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in addition practitioners also want confidence that the learned policy has better performance than the incumbent policy according to downstream
policy
policy evaluation
in addition practitioners also want confidence that the learned policy has better performance than the incumbent policy according to downstream policy evaluation
tree embedding has been a fundamental method in algorithm design with
wide
tree edit
tree embedding has been a fundamental method in algorithm design with wide applications
we ultimately wish to answer the fundamental question what are the physically realizable
correlations
quantum correlations
we ultimately wish to answer the fundamental question what are the physically realizable correlations between multiple parties under varying latency constraints
generative artificial intelligence genai can aid
humans
ai use
generative artificial intelligence genai can aid humans in a wide range of tasks but its effectiveness critically depends on users being able to evaluate the accuracy of genai outputs and their own expertise
we investigate whether large language models
llms
large language
we investigate whether large language models llms can act as in-context meta-learners for this task
recent work has shown that different large language models
llms
large language models llms
recent work has shown that different large language models llms converge to similar and accurate input embedding representations for numbers
secondly sufficient conditions for a central
limit
central limit
secondly sufficient conditions for a central limit theorem with a standard rate of convergence are supplied
quantifying the uncertainty in the output of a
neural
neural network
quantifying the uncertainty in the output of a neural network is essential for deployment in scientific or engineering applications where decisions must be made under limited or noisy data
we show that assignment rules with more than one
variable
treatment assignment
we show that assignment rules with more than one variable allow the estimation of a more comprehensive set of treatment effects relaxing in a research-driven style the local and sometimes limiting nature of univariate rd designs
to address this we leverage a suite of representational similarity metrics-each capturing a distinct facet of representational correspondence such as geometry unit-level tuning or
linear
encoding models
to address this we leverage a suite of representational similarity metrics-each capturing a distinct facet of representational correspondence such as geometry unit-level tuning or linear decodability-and assess brain region or model separability using multiple complementary measures
however current watermarking solutions hardly resolve the trust issue the non-public watermark
detection
watermarking schemes
however current watermarking solutions hardly resolve the trust issue the non-public watermark detection cannot prove itself faithfully conducting the detection
spin readout after coherent control of single nvs is demonstrated using charge
readout
spin readout
spin readout after coherent control of single nvs is demonstrated using charge readout in a protocol we call charge-capture detected magnetic resonance ccdmr and we use charge-based imaging to identify charge carrier generation and trapping processes
the graph constructed from the power system model requires only knowledge of the dependencies between state-to-state and output-to-state variables within a
state-space
power flow
the graph constructed from the power system model requires only knowledge of the dependencies between state-to-state and output-to-state variables within a state-space framework
while transferring into hand articulatied object interaction haoi the hand grasps synthesis requires not only object functionality but also long-term
manipulation
manipulation ordering
while transferring into hand articulatied object interaction haoi the hand grasps synthesis requires not only object functionality but also long-term manipulation sequence along the object deformation
for three decades statistical physics has been providing a framework to analyse
neural
deep learning
for three decades statistical physics has been providing a framework to analyse neural networks
with a software-defined radio our approach can dynamically sweep the synthetic
wavelength
optical communication
with a software-defined radio our approach can dynamically sweep the synthetic wavelength and measure absolute optical range
we consider a class of algorithms for this problem which is provably
minimax
minimax optimal
we consider a class of algorithms for this problem which is provably minimax optimal up to a constant factor
secondly sufficient conditions for a central limit theorem with a standard
rate
convergence rate
secondly sufficient conditions for a central limit theorem with a standard rate of convergence are supplied
point convergence analysis of the accelerated
gradient
gradient descent
point convergence analysis of the accelerated gradient method for multiobjective optimization continuous and discrete
simulations show that these continuous-time networks stably learn at
biological
continual learning
