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an optimal solution can be found with a greedy algorithm steel systematic biology 2005 pardi and goldman plos
genetics
phylogenetic diversity
an optimal solution can be found with a greedy algorithm steel systematic biology 2005 pardi and goldman plos genetics 2005
this paper develops a unified framework for identifying spatial and temporal
boundaries
average treatment effect
this paper develops a unified framework for identifying spatial and temporal boundaries of treatment effects in difference-in-differences designs
analysis of search task performance and post-experiment item
recall
task performance
analysis of search task performance and post-experiment item recall revealed differing attention to physical and virtual objects
these inferred thinking traces are applied to two complementary tasks 1 fine-tuning open llm
raters
llm raters
these inferred thinking traces are applied to two complementary tasks 1 fine-tuning open llm raters and 2 synthesizing clearer annotation guidelines for proprietary llm raters
moreover with this relaxed latency constraint we can also have quantum
communication
quantum channels
moreover with this relaxed latency constraint we can also have quantum communication between a subset of parties and thereby achieve possible quantum violations of these new inequalities
to this end we introduce a new dataset covering a wide range of formal patterns of reasoning in both
normative
normative reasoning
to this end we introduce a new dataset covering a wide range of formal patterns of reasoning in both normative and epistemic domains while also incorporating non-formal cognitive factors that influence human reasoning
extensions to longitudinal data dynamic treatment regimes and multiplicative
instrumental
treatment effect
extensions to longitudinal data dynamic treatment regimes and multiplicative instrumental variables are further developed
identification and debiased learning of causal
effects
causal inference
identification and debiased learning of causal effects with general instrumental variables
we discuss major tf-qkd variants including
phase-matching
-dtc phases
we discuss major tf-qkd variants including phase-matching qkd and sending-or-not-sending qkd with various improved versions
specifically our img performs weighted resampling during the
diffusion
diffusion models
specifically our img performs weighted resampling during the diffusion generation process according to the expected aggregated multi-objective values
the simulated galaxies reproduce the observed stellar-to-halo mass mass--metallicity and size--mass relations yielding stellar
masses
stellar population
the simulated galaxies reproduce the observed stellar-to-halo mass mass--metallicity and size--mass relations yielding stellar masses of 10 6-10 8 m_ odot and metallicities consistent with those of local group dwarf galaxies
this allows us to create universal probes for each
llm
models llms
this allows us to create universal probes for each llm and to trace information -- including the causes of output errors -- to specific layers
in ate estimation the balancing weights and the regression functions of the outcome play important roles where the
balancing
covariate balancing
in ate estimation the balancing weights and the regression functions of the outcome play important roles where the balancing weights are referred to as the riesz representer bias-correction term and clever covariates depending on the context
objective to develop validate and deploy a
natural
natural language
objective to develop validate and deploy a natural language processing nlp pipeline to identify itfs in radiology reports and assess their prevalence features and clinical outcomes
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
photonic circuits
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
these solutions are surprisingly simple and have some interesting implications including a necessary and sufficient condition for mutation
selection
evolutionary dynamics
these solutions are surprisingly simple and have some interesting implications including a necessary and sufficient condition for mutation selection balance a very simple formula for mean fitness and the fact that the shape of the equilibrium fitness distribution is determined solely by mutation whereas the scale is de...
