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by presenting efficient numerical samplers which converge with optimal rate in terms of discretizations step we provide a comprehensive comparison of models based on confined specularly reflected kinetic langevin diffusion with models based on reflected
diffusion
diffusion models
by presenting efficient numerical samplers which converge with optimal rate in terms of discretizations step we provide a comprehensive comparison of models based on confined specularly reflected kinetic langevin diffusion with models based on reflected diffusion with local time
24 96 pc the b-fields in the dusty and molecular outflows of arp 220 the closest 78 mpc ultra-luminous infrared galaxy hosting two interacting
nuclei
galactic disk
24 96 pc the b-fields in the dusty and molecular outflows of arp 220 the closest 78 mpc ultra-luminous infrared galaxy hosting two interacting nuclei denoted as east and west
this research provides an indication of potential advances in the exploration of all four fundamental aspects of tool usage enabling robots to master the intricate art of tool
manipulation
multi-robot collaboration
this research provides an indication of potential advances in the exploration of all four fundamental aspects of tool usage enabling robots to master the intricate art of tool manipulation across diverse tasks
coherent control of quantum emitters is essential for
scalable
coherent control
coherent control of quantum emitters is essential for scalable quantum photonic technologies
we outline a multi-phase research methodology focused on preparing re datasets fine-tuning ai models and designing collaborative
human-ai
artificial intelligence
we outline a multi-phase research methodology focused on preparing re datasets fine-tuning ai models and designing collaborative human-ai workflows
in this paper we measure the m_ rm hi -m_ star relation based on a
stellar-mass
hi mass
in this paper we measure the m_ rm hi -m_ star relation based on a stellar-mass selected sample at 0
i develop a comprehensive theoretical framework for dynamic
spatial
treatment effect boundaries
i develop a comprehensive theoretical framework for dynamic spatial treatment effect boundaries using continuous functional definitions grounded in navier-stokes partial differential equations
this completes the theoretical foundation of
compressed
compressed indexing
this completes the theoretical foundation of compressed indexing closing a crucial gap between upper and lower bounds and providing a clear target for future data structures seeking either the optimal time in the smallest space or the fastest time in the optimal space both of which are now known for central string quer...
this gap has motivated growing efforts to design
collaborative
human-machine teaming
this gap has motivated growing efforts to design collaborative frameworks that combine the complementary strengths of humans and ai
our results reveal how the limits of quantum
chaos
quantum coherence
our results reveal how the limits of quantum chaos constrain information preservation in thermalizing quantum systems
2024 develops riesz regression for automatic
debiased
debiased machine
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
we implement a minimal sequence generator inspired by neurobiology and pair it with an actor-critic learner for
egocentric
recurrent neural
we implement a minimal sequence generator inspired by neurobiology and pair it with an actor-critic learner for egocentric visual navigation
for this recurrence time as well as for measures of clonal diversity and the
size
population genetics
for this recurrence time as well as for measures of clonal diversity and the size of the largest resistant clone at recurrence we derive corresponding law of large number limits
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
visual stimuli
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
we demonstrate three key properties i self-organization of hierarchical latent dynamics that regulate task transitions capture variability in uncertainty and infer occluded states ii robustness to degraded vision through visuo-proprioceptive integration and iii asymmetric interference in multitask learning where the mo...
repositioning
working memory
we demonstrate three key properties i self-organization of hierarchical latent dynamics that regulate task transitions capture variability in uncertainty and infer occluded states ii robustness to degraded vision through visuo-proprioceptive integration and iii asymmetric interference in multitask learning where the mo...