simulations show that these continuous-time networks stably learn at biological timescales even under temporal mismatches and integration noise
these applications have motivated a growing demand for compact reconfigurable
vortex
vortex phase
these applications have motivated a growing demand for compact reconfigurable vortex arrays with tunable topological charge yet integrating these functionalities into nanophotonic platforms remains elusive
it is shown however that under control gain variation the safe set of these
controllers
predictive control
it is shown however that under control gain variation the safe set of these controllers is locally asymptotically stable which implies that their safety is sensitive to large but bounded disturbances
we demonstrate the practical value of our approach through applications across economics biology and
machine
machine learning
we demonstrate the practical value of our approach through applications across economics biology and machine learning benchmarks
in 5g nr reciprocity-based beamforming via uplink sounding reference
signals
beamforming design
in 5g nr reciprocity-based beamforming via uplink sounding reference signals srs face resource and coverage constraints motivating sparse non-uniform srs allocation
our modification introduces an auxiliary anchor class enabling consistent density ratio
estimation
density ratio
our modification introduces an auxiliary anchor class enabling consistent density ratio estimation and yielding a plug-in mi estimator with significantly reduced bias
this gives rise to a new family of explicitly constructed
graphs
spanning trees
this gives rise to a new family of explicitly constructed graphs which may have other applications
we define symmetric and asymmetric branching trees a class of processes particularly suited for
modeling
basic reproduction
we define symmetric and asymmetric branching trees a class of processes particularly suited for modeling genealogies of inhomogeneous populations where individuals may reproduce throughout life
our findings suggest the smc has a higher production of eu with respect to the alpha -elements than the
milky
milky way
our findings suggest the smc has a higher production of eu with respect to the alpha -elements than the milky way but in line with what observed in other dwarf systems within the local group
bridging the gap between empirical welfare maximization and conditional average treatment effect estimation in
policy
reinforcement learning
bridging the gap between empirical welfare maximization and conditional average treatment effect estimation in policy learning
in this setting the usual constant diffusion coefficient is replaced by the spatially varying coefficient produced by the learned density yielding
dynamics
langevin dynamics
in this setting the usual constant diffusion coefficient is replaced by the spatially varying coefficient produced by the learned density yielding dynamics that differ significantly from those obtained with conventional constant-diffusion models
we also review and discuss different methods for m_
bullet
dwarf galaxies
we also review and discuss different methods for m_ bullet inference in tdes and find that approaches based on physical models of the early-time uv optical emission are not able to recover at a statistically significant level black hole-host galaxy scalings
phylogenetic trees capture evolutionary relationships among
species
phylogenetic diversity
phylogenetic trees capture evolutionary relationships among species and reflect the forces that shaped them
a logic-based algorithmic meta-theorem for
treedepth
-errata trees
a logic-based algorithmic meta-theorem for treedepth single exponential fpt time and polynomial space
nanovla routing decoupled vision-language understanding for nano-sized generalist
robotic
vision-language models
nanovla routing decoupled vision-language understanding for nano-sized generalist robotic policies
these embodied computers enable the soft robot to perform complex behaviors that would otherwise require cmos-based electronics -- including coordinated locomotion with obstacle avoidance payload weight and orientation
classification
physical computing
these embodied computers enable the soft robot to perform complex behaviors that would otherwise require cmos-based electronics -- including coordinated locomotion with obstacle avoidance payload weight and orientation classification and programmable operation based on logical rules
this paper introduces a simple code-agnostic framework that reduces the worst-case complexity by a factor of n down to q k operations a highly desirable
reduction
integer programs
this paper introduces a simple code-agnostic framework that reduces the worst-case complexity by a factor of n down to q k operations a highly desirable reduction in practice
this allows us to infer a dense turn-by-turn reward signal grounded in the expert s revealed strategy decomposing the intractable long-horizon problem into a series of supervised
learning
reinforcement learning
this allows us to infer a dense turn-by-turn reward signal grounded in the expert s revealed strategy decomposing the intractable long-horizon problem into a series of supervised learning tasks and training a policy to output a structured texttt action state_assessment tuple governing both textbf what to ask and crucia...