understanding how learning algorithms shape the computational
strategies
artificial intelligence
understanding how learning algorithms shape the computational strategies that emerge in neural networks remains a fundamental challenge in machine intelligence
this is a method for sampling from a general class of probability
densities
density estimation
this is a method for sampling from a general class of probability densities defined on riemannian manifolds
bayesian network fusion of large language models for
sentiment
large language models llms
bayesian network fusion of large language models for sentiment analysis
our findings provide a new basis for the automated design of collaborative
multi-agent
llm agents
our findings provide a new basis for the automated design of collaborative multi-agent llm teams
phase inversion under front- versus back-side excitation confirms the ishe origin while a macrospin landau-lifshitz-gilbert model reproduces the field
dependence
phase transition
phase inversion under front- versus back-side excitation confirms the ishe origin while a macrospin landau-lifshitz-gilbert model reproduces the field dependence and separates layer-specific contributions
we propose viz-coast a method of leveraging the common-sense spatial reasoning of large pretrained
vision-language
vision-language models
we propose viz-coast a method of leveraging the common-sense spatial reasoning of large pretrained vision-language models to identify issues with downward refinement a priori bypassing the need to fix these failures during planning
we show that all but the fourth problem are np-complete in all settings while the
complexity
time complexity
we show that all but the fourth problem are np-complete in all settings while the complexity of the fourth one remains open for the directed and undirected cases
5-4b models across visual reasoning tasks demonstrate that our methods consistently improve visual
reasoning
spatial reasoning
5-4b models across visual reasoning tasks demonstrate that our methods consistently improve visual reasoning capabilities outperforming vanilla self-improvement by 3
while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle normative
reasoning
reasoning curriculum
while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle normative reasoning remains underexplored
error analysis of triangular optimal transport
maps
optimal transport
error analysis of triangular optimal transport maps for filtering
the ac optimal power flow ac-opf problem is central to
power
inverse optimal
the ac optimal power flow ac-opf problem is central to power system operation but challenging to solve efficiently due to its nonconvex and nonlinear nature
experiments demonstrate the effectiveness of the proposed framework under mobility-induced dynamics and offer useful insights for the practical deployment of fl over
wireless
wireless systems
experiments demonstrate the effectiveness of the proposed framework under mobility-induced dynamics and offer useful insights for the practical deployment of fl over wireless channels
the nonlinear disturbance observer attenuates constant and nonlinear
disturbances
disturbance observer
the nonlinear disturbance observer attenuates constant and nonlinear disturbances as well as band-limited white noise
we then evaluate the impact of heuristic support adaptation on parameter inference and policy learning for a dynamic deformable linear object dlo
manipulation
robotic manipulation
we then evaluate the impact of heuristic support adaptation on parameter inference and policy learning for a dynamic deformable linear object dlo manipulation task
computer-using agents powered by vision-language
models
ai assistance
computer-using agents powered by vision-language models vlms have demonstrated human-like capabilities in operating digital environments like mobile platforms
this tension points to the need for a more systematic study of how number influences
collective
human disturbance
this tension points to the need for a more systematic study of how number influences collective behavior
moreover it gives access at the same time to the spatial distribution within the monolayer of the individual spin-segregated states responsible for the hidden
spin
hidden spin texture
moreover it gives access at the same time to the spatial distribution within the monolayer of the individual spin-segregated states responsible for the hidden spin textures not provided by other techniques
first to ensure safety at the path-segment level a segment-wise conservative collision test is applied where risk-prone trajectory path segments are recursively subdivided until
collision
collision avoidance
first to ensure safety at the path-segment level a segment-wise conservative collision test is applied where risk-prone trajectory path segments are recursively subdivided until collision risks are eliminated
in particular we introduce a variant of the virtual cross-validation formulas tailored to
quantile
quantile regression
in particular we introduce a variant of the virtual cross-validation formulas tailored to quantile functions
to address these issues we propose in-context steered
policy
reinforcement learning
to address these issues we propose in-context steered policy optimization icpo a unified framework that leverages the inherent in-context learning capability of lrms to provide expert guidance using existing datasets
bots a unified framework for bayesian online task selection in llm
reinforcement
reinforcement learning
bots a unified framework for bayesian online task selection in llm reinforcement finetuning
our results demonstrate that models trained across animals with partial observations can successfully in-paint the dynamics of unrecorded areas enabling
multi-area
receptive fields
our results demonstrate that models trained across animals with partial observations can successfully in-paint the dynamics of unrecorded areas enabling multi-area analyses that transcend the limitations of any single experiment
by mapping the system onto a gas of non-interacting spin-1 2 particles we derive exact analytical results for the dynamics with different
initial
initial states
by mapping the system onto a gas of non-interacting spin-1 2 particles we derive exact analytical results for the dynamics with different initial states
extensive quantitative and qualitative experiments demonstrate that braincognizer outperforms state-of-the-art approaches on
multiple
cognitive neuroscience
extensive quantitative and qualitative experiments demonstrate that braincognizer outperforms state-of-the-art approaches on multiple evaluation metrics
large language models llms show strong potential to support creative tasks but the role of the interface
design
language models
large language models llms show strong potential to support creative tasks but the role of the interface design is poorly understood
stellar abundances of elements with production channels that are metallicity-dependent most notably aluminium have provided an empirical route for separating different
galactic
star formation rates
stellar abundances of elements with production channels that are metallicity-dependent most notably aluminium have provided an empirical route for separating different galactic components
however prevailing strategies score candidates using only external
outputs
evaluation metrics
however prevailing strategies score candidates using only external outputs such as token probabilities entropies or self evaluations and these signals can be poorly calibrated after post training
we revisit the classical problem of comparing regression
functions
regression function
we revisit the classical problem of comparing regression functions a fundamental question in statistical inference with broad relevance to modern applications such as data integration transfer learning and causal inference
we suggest that interactions between parallel subnetworks in the brain may underlie such learning we present a model of representation learning by ensembles of neural networks where each network learns to encode stimuli into an
abstract
neural codes
we suggest that interactions between parallel subnetworks in the brain may underlie such learning we present a model of representation learning by ensembles of neural networks where each network learns to encode stimuli into an abstract representation space by cross-supervising interactions with other networks for inpu...
