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we explore the fate of different strategies under sustained environmental
change
environmental change
we explore the fate of different strategies under sustained environmental change by considering a mathematical model for a large population of asexual organisms
we formalize the concept of treatment effect
boundaries
treatment effect
we formalize the concept of treatment effect boundaries as structural parameters characterizing regime transitions where causal effects cease to operate
one recurring problem in this task is the weaknesses found in some detectors such as the difficulty in detecting
loose
incident detection
one recurring problem in this task is the weaknesses found in some detectors such as the difficulty in detecting loose edges and the lack of context to extract relevant information from specific problems
finally we outline open problems in the field and present a roadmap for integrating tf-qkd into scalable quantum
networks
quantum dot
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
structural characterization using atomic force and scanning
electron
electron microscopy
structural characterization using atomic force and scanning electron microscopy is complemented by fluorescence imaging and kelvin probe force microscopy confirming that aqueous solutions fill and remain stably retained within the nanochannels for periods exceeding 10 hours
remarkably however we show that if the system is stabilizable then using this as prior knowledge leads to necessary and sufficient conditions that are weaker than those for data-driven
stabilization
data-driven stabilization
remarkably however we show that if the system is stabilizable then using this as prior knowledge leads to necessary and sufficient conditions that are weaker than those for data-driven stabilization without prior knowledge
experiments show that rpd-selected training yields more varied outputs and
higher
reward density
experiments show that rpd-selected training yields more varied outputs and higher pass k with an average 2
thus as a prerequisite for the successful implementation of numerous
isac
communication isac
thus as a prerequisite for the successful implementation of numerous isac use cases the need for an optimal angular estimation of targets and their separation based on the minimal number of angular samples arises
2 we further show that other common queries currently supported in o log log n time and o delta t log o 1 n space including the burrows-wheeler transform bwt permuted longest common prefix plcp array last-to-first lf inverse lf lexicographic predecessor phi and inverse phi
queries
query complexity
2 we further show that other common queries currently supported in o log log n time and o delta t log o 1 n space including the burrows-wheeler transform bwt permuted longest common prefix plcp array last-to-first lf inverse lf lexicographic predecessor phi and inverse phi queries all require omega log log n time yield...
we hope these findings motivate a broader reconsideration of precision trade-offs in
rl
reinforcement learning rl
we hope these findings motivate a broader reconsideration of precision trade-offs in rl fine-tuning
additionally the analysis in this work relies on verification of
robot
dynamic obstacles
additionally the analysis in this work relies on verification of robot behaviors using fundamental robot-obstacle experimental scenarios
hybrid consistency policy decoupling multi-modal diversity and real-time efficiency in
robotic
robotic manipulation
hybrid consistency policy decoupling multi-modal diversity and real-time efficiency in robotic manipulation
nonparametric identification of spatial treatment effect
boundaries
effect boundaries
nonparametric identification of spatial treatment effect boundaries evidence from bank branch consolidation
neyman targeted estimation also yields tmle as a special
case
maximum likelihood
neyman targeted estimation also yields tmle as a special case for regression function estimation
lastly we apply inputdsa to neural data recorded from rats performing a
cognitive
fmri data
lastly we apply inputdsa to neural data recorded from rats performing a cognitive task demonstrating that it identifies a transition from input-driven evidence accumulation to intrinsically-driven decision-making
first technology adoption exhibits strong exponential geographic decay with spatial
decay
spatial decay
first technology adoption exhibits strong exponential geographic decay with spatial decay rate kappa approx 0
an optimal solution can be found with a greedy algorithm steel systematic biology 2005 pardi and goldman plos
genetics
population genetics
an optimal solution can be found with a greedy algorithm steel systematic biology 2005 pardi and goldman plos genetics 2005
here we compare three different ar navigation aids on-screen compass on-screen radar and in-world vertical arrows in a wide-area outdoor user study n 24 where participants search for hidden virtual target items amongst
physical
mobile ar
here we compare three different ar navigation aids on-screen compass on-screen radar and in-world vertical arrows in a wide-area outdoor user study n 24 where participants search for hidden virtual target items amongst physical and virtual objects
cross-lingual alignment cla aims to align
multilingual
large language
cross-lingual alignment cla aims to align multilingual representations enabling large language models llms to seamlessly transfer knowledge across languages
neural networks are parametric and powerful tools for function approximation and the choice of architecture
heavily
deep learning
neural networks are parametric and powerful tools for function approximation and the choice of architecture heavily influences their interpretability efficiency and generalization
unsupervised learning is therefore a natural approach for exploring the design of