we study two-stage bipartite matching in which the edges of a
bipartite
bipartite graphs
we study two-stage bipartite matching in which the edges of a bipartite graph on vertices b_1 cup b_2 i are revealed in two batches
the difference-in-differences did research design is a key identification strategy which allows researchers to estimate
causal
causal effects
the difference-in-differences did research design is a key identification strategy which allows researchers to estimate causal effects under the parallel trends assumption
while dob-based designs have shown effectiveness in rejecting
disturbances
disturbance observer
while dob-based designs have shown effectiveness in rejecting disturbances under nominal conditions their performance deteriorates considerably in the presence of unknown time delays
our model uniquely utilizes a quantum-enhanced generator that outputs parameters mean and log-variance of a gaussian distribution via reparameterization combined with a
wasserstein
generative models
our model uniquely utilizes a quantum-enhanced generator that outputs parameters mean and log-variance of a gaussian distribution via reparameterization combined with a wasserstein critic to stabilize adversarial training
flexible tactile sensors are increasingly used in real-world applications such as robotic grippers prosthetic hands wearable gloves and assistive devices where they need to conform to
curved
tactile sensors
flexible tactile sensors are increasingly used in real-world applications such as robotic grippers prosthetic hands wearable gloves and assistive devices where they need to conform to curved and irregular surfaces
we develop an online algorithm and prove that it achieves a
competitive
online algorithm
we develop an online algorithm and prove that it achieves a competitive ratio of max 2 min gamma 3 where gamma is the max min storage cost ratio among all servers
a three-dimensional reconstruction of the
interstellar
star formation
a three-dimensional reconstruction of the interstellar magnetic field toward a star-forming region
maps converts attribution maps into explanation-masked images emis and compares image-by-image human accuracies on these minimal
images
higher-order visual
maps converts attribution maps into explanation-masked images emis and compares image-by-image human accuracies on these minimal images with limited pixel budgets with accuracies on the full stimuli
theoretical properties including bounds on bias estimation errors and improvements in prediction
accuracy
predictive performance
theoretical properties including bounds on bias estimation errors and improvements in prediction accuracy are provided
bnlf performs late fusion by modelling the
sentiment
large language models llms
bnlf performs late fusion by modelling the sentiment predictions from multiple llms as probabilistic nodes within a bayesian network
finally we outline open problems in the field and present a roadmap for integrating tf-qkd into scalable quantum
networks
quantum channels
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
2024 develops riesz regression for automatic debiased machine learning which directly estimates the
riesz
riesz regression
2024 develops riesz regression for automatic debiased machine learning which directly estimates the riesz representer or equivalently the bias-correction term by minimizing the mean squared error
based on the similarity transformations of these cooperative geometric primitives we derive an abstraction of complex
robotic
robotic systems
based on the similarity transformations of these cooperative geometric primitives we derive an abstraction of complex robotic systems that enables representing these systems in a way that directly corresponds to single-arm systems
we then analyze the representation power of the abstraction and give
provable
representation learning
we then analyze the representation power of the abstraction and give provable learning guarantees
at each time step each individual produces a large
number
basic reproduction
at each time step each individual produces a large number of offspring that inherit the fitness of their parents up to independent and identically distributed fluctuations
braincognizer brain decoding with human visual
cognition
human brain
braincognizer brain decoding with human visual cognition simulation for fmri-to-image reconstruction
our findings suggest the smc has a higher production of eu with respect to the alpha -elements than the milky
way
galactic nuclei
our findings suggest the smc has a higher production of eu with respect to the alpha -elements than the milky way but in line with what observed in other dwarf systems within the local group
using photoionisation models from the photodissociation region toolbox we quantify the
ism
dwarf galaxies
using photoionisation models from the photodissociation region toolbox we quantify the ism conditions in the different regions determining that the southern star-forming regions have a high density n_h sim 10 5 cm -3 and are irradiated by a moderate uv radiation field g_0 sim 10 3 habing
to realize this vision we introduce asynchronous thinking asyncthink as a new paradigm of reasoning with large language models which organizes the internal
thinking
reasoning curriculum
to realize this vision we introduce asynchronous thinking asyncthink as a new paradigm of reasoning with large language models which organizes the internal thinking process into concurrently executable structures
notably our algorithm can be viewed as an optimized
diffusion
diffusion models
notably our algorithm can be viewed as an optimized diffusion process and can be integrated into existing methods to further improve their performance
since the organ of biological cognition is the nervous system whether biological
cognition
surrogate brain
since the organ of biological cognition is the nervous system whether biological cognition relies on a lot depends on how neural hardware works
