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a mitigation strategy is a collections of
mitigation
mitigation methods
a mitigation strategy is a collections of mitigation methods and compilation procedures designed to mitigate all relevant errors for a given piece of characterised hardware
in particular we establish the existence of an optimal dissipative environment for accelerated
spontaneous
spontaneous emission
in particular we establish the existence of an optimal dissipative environment for accelerated spontaneous emission
pvmark hinges upon the proof of correct execution of watermark
detection
watermarking schemes
pvmark hinges upon the proof of correct execution of watermark detection on which a set of zkp constraints are built including mapping random number generation comparison and summation
omnix from unified panoramic generation and perception to
graphics-ready
video generation
omnix from unified panoramic generation and perception to graphics-ready 3d scenes
this task can be viewed as a language generation task that bridges
natural
natural language
this task can be viewed as a language generation task that bridges natural language human knowledge and programming logic
we develop an efficient algorithm to solve this bilevel optimization problem which computes parameter
gradients
accelerated gradient
we develop an efficient algorithm to solve this bilevel optimization problem which computes parameter gradients without backpropagating through the solver
here we show mathematically that abstract representations of latent variables are guaranteed to appear in the last hidden layer of feedforward nonlinear networks when they are
trained
recurrent neural networks
here we show mathematically that abstract representations of latent variables are guaranteed to appear in the last hidden layer of feedforward nonlinear networks when they are trained on tasks that depend directly on these latent variables
allowing the order of quantum operations to exist in superposition is known to
open
quantum correlations
allowing the order of quantum operations to exist in superposition is known to open new routes for thermodynamic tasks
finally we discuss the practical implications of isoergotropic states and
operations
quantum batteries
finally we discuss the practical implications of isoergotropic states and operations in optimizing charging protocols and mitigating charge loss in open quantum batteries
low probability of detection communication using
noncoherent
wireless communication
low probability of detection communication using noncoherent grassmannian signaling
we consider populations evolving according to natural selection mutation and recombination and assume that the genomes of all or a representative
selection
population genetics
we consider populations evolving according to natural selection mutation and recombination and assume that the genomes of all or a representative selection of individuals are known
the analysis assesses cost gaps between european green products and lower-cost imports and evaluates strategies such as intra-european relocation selective imports of
green
green finance
the analysis assesses cost gaps between european green products and lower-cost imports and evaluates strategies such as intra-european relocation selective imports of green intermediates and targeted subsidies
beyond reasoning benchmarks srl generalizes effectively to
agentic
reinforcement learning rl
beyond reasoning benchmarks srl generalizes effectively to agentic software engineering tasks establishing it as a robust and versatile training framework for reasoning-oriented llms
in contrast to the existing approaches we regard classification
training
machine learning
in contrast to the existing approaches we regard classification training as a sequential process where classes are learned sequentially which we call emph inductive approach
while imitation learning il enables effective visual navigation il
policies
learning agents
while imitation learning il enables effective visual navigation il policies are prone to unpredictable failures in out-of-distribution ood scenarios
from the collection attains a high maximal
value
submodular maximization
from the collection attains a high maximal value on average when optimized over the restricted ground set
data-driven stabilization using prior knowledge on
stabilizability
data-driven stabilization
data-driven stabilization using prior knowledge on stabilizability and controllability
adaptive trajectory refinement for optimization-based local
planning
collision avoidance
adaptive trajectory refinement for optimization-based local planning in narrow passages
given the large-scale and nonlinear nature of the problem an improved quantum
genetic
genetic algorithm
given the large-scale and nonlinear nature of the problem an improved quantum genetic algorithm iqga that integrates two customized operators is proposed to enhance neighbor searching and solution refinement thereby improving the observability of uav pairs
here we develop a tripartite entanglement distillation scheme using an eight-photon quantum platform demonstrating entanglement superactivation phenomena which are unique to
multipartite
multipartite entanglement
here we develop a tripartite entanglement distillation scheme using an eight-photon quantum platform demonstrating entanglement superactivation phenomena which are unique to multipartite systems
