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to address this we employ a machine learning interatomic potential mlip to investigate the
structural
electronic structure
to address this we employ a machine learning interatomic potential mlip to investigate the structural and defect-related physical properties in al _x ga _ 1-x n
bike-sharing systems bss are key components of urban
mobility
mobility networks
bike-sharing systems bss are key components of urban mobility promoting active travel and complementing public transport
using this transformed model we apply lyapunov theory to derive a
backstepping
control law
using this transformed model we apply lyapunov theory to derive a backstepping control law
this research provides an indication of potential advances in the exploration of all four fundamental aspects of tool usage enabling robots to master the intricate art of tool
manipulation
robotic manipulation
this research provides an indication of potential advances in the exploration of all four fundamental aspects of tool usage enabling robots to master the intricate art of tool manipulation across diverse tasks
l_ bol disk l_ edd propto t_p 4 propto m_ bullet -1 tde-specific physics correlations l_ plat propto m_ bullet 2 3 and r_ out r_g propto m_ bullet -2 3 and black hole-host galaxy correlations m_ bullet - m_ star and m_ bullet - sigma_ star naturally emerge from the data and for the first time are self-consistently exte...
bullet
massive galaxies
l_ bol disk l_ edd propto t_p 4 propto m_ bullet -1 tde-specific physics correlations l_ plat propto m_ bullet 2 3 and r_ out r_g propto m_ bullet -2 3 and black hole-host galaxy correlations m_ bullet - m_ star and m_ bullet - sigma_ star naturally emerge from the data and for the first time are self-consistently exte...
therefore we can scope the parameter-space which provides some
spoofing
spoofing resilience
therefore we can scope the parameter-space which provides some spoofing resilience without relying upon the prohibitive method of acquiring detector data for all combinations of the experimental parameters
second supply chain connections create technology-specific
networks
supply chain
second supply chain connections create technology-specific networks whose algebraic connectivity lambda_2 increases 300-380 percent as adoption spreads with correlation between lambda_2 and adoption exceeding 0
in single-objective optimization the point convergence problem of nesterov s accelerated
gradient
gradient descent
in single-objective optimization the point convergence problem of nesterov s accelerated gradient method at the critical damping parameter alpha 3 has recently been resolved
in this paper we obtain a tight lower bound as well as matching upper
bounds
lower bound
in this paper we obtain a tight lower bound as well as matching upper bounds for the static retrieval problem
by contrast in the unconditional setting diffusion models succeed with only an l 2
bound
diffusion models
by contrast in the unconditional setting diffusion models succeed with only an l 2 bound on the score error
test-time prompt tuning tpt has emerged as a promising
technique
prompt tuning
test-time prompt tuning tpt has emerged as a promising technique for adapting large vision-language models vlms to unseen tasks without relying on labeled data
we bring down the quantum computation runtime from 22 years to just 1
day
computational power
we bring down the quantum computation runtime from 22 years to just 1 day achieving a significant 7
machine learning ml models meanwhile can be
trained
reinforcement learning
machine learning ml models meanwhile can be trained to predict near-optimal decisions at a fraction of the speed
the intrinsic stress determined by the wafer curvature method decreases with increasing film
thickness
film thickness
the intrinsic stress determined by the wafer curvature method decreases with increasing film thickness but increases with the annealing temperature
wigner negativity and genuine multipartite entanglement gme are key nonclassical resources that enable
computational
quantum correlations
wigner negativity and genuine multipartite entanglement gme are key nonclassical resources that enable computational advantages and broader quantum-information tasks
however standard implementations rely on discretizing spike times into binned count data limiting temporal
resolution
temporal resolution
however standard implementations rely on discretizing spike times into binned count data limiting temporal resolution and scalability
we define a new measure called the synchronization bottleneck of a graph which we denote by xi this new network property provides a quantification of the limiting bottleneck of the flow between any subset of
nodes
scale-free networks
we define a new measure called the synchronization bottleneck of a graph which we denote by xi this new network property provides a quantification of the limiting bottleneck of the flow between any subset of nodes regardless of its order and the rest of the networked system
we investigate whether persuasive prompting can recall factual knowledge from
deliberately
normative reasoning
we investigate whether persuasive prompting can recall factual knowledge from deliberately unlearned llms across models ranging from 2
for the variant condition we enforce a robust decrease over a parameterized disturbance ball with nonzero probability and encode the
constraints
soft constraints
for the variant condition we enforce a robust decrease over a parameterized disturbance ball with nonzero probability and encode the constraints via an s-procedure with polynomial multipliers
we evaluate its reasoning behavior across 12 dimensions including spatial geometric physical temporal and embodied
logic
mathematical reasoning