biological
receptive fields
unsupervised learning is therefore a natural approach for exploring the design of biological neural networks and their computations
an analogous relaxation in the lower energy singlet state using spin purified
atomic
molecular dynamics
an analogous relaxation in the lower energy singlet state using spin purified atomic forces is estimated to be 0
nature access is increasingly recognised as a public
health
public health
nature access is increasingly recognised as a public health and equity imperative yet cities lack standardised ways to measure who benefits from green infrastructure
for a graph g the parameter treedepth measures the minimum depth among all forests f called elimination
forests
tree edit
for a graph g the parameter treedepth measures the minimum depth among all forests f called elimination forests such that g is a subgraph of the ancestor-descendant closure of f
the efficacy of our approach is demonstrated through simulation studies of two challenging interactive scenarios an unregulated intersection crossing and a highway
lane
collision avoidance
the efficacy of our approach is demonstrated through simulation studies of two challenging interactive scenarios an unregulated intersection crossing and a highway lane change in dense traffic
we propose explicit measurement sequences that can be readily implemented in systems such as
trapped
trapped ions
we propose explicit measurement sequences that can be readily implemented in systems such as trapped ions
for calibration guarantees that fall short of decision calibration the
minimax
minimax optimal
for calibration guarantees that fall short of decision calibration the minimax optimal decision rule is still efficiently computable and we provide an empirical evaluation of a natural one that applies to any regression model solved to optimize squared error
yet an important question still remains are
video
video generation
yet an important question still remains are video models ready to serve as zero-shot reasoners in challenging visual reasoning scenarios
using multidimensional scaling we recover low-dimensional psychological spaces and find that their axes show a strong correspondence with the principal
axes
higher-order visual
using multidimensional scaling we recover low-dimensional psychological spaces and find that their axes show a strong correspondence with the principal axes of human perceptual space
initially the global income distribution exhibited a bimodal pattern however the growth of middle classes in highly populated countries such as china and india has driven the transition to a unimodal
distribution
income distribution
initially the global income distribution exhibited a bimodal pattern however the growth of middle classes in highly populated countries such as china and india has driven the transition to a unimodal distribution in recent years
anomalies are identified through a novel gating mechanism that initially flags potential
anomalies
anomaly detection
anomalies are identified through a novel gating mechanism that initially flags potential anomalies based on gaussian uncertainty estimates and subsequently verifies them using a composite of critic scores and reconstruction errors
based on our characterization we design a policy optimization algorithm that uses machine learning to predict counterfactual outcomes and then plugs in these predictions to estimate the pareto frontier then the decision-maker can select the policy that optimizes their desired tradeoff after which
policy
policy learning
based on our characterization we design a policy optimization algorithm that uses machine learning to predict counterfactual outcomes and then plugs in these predictions to estimate the pareto frontier then the decision-maker can select the policy that optimizes their desired tradeoff after which policy evaluation can ...
the phase transition is quite robust and becomes progressively conspicuous in the limit of large population size where deterministic
evolutionary
evolutionary dynamics
the phase transition is quite robust and becomes progressively conspicuous in the limit of large population size where deterministic evolutionary game dynamics viz
post-training of large language models llms is crucial for unlocking their task generalization
potential
llm post-training
post-training of large language models llms is crucial for unlocking their task generalization potential and domain-specific capabilities
to overcome the challenge of obtaining clean diverse and suitable training data we leverage pre-trained vision-and-language models
vlms
language models
to overcome the challenge of obtaining clean diverse and suitable training data we leverage pre-trained vision-and-language models vlms in a training-free approach called basic
viewing llms as implicit repositories of human knowledge we propose evontree a novel framework that leverages a small set of high-quality ontology rules to systematically extract validate and enhance domain
knowledge
large language models llms
viewing llms as implicit repositories of human knowledge we propose evontree a novel framework that leverages a small set of high-quality ontology rules to systematically extract validate and enhance domain knowledge within llms without requiring extensive external datasets
next from w we define the operator v which gives the frequency distribution of
genetic
population genetics
next from w we define the operator v which gives the frequency distribution of genetic types
inferring causal relationships between variable pairs in the observational study is crucial but challenging due to the presence of
unmeasured
causal effects
inferring causal relationships between variable pairs in the observational study is crucial but challenging due to the presence of unmeasured confounding
