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additionally the refined annotation guidelines increase agreement among different
llm
llm reasoning
additionally the refined annotation guidelines increase agreement among different llm models
we then show that for fitness fluctuations with exponential tails these operations admit a unique
traveling
traveling waves
we then show that for fitness fluctuations with exponential tails these operations admit a unique traveling wave solution with local stability
here we generalize the model to multilayer networks and name it as the
multilayer
correlation network
here we generalize the model to multilayer networks and name it as the multilayer triadic percolation mtp model
this article will not only review all of these measures but also include two recently proposed algorithms for latency correction which build on spike-order and aim to optimize the spike time alignment of sparse
spike
spike train
this article will not only review all of these measures but also include two recently proposed algorithms for latency correction which build on spike-order and aim to optimize the spike time alignment of sparse spike trains with well-defined global spiking events
existing frameworks largely rely on imitation
learning
reinforcement learning
existing frameworks largely rely on imitation learning il which can be limited by sub-optimal expert demonstrations and covariate shift during deployment
we first demonstrate that these models are competitive point trackers when focusing on static points present in current point
tracking
point tracking
we first demonstrate that these models are competitive point trackers when focusing on static points present in current point tracking benchmarks 33
recently molecular dynamics md simulations using machine-learned force fields mlffs have opened a new avenue for finite-temperature
calculations
first-principles calculations
recently molecular dynamics md simulations using machine-learned force fields mlffs have opened a new avenue for finite-temperature calculations with near-first-principles accuracy
through sed fitting we determine the luminosities of these
quasars
galactic disk
through sed fitting we determine the luminosities of these quasars and find that their dust torus sizes follow the established r_ dust -l_ agn relation reported in previous studies
we motivate the applicability of this process by using it to simulate a number of barely
random
randomized algorithm
we motivate the applicability of this process by using it to simulate a number of barely random algorithms for weighted interval selection single-length arbitrary weights as well as monotone c-benevolent and d-benevolent weighted instances the proportional and general knapsack problems binary string guessing and unweighted job throughput scheduling
this integrated approach offers a general mathematical framework for designing and evaluating control strategies in
infectious
infectious individuals
this integrated approach offers a general mathematical framework for designing and evaluating control strategies in infectious disease outbreaks with applications to low resource settings and beyond
we show that quantum coherence drives spontaneous symmetry breaking while long-range
interactions
quantum mechanics
we show that quantum coherence drives spontaneous symmetry breaking while long-range interactions stabilize global oscillations against quantum-noise-induced desynchronization
anti gravitron a statistical physics perspective on multidimensional metrics of
polarizing
statistical physics
anti gravitron a statistical physics perspective on multidimensional metrics of polarizing inequality
the estimation method linear smoothers maximum
likelihood
maximum likelihood
the estimation method linear smoothers maximum likelihood generalized method of moments etc
here we report the first direct observation of a hcp ice phase using synchrotron x-ray
diffraction
x-ray diffraction
here we report the first direct observation of a hcp ice phase using synchrotron x-ray diffraction in laser-heated diamond anvil cells
at high pressures nuclear quantum effects involving both
hydrogen
molecular dynamics
at high pressures nuclear quantum effects involving both hydrogen molecules and the water lattice become dominant giving rise to a dual-lattice quantum system
carbon-aware optimal power flow with data-driven
carbon
carbon emissions
carbon-aware optimal power flow with data-driven carbon emission tracing
along with the natural language embeddings the representations are trained by an haoi
manipulation
imitation learning
along with the natural language embeddings the representations are trained by an haoi manipulation language model to align the grasping process with its language description in a shared representation space
as llms occupy an increasingly important role in society they are more and more confronted with questions that require them not only to draw on their general knowledge but also to align with certain human
value
models llms
as llms occupy an increasingly important role in society they are more and more confronted with questions that require them not only to draw on their general knowledge but also to align with certain human value systems
the optimal control model supports the development and seasonal timing of cost-effective mosquito
control
control strategies
the optimal control model supports the development and seasonal timing of cost-effective mosquito control methods
this approach requires only a dimension-independent number of zero-order evaluations -- as few as eight -- at each
iteration
zeroth-order methods
this approach requires only a dimension-independent number of zero-order evaluations -- as few as eight -- at each iteration step
in this study we will explore the optimal
uav