our results demonstrate that large electrical stark shifts can overcome the inhomogeneous distribution of transition frequencies representing a significant step toward scalable siv - -based quantum technologies such as
quantum
quantum technologies
our results demonstrate that large electrical stark shifts can overcome the inhomogeneous distribution of transition frequencies representing a significant step toward scalable siv - -based quantum technologies such as quantum repeaters
even when such environmental noise is unbiased we find it can have a qualitative
impact
environmental change
even when such environmental noise is unbiased we find it can have a qualitative impact on the behaviors that evolve in a population
network nonlocality breaking channels model environmental influences which results in the
loss
network nonlocality
network nonlocality breaking channels model environmental influences which results in the loss of resource i
finally we apply our method on a real agricultural data set and estimate the plant root parameters with
uncertainty
uncertainty quantification
finally we apply our method on a real agricultural data set and estimate the plant root parameters with uncertainty quantification
recent advances advocate easily obtainable channel state information csi by commercial wifi devices for lightweight rf fingerprinting while falling short in addressing the challenges of coarse granularity of
csi
channel state information csi
recent advances advocate easily obtainable channel state information csi by commercial wifi devices for lightweight rf fingerprinting while falling short in addressing the challenges of coarse granularity of csi measurements in an open-world setting
unlike iterative approximation using dynamic programming in the drl a closed-form expression for the random return can be exactly characterized in the distributional lqr which is defined over infinitely many
random
random return
unlike iterative approximation using dynamic programming in the drl a closed-form expression for the random return can be exactly characterized in the distributional lqr which is defined over infinitely many random variables
we propose that this behavior is not simply a flaw indicative of information loss but an adaptation to different information retrieval
demands
working memory
we propose that this behavior is not simply a flaw indicative of information loss but an adaptation to different information retrieval demands during pre-training some tasks require uniform recall across the entire input a long-term memory demand while others prioritize the most recent information a short-term memory d...
chemical separation of stellar populations analytic solutions for
chemical
stellar mass function
chemical separation of stellar populations analytic solutions for chemical evolution models with metallicity-dependent yields
we design and demonstrate heuristic quantum advantage with peaked circuits hqap
circuits
peaked circuits
we design and demonstrate heuristic quantum advantage with peaked circuits hqap circuits on quantinuum s system model h2 quantum processor
distributed quantum computing dqc provides a promising route toward scalable quantum
computation
quantum batteries
distributed quantum computing dqc provides a promising route toward scalable quantum computation where entanglement-assisted locc and circuit knitting represent two complementary approaches
unravelling the mechanisms of manipulating numbers in
language
large language models llms
unravelling the mechanisms of manipulating numbers in language models
self-improvement has emerged as a mainstream paradigm for advancing the reasoning capabilities of large
vision-language
vision-language models vlms
self-improvement has emerged as a mainstream paradigm for advancing the reasoning capabilities of large vision-language models lvlms where models explore and learn from successful trajectories iteratively
we conclude that ly alpha radiation pressure severely limits a possible extremely efficient feedback-free phase of star formation in
dense
star formation rates
we conclude that ly alpha radiation pressure severely limits a possible extremely efficient feedback-free phase of star formation in dense metal-poor clouds
we confirm that galaxies with star formation efficiencies lower than the milky
way
active galactic
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
accordingly redundancy reduction has been suggested as a prominent design principle of neural encoding but its mechanistic
biological
artificial neural
accordingly redundancy reduction has been suggested as a prominent design principle of neural encoding but its mechanistic biological implementation is unclear
large language models llms such as chatgpt are
increasingly
large language
large language models llms such as chatgpt are increasingly integrated into high-stakes decision-making yet little is known about their susceptibility to social influence
we empirically validate the performance of our
online
online algorithm
we empirically validate the performance of our online algorithm with experiments on real datasets
the study results support the implementation of ar experiences in limited
physical
virtual reality
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
we sketch our protocol for designing these circuits and provide
extensive
numerical simulations
we sketch our protocol for designing these circuits and provide extensive numerical results leading to our extrapolation estimates
