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to mitigate the downlink peak-to-average power ratio increase caused by fdma we further develop a multi-user downlink ce transmission scheme including multiple access mechanism
downlink
uplink communication
to mitigate the downlink peak-to-average power ratio increase caused by fdma we further develop a multi-user downlink ce transmission scheme including multiple access mechanism downlink control information design and corresponding system-level implementation which ensures compatibility with the new radio standard
cooperative task spaces for multi-arm manipulation
control
robotic manipulation
cooperative task spaces for multi-arm manipulation control based on similarity transformations
dynamic beamforming and power allocation in isac via deep
reinforcement
deep reinforcement
dynamic beamforming and power allocation in isac via deep reinforcement learning
moreover we show that a poly-logarithmic approximation ratio and hence an approximation
ratio
approximation ratio
moreover we show that a poly-logarithmic approximation ratio and hence an approximation ratio below the adaptivity gap can be achieved by a randomized algorithm with quasi-polynomial running time
in some bulges we also find up to a 32 of
stars
bulge stars
in some bulges we also find up to a 32 of stars that migrated from the disk due to secular evolution with a median of 10
this requirement is tightly linked to how rapidly the
channel
channel state information
this requirement is tightly linked to how rapidly the channel gains vary i
in this work we extend our previous work on the extrapolation of single-time observables to demonstrate an efficient scheme for computing two-time impurity correlation functions by combining the non-markovian quantum mpemba effect nmqmpe with a dynamical map-based framework for
open
open quantum
in this work we extend our previous work on the extrapolation of single-time observables to demonstrate an efficient scheme for computing two-time impurity correlation functions by combining the non-markovian quantum mpemba effect nmqmpe with a dynamical map-based framework for open quantum systems
8-ev femtosecond laser through cascaded third-harmonic
generation
nonlinear optical
8-ev femtosecond laser through cascaded third-harmonic generation which operates at a repetition rate of 1 mhz and delivers a photon flux of approximately 1012 photons s
we present combined jwst nirspec and miri mrs integral field spectroscopy data of the nuclear and circumnuclear regions of the highly dust obscured seyfert 2 galaxy ngc 7582 which is part of the
sample
dark matter
we present combined jwst nirspec and miri mrs integral field spectroscopy data of the nuclear and circumnuclear regions of the highly dust obscured seyfert 2 galaxy ngc 7582 which is part of the sample of agn in the galaxy activity torus and outflow survey gatos
we employ in-game performance scores as quantitative
metrics
evaluation metrics
we employ in-game performance scores as quantitative metrics to assess performance across different task types
based on the real-world hierarchical structure of resource allocation this paper presents a coupled dynamic model of resource allocation and epidemic spreading that incorporates a role-based division of network nodes into
resource
resource allocation
based on the real-world hierarchical structure of resource allocation this paper presents a coupled dynamic model of resource allocation and epidemic spreading that incorporates a role-based division of network nodes into resource allocators and recipients
these results highlight the significant room for improving the mathematical
reasoning
models llms
these results highlight the significant room for improving the mathematical reasoning in current llms
this tradeoff leaves neutral atom systems stuck between slow but accurate
readout
atom interferometry
this tradeoff leaves neutral atom systems stuck between slow but accurate readout and fast but unreliable readout
extensive experiments demonstrate that oracleagent achieves superior performance across a range of multimodal reasoning and generation tasks surpassing leading mainstream multimodal large
language
large language
extensive experiments demonstrate that oracleagent achieves superior performance across a range of multimodal reasoning and generation tasks surpassing leading mainstream multimodal large language models mllms e
this approach allows the system to be characterised by its experimental parameters and
quantum
quantum technologies
this approach allows the system to be characterised by its experimental parameters and quantum states rather than just its detector data
we consistently observe that the drift rate increases with the variance and the
dimension
task performance
we consistently observe that the drift rate increases with the variance and the dimension of the data in the task-irrelevant subspace