a unified theory for causal inference direct
debiased
debiased machine
a unified theory for causal inference direct debiased machine learning via bregman-riesz regression
simulations reveal diverse emergent behaviors such as prey dispersal and regrouping oscillatory predation with
collective
ecological communities
simulations reveal diverse emergent behaviors such as prey dispersal and regrouping oscillatory predation with collective defense and predator encirclement
quantum enhanced dark-matter search with entangled fock
states
quantum dot
quantum enhanced dark-matter search with entangled fock states in high-quality cavities
we show here that in models equipped with a learning rule inferred from neurobiological data spurious
overlaps
continual learning
we show here that in models equipped with a learning rule inferred from neurobiological data spurious overlaps collectively reduce the mean synaptic inputs to neurons and that this mean reduction causes in turn an increase in storage capacity through a sparsening of network activity
to tackle this challenge we propose braincognizer a novel brain decoding model inspired by human visual
cognition
brain decoding
to tackle this challenge we propose braincognizer a novel brain decoding model inspired by human visual cognition which explores multi-level semantics and correlations without fine-tuning of generative models
in the algorithmic kolmogorov view agents are programs that track and compress
sensory
predictive processing
in the algorithmic kolmogorov view agents are programs that track and compress sensory streams using generative programs
while many real scale-free networks are known to contain shorter loops such as triangles it remains to investigate the distributions of longer
loops
scale-free networks
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
finally we analyze the generalization performance of a gradient-based
meta-reinforcement
reinforcement learning
finally we analyze the generalization performance of a gradient-based meta-reinforcement learning algorithm
we analyze a model where the mlp comprises two layers with the first layer trained via a single gradient step and the second
layer
neural network
we analyze a model where the mlp comprises two layers with the first layer trained via a single gradient step and the second layer fully optimized
our benchmark results reflect general improvements of recommender systems on the public
datasets
preference data
our benchmark results reflect general improvements of recommender systems on the public datasets with variable individual performances
we focus on the efficiency of building tree
embedding
spanning trees
we focus on the efficiency of building tree embedding in various computational settings under high-dimensional euclidean mathbb r d
resmatching noise-resilient computational super-resolution via guided conditional
flow
optical flow
resmatching noise-resilient computational super-resolution via guided conditional flow matching
while extensive progress has been made for one-dimensional strings many real-world
datasets
real-world datasets
while extensive progress has been made for one-dimensional strings many real-world datasets such as images maps and adjacency matrices are inherently two-dimensional and highly compressible
our findings reveal that while current video models demonstrate promising reasoning patterns on short-horizon spatial coherence fine-grained grounding and locally consistent dynamics they remain limited in long-horizon causal
reasoning
mathematical reasoning
our findings reveal that while current video models demonstrate promising reasoning patterns on short-horizon spatial coherence fine-grained grounding and locally consistent dynamics they remain limited in long-horizon causal reasoning strict geometric constraints and abstract logic
we show that if the system is controllable then incorporating this as prior knowledge does not relax the
conditions
optimal control
we show that if the system is controllable then incorporating this as prior knowledge does not relax the conditions required for data-driven stabilization
we opt to model human driver decisions as a markov decision process and propose a method for handling
collision
collision avoidance
we opt to model human driver decisions as a markov decision process and propose a method for handling collision avoidance between non-convex vehicle shapes by imposing a positive distance constraint between compact sets
the intermittent nature of renewable power availability is one of the major sources of uncertainty in
power
power systems
the intermittent nature of renewable power availability is one of the major sources of uncertainty in power systems
preliminary numerical experiments on synthetic datasets and real-world quadratic
programming
quadratic programming
preliminary numerical experiments on synthetic datasets and real-world quadratic programming problems in portfolio optimization demonstrate the effectiveness and superiority of the proposed algorithm
building on this insight we propose attncache a framework that accelerates the prefill stage of llm
inference
models llms
building on this insight we propose attncache a framework that accelerates the prefill stage of llm inference by retrieving and reusing similar attention maps
our method constructs a language model graph that maps relationships between models from the semantic coherence of pairwise conversations and then applies community detection to identify
synergistic
language agents
our method constructs a language model graph that maps relationships between models from the semantic coherence of pairwise conversations and then applies community detection to identify synergistic model clusters
the system integrates advanced computer vision robotic control and real-time
stabilization
data-driven stabilization
