
our results advance the understanding of transient dynamics across network structures and input types extend the existing theory to more general settings and provide practical guidance for optimizing transient responses
6g wireless networks are poised to seamlessly integrate
communication
wireless communication
6g wireless networks are poised to seamlessly integrate communication computing localization and sensing functionalities ensuring high reliability and trustworthiness
for which all trajectories converge to a disease-free
equilibrium
evolutionary dynamics
for which all trajectories converge to a disease-free equilibrium or convergence to a unique endemic equilibrium
weighted food webs make computing phylogenetic
diversity
food web
weighted food webs make computing phylogenetic diversity so much harder
in addition to the exact result for the mathcal r_0 we provide an approximation denoted as tau which is easier to compute and more straightforward to interpret in terms of the parameters of the system and shares most of the expected properties of the
basic
basic reproduction
in addition to the exact result for the mathcal r_0 we provide an approximation denoted as tau which is easier to compute and more straightforward to interpret in terms of the parameters of the system and shares most of the expected properties of the basic reproduction number
for this problem we develop a direct debiased machine
learning
machine learning
for this problem we develop a direct debiased machine learning framework with an end-to-end algorithm
a framework for the systematic evaluation of
obstacle
dynamic obstacles
a framework for the systematic evaluation of obstacle avoidance and object-aware controllers
deep neural networks dnns have been used to model complex optimization problems in many applications yet have difficulty guaranteeing
solution
neural network
deep neural networks dnns have been used to model complex optimization problems in many applications yet have difficulty guaranteeing solution optimality and feasibility despite training on large datasets
for example existing studies often employ maximum likelihood or covariate
balancing
ate estimation
for example existing studies often employ maximum likelihood or covariate balancing to estimate e_0 but these approaches may not be optimal for accurately estimating h_0 or the ate
specifically we first construct a dataset tailored for training and evaluating secure code
review
code review
specifically we first construct a dataset tailored for training and evaluating secure code review capabilities
the infection propagates with independent random
time
viral replication
the infection propagates with independent random time increments i
generate with low randomness and adjusts its predicted temperature and top-p on a token-by-token basis opening a new paradigm for steerable and interactive
llm
large language models llms
generate with low randomness and adjusts its predicted temperature and top-p on a token-by-token basis opening a new paradigm for steerable and interactive llm decoding
during massive star formation dense gas undergoes
chemical
star clusters
during massive star formation dense gas undergoes chemical evolution producing both simple and complex organic molecules coms characteristic of hot molecular cores
our cross-system comparison also suggests actionable ways that cooperation can be improved in large-scale common pool resources problems like
climate
climate change
our cross-system comparison also suggests actionable ways that cooperation can be improved in large-scale common pool resources problems like climate change
to address these shortcomings we propose scout scenario coverage oversight and understanding tool a lightweight surrogate model designed to predict scenario
coverage
scenario coverage
to address these shortcomings we propose scout scenario coverage oversight and understanding tool a lightweight surrogate model designed to predict scenario coverage labels directly from an agent s latent sensor representations
in this work we study data-driven stabilization of linear time-invariant systems using
prior
predictive control
in this work we study data-driven stabilization of linear time-invariant systems using prior knowledge of system-theoretic properties specifically stabilizability and controllability
although the evaluation was limited to simulation these results establish predictive processing as a universal and scalable computational principle pointing toward robust flexible and autonomous caregiving robots while offering theoretical insight into the human brain s ability to achieve
flexible
brain-computer interface
although the evaluation was limited to simulation these results establish predictive processing as a universal and scalable computational principle pointing toward robust flexible and autonomous caregiving robots while offering theoretical insight into the human brain s ability to achieve flexible adaptation in uncertain real-world environments
soft constraints allow temporary violations within predefined safety margins to accommodate uncertainty and competing operational demands albeit at a cost such as increased wear or higher
operational
soft constraints
soft constraints allow temporary violations within predefined safety margins to accommodate uncertainty and competing operational demands albeit at a cost such as increased wear or higher operational expenses
by grounding llm reasoning in a deterministic symbolic engine symcode represents a key step towards more accurate and trustworthy
ai
llm inference
by grounding llm reasoning in a deterministic symbolic engine symcode represents a key step towards more accurate and trustworthy ai in formal domains
wilson-cowan and amari-type models capture
nonlinear
neural codes
wilson-cowan and amari-type models capture nonlinear neural population dynamics providing a fundamental framework for modeling how sensory and other exogenous inputs shape activity in neural tissue
theoretical properties including bounds on
bias
debiased machine learning
theoretical properties including bounds on bias estimation errors and improvements in prediction accuracy are provided
this paper introduces a likelihood ratio lr -type test that possesses the
robustness
maximum likelihood
this paper introduces a likelihood ratio lr -type test that possesses the robustness properties of c alpha -type procedures in an extremum estimation setting
importantly i its width scales as the input dimension making it more prone to feature learning than ultra wide
networks
deep learning
importantly i its width scales as the input dimension making it more prone to feature learning than ultra wide networks and more expressive than narrow ones or with fixed embedding layers and ii we focus on the challenging interpolation regime where the number of trainable parameters and data are comparable which forces the model to adapt to the task