the attained sample complexities improve those of existing zeroth-order methods in the problem setting that allows nonconvexity and unboundedness of the
objective
objective function
the attained sample complexities improve those of existing zeroth-order methods in the problem setting that allows nonconvexity and unboundedness of the objective function
through sed fitting we determine the luminosities of these
quasars
galactic nuclei
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
drawing substantial scientific inferences from the results say about theoretical tasks like image classification requires additional assumptions about the
theoretical
theoretical findings
drawing substantial scientific inferences from the results say about theoretical tasks like image classification requires additional assumptions about the theoretical structure of the learning problems evaluation functions and data distributions
these subclumps exhibit parabolic morphologies consistent with ram-pressure-confined droplets with their heads tending to point toward the
galactic
massive galaxies
these subclumps exhibit parabolic morphologies consistent with ram-pressure-confined droplets with their heads tending to point toward the galactic plane
we further introduce a locally linear treatment effects
assumption
treatment effect
we further introduce a locally linear treatment effects assumption which enhances the interpretability of the treatment effect derivative proposed by dong and lewbel
6 thin films studied by xray reflectivity and hard
xray
x-ray diffraction
6 thin films studied by xray reflectivity and hard xray photoemission
rlmeval targets the evaluation of neural theorem proving and proof autoformalization on
challenging
reinforcement learning rl
rlmeval targets the evaluation of neural theorem proving and proof autoformalization on challenging research-level theorems by leveraging real lean blueprint formalization projects
reinforcement learning rl is widely used to produce robust robotic manipulation
policies
learning agents
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
furthermore we provide several characterizations of this class including nonsmooth and differentiable cases and derive key properties that fa -ci -li -ta -te the implementation of
first-order
first-order methods
furthermore we provide several characterizations of this class including nonsmooth and differentiable cases and derive key properties that fa -ci -li -ta -te the implementation of first-order methods
we use real data as well as numerical simulations to illustrate the performance of the
proposed
existing methods
we use real data as well as numerical simulations to illustrate the performance of the proposed methods
assessing the effects of monetary shocks on
macroeconomic
monetary policy
assessing the effects of monetary shocks on macroeconomic stars a smuc-iv framework
we show that for sparse plant spectra it is possible to reconstruct the continuous green vegetation
spectra
spectral range
we show that for sparse plant spectra it is possible to reconstruct the continuous green vegetation spectra with rmse less than 1 with as few as 25 leds
while llms are able to identify key financial risk indicators their
feature
llm raters
while llms are able to identify key financial risk indicators their feature importance rankings diverge notably from lightgbm and their self-explanations often fail to align with empirical shap attributions
we introduce the textbf boundless large model blm _1 a multimodal spatial foundation model that preserves instruction following and reasoning incorporates embodied knowledge and supports
robust
imitation learning
we introduce the textbf boundless large model blm _1 a multimodal spatial foundation model that preserves instruction following and reasoning incorporates embodied knowledge and supports robust cross-embodiment control
galaxy mergers trigger starburst activity and
galactic
active galactic
galaxy mergers trigger starburst activity and galactic outflows that enrich the circumgalactic medium profoundly impacting galaxy evolution
considering structured data with an underlying feature space of small dimension we show that maximizing the
mutual
brain decoding
considering structured data with an underlying feature space of small dimension we show that maximizing the mutual information implies i finding an appropriate projection space and ii building a neural representation with the appropriate metric
through comprehensive experimentation across six diverse tasks and utilizing six distinct llms our methodology demonstrates remarkable results achieving
speeds
extensive experiments
through comprehensive experimentation across six diverse tasks and utilizing six distinct llms our methodology demonstrates remarkable results achieving speeds up to 5
we use the database constructed in wasleske baldassare 2024 which contains dwarf galaxies that were selected as
active
dwarf galaxies
we use the database constructed in wasleske baldassare 2024 which contains dwarf galaxies that were selected as active galaxies by optical spectroscopy infrared colors x-ray brightness and photometric variability
in this paper we design high-performance matrix multiplication matmul a critical compute kernel for llm
inference
llm inference
in this paper we design high-performance matrix multiplication matmul a critical compute kernel for llm inference on trainium
as such the development of mathematical frameworks that account for spatially correlated infections is of great interest as they offer a compromise between accurate
disease
infectious individuals
as such the development of mathematical frameworks that account for spatially correlated infections is of great interest as they offer a compromise between accurate disease forecasting and analytic tractability
the results show that the proposed model can accurately reconstruct original
scenarios
real-world scenarios
the results show that the proposed model can accurately reconstruct original scenarios and generate realistic diverse synthetic scenarios
debiased machine learning typically requires
estimation
representation learning
debiased machine learning typically requires estimation of the riesz representer and the regression function