the system integrates advanced computer vision robotic control and real-time stabilization technologies via a multi-sensor fusion approach
driven by the essential components of tool usage - grasping the desired outcome selecting the most suitable tool determining optimal
tool
robotic manipulation
driven by the essential components of tool usage - grasping the desired outcome selecting the most suitable tool determining optimal tool orientation and executing precise manipulations - we introduce a pioneering framework
the study of complex systems has attracted widespread attention from researchers in the fields of natural sciences
social
complex systems
the study of complex systems has attracted widespread attention from researchers in the fields of natural sciences social sciences and engineering
recent alignment techniques such as reinforcement learning from human feedback have been widely adopted to align large language models with human preferences by learning and leveraging
reward
reward models
recent alignment techniques such as reinforcement learning from human feedback have been widely adopted to align large language models with human preferences by learning and leveraging reward models
these results deepen the understanding of adaptive decision-making in spatial
ecology
ecological communities
these results deepen the understanding of adaptive decision-making in spatial ecology linking cognitive complexity to ecosystem resilience and extinction risk
averaging the hamiltonian over the inner orbit we find that magnetic tides introduce new resonances absent at lower
order
tidal field
averaging the hamiltonian over the inner orbit we find that magnetic tides introduce new resonances absent at lower order leading to additional eccentricity excitations and significantly modifying the binary s long-term evolution
this survey provides an analysis of current methodologies integrating legal and logical specifications into the perception prediction and planning modules of automated
driving
autonomous driving
this survey provides an analysis of current methodologies integrating legal and logical specifications into the perception prediction and planning modules of automated driving systems
our approach reconciles local heterogeneity with universal representation offering a new pathway toward a more comprehensive
urban
urban systems
our approach reconciles local heterogeneity with universal representation offering a new pathway toward a more comprehensive urban science
this paper presents a novel approach to formulating the actor-critic method for optimal
control
predictive control
this paper presents a novel approach to formulating the actor-critic method for optimal control by casting policy iteration in reproducing kernel hilbert spaces rkhss -- also known as native spaces
humans possess spatial reasoning abilities that enable them to understand spaces through
multimodal
spatial reasoning
humans possess spatial reasoning abilities that enable them to understand spaces through multimodal observations such as vision and sound
to overcome these limitations we propose a novel multiplicative update proximal
gradient
gradient descent
to overcome these limitations we propose a novel multiplicative update proximal gradient algorithm sso-pga with convergence guarantees which is designed for robustness in non-negative inverse problems
we establish coverage guarantees under two sets of assumptions exact finite-sample validity under exchangeability relevant for cross-sectional data and asymptotic
validity
external validity
we establish coverage guarantees under two sets of assumptions exact finite-sample validity under exchangeability relevant for cross-sectional data and asymptotic validity under stationarity relevant for time-series data
soliton interaction and bound state formation in coupled
kerr
kerr rotation
soliton interaction and bound state formation in coupled kerr resonators
finally our theoretical findings are validated by extensive
numerical
theoretical findings
finally our theoretical findings are validated by extensive numerical results
understanding the encoding and decoding mechanisms of
dynamic
higher-order visual
understanding the encoding and decoding mechanisms of dynamic neural responses to different visual stimuli is an important topic in exploring how the brain represents visual information
however problems in rendering can create sensorimotor disruptions that undermine presence and
task
task performance
however problems in rendering can create sensorimotor disruptions that undermine presence and task performance
we find that some configurations preserve or even improve
multilingual
large language
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
jogs joint optimization of pose estimation and 3d
gaussian
gaussian splatting
jogs joint optimization of pose estimation and 3d gaussian splatting
the main difficulties to treat such problems are the lack of smoothing properties of the linear part of the hjb equation the presence of unbounded
control
optimal control
the main difficulties to treat such problems are the lack of smoothing properties of the linear part of the hjb equation the presence of unbounded control operators the presence of state-dependent costs
a three-stage bayesian transfer learning framework to improve
predictions
policy learning
a three-stage bayesian transfer learning framework to improve predictions in data-scarce domains
together our results show that sparse input synergizes with sequence-generating dynamics providing both a mechanistic account of place cell sequences in the mammalian hippocampus and a simple inductive bias for
reinforcement
reinforcement learning
together our results show that sparse input synergizes with sequence-generating dynamics providing both a mechanistic account of place cell sequences in the mammalian hippocampus and a simple inductive bias for reinforcement learning based on sparse egocentric inputs in navigation tasks
