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we find that low energy global minima develop soft-modes which the optimization dynamics can exploit to descend the
energy
global minima
we find that low energy global minima develop soft-modes which the optimization dynamics can exploit to descend the energy landscape
both coherence resonance and equilibrium states resulting from the tightly clustering of cooperator agglomerates enhance population survival and
environmental
ecological interactions
both coherence resonance and equilibrium states resulting from the tightly clustering of cooperator agglomerates enhance population survival and environmental quality
we observe that it is attributed to the secret key mostly used in the watermark detection -- it cannot be public or the adversary may launch removal attacks provided the key nor can it be private or the
watermarking
watermark detection
we observe that it is attributed to the secret key mostly used in the watermark detection -- it cannot be public or the adversary may launch removal attacks provided the key nor can it be private or the watermarking detection is opaque to the public
there are two prevalent ways to constructing 3d scenes procedural
generation
video generation
there are two prevalent ways to constructing 3d scenes procedural generation and 2d lifting
we also provide new data-driven control design methods in terms of
linear
data-driven stabilization
we also provide new data-driven control design methods in terms of linear matrix inequalities that complement the conditions for informativity
we establish feasibility and uniqueness of strictly positive
solutions
strongly convex
we establish feasibility and uniqueness of strictly positive solutions when the benchmark and targets satisfy convex-hull conditions
finally we investigate how multi-slice electron ptychography could provide even further insight on nanotube defect structures thanks to its close to 3d imaging capabilities at
atomic
electron microscopy
finally we investigate how multi-slice electron ptychography could provide even further insight on nanotube defect structures thanks to its close to 3d imaging capabilities at atomic resolution
however the decoding results are found to be mostly negative underscoring the difficulty of decoding
inner
inner speech
however the decoding results are found to be mostly negative underscoring the difficulty of decoding inner speech
we prove the exactness of a convex relaxation of the non-convex problem obtained by replacing all constraints with the lower and upper bounds for the variables corresponding to the minimum and
maximum
strongly convex
we prove the exactness of a convex relaxation of the non-convex problem obtained by replacing all constraints with the lower and upper bounds for the variables corresponding to the minimum and maximum elements of the lattice respectively
82 10 8 m _ sun kpc -2 - values close to those of nearby
quiescent
massive stars
82 10 8 m _ sun kpc -2 - values close to those of nearby quiescent galaxies
its success is partly attributed to conditioning policies on large fixed
context
continual learning
its success is partly attributed to conditioning policies on large fixed context length
in the literature of cognitive neuroscience researchers tend to assume a linear
relationship
working memory
in the literature of cognitive neuroscience researchers tend to assume a linear relationship between brain activation level and task performance however controversial findings have been reported in participants at different ages and different proficiency levels
on the go with ar attention to virtual and
physical
physical virtual
on the go with ar attention to virtual and physical targets while varying augmentation density
existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning
capabilities
large language models llms
existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning capabilities of large language models llms
monitoring the calibration of probability forecasts with an application to concept drift detection involving
image
image classification
monitoring the calibration of probability forecasts with an application to concept drift detection involving image classification
however opportunities exist when these approaches can be further developed and integrated in concerted efforts in which ai
ml
machine learning ml
however opportunities exist when these approaches can be further developed and integrated in concerted efforts in which ai ml approaches could play more important roles
twin-field quantum key distribution protocols
security
key distribution
twin-field quantum key distribution protocols security and open problems
a benefit of compression relative to expansion is that it allows individuals to retain fewer essential dimensions underlying stimulus
variation
higher-order visual
a benefit of compression relative to expansion is that it allows individuals to retain fewer essential dimensions underlying stimulus variation -- a process linked to higher-order visual processing -- without hindering discrimination
this paper develops a nonparametric framework for identifying and estimating spatial
boundaries
effect boundaries
this paper develops a nonparametric framework for identifying and estimating spatial boundaries of treatment effects in settings with geographic spillovers
with this approach we determine and study the hidden spin textures of the upper valence bands of the ptte2 monolayer together with the spatial behavior of the probability densities and spin polarization densities of the corresponding maximally segregated