numerous mitigation methods exist for quantum noise suppression making it challenging to identify the optimum approach for a specific application especially as ongoing advances in hardware tuning and error correction are expected to reduce logical
error
fault-tolerant quantum
numerous mitigation methods exist for quantum noise suppression making it challenging to identify the optimum approach for a specific application especially as ongoing advances in hardware tuning and error correction are expected to reduce logical error rates
moreover we quantitatively interpret our components from a neuroscience perspective and analyze the associations between different visual
patterns
cognitive neuroscience
moreover we quantitatively interpret our components from a neuroscience perspective and analyze the associations between different visual patterns and brain functions
we also report that strikingly a slight misalignment of laser polarization induces an additional super
resonance
phonon polaritons
we also report that strikingly a slight misalignment of laser polarization induces an additional super resonance that selectively populates the orthogonal exciton state without altering the nominal excitation polarization
the local convergence of such optimization algorithms on functions that have lipschitz continuous p th derivatives and are uniformly convex of order q has been studied by doikov and
nesterov
gradient descent
the local convergence of such optimization algorithms on functions that have lipschitz continuous p th derivatives and are uniformly convex of order q has been studied by doikov and nesterov math
the performance of artificial intelligence ai
systems
machine learning
the performance of artificial intelligence ai systems fundamentally depends on high-quality training data
energy-related problems including energy deficiency and issues with wind and solar facilities rank high as combined
climate
climate change
energy-related problems including energy deficiency and issues with wind and solar facilities rank high as combined climate and land use risks
nowcasting and aggregation why small euro
area
european banking
nowcasting and aggregation why small euro area countries matter
we decompose the observed joint probability of outcomes and treatment into marginal probabilities of potential outcomes and treatment and association parameters that capture selection
bias
bias-correction term
we decompose the observed joint probability of outcomes and treatment into marginal probabilities of potential outcomes and treatment and association parameters that capture selection bias due to unobserved heterogeneity
large language models llms are catalyzing the development of autonomous ai research
agents
llm agents
large language models llms are catalyzing the development of autonomous ai research agents for scientific and engineering discovery
the system features a counter-propagating beam at the same wavelength as the
quantum
quantum emitters
the system features a counter-propagating beam at the same wavelength as the quantum state which simultaneously actively stabilizes the cavity and after transmission acts as the local oscillator for homodyne detection
while large language models llms offer opportunities in document
understanding
language models
while large language models llms offer opportunities in document understanding current systems struggle with complex multi-page visual documents particularly in fine-grained reasoning over elements and pages
this representational inefficiency potentially limits the agent s adaptability and
generalization
abstract representations
this representational inefficiency potentially limits the agent s adaptability and generalization capacity
we present a deep reinforcement learning framework based on proximal
policy
deep reinforcement learning
we present a deep reinforcement learning framework based on proximal policy optimization ppo for autonomous qos-aware load balancing implemented end-to-end in a lightweight pure-python simulation environment
we present results from crocodile-dwarf a suite of cosmological zoom-in hydrodynamic simulations of isolated field dwarf galaxies with halo
masses
massive galaxies
we present results from crocodile-dwarf a suite of cosmological zoom-in hydrodynamic simulations of isolated field dwarf galaxies with halo masses of sim10 10 m_ odot at z 0 performed with the textsc gadget4-osaka code
phylogenetic inference the task of reconstructing how related
sequences
phylogenetic tree
phylogenetic inference the task of reconstructing how related sequences evolved from common ancestors is a central task in evolutionary genomics
the use of magnetic nanographenes as building blocks for artificial spin lattices is enabling the exploration of flagship model hamiltonians of one-dimensional
quantum
quantum technologies
the use of magnetic nanographenes as building blocks for artificial spin lattices is enabling the exploration of flagship model hamiltonians of one-dimensional quantum magnetism with an unprecedented degree of control