non-asymptotic error bounds are established for the resulting estimators under heavy-tailed regime and the minimax optimal convergence
rate
asymptotic normality
non-asymptotic error bounds are established for the resulting estimators under heavy-tailed regime and the minimax optimal convergence rate is derived
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
llm reasoning
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
engineered kerr nonlinearities for precise quantum control of
fock
quantum dot
engineered kerr nonlinearities for precise quantum control of fock states
only if the right local model minimizer is used the p q-1 th-order local
convergence
superlinear convergence
only if the right local model minimizer is used the p q-1 th-order local convergence from the non-adaptive case is preserved for p q-1 otherwise the superlinear rate can degrade
structural vulnerability assessment in urban
transport
gromov-wasserstein distance
structural vulnerability assessment in urban transport networks a network-wide geometric approach using gromov-wasserstein
existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning
capabilities
reasoning curriculum
existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning capabilities of large language models llms
we compare models that use only macro-level incidence models that add
mobility
urban systems
we compare models that use only macro-level incidence models that add mobility network features and their interactions with macro incidence and autoregressive ar models that include town-level recent cases
specifically we first analyze the trajectory of the airy beam and the
beam
airy beam
specifically we first analyze the trajectory of the airy beam and the beam pattern at the receiver using a discrete fourier transform dft codebook in the presence of obstacles
the street has emerged as a primary site where everyday publics are confronted with ai as an infrastructural phenomenon as machine learning-based
systems
human-ai interaction
the street has emerged as a primary site where everyday publics are confronted with ai as an infrastructural phenomenon as machine learning-based systems are now commonly deployed in this setting in the form of automated cars facial recognition smart billboards and the like
0 and sample-efficient reinforcement learning on continuous control tasks without
replay
continual learning
0 and sample-efficient reinforcement learning on continuous control tasks without replay buffers
one major obstacle lies in methodological limitations most studies rely on non-invasive neural measures with limited spatial or temporal resolution making it difficult to disentangle proper nccs from concurrent
cognitive
surrogate brain
one major obstacle lies in methodological limitations most studies rely on non-invasive neural measures with limited spatial or temporal resolution making it difficult to disentangle proper nccs from concurrent cognitive processes
heterogeneous graph neural networks hgnns have emerged as a promising paradigm for
anomaly
anomaly detection
heterogeneous graph neural networks hgnns have emerged as a promising paradigm for anomaly detection by incorporating type-aware transformations and relation-sensitive aggregation enabling more expressive modeling of complex cyber data
since conventional methods are computationally intensive and often yield unstable estimates we develop a new
gaussian
gaussian process
since conventional methods are computationally intensive and often yield unstable estimates we develop a new gaussian process collocation method for efficient bayesian inference
however connected autonomous vehicles cav are inherently affected by communication delays and computation
delays
time delays
however connected autonomous vehicles cav are inherently affected by communication delays and computation delays which significantly degrade the performance of conventional controllers such as pid or other more advanced controllers like disturbance observers dob
we propose a two-stage learner that first identifies a set of near-optimal policies and then constructs an
abstention
policy learning
we propose a two-stage learner that first identifies a set of near-optimal policies and then constructs an abstention rule from their disagreements
bell inequality violation is the phenomenon where multiple non-communicating parties can exhibit
correlations
quantum coherence
bell inequality violation is the phenomenon where multiple non-communicating parties can exhibit correlations using quantum resources that are impossible if they can only use classical resources
however its potential is constrained by the difficulty of acquiring accurate user-to-ris channel state information
csi
channel state information csi
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
simultaneously strongly aligning with human
visual
multimodal reasoning
simultaneously strongly aligning with human visual attention
in some bulges we also find up to a 32 of
stars
massive stars
in some bulges we also find up to a 32 of stars that migrated from the disk due to secular evolution with a median of 10
furthermore we incorporate focaler-siou to strengthen the model s bounding box matching capability and increase its sensitivity to small-object features thereby further enhancing
detection
vision transformers
furthermore we incorporate focaler-siou to strengthen the model s bounding box matching capability and increase its sensitivity to small-object features thereby further enhancing detection accuracy and robustness
to complement this we derive a tight upper bound of 2n k-1 for chordal bigraphs and 54n k-1 for grid intersection graphs gig a prominent graph class residing in four ferrers dimensions and capturing planar bipartite graphs as well as bipartite intersection
graphs
bipartite graphs
to complement this we derive a tight upper bound of 2n k-1 for chordal bigraphs and 54n k-1 for grid intersection graphs gig a prominent graph class residing in four ferrers dimensions and capturing planar bipartite graphs as well as bipartite intersection graphs of rectangles
spatial and temporal boundaries in difference-in-differences a framework from
navier-stokes
effect boundaries
spatial and temporal boundaries in difference-in-differences a framework from navier-stokes equation