in all cases in which the fokker-planck type equations can be treated through these distances it is shown that the rate of decay is improved with respect to known results which are based on the
decay
vacuum decay
in all cases in which the fokker-planck type equations can be treated through these distances it is shown that the rate of decay is improved with respect to known results which are based on the decay of relative entropy
test-time alignment of large language models llms attracts attention because fine-tuning
llms
language models
test-time alignment of large language models llms attracts attention because fine-tuning llms requires high computational costs
here we develop a mathematical model which uses an optimisation framework to determine the higher-order
spatial
spatial structure
here we develop a mathematical model which uses an optimisation framework to determine the higher-order spatial structure of a collective that optimises group-level knowledge transfer
experiments on contemporary llms show that choosing an
effective
models llms
experiments on contemporary llms show that choosing an effective format and prompt combination can improve accuracy by up to 8
the model s superiority was further cemented by its leading
overall
significantly outperforms
the model s superiority was further cemented by its leading overall accuracy of 0
with the development of artificial intelligence ai techniques implementing ai-based techniques to improve
wireless
wireless systems
with the development of artificial intelligence ai techniques implementing ai-based techniques to improve wireless transceivers becomes an emerging research topic
randomized experiments or randomized controlled
trials
randomized experiments
randomized experiments or randomized controlled trials rcts are gold standards for causal inference yet cost and sample-size constraints limit power
while a multi-agent approach based on large language models
llms
llm agents
while a multi-agent approach based on large language models llms represents a promising strategy to surpass the capabilities of single models its success is critically dependent on synergistic team composition
here we show that spin-1 nanographenes can also be used to explore the topological phase transition between the haldane phase and a dimerized
phase
phase transition
here we show that spin-1 nanographenes can also be used to explore the topological phase transition between the haldane phase and a dimerized phase predicted for spin-1 chains with bond-alternation
by applying both exact diagonalization and density-matrix renormalization group theory to the quantum heisenberg hamiltonian we show how a quantum-mechanical treatment of an ab initio parametrized
spin
spin-momentum locking
by applying both exact diagonalization and density-matrix renormalization group theory to the quantum heisenberg hamiltonian we show how a quantum-mechanical treatment of an ab initio parametrized spin model can significantly improve the predicted low-temperature spin-flop field over a classical description when compar...
in difference-in-differences did settings with categorical
outcomes
average treatment
in difference-in-differences did settings with categorical outcomes such as voting occupation or major choices treatments often affect both total counts e
its important variant the interval dinkelbach method 1991 constructs convergent upper and lower bound sequences that bracket the solution and achieve quadratic and superlinear
convergence
superlinear convergence
its important variant the interval dinkelbach method 1991 constructs convergent upper and lower bound sequences that bracket the solution and achieve quadratic and superlinear convergence respectively under the assumption that the parametric function is twice continuously differentiable
from incremental transitive cover to strongly
polynomial
strongly polynomial
from incremental transitive cover to strongly polynomial maximum flow
this work propose a new network formation model the vari-linear network which includes two core mechanisms exponential probabilistic growth and
vari-linear
scale-free networks
this work propose a new network formation model the vari-linear network which includes two core mechanisms exponential probabilistic growth and vari-linear preferential attachment
the system is implemented in ros gazebo turtlebot3 and evaluated with pathbench metrics including success rate collision rate path efficiency and re-planning
efficiency
mobile robots
the system is implemented in ros gazebo turtlebot3 and evaluated with pathbench metrics including success rate collision rate path efficiency and re-planning efficiency in dynamic and partially observable environments
slt thus provides a formal framework for understanding the amplification and coherence of social energy leading to abrupt phase-like transitions in
collective
collective action
slt thus provides a formal framework for understanding the amplification and coherence of social energy leading to abrupt phase-like transitions in collective behavior
the framework successfully diagnoses when scope conditions hold positive
decay
spatial decay
the framework successfully diagnoses when scope conditions hold positive decay parameters validate diffusion assumptions near hospitals while negative parameters correctly signal urban confounding effects
we then use this idea to find overlooked critical numbers in past studies of
collective
collective systems
we then use this idea to find overlooked critical numbers in past studies of collective behavior and explore the implications for their conclusions
the minimum cardinality any subset of the