optimal uav
in this study we will explore the optimal uav deployment problem in road networks in conjunction with sampled connected vehicle data to achieve more reliable estimation of macroscopic path flow as well as microscopic arrival rates and queue lengths
we study a continuous-time neural model that unifies several
biologically
neural representations
we study a continuous-time neural model that unifies several biologically plausible learning algorithms and removes the need for phase separation
the goal of policy learning is to train a
policy
reinforcement learning
the goal of policy learning is to train a policy function that recommends a treatment given covariates to maximize population welfare
finally we validate our theoretical results through
simulations
world models
finally we validate our theoretical results through simulations on synthetic and real-world datasets
our work has implications for developing nlp tools for minority
languages
large language
our work has implications for developing nlp tools for minority languages and supporting language preservation in communities under lexical pressure from dominant languages
these results have implications for amplified oversight -- the challenge of combining
humans
human-machine teaming
these results have implications for amplified oversight -- the challenge of combining humans and ai to supervise ai systems even as they surpass human expert performance
reinforcement learning with verifiable rewards
rlvr
reinforcement learning rl
reinforcement learning with verifiable rewards rlvr is a promising approach for enhancing agentic deep search
finally we present a proof-of-principle simulation on the ibm quantum experience platform realizing a quantum switch of two measurement
channels
entanglement entropy
finally we present a proof-of-principle simulation on the ibm quantum experience platform realizing a quantum switch of two measurement channels with tunable strengths and experimentally confirming the predicted efficiency enhancement enabled by correlation-assisted superposed causal order
to guide the image reconstruction bit predicts two complementary localized patch-level image features i high-level semantic features which steer the diffusion model toward the correct semantic content of the image and ii low-level
structural
image reconstruction
to guide the image reconstruction bit predicts two complementary localized patch-level image features i high-level semantic features which steer the diffusion model toward the correct semantic content of the image and ii low-level structural features which help to initialize the diffusion process with the correct coarse layout of the image
in neuroscience methods from information geometry ig have been successfully applied in the modelling of binary vectors from spike train data using the orthogonal decomposition of the kullback-leibler divergence and
mutual
mutual information
in neuroscience methods from information geometry ig have been successfully applied in the modelling of binary vectors from spike train data using the orthogonal decomposition of the kullback-leibler divergence and mutual information to isolate different orders of interaction between neurons
in visuomotor policy learning diffusion-based imitation
learning
imitation learning
in visuomotor policy learning diffusion-based imitation learning has become widely adopted for its ability to capture diverse behaviors
randomized space-time coded stacked intelligent metasurfaces for massive multiuser
downlink
uplink communication
randomized space-time coded stacked intelligent metasurfaces for massive multiuser downlink connectivity
these results suggest that llms can serve as practical proxies for otherwise unrevealed human thinking
traces
llm raters
these results suggest that llms can serve as practical proxies for otherwise unrevealed human thinking traces enabling label-only corpora to be extended into thinking-trace-augmented resources that enhance the reliability of llm raters
toward socially-aware llms a survey of multimodal approaches to human
behavior
models llms
toward socially-aware llms a survey of multimodal approaches to human behavior understanding
to formalize this we extend the concept of data informativity by requiring the existence of a controller that stabilizes all systems consistent with the data and the
prior
predictive control
to formalize this we extend the concept of data informativity by requiring the existence of a controller that stabilizes all systems consistent with the data and the prior knowledge
our extensive evaluation demonstrates that our approach can localize within 200m more than 68 of queries of a dataset covering a
large
large language
our extensive evaluation demonstrates that our approach can localize within 200m more than 68 of queries of a dataset covering a large part of europe
inspired by structural plasticity pruning is often used in machine learning to remove weak
connections
continual learning
inspired by structural plasticity pruning is often used in machine learning to remove weak connections from trained models to reduce the computational requirements of inference
we introduce underline s ynergistic underline s parse and underline l ow-rank
underline
large language models llms
we introduce underline s ynergistic underline s parse and underline l ow-rank underline c ompression sslc methods for llms which leverages the strengths of both techniques low-rank approximation compresses the model by retaining its essential structure with minimal information loss whereas sparse optimization eliminates non-essential weights preserving those crucial for generalization
these results have implications for amplified oversight -- the challenge of combining
humans
human-ai interaction