scalable predictive processing framework for multitask
caregiving
predictive processing
scalable predictive processing framework for multitask caregiving robots
in the human brain the allowed patterns of activity are constrained by the
correlations
fmri data
in the human brain the allowed patterns of activity are constrained by the correlations between brain regions
the presence of occlusions has provided substantial challenges to typically-powerful
object
computer vision
the presence of occlusions has provided substantial challenges to typically-powerful object recognition algorithms
bridging the gap between empirical welfare maximization and conditional average treatment effect estimation in
policy
policy learning
bridging the gap between empirical welfare maximization and conditional average treatment effect estimation in policy learning
this paper explores how we can leverage ai to
improve
ai agents
this paper explores how we can leverage ai to improve the quality of human oversight
we also demonstrate that the inter-layer magnetic coupling in these materials can be tuned by strain
enabling
quantum materials
we also demonstrate that the inter-layer magnetic coupling in these materials can be tuned by strain enabling the switching between the ahe and the axionic states
newton s method may exhibit slower convergence than vanilla
gradient
accelerated gradient
newton s method may exhibit slower convergence than vanilla gradient descent in its initial phase on strongly convex problems
nearly all fundamental queries can currently be efficiently supported in o delta t log o 1 n space where delta t is the substring complexity a strong compressibility measure that lower-bounds the optimal
space
compressed indexing
nearly all fundamental queries can currently be efficiently supported in o delta t log o 1 n space where delta t is the substring complexity a strong compressibility measure that lower-bounds the optimal space to represent the text kociumaka navarro prezza ieee trans
trajectory planning for mobile robots in cluttered
environments
dynamic obstacles
trajectory planning for mobile robots in cluttered environments remains a major challenge due to narrow passages where conventional methods often fail or generate suboptimal paths
fully programmable plasmonic pt-symmetric dimer with epsilon near zero and phase-change materials for
integrated
integrated photonics
fully programmable plasmonic pt-symmetric dimer with epsilon near zero and phase-change materials for integrated photonics
we believe that this work outlines a significant route for next-generation programmable photonics delivering subwavelength confinement energy-efficient operation and high-dimensional optical reconfigurability within an
integrated
integrated photonics
we believe that this work outlines a significant route for next-generation programmable photonics delivering subwavelength confinement energy-efficient operation and high-dimensional optical reconfigurability within an integrated scalable and manufacturable platform
for task assignment we present two multi-objective algorithms non-dominated sorting
genetic
genetic algorithm
for task assignment we present two multi-objective algorithms non-dominated sorting genetic algorithm nsga and adaptive large neighborhood search alns
learning to generalize in evolution through
annealed
population genetics
learning to generalize in evolution through annealed population heterogeneity
however its potential is constrained by the difficulty of acquiring accurate user-to-ris channel state information csi due to the cascaded
channel
channel state
however its potential is constrained by the difficulty of acquiring accurate user-to-ris channel state information csi due to the cascaded channel structure and the high pilot overhead of non-parametric methods
this includes the energy of the excited triplet as well as the two lowest singlet states with respect to the
ground
ground state
this includes the energy of the excited triplet as well as the two lowest singlet states with respect to the ground triplet state
however when a food web representing predator-prey relationships is given finding a set of species that optimizes phylogenetic diversity subject to the condition that each saved species should be able to find
food
food web
however when a food web representing predator-prey relationships is given finding a set of species that optimizes phylogenetic diversity subject to the condition that each saved species should be able to find food among the preserved species is np-hard spillner et al
single-light-pulse driven compact atom interferometry with
measurement
atom interferometry
single-light-pulse driven compact atom interferometry with measurement induced large momentum transfer
we present a parallel algorithm for computing 1
epsilon
-approximation algorithm
we present a parallel algorithm for computing 1 epsilon -approximate mincost flow on an undirected graph with m edges where capacities and costs are assigned to both edges and vertices
we then use this idea to find overlooked critical numbers in past studies of
collective
human disturbance
we then use this idea to find overlooked critical numbers in past studies of collective behavior and explore the implications for their conclusions
the interplay between the accretion of supermassive black
holes
black hole mass
the interplay between the accretion of supermassive black holes smbhs and the stellar mass growth of the host galaxies is still a matter of hot debate
presence is typically assessed with post-hoc questionnaires but their coarse temporal resolution limits insight into how sensorimotor
disruptions
sensorimotor disruptions
presence is typically assessed with post-hoc questionnaires but their coarse temporal resolution limits insight into how sensorimotor disruptions shape user experience