consequently the average performance achieved by llms
remains
llm raters
consequently the average performance achieved by llms remains considerably below the human baseline
5-4b models across visual reasoning tasks demonstrate that our methods consistently improve visual reasoning
capabilities
reasoning tasks
5-4b models across visual reasoning tasks demonstrate that our methods consistently improve visual reasoning capabilities outperforming vanilla self-improvement by 3
identifying asymptomatic individuals is critical for measuring and controlling an epidemic but periodic and widespread testing of healthy
individuals
infectious individuals
identifying asymptomatic individuals is critical for measuring and controlling an epidemic but periodic and widespread testing of healthy individuals is often too costly
most counterfactual inference frameworks traditionally assume acyclic structural
causal
causal effect
most counterfactual inference frameworks traditionally assume acyclic structural causal models scms i
these annotations draw inspiration from cognitive science research on how humans identify and resolve anomalies providing a comprehensive framework for evaluating vision-language models vlms in detecting and
understanding
language agents
these annotations draw inspiration from cognitive science research on how humans identify and resolve anomalies providing a comprehensive framework for evaluating vision-language models vlms in detecting and understanding anomalies
we approach this question by introducing appropriate simplifying abstractions as follows first we use
imbalanced
imbalanced data
we approach this question by introducing appropriate simplifying abstractions as follows first we use imbalanced data as a testbed
however their reliability is often limited for subjective tasks when human judgments
involve
human feedback
however their reliability is often limited for subjective tasks when human judgments involve subtle reasoning beyond annotation labels
in addition such data could also be used to improve the training of both pathologists and ai
systems
ai use
in addition such data could also be used to improve the training of both pathologists and ai systems that might support human experts
this capability is particularly relevant for active
photonic
integrated photonics
this capability is particularly relevant for active photonic circuits that generate quantum light directly on-chip
tensor network methods strike a middle ground between fully-fledged quantum computing and classical computing as they take inspiration from
quantum
quantum technologies
tensor network methods strike a middle ground between fully-fledged quantum computing and classical computing as they take inspiration from quantum systems to significantly speed up certain classical operations
it emphasizes traceability interpretability and data-driven decision making offering a unified human-understandable framework for machine learning and achieves at or near state-of-the-art performance across most common
machine
machine learning
it emphasizes traceability interpretability and data-driven decision making offering a unified human-understandable framework for machine learning and achieves at or near state-of-the-art performance across most common machine learning tasks
quantum simulation of actinide chemistry towards scalable
algorithms
quantum batteries
quantum simulation of actinide chemistry towards scalable algorithms on trapped ion quantum computers
phylogenetic trees capture evolutionary relationships among
isolates
phylogenetic diversity
phylogenetic trees capture evolutionary relationships among isolates and provide a natural framework for detecting such adaptive signals
we resolve this question by presenting the first bidirectional reduction showing that suffix array queries are up to an additive o log log n term in query time equivalent to prefix-select
queries
query complexity
we resolve this question by presenting the first bidirectional reduction showing that suffix array queries are up to an additive o log log n term in query time equivalent to prefix-select queries in all parameters
we further formulate a degradation model for multi-modal restoration and derive its sso-pga-based optimization
algorithm
gradient descent
we further formulate a degradation model for multi-modal restoration and derive its sso-pga-based optimization algorithm which is then unfolded into a deep network to marry the interpretability of optimization with the power of deep learning
the proposed approach provides formal guarantees on safety and timing and is computationally lightweight
model-free
external disturbances
the proposed approach provides formal guarantees on safety and timing and is computationally lightweight model-free and robust to unknown disturbances
generative artificial intelligence genai can aid
humans
trustworthy ai
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
the research aims to investigate what happens in the brain when we perceive visual stimuli or engage in covert speech inner
speech
inner speech
the research aims to investigate what happens in the brain when we perceive visual stimuli or engage in covert speech inner speech and enhance the decoding performance of such stimuli
voltage and local scanning tunneling spectroscopy measurements
demonstrated
ionic conduction
voltage and local scanning tunneling spectroscopy measurements demonstrated a notable increase in electrical conductivity
during massive star formation dense gas undergoes chemical evolution producing both simple and complex organic molecules coms characteristic of hot
molecular
dense gas
during massive star formation dense gas undergoes chemical evolution producing both simple and complex organic molecules coms characteristic of hot molecular cores
this paper explores how we can leverage ai to
improve
ai systems
this paper explores how we can leverage ai to improve the quality of human oversight
porous microstructures while central to many functional materials remain difficult to characterize quantitatively by
atom
electron microscopy
porous microstructures while central to many functional materials remain difficult to characterize quantitatively by atom probe tomography apt