we evaluate its reasoning behavior across 12 dimensions including spatial geometric physical temporal and embodied logic systematically characterizing both its strengths and failure modes
we pool data from four mobile ar studies with a total of 1 152 object recall probes and fit a partial least squares structural equation model pls-sem with formative object scene and user state composites predicting
recall
object recall
we pool data from four mobile ar studies with a total of 1 152 object recall probes and fit a partial least squares structural equation model pls-sem with formative object scene and user state composites predicting recall also benchmarking against random forest and multilayer perceptron classifiers
keywords small language models factual grounding directed
reasoning
language models
keywords small language models factual grounding directed reasoning fine-tuning model alignment cost-efficient ai
centrality metrics aim to identify the most relevant
nodes
scale-free networks
centrality metrics aim to identify the most relevant nodes in a network
few-shot examples substantially improve performance indicating potential for targeted enhancement of llms
vr
physical virtual
few-shot examples substantially improve performance indicating potential for targeted enhancement of llms vr manipulation capabilities
importantly although our approach relies on regression our design-based framework allows for misspecification of the
regression
riesz regression
importantly although our approach relies on regression our design-based framework allows for misspecification of the regression model
yet robust decisions under uncertainty still rely on capabilities that current
ai
uncertainty quantification
yet robust decisions under uncertainty still rely on capabilities that current ai lacks domain knowledge not captured by data long horizon context and reasoning grounded in the physical world
this potential molecular gas supply however does not correlate with the current accretion efficiency of the smbhs suggesting that only a fraction of the observed
non-rotating
molecular gas
this potential molecular gas supply however does not correlate with the current accretion efficiency of the smbhs suggesting that only a fraction of the observed non-rotating gas is currently reaching the smbh
the global encoder captures global semantic features from the entire image while the local
encoder
dual encoder
the global encoder captures global semantic features from the entire image while the local encoder focuses on features from the prior network
this work aims to develop the mathematical underpinnings of such a representation -- specifically the goal is to develop
safety
safety filter
this work aims to develop the mathematical underpinnings of such a representation -- specifically the goal is to develop safety filters that are risk-aware
our first result is a one-sided non-adaptive algorithm for this problem that makes tilde o log n epsilon
samples
randomized algorithm
our first result is a one-sided non-adaptive algorithm for this problem that makes tilde o log n epsilon samples and queries where n f -1 1 is the number of satisfying assignments of the function that is being tested and the value of n is given as an input parameter to the algorithm
the ewm approach is analogous to a classification problem where one first builds an estimator of the population welfare which is a functional of policy functions and then trains a
policy
policy learning
the ewm approach is analogous to a classification problem where one first builds an estimator of the population welfare which is a functional of policy functions and then trains a policy by maximizing the estimated welfare
existing approaches often employ an external optimization loop such as an evolutionary algorithm to the
diffusion
diffusion models
existing approaches often employ an external optimization loop such as an evolutionary algorithm to the diffusion model
specifically we assess the consistency and robustness of these
metrics
evaluation metrics
specifically we assess the consistency and robustness of these metrics under three controlled conditions paraphrasing hallucinations in model outputs and variations in sentence length
beyond reality designing personal experiences and interactive narratives in
ar
user experience
beyond reality designing personal experiences and interactive narratives in ar theater
moreover we show that a poly-logarithmic approximation ratio and hence an approximation
ratio
approximation guarantee
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
we initiate this study by focusing on collective
behaviors
human disturbance
we initiate this study by focusing on collective behaviors that change abruptly at certain critical numbers of individuals
this survey bridges that gap by delivering a forward-looking analysis of object detection in avs emphasizing emerging paradigms such as
vision-language
vision-language models
this survey bridges that gap by delivering a forward-looking analysis of object detection in avs emphasizing emerging paradigms such as vision-language models vlms large language models llms and generative ai rather than re-examining outdated techniques
we demonstrate that classical correlations can significantly delay the decay of quantum
correlations
quantum dot
we demonstrate that classical correlations can significantly delay the decay of quantum correlations and coherence
through comprehensive experimentation across six diverse tasks and utilizing six distinct
llms
large language models llms
through comprehensive experimentation across six diverse tasks and utilizing six distinct llms our methodology demonstrates remarkable results achieving speeds up to 5
emergence of hybrid computational dynamics through
reinforcement
reinforcement learning
emergence of hybrid computational dynamics through reinforcement learning