spin
hidden spin texture
with this approach we determine and study the hidden spin textures of the upper valence bands of the ptte2 monolayer together with the spatial behavior of the probability densities and spin polarization densities of the corresponding maximally segregated spin states
the domain of the objective function is a set of weighted simplicial sets which can fully represent the
spatial
spatial structure
the domain of the objective function is a set of weighted simplicial sets which can fully represent the spatial structure from a topological perspective
motdiff high-resolution motion trajectory estimation from a
single
motion trajectory
motdiff high-resolution motion trajectory estimation from a single blurred image using diffusion models
spiking patches gives the means to preserve the unique properties of
event
spiking patches
spiking patches gives the means to preserve the unique properties of event cameras and we show in our experiments that this comes without sacrificing accuracy
based on various real-world videos locot2v-bench introduces a suite of realistic and
complex
video generation
based on various real-world videos locot2v-bench introduces a suite of realistic and complex prompts incorporating elements like scene transitions and event dynamics
viruses are microscopic infectious agents that require a
host
viral replication
viruses are microscopic infectious agents that require a host cell for replication
in this paper we extend such a theory to the case of infinite horizon optimal
control
predictive control
in this paper we extend such a theory to the case of infinite horizon optimal control problems which are very common in particular in economic applications
specifically braincognizer introduces two modules the cognitive integration module which incorporates prior human knowledge to extract hierarchical region semantics and the
cognitive
cognitive neuroscience
specifically braincognizer introduces two modules the cognitive integration module which incorporates prior human knowledge to extract hierarchical region semantics and the cognitive correlation module which captures contextual semantic relationships across regions
high-fidelity spin readout is a crucial component for quantum information processing with optically interfaced
solid-state
spin readout
high-fidelity spin readout is a crucial component for quantum information processing with optically interfaced solid-state spins
bots a unified framework for bayesian online task selection in
llm
llm agents
bots a unified framework for bayesian online task selection in llm reinforcement finetuning
to address this challenge we propose a novel strategy called inference-aware policy optimization which modifies policy optimization to account for how the
policy
policy evaluation
to address this challenge we propose a novel strategy called inference-aware policy optimization which modifies policy optimization to account for how the policy will be evaluated downstream
we train neural networks to compress perceptual and
semantic
neural networks
we train neural networks to compress perceptual and semantic factors of stimuli measuring lossiness using the mathematical framework underlying compression
we consider the problem of maximizing a submodular function with access to a noisy value
oracle
-approximation algorithm
we consider the problem of maximizing a submodular function with access to a noisy value oracle for the function instead of an exact value oracle
identification and debiased learning of causal
effects
causal effects
identification and debiased learning of causal effects with general instrumental variables
this yields a transparent bias-variance trade-off that requires no prespecified
bias
bias-correction term
this yields a transparent bias-variance trade-off that requires no prespecified bias bound and depends only on information about the precision of the estimators and the estimand s sensitivity to the underlying parameters
this stands in sharp contrast to maximal matching in regular
graphs
bipartite graphs
this stands in sharp contrast to maximal matching in regular graphs which requires some dependence on the number of nodes n or the degree delta
computing binary integer programming via a
new
quadratic programming
computing binary integer programming via a new exact penalty function
large language model agent personality and response appropriateness evaluation by human linguistic experts llm-as-judge and natural
language
large language
large language model agent personality and response appropriateness evaluation by human linguistic experts llm-as-judge and natural language processing model
locations with high habitat quality may play a minor role in
species
ecological interactions
locations with high habitat quality may play a minor role in species spread if they are geographically isolated
however explicit use of this gradient-based attention information integrated directly into
cnn
convolutional neural
however explicit use of this gradient-based attention information integrated directly into cnn representations for semantic object understanding remains limited
in this paper we provide a formal analysis of
weak-to-strong
deep learning
in this paper we provide a formal analysis of weak-to-strong generalization from a linear cnn weak to a two-layer relu cnn strong
the tensor brain is a recently proposed framework for modeling perception and memory in the brain providing a biologically