vacuum decay posits that the universe s apparent
vacuum
vacuum metastable
vacuum decay posits that the universe s apparent vacuum is metastable and could transition to a lower-energy state
here we harness these capabilities in twisted bilayer moire
photonic
photonic crystal
here we harness these capabilities in twisted bilayer moire photonic crystals tbmpcs to realize vortex array generation with tunable oam demonstrated both analytically and experimentally
at low redshift massive quiescent galaxies mqgs are most frequently found in massive rich galaxy
clusters
massive stars
at low redshift massive quiescent galaxies mqgs are most frequently found in massive rich galaxy clusters but at high redshift the trend is less clear
the integration of large language models into intelligent tutoring systems pre-sents significant challenges in aligning with diverse and often conflicting values from
students
language models
the integration of large language models into intelligent tutoring systems pre-sents significant challenges in aligning with diverse and often conflicting values from students parents teachers and institutions
potential old stellar populations may be necessary to account for the derived
metallicity
stellar mass function
potential old stellar populations may be necessary to account for the derived metallicity of sim0
the current best quantum algorithm has the query complexity o n 7 4 which is an improvement over the trivial bound o
n
open quantum
the current best quantum algorithm has the query complexity o n 7 4 which is an improvement over the trivial bound o n 2
the infonce objective originally introduced for contrastive
representation
representation learning
the infonce objective originally introduced for contrastive representation learning has become a popular choice for mutual information mi estimation despite its indirect connection to mi
however traditional one-dimensional opinion models -- assuming support for one party equals opposition to another -- fail to capture the nuanced dynamics of swing
voters
swing voters
however traditional one-dimensional opinion models -- assuming support for one party equals opposition to another -- fail to capture the nuanced dynamics of swing voters including neutrals left leaners and right leaners who are critical for the final election outcomes
graph-theoretical analyses were applied to functional
connectivity
functional connectivity
graph-theoretical analyses were applied to functional connectivity matrices and clustered based on graph similarity
in recent work it has been shown that this random return can be well approximated by a finite number of random variables which we call truncated
random
truncated random
in recent work it has been shown that this random return can be well approximated by a finite number of random variables which we call truncated random return
the simulations include detailed modeling of star formation
chemical
star clusters
the simulations include detailed modeling of star formation chemical enrichment and supernova feedback using the textsc celib and textsc grackle libraries achieving baryonic resolutions of sim2 times10 3 m_ odot
in single-objective optimization the point convergence problem of nesterov s accelerated
gradient
accelerated gradient
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
current steering methods such as vector addition and directional ablation are constrained within a two-dimensional subspace defined by the activation and
feature
angular steering
current steering methods such as vector addition and directional ablation are constrained within a two-dimensional subspace defined by the activation and feature direction making them sensitive to chosen parameters and potentially affecting unrelated features due to unintended interactions in activation space
we detail the design of a large language model
llm
language models
we detail the design of a large language model llm -driven instructor agent and introduce a pedagogical framework that integrates the instructor agent into the course workflow for actively interacting with the students for content delivery supplemented by the human instructor to offer the course structure and undertake...
unlike a passive ris where the reflected signal suffers from multiplicative path loss an active
ris
active ris
unlike a passive ris where the reflected signal suffers from multiplicative path loss an active ris amplifies the signal improving its practicality in real deployments
5 cdot w 4 cdot n m -time algorithm for pmwed under the assumption that the weight function is a metric with integer values between 0 and
w
-time algorithm
5 cdot w 4 cdot n m -time algorithm for pmwed under the assumption that the weight function is a metric with integer values between 0 and w and c an tilde o n k 4 cdot n m -time algorithm for pmwed for the case of arbitrary weights
to realize this vision we introduce asynchronous thinking asyncthink as a new paradigm of
reasoning
reasoning capabilities
to realize this vision we introduce asynchronous thinking asyncthink as a new paradigm of reasoning with large language models which organizes the internal thinking process into concurrently executable structures
because it is chemically inert it has never been considered in astrochemical models that studied
molecular
molecular gas
because it is chemically inert it has never been considered in astrochemical models that studied molecular evolution
the ability to continually learn retain and deploy skills to accomplish goals is a key feature of
intelligent
cognitive science
the ability to continually learn retain and deploy skills to accomplish goals is a key feature of intelligent and efficient behavior
semantic category features of visual stimuli from
population
receptive fields
semantic category features of visual stimuli from population activity with reconstructions preserving key perceptual attributes as quantified by feature-based similarity metrics