our identification strategy also clarifies how richer exogenous instrument variation such as multi-valued or multiple
instruments
instrumental variable
our identification strategy also clarifies how richer exogenous instrument variation such as multi-valued or multiple instruments can further tighten these bounds
large language models llms excel at general
tasks
language models
large language models llms excel at general tasks but underperform in specialized domains like economics and psychology which require deep principled understanding
under mild assumptions on how close the actual violation is to the acceptable level we provide a consistent preliminary test as well confidence
intervals
confidence intervals
under mild assumptions on how close the actual violation is to the acceptable level we provide a consistent preliminary test as well confidence intervals which are valid when conditioned on the result of the test
we complement our theoretical results with experiments on various
real-world
synthetic data
we complement our theoretical results with experiments on various real-world datasets which show that the proposed sketches are lightweight and achieve consistently low error in practice
from linear to nonlinear provable weak-to-strong
generalization
machine learning
from linear to nonlinear provable weak-to-strong generalization through feature learning
using a multi-view teleoperated franka and mimic-hand dataset augmented with mediapipe
hand
vision-language-action vla
using a multi-view teleoperated franka and mimic-hand dataset augmented with mediapipe hand poses we demonstrate that delta actions are well-behaved and that four principal components explain 96 of hand-joint variance
we also explore applications of coherence to
graph
graph neural
we also explore applications of coherence to graph problems
in this paper we prove that the iterates of the accelerated nesterov
s
strongly convex
in this paper we prove that the iterates of the accelerated nesterov s algorithm in the critical regime do converge in the weak topology to a global minimizer of an l -smooth function in a real hilbert space hence answering positively a conjecture posed by h
tailoring reproducing kernels for optimal
control
predictive control
tailoring reproducing kernels for optimal control via policy iteration
within this system framework we formulate an optimization problem for the purpose of maximizing the minimum rate of users for each cell via designing the transmit beamforming of the trtc subject to the
power
transmit power
within this system framework we formulate an optimization problem for the purpose of maximizing the minimum rate of users for each cell via designing the transmit beamforming of the trtc subject to the power constraints of each trtc unit
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
in this paper we obtain a tight lower bound as well as matching upper bounds for the static
retrieval
compressed indexing
in this paper we obtain a tight lower bound as well as matching upper bounds for the static retrieval problem
we investigate a quantum heat engine where energy exchanges are driven by generalized measurements and the sequence of these
operations
quantum mechanics
we investigate a quantum heat engine where energy exchanges are driven by generalized measurements and the sequence of these operations is coherently controlled in a superposition of causal orders
moreover with only 1-hour of fmri data from a new subject we achieve results comparable to current
methods
brain activity
moreover with only 1-hour of fmri data from a new subject we achieve results comparable to current methods trained on full 40-hour recordings
modern vision-language models vlms excel at many
multimodal
vision-language models
modern vision-language models vlms excel at many multimodal tasks yet their grasp of temporal information in video remains weak and crucially under-evaluated
we formulate causal inference validity through a generalized matching condition generalizing the parallel trend
assumption
causal effects
we formulate causal inference validity through a generalized matching condition generalizing the parallel trend assumption in difference-in-differences designs
our first result reveals a separation between bipartite graphs of ferrers dimension three and four while z n k leq 9n k-1 for graphs of ferrers dimension three z n k in omega left n k cdot frac log n log log n right for ferrers
dimension
ferrers dimension
our first result reveals a separation between bipartite graphs of ferrers dimension three and four while z n k leq 9n k-1 for graphs of ferrers dimension three z n k in omega left n k cdot frac log n log log n right for ferrers dimension four graphs chan har-peled 2023 chazelle 1990
these results have implications for amplified oversight -- the challenge of combining humans and ai to supervise ai
systems
ai systems
these results have implications for amplified oversight -- the challenge of combining humans and ai to supervise ai systems even as they surpass human expert performance
our findings reveal how families co-construct children s ai literacy exposing tensions between practical expectations and
critical
ai literacy
our findings reveal how families co-construct children s ai literacy exposing tensions between practical expectations and critical literacies and provide design implications that foster sdl while balancing autonomy and oversight
comparative evaluations show that these proposed methods perform better than existing approaches in both collision
avoidance
obstacle avoidance
comparative evaluations show that these proposed methods perform better than existing approaches in both collision avoidance and task assignment
we further show that performance is optimal for small
receptive
receptive fields
we further show that performance is optimal for small receptive fields and that sparse connectivity between networks is nearly as accurate as all-to-all interactions with far fewer computations