inspired
artificial neural
the tensor brain is a recently proposed framework for modeling perception and memory in the brain providing a biologically inspired mechanism for efficiently integrating generated symbolic representations into reasoning processes
our general interaction framework which reduces to several previously studied
models
quantum advantage
our general interaction framework which reduces to several previously studied models as special cases provides a versatile platform for engineering quantum correlations with applications in quantum simulation state preparation and sensing protocols
emission-line diagnostics suggest stellar
populations
stellar population
emission-line diagnostics suggest stellar populations as the primary ionizing source although an agn fraction of 14 is found
we begin our journey by recalling the fundamentals of
probability
theoretical guarantees
we begin our journey by recalling the fundamentals of probability theory that underlie one of its most significant applications to real-world problems parametric estimation
we develop the semiconductor wannier equations swes a real-time real-space formulation of ultrafast
light-matter
light-matter interactions
we develop the semiconductor wannier equations swes a real-time real-space formulation of ultrafast light-matter dynamics in crystals by deriving the equations of motion for the electronic reduced density matrix in a localized wannier basis
experimental results showed that compared to the state-of-the-art method sota the accuracy improvement rate in a cg dataset with dynamic
obstacles
dynamic obstacles
experimental results showed that compared to the state-of-the-art method sota the accuracy improvement rate in a cg dataset with dynamic obstacles is 1
additionally we used a gas-grain chemical code to simulate a pre-stellar
core
star clusters
additionally we used a gas-grain chemical code to simulate a pre-stellar core and determine where ne can affect the chemistry
by enhancing the vision encoder with temporal structure we address a critical gap in
video
optical flow
by enhancing the vision encoder with temporal structure we address a critical gap in video understanding for video-llms
in these systems the magnetic activity is not uniformly distributed along the edges but localized on specific
magnetic
magnetic anisotropy
in these systems the magnetic activity is not uniformly distributed along the edges but localized on specific magnetic islands around molybdenum edge atoms
extensive evaluations on multiple datasets demonstrate that our approach significantly outperforms existing colmap-free techniques in
reconstruction
image reconstruction
extensive evaluations on multiple datasets demonstrate that our approach significantly outperforms existing colmap-free techniques in reconstruction quality and also surpasses the standard colmap-based baseline in general
for tree edit distance we introduce a new
static
tree edit distance
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
here the first step of laser processing provides an initial pattern on the material surface which is enhanced or developed at the
second
pulsed laser
here the first step of laser processing provides an initial pattern on the material surface which is enhanced or developed at the second step
we propose a command-filter backstepping controller that integrates a
disturbance
bounded disturbances
we propose a command-filter backstepping controller that integrates a disturbance observer and a high-gain observer hgo to handle unknown internal and external disturbances acting on a quadrotor
accelerated calculation of impurity green s functions exploiting the extreme
mpemba
mpemba effect
accelerated calculation of impurity green s functions exploiting the extreme mpemba effect
various dynamical diagnostics - including galaxy pairwise separations velocity dispersions and the offset of the first-ranked galaxy from the group barycentre
-
active galactic
various dynamical diagnostics - including galaxy pairwise separations velocity dispersions and the offset of the first-ranked galaxy from the group barycentre - indicate that single-bgg groups evolve more rapidly towards virialisation than double- and especially non-bgg systems
a minimal quantitative model of perceptual
suppression
human cognition
a minimal quantitative model of perceptual suppression and breakthrough in visual rivalry
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
image fusion
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
as a corollary we establish the first local central
limit
asymptotic normality
as a corollary we establish the first local central limit theorem for densities in growing dimensions under the condition d 2 n to 0 and provide explicit multiplicative error bounds
accurate world models are essential for enabling
agents
reasoning capabilities
accurate world models are essential for enabling agents to think plan and reason effectively in complex dynamic settings
our results reveal temporal stability in aggregate route choice behavior across the entire
urban
mobility networks
our results reveal temporal stability in aggregate route choice behavior across the entire urban region throughout 2023
this system is designed for heterogeneous
multi-robot
multi-robot collaboration
this system is designed for heterogeneous multi-robot exploratory missions tackling the challenges presented by extraterrestrial environments
most prior work focuses on minimizing its time