tree
tree edit
the minimum cardinality any subset of the tree s vertices must have so that all clusters of vertices further away than some l do not exceed a cardinality threshold
based on this model we first design a nominal stabilizing controller that guarantees stochastic l _2 string
stability
data-driven stabilization
based on this model we first design a nominal stabilizing controller that guarantees stochastic l _2 string stability under imperfect mode estimation
these results demonstrate efficiency gains without cognitive change suggesting that current narrow ai
systems
ai agents
these results demonstrate efficiency gains without cognitive change suggesting that current narrow ai systems serve as cognitive scaffolds extending performance without transforming underlying mental capacities
the emergence of large vision-language models vlms such as gpt and claude enables zero-shot semantic
reasoning
vision-language models
the emergence of large vision-language models vlms such as gpt and claude enables zero-shot semantic reasoning from visual and textual inputs
this approach opens the way to the use of partial intercalation to define regions with distinct
magnetic
magnetic properties
this approach opens the way to the use of partial intercalation to define regions with distinct magnetic properties within a single flake
this setting motivates us to align semantic information in
unstructured
natural language
this setting motivates us to align semantic information in unstructured text with the structured normative elements of regulations
by evaluating agent responses with natural language processing models other llms and human experts our findings illustrate the limitations of purely deep learning solutions and emphasize the
critical
artificial intelligence
by evaluating agent responses with natural language processing models other llms and human experts our findings illustrate the limitations of purely deep learning solutions and emphasize the critical role of interdisciplinary design in agent development
in this study we used a data-driven network approach to examine whether resting-state eeg
connectivity
functional connectivity
in this study we used a data-driven network approach to examine whether resting-state eeg connectivity patterns differentiate individuals according to their creative abilities
self-gravitating galactic halos composed of self-interacting
dark
dark matter
self-gravitating galactic halos composed of self-interacting dark matter exhibit the formation of a highly dense core at the galactic center--a gravothermal collapse
we characterize their minimax optimal decision rule via a duality argument and show that surprisingly trusting the predictions and acting accordingly is recovered in this minimax sense by emph decision calibration and any strictly stronger notion of
calibration
debiased machine learning
we characterize their minimax optimal decision rule via a duality argument and show that surprisingly trusting the predictions and acting accordingly is recovered in this minimax sense by emph decision calibration and any strictly stronger notion of calibration a substantially weaker and more tractable condition than f...
plugging regression functions estimated by machine learning methods into the identifying equations can yield poor
performance
predictive performance
plugging regression functions estimated by machine learning methods into the identifying equations can yield poor performance because of first-stage bias
we study this problem for weighted threshold potential functions a large and important subclass of monotone
submodular
monotone submodular
we study this problem for weighted threshold potential functions a large and important subclass of monotone submodular functions that includes influence maximization data summarization and facility location to name a few
retrieval augmented generation-enhanced distributed
llm
llm agents
retrieval augmented generation-enhanced distributed llm agents for generalizable traffic signal control with emergency vehicles
comap is a line intensity mapping lim experiment targeting dense
molecular
molecular gas
comap is a line intensity mapping lim experiment targeting dense molecular gas via co 1--0 emission at z sim3
however their reliability is often limited for subjective tasks when human judgments
involve
normative reasoning
however their reliability is often limited for subjective tasks when human judgments involve subtle reasoning beyond annotation labels
in ate estimation the balancing weights and the regression functions of the outcome play important roles where the balancing weights are referred to as the
riesz
riesz regression
in ate estimation the balancing weights and the regression functions of the outcome play important roles where the balancing weights are referred to as the riesz representer bias-correction term and clever covariates depending on the context
our general interaction framework which reduces to several previously studied models as special cases provides a versatile platform for engineering quantum correlations with applications in quantum
simulation
quantum computing
our general interaction framework which reduces to several previously studied models as special cases provides a versatile platform for engineering quantum correlations with applications in quantum simulation state preparation and sensing protocols
additionally we used a gas-grain chemical code to simulate a pre-stellar
core
star formation
additionally we used a gas-grain chemical code to simulate a pre-stellar core and determine where ne can affect the chemistry