these results have implications for amplified oversight -- the challenge of combining humans and ai to supervise ai systems even as they surpass human expert performance
we provide an algorithm that finds a 1 epsilon -approximate solution to this problem using o d 1 3 epsilon 1 epsilon 2 log n
epsilon
epsilon -approximate
we provide an algorithm that finds a 1 epsilon -approximate solution to this problem using o d 1 3 epsilon 1 epsilon 2 log n epsilon linear system solves
this paper introduce textbf infoflow a systematic framework that
tackles
natural language
this paper introduce textbf infoflow a systematic framework that tackles this problem from three aspects
our methodology is twofold first we develop algorithms to process raw position data accurately extracting the
commuting
mobility networks
our methodology is twofold first we develop algorithms to process raw position data accurately extracting the commuting trajectory transportation mode and transfer stations
we used these disentangled embeddings to model intracranial ecog brain
recordings
brain-computer interface
we used these disentangled embeddings to model intracranial ecog brain recordings from neurosurgical patients listening to natural speech
however these evaluations rely on llms proxy
llms
llm responses
however these evaluations rely on llms proxy llms to gauge compliance with privacy norms overlooking real users perceptions
to guide the image reconstruction bit predicts two complementary localized patch-level image features i high-level semantic features which steer the diffusion model toward the correct semantic content of the image and ii low-level structural features which help to initialize the diffusion
process
image generation
to guide the image reconstruction bit predicts two complementary localized patch-level image features i high-level semantic features which steer the diffusion model toward the correct semantic content of the image and ii low-level structural features which help to initialize the diffusion process with the correct coarse layout of the image
reward models rms play a critical role in aligning large
language
large language
reward models rms play a critical role in aligning large language models llms with human preferences
we address two key questions 1 how can the intent of a group trajectory be optimally formalized as the characteristic function of a
cooperative
cooperative game
we address two key questions 1 how can the intent of a group trajectory be optimally formalized as the characteristic function of a cooperative game
ai-powered approaches specifically large language
models
ai systems
ai-powered approaches specifically large language models llms natural language processing nlp and generative ai offer transformative solutions and reduce inefficiencies
we analyze a model where the mlp comprises two layers with the first layer trained via a single gradient step and the second
layer
machine learning
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
in 5g networks a terminal position is determined from the time of arrival of positioning reference signals transmitted by
base
base station
in 5g networks a terminal position is determined from the time of arrival of positioning reference signals transmitted by base stations
accelerating mathematical research with language
models
language models
accelerating mathematical research with language models a case study of an interaction with gpt-5-pro on a convex analysis problem
whereas existing work typically imposes strong conditions to restore just-identification before deriving the efficiency bound we relax such assumptions and characterize the general efficiency
bound
efficiency bound
whereas existing work typically imposes strong conditions to restore just-identification before deriving the efficiency bound we relax such assumptions and characterize the general efficiency bound along with efficient estimators in the overidentified models ii and iii
the good agreement with experimental estimates demonstrates how time-independent variational calculations of excited states using density functionals can give accurate results and thereby provide a powerful screening tool for identifying other defect systems as candidates for
quantum
quantum technologies
the good agreement with experimental estimates demonstrates how time-independent variational calculations of excited states using density functionals can give accurate results and thereby provide a powerful screening tool for identifying other defect systems as candidates for quantum technologies
experimental results showed that compared to the state-of-the-art method sota the accuracy improvement rate in a cg dataset with dynamic
obstacles
collision avoidance
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
the observed polarizabilities are 3-25 times
larger
photonic crystal
the observed polarizabilities are 3-25 times larger than those of tin vacancy centers which we attribute to valence band resonances that delocalize the e_u wavefunctions
here we propose an expression of mathcal r_0 in the context of
multiplex
correlation network
here we propose an expression of mathcal r_0 in the context of multiplex networks enabling the analysis of disease transmission across multiple social layers
additionally they imply an m 1 o 1 w -time algorithm for solving the problem on graphs with a given
tree
-time algorithm
additionally they imply an m 1 o 1 w -time algorithm for solving the problem on graphs with a given tree decomposition of width w
here we explore topological effects on photon-pair generation via spontaneous parametric down-conversion spdc in nonlinear
waveguide
integrated photonics
here we explore topological effects on photon-pair generation via spontaneous parametric down-conversion spdc in nonlinear waveguide arrays both theoretically and experimentally