complexity
polynomial time
most prior work focuses on minimizing its time complexity i
based on previous understanding of hsg in
bulk
bulk gaas
based on previous understanding of hsg in bulk gaas in terms of bloch-wave interferometry an analytic model is derived to quantitatively connect the hamiltonian parameters with the measured sideband electric fields under strong low-frequency thz fields
dynamic context-aware scene reasoning using vision-language alignment in
zero-shot
multimodal reasoning
dynamic context-aware scene reasoning using vision-language alignment in zero-shot real-world scenarios
this gap has motivated growing efforts to design collaborative frameworks that combine the complementary strengths of
humans
human-ai interaction
this gap has motivated growing efforts to design collaborative frameworks that combine the complementary strengths of humans and ai
reinforcement learning rl is widely used to produce robust robotic manipulation
policies
optimal control
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
4 spatial durbin estimates show positive spillovers the coupling of green finance and
green
green finance
4 spatial durbin estimates show positive spillovers the coupling of green finance and green technology innovation not only improves the level of local coordination but also drives the improvement of environmental performance in adjacent areas
early-assembling high-concentration halos
form
dense gas
early-assembling high-concentration halos form stars efficiently and become gas-poor by z 0 while late-assembling low-concentration halos remain gas-rich due to delayed star formation and rejuvenated gas accretion
our method extends prior work by decoupling the upper and lower
bounds
lower bounds
our method extends prior work by decoupling the upper and lower bounds enabling more flexible and tighter approximations
second-order stark shifts exceeding 10 ghz in electrically contacted
siv
ghz ghz
second-order stark shifts exceeding 10 ghz in electrically contacted siv - centers in diamond
our results suggest the need to conduct user-centered studies on measuring
llms
models llms
our results suggest the need to conduct user-centered studies on measuring llms ability to help users while preserving privacy
our approach is validated with experiments notably on real-world question-answering datasets using embeddings derived from state-of-the-art large
language
large language
our approach is validated with experiments notably on real-world question-answering datasets using embeddings derived from state-of-the-art large language models
recently proposed generative models for discrete data such as masked diffusion models mdms exploit conditional independence approximations to reduce the computational cost of popular auto-regressive models arms at the price of some bias in the
sampling
generative models
recently proposed generative models for discrete data such as masked diffusion models mdms exploit conditional independence approximations to reduce the computational cost of popular auto-regressive models arms at the price of some bias in the sampling distribution
formulas for calculating the mean square error and the spectral characteristic of the optimal linear estimate of the functional are proposed under condition of spectral certainty where
spectral
spectral density matrices
formulas for calculating the mean square error and the spectral characteristic of the optimal linear estimate of the functional are proposed under condition of spectral certainty where spectral densities of the sequences xi m and eta m are exactly known
to formalize interventional constraints we propose a metric to quantify total causal effects for linear
causal
interventional constraints
to formalize interventional constraints we propose a metric to quantify total causal effects for linear causal models and formulate the problem as a constrained optimization task solved using a two-stage constrained optimization method
drivers of variation in the optimal spatial structure of
collective
social interactions
drivers of variation in the optimal spatial structure of collective information gatherers
here we present mobilitygen a deep generative model that produces realistic
mobility
mobility networks
here we present mobilitygen a deep generative model that produces realistic mobility trajectories spanning days to weeks at large spatial scales
we quantify the dependence of magnetic fields on star formation
activity
bulge stars
we quantify the dependence of magnetic fields on star formation activity including both regular and starburst galaxies
these results establish a general framework for multi-port spectral engineering in integrated photonics with broad implications for tunable filters modulators sensors and
nonlinear
nonlinear optical
these results establish a general framework for multi-port spectral engineering in integrated photonics with broad implications for tunable filters modulators sensors and nonlinear optical systems
experiments on both synthetic and real-world
datasets
synthetic data
experiments on both synthetic and real-world datasets validate our theoretical insights and show that the proposed method effectively improves fairness while preserving predictive performance
recent breakthroughs in artificial intelligence
ai
artificial intelligence
recent breakthroughs in artificial intelligence ai are reshaping the way we construct computational counterparts of the brain giving rise to a new class of surrogate brains