we study an optimal control problem for the stochastic wave equation driven by affine multiplicative noise formulated as a
stochastic
quadratic programming
we study an optimal control problem for the stochastic wave equation driven by affine multiplicative noise formulated as a stochastic linear-quadratic slq problem
the report is organized around three core capabilities required for brain emulation recording brain function neural dynamics mapping brain structure connectomics and
emulation
brain regions
the report is organized around three core capabilities required for brain emulation recording brain function neural dynamics mapping brain structure connectomics and emulation and embodiment computational neuroscience
dynamic spatial treatment effect boundaries a
continuous
treatment effect boundaries
dynamic spatial treatment effect boundaries a continuous functional framework from navier-stokes equations
the simulated galaxies reproduce the observed stellar-to-halo mass mass--metallicity and size--mass relations yielding stellar
masses
galactic nuclei
the simulated galaxies reproduce the observed stellar-to-halo mass mass--metallicity and size--mass relations yielding stellar masses of 10 6-10 8 m_ odot and metallicities consistent with those of local group dwarf galaxies
omnipresent yet overlooked heat kernels in
combinatorial
heat kernels
omnipresent yet overlooked heat kernels in combinatorial bayesian optimization
dyad-level effects provide a richer and more realistic representation of heterogeneity across pairs of
dimensions
effect boundaries
dyad-level effects provide a richer and more realistic representation of heterogeneity across pairs of dimensions e
the architecture incorporates a brain-region to image-feature cross-attention mechanism enabling
nonlinear
neural representations
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
when a high level decision making agent generates a collision free path a
robust
optimal control
when a high level decision making agent generates a collision free path a robust low level controller is required to precisely follow this trajectory
we present fm agent a novel and general-purpose multi-agent framework that leverages a synergistic combination of llm-based reasoning and
large-scale
fm agent
we present fm agent a novel and general-purpose multi-agent framework that leverages a synergistic combination of llm-based reasoning and large-scale evolutionary search to address complex real-world challenges
however current research on hgnn-based anomaly
detection
anomaly detection
however current research on hgnn-based anomaly detection remains fragmented with diverse modeling strategies limited comparative evaluation and an absence of standardized benchmarks
additionally we consider emerging modalities such as audio and egocentric
video
point tracking
additionally we consider emerging modalities such as audio and egocentric video which contribute to novel spatial understanding through new sensors
the prohibitive cost of evaluating large language models
llms
large language models llms
the prohibitive cost of evaluating large language models llms on comprehensive benchmarks necessitates the creation of small yet representative data subsets i
evolutionary systems must learn to generalize often extrapolating from a limited set of selective conditions to anticipate future
environmental
environmental change
evolutionary systems must learn to generalize often extrapolating from a limited set of selective conditions to anticipate future environmental changes
defining the urban local with low dimensional manifolds of human
mobility
urban systems
defining the urban local with low dimensional manifolds of human mobility networks
the protocol utilizes a probabilistic approach to dynamically determine
channel
channel state information csi
the protocol utilizes a probabilistic approach to dynamically determine channel polling listening intervals
to address this challenge this paper introduces a unified hybrid modeling framework termed physics-guided residual lifting with control-consistent correction which integrates a transient mechanistic model with a stability-constrained
data-driven
data-driven stabilization
to address this challenge this paper introduces a unified hybrid modeling framework termed physics-guided residual lifting with control-consistent correction which integrates a transient mechanistic model with a stability-constrained data-driven component
we provide a rigorous theoretical analysis of our proposals and
complement
theoretical guarantees
we provide a rigorous theoretical analysis of our proposals and complement it with supporting simulations
online randomness extraction simulating barely random algorithms in the
random
randomized algorithm
online randomness extraction simulating barely random algorithms in the random order arrival model
deriving robust precoders under imperfect
channel
channel state information
deriving robust precoders under imperfect channel state information is not only analytically intractable in general but often requires substantial relaxations of the optimization problem or heuristic constraints to obtain feasible solutions
this completes the theoretical foundation of compressed indexing closing a crucial gap between upper and lower bounds and providing a clear target for future data structures seeking either the optimal time in the smallest space or the fastest time in the optimal
space
query complexity
this completes the theoretical foundation of compressed indexing closing a crucial gap between upper and lower bounds and providing a clear target for future data structures seeking either the optimal time in the smallest space or the fastest time in the optimal space both of which are now known for central string quer...