existing causal discovery methods allow enforcing structural constraints for example requiring a causal path from pip3 to akt but they may still produce incorrect
causal
interventional constraints
existing causal discovery methods allow enforcing structural constraints for example requiring a causal path from pip3 to akt but they may still produce incorrect causal conclusions such as learning that pip3 inhibits akt
results demonstrate that icpo consistently enhances
reinforcement
policy learning
results demonstrate that icpo consistently enhances reinforcement learning performance and training stability on mathematical reasoning benchmarks revealing a scalable and effective rlvr paradigm for lrms
we describe how weak phase modulations applied to classical
coherent
optical communication
we describe how weak phase modulations applied to classical coherent light in specially modified linear interferometers can be used to perform primitive computational tasks
large language models llms have significantly advanced generative
applications
llm inference
large language models llms have significantly advanced generative applications in natural language processing nlp
tight lower bounds for central string queries in
compressed
query complexity
tight lower bounds for central string queries in compressed space
using network gradients it is possible to identify regions where the
network
neural network
using network gradients it is possible to identify regions where the network pays attention during image recognition tasks
our results indicate that although llms generally adhere to valid reasoning patterns they exhibit notable inconsistencies in specific types of
normative
reasoning curriculum
our results indicate that although llms generally adhere to valid reasoning patterns they exhibit notable inconsistencies in specific types of normative reasoning and display cognitive biases similar to those observed in psychological studies of human reasoning
the dc conductivity results reveal a two orders of magnitude enhancement of ionic
conductivity
heat conduction
the dc conductivity results reveal a two orders of magnitude enhancement of ionic conductivity from 3
this is formulated as a bilevel optimization problem the inner optimization solves the qp under a given projection using a
qp
bilevel optimization
this is formulated as a bilevel optimization problem the inner optimization solves the qp under a given projection using a qp solver while the outer optimization updates the model parameters
emission-line diagnostics suggest stellar populations as the
primary
emission line
emission-line diagnostics suggest stellar populations as the primary ionizing source although an agn fraction of 14 is found
however in recent years with the rise of generative ai especially large
language
large language
however in recent years with the rise of generative ai especially large language models llm and particularly with the widespread popularity of the chatgpt model that concern became practical
we derived the formalism for arbitrary observed orientation of the galaxy cgm model and quasar
line
milky way
we derived the formalism for arbitrary observed orientation of the galaxy cgm model and quasar line of sight positioning
in this paper we address this challenge by developing a novel framework based on gaussian process regression gpr that predicts full
csi
csi dataset
in this paper we address this challenge by developing a novel framework based on gaussian process regression gpr that predicts full csi from only a few observed entries thereby reducing pilot overhead
this paper presents a decentralized control barrier function cbf based approach for highway merging of connected and
automated
collision avoidance
this paper presents a decentralized control barrier function cbf based approach for highway merging of connected and automated vehicles cavs
when conditional exchangeability was violated
causal
causal effect
when conditional exchangeability was violated causal forest and x-learner models failed to recover true treatment effect heterogeneity and in some cases falsely indicated heterogeneity when there was none
here we present mobilitygen a deep generative model that produces realistic
mobility
traffic dynamics
here we present mobilitygen a deep generative model that produces realistic mobility trajectories spanning days to weeks at large spatial scales
for p infty we establish a hardness of tilde omega log 2 n improving upon the previous tilde
omega
omega log
for p infty we establish a hardness of tilde omega log 2 n improving upon the previous tilde omega log n hardness result
various dynamical diagnostics - including galaxy pairwise separations velocity dispersions and the offset of the first-ranked galaxy from the group barycentre
-
massive galaxies
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
here we address this shortcoming by using dynamical mean-field theory to integrate ecology into classical population
genetics
population genetics
here we address this shortcoming by using dynamical mean-field theory to integrate ecology into classical population genetics models
brain decoding is a key neuroscience field that reconstructs the visual stimuli from brain activity with
fmri
brain regions
brain decoding is a key neuroscience field that reconstructs the visual stimuli from brain activity with fmri which helps illuminate how the brain represents the world
for the latter we discover a nonstandard rate of n 1 4 log n -3 8 with a heavy-tailed stable
limit
central limit theorem
for the latter we discover a nonstandard rate of n 1 4 log n -3 8 with a heavy-tailed stable limit distribution
in nonlinear optics and plasma physics the use of structured
pulses
pulsed laser
in nonlinear optics and plasma physics the use of structured pulses typically follows a forward design approach in which the efficacy of a known structure is analyzed for a particular application