simulation studies validate the practical advantages of our approach showing improved estimation accuracy when employing
data
data fusion
simulation studies validate the practical advantages of our approach showing improved estimation accuracy when employing data fusion
in difference-in-differences did settings with categorical
outcomes
average treatment effect
in difference-in-differences did settings with categorical outcomes such as voting occupation or major choices treatments often affect both total counts e
however the use of ai in re also brings challenges like algorithmic bias lack of explainability and
ethical
ai literacy
however the use of ai in re also brings challenges like algorithmic bias lack of explainability and ethical concerns related to automation
picosecond wireless synchronization with entangled photons via grid-based
quantum
optical communication
picosecond wireless synchronization with entangled photons via grid-based quantum coverage in indoor optical systems
clone deterministic 3d worlds with geometrically-regularized
world
world models
clone deterministic 3d worlds with geometrically-regularized world models
inflation forecasting is a core socio-economic challenge in modern
macroeconomic
monetary policy
inflation forecasting is a core socio-economic challenge in modern macroeconomic modeling especially when cyclical structural and shock factors act simultaneously
we focus on an important safety problem that is already challenging for
humans
ai assistance
we focus on an important safety problem that is already challenging for humans fact-verification of ai outputs
a key innovation of divrit is its use of a hebrew visual language model which processes undiacritized text as an image allowing diacritic information to be embedded directly within the
input
vision-language models
a key innovation of divrit is its use of a hebrew visual language model which processes undiacritized text as an image allowing diacritic information to be embedded directly within the input s vector representation
maximal load shedding verification for neural network models of
ac
load shedding
maximal load shedding verification for neural network models of ac line switching
to address this limitation here we derive partial
differential
stochastic differential
to address this limitation here we derive partial differential equations for the probability density function of tagged-agent trajectories
preliminary numerical experiments on synthetic datasets and real-world quadratic programming problems in portfolio optimization
demonstrate
bilevel optimization
preliminary numerical experiments on synthetic datasets and real-world quadratic programming problems in portfolio optimization demonstrate the effectiveness and superiority of the proposed algorithm
these insights are then consolidated into a set of
future
existing approaches
these insights are then consolidated into a set of future research directions
x-ray diffraction and atomic force microscopy reveal that while thin aln layers 120 nm exhibit compressive strain and smooth step-flow
surfaces
atomic force microscopy
x-ray diffraction and atomic force microscopy reveal that while thin aln layers 120 nm exhibit compressive strain and smooth step-flow surfaces thicker single-layer buffers 550 nm develop tensile strain and increased surface roughness
this alignment anchors the reasoning of a judge large
language
large language
this alignment anchors the reasoning of a judge large language model llm in structured information and helps reduce the burden of regulatory interpretation and event parsing enabling a focus on the core reasoning step
we derive and discuss the corresponding scaling functions for the
casimir
super-heisenberg scaling
we derive and discuss the corresponding scaling functions for the casimir energy
a critical visual computation is to construct global scene properties from activities of early visual cortical
neurons
neural codes
a critical visual computation is to construct global scene properties from activities of early visual cortical neurons which have small receptive fields
motivated by this question we view our randomness extraction applications as a constructive approach towards understanding the relation between
randomized
randomized algorithm
motivated by this question we view our randomness extraction applications as a constructive approach towards understanding the relation between randomized online algorithms and deterministic rom algorithms
each scenario features 1 to 50 satellites and 50 to 300
imaging
achieves state-of-the-art
each scenario features 1 to 50 satellites and 50 to 300 imaging tasks
the tidal torque theory ttt predicts that galaxy spins are correlated with the surrounding
tidal
tidal field
the tidal torque theory ttt predicts that galaxy spins are correlated with the surrounding tidal field reflecting how angular momentum is acquired during structure formation
large language models llms have significantly advanced generative
applications
models llms
large language models llms have significantly advanced generative applications in natural language processing nlp
these results highlight the significant room for improving the
mathematical
mathematical reasoning
these results highlight the significant room for improving the mathematical reasoning in current llms
while imitation learning il enables effective visual navigation il
policies
imitation learning
while imitation learning il enables effective visual navigation il policies are prone to unpredictable failures in out-of-distribution ood scenarios