sentiment analysis of social media data for predicting consumer behavior trends using
machine
machine learning
sentiment analysis of social media data for predicting consumer behavior trends using machine learning
networks of coupled nonlinear oscillators are emerging as powerful physical platforms for implementing
ising
ising machines
networks of coupled nonlinear oscillators are emerging as powerful physical platforms for implementing ising machines
long-horizon contact-rich bimanual manipulation presents a significant challenge requiring complex coordination involving a mixture of parallel execution and sequential
collaboration
multi-robot collaboration
long-horizon contact-rich bimanual manipulation presents a significant challenge requiring complex coordination involving a mixture of parallel execution and sequential collaboration between arms
analyzing such data is crucial for understanding phenomena such as opinion
dynamics
diffusion models
analyzing such data is crucial for understanding phenomena such as opinion dynamics community formation and information diffusion
experiments on the movielens 100k and 1m datasets show consistent improvements over state-of-the-art baselines in precision ndcg and map while demonstrating
robustness
real-world datasets
experiments on the movielens 100k and 1m datasets show consistent improvements over state-of-the-art baselines in precision ndcg and map while demonstrating robustness for users with limited interaction history
by openly releasing all models datasets code and checkpoints
gaperon
open-source models
by openly releasing all models datasets code and checkpoints gaperon establishes a reproducible foundation for exploring the trade-offs between data curation evaluation safety and openness in multilingual language model development
our results establish the learning algorithm as a primary determinant of emergent computation revealing how reward-based
optimization
reinforcement learning
our results establish the learning algorithm as a primary determinant of emergent computation revealing how reward-based optimization autonomously discovers sophisticated dynamical mechanisms that are less accessible to direct gradient-based optimization
we derive nash strategies under bi-directional mutation and subsequently consider the
special
game theory
we derive nash strategies under bi-directional mutation and subsequently consider the special case of unidirectional mutation
brain imaging combined with machine learning may help identify more
objective
surrogate brain
brain imaging combined with machine learning may help identify more objective patterns linked to asd
in this work we take a step toward building a truly accurate
world
world models
in this work we take a step toward building a truly accurate world model by addressing a fundamental yet open problem constructing a model that can fully clone and overfit to a deterministic 3d world
to facilitate valid uncertainty quantification and hypothesis testing on matching decisions we further
develop
debiased machine learning
to facilitate valid uncertainty quantification and hypothesis testing on matching decisions we further develop a general debiasing and projection framework for arbitrary linear forms of the reward matrix deriving asymptotic normality with finite-sample guarantees under matching-induced dependent sampling
in this paper we systematically evaluate llms reasoning
capabilities
llm agents
in this paper we systematically evaluate llms reasoning capabilities in the normative domain from both logical and modal perspectives
in this work we measured the sc gap in high-quality single crystal of beta-pdbi2 by using high-resolution laser angle-resolved
photoemission
photoemission spectroscopy
in this work we measured the sc gap in high-quality single crystal of beta-pdbi2 by using high-resolution laser angle-resolved photoemission spectroscopy below tc
while cave automatic virtual environment cave systems have long enabled room-scale virtual
reality
virtual reality
while cave automatic virtual environment cave systems have long enabled room-scale virtual reality and various kinds of interactivity their content has largely remained predetermined
to address this challenge the proposed framework divides the inspection task into a generating the initial global view-plan for region of interests based on a historical map and b local
view
visual navigation
to address this challenge the proposed framework divides the inspection task into a generating the initial global view-plan for region of interests based on a historical map and b local view replanning to adapt to the current morphology of the inspection scene
basicavsr arbitrary-scale video super-resolution via image priors and enhanced
motion
image reconstruction
basicavsr arbitrary-scale video super-resolution via image priors and enhanced motion compensation
the results of the adam challenge - the most comprehensive amd detection from rgb fundus
images
rgb fundus