mobility data are now routinely used to improve such forecasts yet work diverges on whether the volume of mobility or the structure of
mobility
human mobility
mobility data are now routinely used to improve such forecasts yet work diverges on whether the volume of mobility or the structure of mobility networks carries the most predictive signal
on a real robot with 22 degrees of freedom dofs get-use outperforms state-of-the-art methods by 30-60
success
motion planning
on a real robot with 22 degrees of freedom dofs get-use outperforms state-of-the-art methods by 30-60 success rates across three vision-based bimanual mobile manipulation tool-usage tasks
these findings offer fundamental insights into
systems
complex networks
these findings offer fundamental insights into systems with competing order parameters and have direct implications for multilayer biological networks social media ecosystems and political debates characterized by competing priorities
results show that lower and more homogeneously distributed learning rates promote scale-free networks while higher or more heterogeneously distributed
learning
complex networks
results show that lower and more homogeneously distributed learning rates promote scale-free networks while higher or more heterogeneously distributed learning rates lead to the emergence of core-periphery topologies
their prevalence features and clinical consequences
remain
findings highlight
their prevalence features and clinical consequences remain undefined
to address this we analyze one year of smartphone position data from over one million users in the tokyo metropolitan area to extract high-resolution
commuting
mobility networks
to address this we analyze one year of smartphone position data from over one million users in the tokyo metropolitan area to extract high-resolution commuting trajectories
specifically we characterize the global asymptotic behavior of the disease determining conditions for quick eradication of the
disease
disease transmission
specifically we characterize the global asymptotic behavior of the disease determining conditions for quick eradication of the disease i
unveiling intrinsic text bias in multimodal large
language
language models
unveiling intrinsic text bias in multimodal large language models through attention key-space analysis
don t blind your vla aligning visual representations for
ood
visual navigation
don t blind your vla aligning visual representations for ood generalization
this paper introduces cypress crop yield prediction via regression on prithvi s encoder for satellite sensing a deep learning model designed for high-resolution intra-field canola
yield
yield prediction
this paper introduces cypress crop yield prediction via regression on prithvi s encoder for satellite sensing a deep learning model designed for high-resolution intra-field canola yield prediction
in parallel an extended kalman filter fuses imu and actuator encoder feedback to provide accurate and reliable state
estimation
state estimation
in parallel an extended kalman filter fuses imu and actuator encoder feedback to provide accurate and reliable state estimation under sensor noise and external disturbances
in real-world reasoning scenarios much of the available information is irrelevant and effective deductive inference requires identifying and
ignoring
normative reasoning
in real-world reasoning scenarios much of the available information is irrelevant and effective deductive inference requires identifying and ignoring such distractions
these findings show that transferring proprioceptive experiences into
working
working memory
these findings show that transferring proprioceptive experiences into working memory introduces systematic temporal and structural distortions
experimental results show that lagmemo s memory module enables effective multi-modal open-vocabulary goal localization and that lagmemo outperforms state-of-the-art methods in multi-goal
visual
multi-goal visual
experimental results show that lagmemo s memory module enables effective multi-modal open-vocabulary goal localization and that lagmemo outperforms state-of-the-art methods in multi-goal visual navigation
controlling specific behaviors in large language models while preserving their general
capabilities
large language
controlling specific behaviors in large language models while preserving their general capabilities is a central challenge for safe and reliable artificial intelligence deployment
platforms such as the bee robeetle smallbug smarti waterstrider vleibot and frisshbot exemplify how feedback loops decision logics sensing mechanisms and smart actuation strategies can be embedded into the physical properties of the
robotic
robotic manipulation
platforms such as the bee robeetle smallbug smarti waterstrider vleibot and frisshbot exemplify how feedback loops decision logics sensing mechanisms and smart actuation strategies can be embedded into the physical properties of the robotic system itself
inverse reinforcement learning using just
classification
policy learning
inverse reinforcement learning using just classification and a few regressions
this mass inflow predominantly manifests itself in the
form
dense gas
this mass inflow predominantly manifests itself in the form of so-called streamers filaments and arcs of gas connecting large-scale extended gas structures to disk scales
modern vision-language models vlms excel at many
multimodal
language models
modern vision-language models vlms excel at many multimodal tasks yet their grasp of temporal information in video remains weak and crucially under-evaluated
a major goal of computational astrophysics is to simulate the
milky
milky way
a major goal of computational astrophysics is to simulate the milky way galaxy with sufficient resolution down to individual stars