collective action against algorithmic systems which enables
groups
emergent behaviors
collective action against algorithmic systems which enables groups to promote their own interests is poised to grow
our findings reveal that orientational ordering in hh occurs at much lower pressures than in solid hydrogen by inducing structural changes in the water network and enhancing the coupling of water and
hydrogen
molecular dynamics
our findings reveal that orientational ordering in hh occurs at much lower pressures than in solid hydrogen by inducing structural changes in the water network and enhancing the coupling of water and hydrogen dynamics
this study highlights the potential of data fusion for estimating non-smooth parameters such as
causal
causal inference
this study highlights the potential of data fusion for estimating non-smooth parameters such as causal dose-response functions
reciprocity deficits observing ai in the street with
everyday
human-ai interaction
reciprocity deficits observing ai in the street with everyday publics
results highlight the extreme vulnerability of urban wildlife to anthropogenic pressures demonstrating how
disturbance
human disturbance
results highlight the extreme vulnerability of urban wildlife to anthropogenic pressures demonstrating how disturbance intensity governs system stability
we then ground these concepts by describing the modern media ecosystem where these
dynamics
opinion dynamics
we then ground these concepts by describing the modern media ecosystem where these dynamics currently unfold including a comparative analysis of platforms and the challenge of information disorders
for each sfh we compute its predicted stellar mass and present-day
sfr
stellar mass function
for each sfh we compute its predicted stellar mass and present-day sfr and retain only those consistent with the observed values within a 20 tolerance
a key feature of our approach is the use of an external instrument to identify monetary
policy
monetary policy
a key feature of our approach is the use of an external instrument to identify monetary policy shocks within the multivariate unob- served components modeling framework
our findings reinforce the need for designing llm-based tools that more clearly communicate their
programming
llm responses
our findings reinforce the need for designing llm-based tools that more clearly communicate their programming capabilities to users
optical and infrared time-domain studies of
quasars
galactic disk
optical and infrared time-domain studies of quasars remain scarce
our main findings from simple human memory paradigms also generalize to a
sequence
recurrent neural
our main findings from simple human memory paradigms also generalize to a sequence completion task which more closely resembles the next-token prediction process in llm pre-training
improving classification of occluded objects through
scene
object detection
improving classification of occluded objects through scene context
for tree edit distance we introduce a new
static
tree edit
for tree edit distance we introduce a new static reduction that improves the best-known approximation ratio from n 3 4 to tilde o sqrt n and removes the restriction to constant-degree trees
two-step recording-development approaches in
laser
pulsed laser ablation liquids
two-step recording-development approaches in laser processing of materials
this paper describes the development and validation process of a trust measure instrument which follows psychometric principles and consists of a 16-items
trust
trustworthy ai
this paper describes the development and validation process of a trust measure instrument which follows psychometric principles and consists of a 16-items trust scale
unlike methods based on reinforcement learning or imitation
learning
reinforcement learning rl
unlike methods based on reinforcement learning or imitation learning which require specified rewards or labeled expert objectives our gan-based architecture learns directly from the joint distribution of observed holdings and market data
among the various strategies explored strain
engineering
strain engineering
among the various strategies explored strain engineering has been proven to be a powerful method for tuning ferroelectric polarization in materials
the basic reproduction number mathcal r _0 was derived and analyzed within stochastic frameworks effectively bridging the gap between these two
modeling
basic reproduction
the basic reproduction number mathcal r _0 was derived and analyzed within stochastic frameworks effectively bridging the gap between these two modeling approaches
a minimal model of self-organized clusters with
phase
phase transition
a minimal model of self-organized clusters with phase transitions in ecological communities
by leveraging multiple reconfigurable intelligent surfaces riss and transceiver designs we engineer the ambient
wireless
wireless networks
by leveraging multiple reconfigurable intelligent surfaces riss and transceiver designs we engineer the ambient wireless propagation environment to emulate the operations of a cnn layer
we begin by isolating a clean and analyzable instance of transformer
reasoning
reasoning capabilities
we begin by isolating a clean and analyzable instance of transformer reasoning that is incompatible with memory as strictly a storage of the local co-occurrences specified during training