we find that dwarf agn selected by infrared colors are the most distinct population with the highest star formation
rates
galactic nuclei
we find that dwarf agn selected by infrared colors are the most distinct population with the highest star formation rates and lowest stellar masses
we study massachusetts towns april 2020-april 2021 build a weekly directed
mobility
mobility networks
we study massachusetts towns april 2020-april 2021 build a weekly directed mobility network from anonymized smartphone traces derive dynamic topology measures and evaluate their out-of-sample value for one-week-ahead covid-19 forecasts
can llms translate human instructions into a reinforcement
learning
imitation learning
can llms translate human instructions into a reinforcement learning agent s internal emergent symbolic representation
in difference to the typical case we show the interaction topology and system dynamics combine to produce power law abundance distributions in a critical region of the
phase
phase transition
in difference to the typical case we show the interaction topology and system dynamics combine to produce power law abundance distributions in a critical region of the phase diagram identifiable as a griffiths phase
here we develop a general theoretical framework that establishes quantitative relationships between the strength and timing of transient dynamics to
various
scale-free networks
here we develop a general theoretical framework that establishes quantitative relationships between the strength and timing of transient dynamics to various inputs in heterogeneous networks
to make inverse optimal issf controllers robust to gain variation we propose a
gain
control strategy
to make inverse optimal issf controllers robust to gain variation we propose a gain margin improvement approach at the expense of an increased control effort
on average across countries the share of urban residents living in
cities
urban systems
on average across countries the share of urban residents living in cities with over one million people rose from 18 in 1975 to 39 in 2025
by leveraging dielectric waveguides and flexibly adjustable
pinching
pinching antenna
by leveraging dielectric waveguides and flexibly adjustable pinching antennas pass establishes short-distance line-of-sight los links while effectively mitigating the significant path loss and potential signal blockage making it a promising solution for high-frequency mec systems
its sensitivity function avoids the sensitivity
tradeoff
sensitivity tradeoff
its sensitivity function avoids the sensitivity tradeoff achieving wideband harmonic suppression without amplifying aperiodic disturbances or shifting harmonic suppression frequencies
in massive and dynamic data streams a central challenge is to design compact sketches that preserve essential structural properties of the
data
data structure
in massive and dynamic data streams a central challenge is to design compact sketches that preserve essential structural properties of the data while enabling efficient queries
to ensure reward fidelity our automated grader calibration pipeline systematically purges noise from the llm-based
reward
reward density
to ensure reward fidelity our automated grader calibration pipeline systematically purges noise from the llm-based reward model with minimal human supervision
the online method adapts to distribution shifts including human behavior evolving through
interaction
human-ai interaction
the online method adapts to distribution shifts including human behavior evolving through interaction with ai a phenomenon we call human to ai adaptation
averaging the hamiltonian over the inner orbit we find that magnetic tides introduce new resonances
absent
tidal disruption
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 task can be viewed as a language generation task that bridges
natural
natural language processing
this task can be viewed as a language generation task that bridges natural language human knowledge and programming logic
specifically it optimizes not only for the estimated objective value but also for the chances that the policy will be statistically significantly better than the observational
policy
policy learning
specifically it optimizes not only for the estimated objective value but also for the chances that the policy will be statistically significantly better than the observational policy used to collect data
5-4b models across visual reasoning tasks demonstrate that our methods consistently improve visual reasoning
capabilities
reasoning curriculum
5-4b models across visual reasoning tasks demonstrate that our methods consistently improve visual reasoning capabilities outperforming vanilla self-improvement by 3
we demonstrate the capabilities of this laser-arpes system by investigating several prototypical materials showcasing its potential for elucidating complex phenomena in
quantum
photonic devices
we demonstrate the capabilities of this laser-arpes system by investigating several prototypical materials showcasing its potential for elucidating complex phenomena in quantum materials
when a high level decision making agent generates a
collision
collision avoidance
when a high level decision making agent generates a collision free path a robust low level controller is required to precisely follow this trajectory
by linking behavioral attributes with environmental context mobilitygen reproduces key
patterns
emergent behaviors
by linking behavioral attributes with environmental context mobilitygen reproduces key patterns such as scaling laws for location visits activity time allocation and the coupled evolution of travel mode and destination choices