the magnetic properties of van der waals materials are profoundly
influenced
van der waals
the magnetic properties of van der waals materials are profoundly influenced by structural defects
it addresses two main challenges i resolving
collisions
collision avoidance
it addresses two main challenges i resolving collisions between agvs and ii assigning tasks to agvs
to overcome these limitations we propose a novel multiplicative update proximal gradient algorithm sso-pga with
convergence
minimax optimal
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
understanding how these systems may be spatially distributed to optimise their collective potential is therefore of importance in both ecology and in
collective
collective systems
understanding how these systems may be spatially distributed to optimise their collective potential is therefore of importance in both ecology and in collective systems design
spiral features appear across stellar populations of different ages confirming their density-wave nature and producing coherent spirals in both
metallicity
stellar population
spiral features appear across stellar populations of different ages confirming their density-wave nature and producing coherent spirals in both metallicity and mean stellar age distributions-consistent with recent gaia observations of the milky way
using a brain encoder as a digital twin offers a powerful data-driven framework for generating and testing hypotheses about visual selectivity in the human brain - hypotheses that can guide future
fmri
human brain
using a brain encoder as a digital twin offers a powerful data-driven framework for generating and testing hypotheses about visual selectivity in the human brain - hypotheses that can guide future fmri experiments
for a conditional version of the measure without such a representation we develop a two-step
semiparametric
nonparametric identification
for a conditional version of the measure without such a representation we develop a two-step semiparametric estimator based on distribution regression and establish its asymptotic properties
results using k-means for longitudinal data three groups were obtained and one of these groups showed
cognitive
cognitive science
results using k-means for longitudinal data three groups were obtained and one of these groups showed cognitive decline over the three years of follow-up
the lowering of this strain energy will favor atomic anisotropic environments for neodymium that explains the perpendicular
anisotropy
magnetic anisotropy
the lowering of this strain energy will favor atomic anisotropic environments for neodymium that explains the perpendicular anisotropy and its thickness dependence of these thin film compounds
coordinated multipoint transmission in pinching
antenna
pinching antenna
coordinated multipoint transmission in pinching antenna systems
these direct and quantitative experimental results support the possibility of beta-pdbi2 as a topological superconductor characterized by unique crystal and
electronic
electronic structure
these direct and quantitative experimental results support the possibility of beta-pdbi2 as a topological superconductor characterized by unique crystal and electronic band structures
this approach requires only a dimension-independent
number
computationally efficient
this approach requires only a dimension-independent number of zero-order evaluations -- as few as eight -- at each iteration step
this enables high-speed coherent communications and ultra-precise
coherent
optical communication
this enables high-speed coherent communications and ultra-precise coherent timing and positioning between ground and space
large cities lose their growth edge as urban
systems
urban systems
large cities lose their growth edge as urban systems mature
07 are obtained for sustainable supply chain in terms of 5 product group classification and 4 product relation
classification
supply chain
07 are obtained for sustainable supply chain in terms of 5 product group classification and 4 product relation classification respectively
to this end we compare different representation extraction strategies and
introduce
generative models
to this end we compare different representation extraction strategies and introduce two model-agnostic embedding augmentations
informative sample selection model for skeleton-based
action
action recognition
informative sample selection model for skeleton-based action recognition with limited training samples
however works on collaborative training across
clients
federated learning
however works on collaborative training across clients with fundamentally different neural architectures and non-identically distributed datasets remain scarce
in this work we extend our previous work on the extrapolation of single-time observables to demonstrate an efficient scheme for
computing
quantum key distribution
in this work we extend our previous work on the extrapolation of single-time observables to demonstrate an efficient scheme for computing two-time impurity correlation functions by combining the non-markovian quantum mpemba effect nmqmpe with a dynamical map-based framework for open quantum systems
to each gonosomic algebra an evolution operator noted w is associated that gives the state of the
offspring
basic reproduction
to each gonosomic algebra an evolution operator noted w is associated that gives the state of the offspring population at the birth stage
figuring out gas galaxies in enzo foggie xi circumgalactic o vi emission traces clumpy
inflowing
dense gas
figuring out gas galaxies in enzo foggie xi circumgalactic o vi emission traces clumpy inflowing recycled gas
quantifying spike train synchrony and directionality
measures
spike train
quantifying spike train synchrony and directionality measures and applications