these fields correlate with supernova sn -driven turbulence but whether the scaling is universal across galaxy properties
ism
dwarf galaxies
these fields correlate with supernova sn -driven turbulence but whether the scaling is universal across galaxy properties ism phases and energy budgets remains unclear
to generate physically and semantically plausible supervision signals we introduce a spatial prior labeling method that guides a
vision-language
vision-language models vlms
to generate physically and semantically plausible supervision signals we introduce a spatial prior labeling method that guides a vision-language model to produce reasonable manipulation orders for distillation
nearest neighbor matching is equivalent to least squares density ratio estimation and
riesz
riesz regression
nearest neighbor matching is equivalent to least squares density ratio estimation and riesz regression
we then develop an algorithm for this setting which improves upon prior results by a factor of d in certain regimes and as a corollary achieves a new state-of-the-art
complexity
time complexity
we then develop an algorithm for this setting which improves upon prior results by a factor of d in certain regimes and as a corollary achieves a new state-of-the-art complexity for sub-exponential noise
the goal of policy learning is to train a
policy
reward models
the goal of policy learning is to train a policy function that recommends a treatment given covariates to maximize population welfare
applying this framework to a finite-width relu network we find that its hidden layer exhibits an
abstract
abstract representations
applying this framework to a finite-width relu network we find that its hidden layer exhibits an abstract representation at all global minima of the task objective
this paper studies how to achieve accurate modeling and effective control in
stochastic
predictive control
this paper studies how to achieve accurate modeling and effective control in stochastic nonlinear dynamics with multiple interacting objects
watermarking schemes for large language models
llms
language models
watermarking schemes for large language models llms have been proposed to identify the source of the generated text mitigating the potential threats emerged from model theft
a weighted sum of two conflicting objectives energy consumption and travel
time
optimal control
a weighted sum of two conflicting objectives energy consumption and travel time is minimized
to reduce the reliance on costly annotations of skeletal sequences while maintaining competitive recognition accuracy the task of 3d action recognition with limited training samples also known as semi-supervised 3d
action
action recognition
to reduce the reliance on costly annotations of skeletal sequences while maintaining competitive recognition accuracy the task of 3d action recognition with limited training samples also known as semi-supervised 3d action recognition has been proposed
aisp outperforms best-of-n sampling in terms of rewards over the number of used samples and achieves higher rewards than other reward-based
test-time
test-time alignment
aisp outperforms best-of-n sampling in terms of rewards over the number of used samples and achieves higher rewards than other reward-based test-time alignment methods
based on two theoretical results showing that sufficient
wigner
wigner negativity
based on two theoretical results showing that sufficient wigner negativity can certify gme we present five concrete implementation schemes using controlled parity displacement and beamsplitter operations
our spg-cdenet consists of two key components a spatial prior network and a cross dual
encoder
cross dual encoder network
our spg-cdenet consists of two key components a spatial prior network and a cross dual encoder network
by converting each dataset into interpretable metadata we prompt an
llm
generative models
by converting each dataset into interpretable metadata we prompt an llm to recommend both model families and hyperparameters
its interactive interface provides a transparent workflow where users can trace validate and refine the
agent
trustworthy ai
its interactive interface provides a transparent workflow where users can trace validate and refine the agent s reasoning supporting both adaptability and trustworthiness
fully programmable plasmonic pt-symmetric dimer with epsilon near zero and phase-change
materials
photonic crystal
fully programmable plasmonic pt-symmetric dimer with epsilon near zero and phase-change materials for integrated photonics
characterizing cities through urban structure form and function the framework uncovers bidirectional causal patterns between urban systems and
traffic
traffic dynamics
characterizing cities through urban structure form and function the framework uncovers bidirectional causal patterns between urban systems and traffic dynamics across 30 cities on six continents
as a first foray into quantum computational chemistry of actinides this paper compares the method of quantum computed moments qcm as a noisy intermediate-scale quantum algorithm with a single-ancilla version of quantum phase estimation qpe a quantum
algorithm
quantum batteries
as a first foray into quantum computational chemistry of actinides this paper compares the method of quantum computed moments qcm as a noisy intermediate-scale quantum algorithm with a single-ancilla version of quantum phase estimation qpe a quantum algorithm expected to run on fault-tolerant quantum computers