the results of the adam challenge - the most comprehensive amd detection from rgb fundus images research competition and open dataset to date - serve as a benchmark for our evaluation
beyond summarising comparisons we analyse reported performance metrics using
mixed-effects
mixed-effects regression
beyond summarising comparisons we analyse reported performance metrics using mixed-effects modelling to investigate potential characteristics that can explain and quantify observed differences including application area study year sample size number of predictors and neural network complexity
these challenges reveal key limitations of standard numerical techniques in multi-agent
control
linear control
these challenges reveal key limitations of standard numerical techniques in multi-agent control and underscore the need for more robust nonlinear strategies for coordinating interacting agents
a toy model-based experiment shows that def can identify multiple
patterns
temporal patterns
a toy model-based experiment shows that def can identify multiple patterns with distinct lengths
furthermore for specific pairs of models and
riesz
riesz regression
furthermore for specific pairs of models and riesz representer estimation methods we can automatically obtain the covariate balancing property without explicitly solving the covariate balancing objective
in ate estimation the bias-correction term h_0 x_i d_i frac 1 e_0 x_i -
frac
ate estimation
in ate estimation the bias-correction term h_0 x_i d_i frac 1 e_0 x_i - frac 1 1 - e_0 x_i plays an important role where e_0 x_i is the propensity score the probability of being assigned treatment 1
accurate and timely crop yield prediction is crucial for global food security and modern
agricultural
yield prediction
accurate and timely crop yield prediction is crucial for global food security and modern agricultural management
the traditional approach involves manually selecting and re-editing shots from longer
video
video generation
the traditional approach involves manually selecting and re-editing shots from longer video ads to create shorter versions which is labor-intensive and time-consuming
the structural properties of these graphs make them suitable candidates for
constructing
quantum advantage
the structural properties of these graphs make them suitable candidates for constructing noncontextuality inequalities thereby establishing a bidirectional connection between quantum contextuality and upbs
specifically we iteratively remove one single edge from the original network to simulate a disruptive event and then compute the
gromov-wasserstein
network structures
specifically we iteratively remove one single edge from the original network to simulate a disruptive event and then compute the gromov-wasserstein distance between the original network and the disrupted one
here we present a refractive index-correlated pseudocoloring ricp framework that integrates quantitative
refractive
optical properties
here we present a refractive index-correlated pseudocoloring ricp framework that integrates quantitative refractive index ri maps obtained by holotomography ht with color bf images to enhance diagnostic interpretability
the system is implemented in ros gazebo turtlebot3 and evaluated with pathbench metrics including success rate collision rate path efficiency and re-planning
efficiency
robotic systems
the system is implemented in ros gazebo turtlebot3 and evaluated with pathbench metrics including success rate collision rate path efficiency and re-planning efficiency in dynamic and partially observable environments
the origin of radio afterglows or delayed radio flares in
tidal
tidal field
the origin of radio afterglows or delayed radio flares in tidal disruption events tdes is not fully understood
we propose that atomic hydrogen facilitates the formation of radical sites which promotes covalent bond
formation
atomic force microscopy
we propose that atomic hydrogen facilitates the formation of radical sites which promotes covalent bond formation between adjacent particles or molecular units creating a more interconnected and rigid network with smaller interlayer distance
specifically we semantically decompose the target
prompt
prompt tuning
specifically we semantically decompose the target prompt into multiple sub-prompts compute an independent flow for each and aggregate them to form a unified editing trajectory
we also discuss the symmetry rules governing the shape in the brillouin zone of the hidden
spin
hidden spin texture
we also discuss the symmetry rules governing the shape in the brillouin zone of the hidden spin texture which can be straightforwardly predicted within the present framework
the work systematically analyzes fundamental network metrics including node
centrality
network structures
the work systematically analyzes fundamental network metrics including node centrality average shortest path length and entropy
such measurements are frequently performed with readouts common in circuit
cavity
qubit readout