riesz regression covariate balancing dre and the matching estimator are methods for estimating the balancing weights where
riesz
riesz regression
riesz regression covariate balancing dre and the matching estimator are methods for estimating the balancing weights where riesz regression is essentially equivalent to dre in the ate context the matching estimator is a special case of dre and dre is in a dual relationship with covariate balancing
our experiments show that the best forecasting models achieve
classification
support vector machines
our experiments show that the best forecasting models achieve classification accuracy that matches or even surpasses that of state-of-the-art models pre-trained specifically for classification
we introduce variable projected augmented
lagrangian
augmented lagrangian
we introduce variable projected augmented lagrangian vpal methods for solving generalized nonlinear lasso problems with improved speed and accuracy
the considered scenarios cover both single satellite and cooperative multi-satellite
beamforming
beamforming design
the considered scenarios cover both single satellite and cooperative multi-satellite beamforming using either global or local channel state information and two error models that represent increasing levels of uncertainty
in this work we showcase multi-object tracking based on the probability hypothesis
density
multi-object tracking
in this work we showcase multi-object tracking based on the probability hypothesis density phd filter in the range and doppler speed domain
this paper studies nonparametric local over-
identification
nonparametric identification
this paper studies nonparametric local over- identification in the sense of chen and santos 2018 and the associated semiparametric efficiency in modern causal frameworks
formulas that determine the least favorable spectral
densities
density estimation
formulas that determine the least favorable spectral densities and the minimax spectral characteristics are proposed for some specific sets of admissible densities
we motivate and develop four idealized galaxy cgm spatial-kinematic structures based on empirical data and theoretical predictions 1 a rotating galactic disk extra-planar gas 2 a static or dynamic spherical halo 3 an outflowing bi-polar
galactic
milky way
we motivate and develop four idealized galaxy cgm spatial-kinematic structures based on empirical data and theoretical predictions 1 a rotating galactic disk extra-planar gas 2 a static or dynamic spherical halo 3 an outflowing bi-polar galactic wind and 4 an inward spiraling flared planar accretion
in this work we establish emph non-asymptotic berry--esseen bounds for linear functionals of online least-squares sgd thereby providing a gaussian central
limit
central limit theorem
in this work we establish emph non-asymptotic berry--esseen bounds for linear functionals of online least-squares sgd thereby providing a gaussian central limit theorem clt in a emph growing-dimensional regime
understanding how learning algorithms shape the computational strategies that emerge in neural networks remains a fundamental challenge in
machine
machine learning
understanding how learning algorithms shape the computational strategies that emerge in neural networks remains a fundamental challenge in machine intelligence
we surveyed 415 software practitioners to capture their perceptions of productivity changes associated with ai-assisted development using the space framework - satisfaction and well-being performance activity communication and
collaboration
ai use
we surveyed 415 software practitioners to capture their perceptions of productivity changes associated with ai-assisted development using the space framework - satisfaction and well-being performance activity communication and collaboration and efficiency and flow
we adapt a pre-trained vision-language-action vla model open-vla for dexterous human-robot collaboration with minimal
language
vision-language models
we adapt a pre-trained vision-language-action vla model open-vla for dexterous human-robot collaboration with minimal language prompting
our results indicate that although llms generally adhere to valid reasoning patterns they exhibit notable inconsistencies in specific types of
normative
reasoning tasks
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 prohibitive cost of evaluating large language models
llms
language models
the prohibitive cost of evaluating large language models llms on comprehensive benchmarks necessitates the creation of small yet representative data subsets i
as generative ai becomes embedded in children s learning spaces families face
new
generative ai
as generative ai becomes embedded in children s learning spaces families face new challenges in guiding its use
this exploratory study provides in-depth insights into the dynamics of lwir
phonon
phonon polaritons
this exploratory study provides in-depth insights into the dynamics of lwir phonon polaritons and enz modes in the nanostructured sapphire indicating its great potential for innovative nanophotonic applications
the model naturally accepts interleaved vision-language inputs and generates
interleaved
optical flow
the model naturally accepts interleaved vision-language inputs and generates interleaved vision-language outputs
we show that 1 this isolated reasoning embedding exhibits unique predictive power accounting for variance in neural activity not explained by other linguistic features and even extending to the recruitment of visual
regions
neural codes
we show that 1 this isolated reasoning embedding exhibits unique predictive power accounting for variance in neural activity not explained by other linguistic features and even extending to the recruitment of visual regions beyond classical language areas
by explicitly retaining the quantum coherence of the coupled electron-phonon-photon dynamics our model describes a two-stage buildup of entanglement - first between signal and idler photons and subsequently between idler
photons
single photons
by explicitly retaining the quantum coherence of the coupled electron-phonon-photon dynamics our model describes a two-stage buildup of entanglement - first between signal and idler photons and subsequently between idler photons mediated by material coherence