first a diffusion model is trained to synthesize sketch
images
image generation
first a diffusion model is trained to synthesize sketch images from 2d poses projected from 3d human poses mimicking disproportionate human structures in sketches
recent work has shown that different large language models llms converge to similar and accurate input embedding
representations
large language
recent work has shown that different large language models llms converge to similar and accurate input embedding representations for numbers
existing benchmarks have widely leveraged high school math competitions for evaluating
mathematical
mathematical reasoning
existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning capabilities of large language models llms
to address this limitation this paper studies llm agents in task collaboration particularly under the condition of information asymmetry where
agents
llm agents
to address this limitation this paper studies llm agents in task collaboration particularly under the condition of information asymmetry where agents have disparities in their knowledge and skills and need to work together to complete a shared task
since the conceptual inception numerous sequential
stopping
stopping rules
since the conceptual inception numerous sequential stopping rules have been introduced and many more are currently being refined and developed
the performance of federated learning fl over wireless networks critically depends on accurate and timely channel state information
csi
channel state information csi
the performance of federated learning fl over wireless networks critically depends on accurate and timely channel state information csi across distributed devices
these subclumps exhibit parabolic morphologies consistent with ram-pressure-confined droplets with their heads tending to point toward the
galactic
star-forming region
these subclumps exhibit parabolic morphologies consistent with ram-pressure-confined droplets with their heads tending to point toward the galactic plane
this study demonstrates that providing language models with pragmatic theories as prompts is an effective in-context
learning
language agents
this study demonstrates that providing language models with pragmatic theories as prompts is an effective in-context learning approach for tasks to understand implied meanings
in ate estimation the balancing weights and the regression functions of the outcome play important roles where the balancing weights are referred to as the
riesz
riesz regression
in ate estimation the balancing weights and the regression functions of the outcome play important roles where the balancing weights are referred to as the riesz representer bias-correction term and clever covariates depending on the context
their outstanding performance is achieved by stabilizing their
frequency
optical interference
their outstanding performance is achieved by stabilizing their frequency to ultra-low expansion ule optical cavities
most prior work focuses on minimizing its time
complexity
time complexity
most prior work focuses on minimizing its time complexity i
the architecture incorporates a brain-region to image-feature cross-attention mechanism enabling nonlinear mappings between high-dimensional deep network features and semantic
patterns
human brain
the architecture incorporates a brain-region to image-feature cross-attention mechanism enabling nonlinear mappings between high-dimensional deep network features and semantic patterns encoded in the brain activity
on the impact of weight discretization in qubo-based
svm
support vector machines
on the impact of weight discretization in qubo-based svm training
despite the widespread adoption of parallel join-based trees a major drawback of previous work on such
data
data structure
despite the widespread adoption of parallel join-based trees a major drawback of previous work on such data structures is the inefficiency of their input output i o access patterns
in this work we apply uniaxial tensile and compressive
strain
strain engineering
in this work we apply uniaxial tensile and compressive strain to thin 1t-tas2 flakes using a flexible device-compatible platform and systematically investigate the strain-dependent behavior of the nearly commensurate nc to incommensurate ic cdw phase transition
in contrast we show that a clt holds for sgd iterates when the number of iterations grows as t gtrsim d 1 delta for any delta 0 significantly extending the dimensional regime permitted by prior works while improving
computational
computationally efficient
in contrast we show that a clt holds for sgd iterates when the number of iterations grows as t gtrsim d 1 delta for any delta 0 significantly extending the dimensional regime permitted by prior works while improving computational efficiency
previous length-constrained flow shortcuts haeupler hershkowitz li roeyskoe saranurak
stoc
maximum flow
previous length-constrained flow shortcuts haeupler hershkowitz li roeyskoe saranurak stoc 24 incur a large constant in the length slack which would lead to a large approximation factor
tight lower bounds for central string queries in
compressed
compressed indexing
tight lower bounds for central string queries in compressed space
in the multi-user downlink precoding enables the reuse of frequencies across spatially separated users greatly improving
spectral
spectral efficiency
in the multi-user downlink precoding enables the reuse of frequencies across spatially separated users greatly improving spectral efficiency
topological decoding of grid cell activity via
path
grid cell
topological decoding of grid cell activity via path lifting to covering spaces
wimhf provides a human-centered analysis method for practitioners to better understand and use
preference
preference data
wimhf provides a human-centered analysis method for practitioners to better understand and use preference data
space time and altruism in pandemics and the
climate
climate change
space time and altruism in pandemics and the climate emergency
our gridworld simulation shows that through independent
learning
reinforcement learning
our gridworld simulation shows that through independent learning the agent and human discover their optimal oversight roles
in contrast imitation learning il is easy to train but often underperforms due to its
offline
learning agents
in contrast imitation learning il is easy to train but often underperforms due to its offline nature
for large detailed energy system models this is impossible with
traditional
power systems
for large detailed energy system models this is impossible with traditional methods leading researchers to reduce complexity with linearized investments and zonal or temporal aggregation