such measurements are frequently performed with readouts common in circuit cavity quantum electrodynamic systems trapped ions and atoms and circuit quantum acoustodynamic systems
the paradigm consists of two parts the neural
stability
neural network
the paradigm consists of two parts the neural stability descriptor and the sample-augmented iterative training scheme
we provide a comprehensive discussion of the chemical evolution models in the - plane a diagnostic plane for the separation of in-situ and accreted
galactic
active galactic
we provide a comprehensive discussion of the chemical evolution models in the - plane a diagnostic plane for the separation of in-situ and accreted galactic components
this modification enhances the magnetic anisotropy along the c axis leading to a significant increase in magnetization at low temperatures and under high magnetic fields contrary to conventional expectations for
magnetic
magnetic properties
this modification enhances the magnetic anisotropy along the c axis leading to a significant increase in magnetization at low temperatures and under high magnetic fields contrary to conventional expectations for magnetic dilution
we then apply it to a higher-order spin-glass hamiltonian with 156
qubits
quantum error correction
we then apply it to a higher-order spin-glass hamiltonian with 156 qubits executed on ibm quantum processors
these findings establish group size as a key driver of multi-agent
dynamics
group size
these findings establish group size as a key driver of multi-agent dynamics and highlight the need to consider population-level effects when deploying llm-based systems at scale
we introduce aot-psyphybench a psychophysically validated benchmark that tests whether vlms can infer
temporal
action recognition
we introduce aot-psyphybench a psychophysically validated benchmark that tests whether vlms can infer temporal direction in natural videos using the same stimuli and behavioral baselines established for humans
surprisingly however there have been no results on bounding the i
o-costs
online algorithm
surprisingly however there have been no results on bounding the i o-costs for these algorithms
we mathematically characterize the pareto frontier of
policies
policy learning
we mathematically characterize the pareto frontier of policies according to the tradeoff of these two goals
finally we outline open problems in the field and present a roadmap for integrating tf-qkd into scalable quantum
networks
open quantum
finally we outline open problems in the field and present a roadmap for integrating tf-qkd into scalable quantum networks underscoring its central role in the future quantum internet
vision-language models vlms exhibit uneven performance across
languages
large language
vision-language models vlms exhibit uneven performance across languages a problem that is often exacerbated when the model size is reduced
the attained sample complexities improve those of existing
zeroth-order
first-order methods
the attained sample complexities improve those of existing zeroth-order methods in the problem setting that allows nonconvexity and unboundedness of the objective function
drawing on insights from physics complex systems and decades of empirical research i show that much of what appears unpredictable reveals structure near
transitions
phase transition
drawing on insights from physics complex systems and decades of empirical research i show that much of what appears unpredictable reveals structure near transitions where feedbacks critical thresholds and early-warning signals emerge
we present combined jwst nirspec and miri mrs integral field spectroscopy data of the nuclear and circumnuclear regions of the highly dust obscured seyfert 2 galaxy ngc 7582 which is part of the
sample
active galactic
we present combined jwst nirspec and miri mrs integral field spectroscopy data of the nuclear and circumnuclear regions of the highly dust obscured seyfert 2 galaxy ngc 7582 which is part of the sample of agn in the galaxy activity torus and outflow survey gatos
the system features a counter-propagating beam at the same wavelength as the
quantum
quantum dot
the system features a counter-propagating beam at the same wavelength as the quantum state which simultaneously actively stabilizes the cavity and after transmission acts as the local oscillator for homodyne detection
modelling and evaluating travel information during
disruptions
human mobility
modelling and evaluating travel information during disruptions an illustrative example from swedish railways
predictive benchmarking the evaluation of machine learning models based on
predictive
predictive performance
predictive benchmarking the evaluation of machine learning models based on predictive performance and competitive ranking is a central epistemic practice in machine learning research and an increasingly prominent method for scientific inquiry
for fair and rigorous evaluation we curate goat-core a high-quality core split distilled from goat-bench tailored to multi-modal open-vocabulary