trichome-based suspensions exhibit enhanced viscoelastic response and a threefold
increase
strain engineering
trichome-based suspensions exhibit enhanced viscoelastic response and a threefold increase in yield stress
the results demonstrate the model s capability to generate scenarios for the validation of intelligent
driving
autonomous driving
the results demonstrate the model s capability to generate scenarios for the validation of intelligent driving functions involving multi-agent interactions as well as to augment data for their development and iterative improvement
this improvement allows the inverse optimal safe control to inherit the standard
gain
inverse optimal issf
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
3 standard non-disentangled llm embeddings can be misleading as their predictive success is primarily attributable to linguistically shallow features masking the more subtle contributions of deeper
cognitive
neural representations
3 standard non-disentangled llm embeddings can be misleading as their predictive success is primarily attributable to linguistically shallow features masking the more subtle contributions of deeper cognitive processing
our methods and findings offer not only practical applications for quantum networks but also lead to a deeper understanding of
multipartite
multipartite entanglement
our methods and findings offer not only practical applications for quantum networks but also lead to a deeper understanding of multipartite entanglement structures
can video-llms achieve consistent temporal understanding when
videos
video generation
can video-llms achieve consistent temporal understanding when videos capture the same event from different viewpoints
existing datasets in this domain are typically limited to flat
tabular
real-world datasets
existing datasets in this domain are typically limited to flat tabular structures and fail to capture the spatiotemporal dynamics inherent in delay propagation
nanoparticle synthesis via pulsed laser ablation in
liquids
ablation liquids
nanoparticle synthesis via pulsed laser ablation in liquids has gained prominence as a versatile and environmentally friendly approach for producing ligand-free colloids with controlled composition size and morphology
to address this challenge we develop a calibration model for a widely used resistive
tactile
tactile sensors
to address this challenge we develop a calibration model for a widely used resistive tactile sensor design that enables accurate force estimation on one-dimensional curved surfaces
this paper introduces a novel multi-object tracking mot method dubbed gentrack whose main contributions include a hybrid tracking approach employing both stochastic and deterministic manners to robustly handle unknown and time-varying numbers of targets particularly in maintaining target identity id consistency and man...
tracking
multi-object tracking
this paper introduces a novel multi-object tracking mot method dubbed gentrack whose main contributions include a hybrid tracking approach employing both stochastic and deterministic manners to robustly handle unknown and time-varying numbers of targets particularly in maintaining target identity id consistency and man...
dinosaur photonic crystal cavity interfaces for color center
coupling
integrated photonics
dinosaur photonic crystal cavity interfaces for color center coupling to triangular nanostructures
while many real scale-free networks are known to contain shorter loops such as triangles it remains to investigate the distributions of longer
loops
network structures
while many real scale-free networks are known to contain shorter loops such as triangles it remains to investigate the distributions of longer loops in more wide class of networks
we confirm that galaxies with star formation efficiencies lower than the
milky
star formation
we confirm that galaxies with star formation efficiencies lower than the milky way have high probably indicating a stronger efficiency of the delayed sources of r-process at low metallicities
we conduct a comprehensive comparison between redllm pretrained with prefix language modeling lm and decllm pretrained with causal lm at
different
vision-language models
we conduct a comprehensive comparison between redllm pretrained with prefix language modeling lm and decllm pretrained with causal lm at different model scales ranging from sim 150m to sim 8b
at the lower level a real-time control strategy disaggregates the regulation power among the
constituent
control law
at the lower level a real-time control strategy disaggregates the regulation power among the constituent resources
specifically we iteratively remove one single edge from the original network to simulate a disruptive event and then compute the gromov-wasserstein
distance
gromov-wasserstein distance
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
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
ate estimation
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
among respondents who considered vacuum decay theoretically possible it was generally expected that
artificial
vacuum decay
among respondents who considered vacuum decay theoretically possible it was generally expected that artificial induction would pose significant technological challenges even for a civilization with galactic resources
such simulations -- for which classical methods are often inaccurate -- are critical to advancing our knowledge and understanding of quantum chemistry and materials underpinning a wide range of fields from
biochemistry
classical simulation
such simulations -- for which classical methods are often inaccurate -- are critical to advancing our knowledge and understanding of quantum chemistry and materials underpinning a wide range of fields from biochemistry to clean-energy technologies and chemical synthesis