our witnesses can detect paradigmatic gme states like the dicke and multipartite n00n states which include the w
states
entanglement entropy
our witnesses can detect paradigmatic gme states like the dicke and multipartite n00n states which include the w states as a special case and ghz-type entangled cat states
using the transfer matrix formalism we derive general expressions for the dispersion relations of surface polaritonic
modes
waveguide modes
using the transfer matrix formalism we derive general expressions for the dispersion relations of surface polaritonic modes including the dependence on the bi-isotropic parameter and analyze their coupling to bulk magnon-polaritons
our analysis allows for estimating a diverging number of treatment effects simultaneously and establishes the consistency and asymptotic normality of the
regression-based
treatment effect
our analysis allows for estimating a diverging number of treatment effects simultaneously and establishes the consistency and asymptotic normality of the regression-based estimators
i develop a nonparametric framework for identifying
spatial
treatment effect
i develop a nonparametric framework for identifying spatial boundaries of treatment effects without imposing parametric functional form restrictions
beyond performance our framework provides a lightweight representation-level counterfactual approach offering a practical causal avenue for debiased and reliable
multimodal
multimodal reasoning
beyond performance our framework provides a lightweight representation-level counterfactual approach offering a practical causal avenue for debiased and reliable multimodal reasoning
here we demonstrate that reinforcement learning rl and supervised learning sl drive
recurrent
reinforcement learning
here we demonstrate that reinforcement learning rl and supervised learning sl drive recurrent neural networks rnns toward fundamentally different computational solutions when trained on identical decision-making tasks
finding a computational model has proven elusive particularly because of conflation of consciousness with other
cognitive
brain-computer interface
finding a computational model has proven elusive particularly because of conflation of consciousness with other cognitive capabilities exhibited by humans such as intelligence and physiological sensations
test-time alignment of llms via sampling-based optimal
control
test-time alignment
test-time alignment of llms via sampling-based optimal control in pre-logit space
i show that under independence assumptions vars can identify average treatment effects average
causal
causal effects
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
based on this framework we formulate a max-min fairness optimization problem that jointly optimizes
power
power allocation
based on this framework we formulate a max-min fairness optimization problem that jointly optimizes power allocation message splitting and time slot scheduling to maximize the minimum achievable rate across uds
unlike prior efforts that emphasize only isolated aspects such as modeling or control this work delivers a complete hardware-software
platform
trajectory tracking
unlike prior efforts that emphasize only isolated aspects such as modeling or control this work delivers a complete hardware-software platform validated through both simulation and experiments on static and dynamic trajectories
these constraints require small open-source models that can
run
smaller models
these constraints require small open-source models that can run locally and reliably ground their outputs in correct information
these constraints require small open-source models that can run locally and reliably ground their outputs in
correct
open-source models
these constraints require small open-source models that can run locally and reliably ground their outputs in correct information
current tool-use large language models llms are trained on static datasets enabling them to interact with external tools and
perform
vision-language models
current tool-use large language models llms are trained on static datasets enabling them to interact with external tools and perform multi-step tool-integrated reasoning which produces tool-call trajectories
scalability efficiency and robustness to characterised imperfections in the
mitigation
mitigation methods
scalability efficiency and robustness to characterised imperfections in the mitigation implementation which we combine into application-specific certifications
generating networks that more accurately reflect real-world patterns is a significant topic within
complex
complex networks
generating networks that more accurately reflect real-world patterns is a significant topic within complex network research
reliable state estimation hinges on accurate specification of sensor noise covariances which weigh
heterogeneous
state estimation
reliable state estimation hinges on accurate specification of sensor noise covariances which weigh heterogeneous measurements
with a software-defined radio our approach can dynamically sweep the synthetic wavelength and measure
absolute
spectral range
with a software-defined radio our approach can dynamically sweep the synthetic wavelength and measure absolute optical range
these limitations are particularly apparent in real-life
driving
autonomous driving
these limitations are particularly apparent in real-life driving scenarios where state-of-the-art algorithms struggle to safely or reliably complete overtaking manoeuvres