multi-goal
multi-modal open-vocabulary
for fair and rigorous evaluation we curate goat-core a high-quality core split distilled from goat-bench tailored to multi-modal open-vocabulary multi-goal visual navigation
the study results support the implementation of
ar
mobile ar
the study results support the implementation of ar experiences in limited physical spaces by providing an initial understanding of how users can be subtly encouraged to move throughout a room
while optical flow a computer vision technique for estimating pixel wise
motion
flow matching
while optical flow a computer vision technique for estimating pixel wise motion between consecutive images has advanced rapidly in computer vision its applicability to geophysical problems and to satellite sar imagery remains underexplored
in contrast adjacent generative fields most notably video
generation
image generation
in contrast adjacent generative fields most notably video generation vigen have demonstrated remarkable generalization in modeling human behaviors highlighting transferable insights that mogen can leverage
here we aim to characterize misconceptions that users of
conversational
large language models llms
here we aim to characterize misconceptions that users of conversational llm-based assistants may have in programming contexts
to address these limitations a brain-computer interface bci system is developed using a non-invasive electroencephalogram
eeg
brain-computer interface
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
i show that under independence assumptions vars can identify average treatment effects average
causal
causal inference
i show that under independence assumptions vars can identify average treatment effects average causal responses or a mix of the two depending on the distribution of the policy
debiased machine learning typically requires estimation of the
riesz
debiased machine learning
debiased machine learning typically requires estimation of the riesz representer and the regression function
it is well known that there are many applications where a deterministic rom algorithm significantly outperforms any
randomized
randomized algorithm
it is well known that there are many applications where a deterministic rom algorithm significantly outperforms any randomized online algorithm in terms of competitive ratios
our spg-cdenet consists of two key components a spatial prior network and a cross dual
encoder
dual encoder
our spg-cdenet consists of two key components a spatial prior network and a cross dual encoder network
we find that some configurations preserve or even improve
multilingual
language models
we find that some configurations preserve or even improve multilingual retrieval robustness despite halving model size but others fail to maintain cross-task stability exposing design-sensitive trade-offs that aggregate accuracy alone does not reveal
finally simulation results confirm the efficacy of the proposed method in managing trajectory
tracking
trajectory tracking
finally simulation results confirm the efficacy of the proposed method in managing trajectory tracking and cable length adjustments effectively
our spg-cdenet consists of two key components a spatial prior network and a cross dual
encoder
dual encoder
our spg-cdenet consists of two key components a spatial prior network and a cross dual encoder network
we demonstrate that our method achieves higher success rates on complex contact-rich
tasks
multi-robot collaboration
we demonstrate that our method achieves higher success rates on complex contact-rich tasks than end-to-end rl approaches and produces more efficient coordinated behaviors than traditional sequential-only planners
reconstructing images seen by people from their
fmri
fmri data
reconstructing images seen by people from their fmri brain recordings provides a non-invasive window into the human brain
bulges located at the central regions of galaxies are complex structures expected to be shaped by the physical processes involved in the
assembly
bulge stars
bulges located at the central regions of galaxies are complex structures expected to be shaped by the physical processes involved in the assembly history of their host galaxy such as gravitational collapse mergers interactions and bars
the proposed approach integrates an active ris model with an adaptive maximum likelihood estimator
mle
pilot overhead
the proposed approach integrates an active ris model with an adaptive maximum likelihood estimator mle to recover the main channel parameters using a minimal number of pilots
we model different scenarios of competition between tumor cells using a static evolutionary
game
game theory
we model different scenarios of competition between tumor cells using a static evolutionary game in which cells compete for nutrients and oxygen and might choose to stay and proliferate in the primary tumor or opt to a motility strategy in order to find resources in a metastatic site