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numerical simulations indicate that asymmetric perturbations can alter soliton separations or destroy these
states
phase transitions
numerical simulations indicate that asymmetric perturbations can alter soliton separations or destroy these states while the imposed pump phase difference plays a key role in cluster selection
our analysis loosely favours local starburst
activity
star clusters
our analysis loosely favours local starburst activity as the driver of the shocks and circumnuclear gas dynamics in ngc 7582 though the possibility of an agn jet contribution cannot be excluded
smbhs are evolved following the stellar mass growth of their host galaxies by assigning an accretion rate at each redshift from the empirical eddington
ratio
stellar mass function
smbhs are evolved following the stellar mass growth of their host galaxies by assigning an accretion rate at each redshift from the empirical eddington ratio distributions and duty cycles
with the development of artificial intelligence ai techniques implementing ai-based techniques to improve
wireless
wireless communication
with the development of artificial intelligence ai techniques implementing ai-based techniques to improve wireless transceivers becomes an emerging research topic
we propose a new and more substantively appropriate conditional extrapolation assumption which requires an analyst to conduct a preliminary test to determine whether the severity of pre-treatment
parallel
treatment effect boundaries
we propose a new and more substantively appropriate conditional extrapolation assumption which requires an analyst to conduct a preliminary test to determine whether the severity of pre-treatment parallel trend violations falls below an acceptable level before extrapolation to the post-treatment period is justified
if the reward structures of the human-agent game meet these conditions we have a formal guarantee that the
agent
reward density
if the reward structures of the human-agent game meet these conditions we have a formal guarantee that the agent improving its own outcome will not harm the human s
strong empirical evidence from laboratory experiments and more recently from population surveys shows that individuals when evaluating their situations pay attention to whether they experience gains or losses with
losses
potential outcomes
strong empirical evidence from laboratory experiments and more recently from population surveys shows that individuals when evaluating their situations pay attention to whether they experience gains or losses with losses weighing more heavily than gains
this learned geometric knowledge can then be distilled to perform generalized
tool
geometric primitives
this learned geometric knowledge can then be distilled to perform generalized tool usage tasks by selecting and using the best available real-world object as tool
traditional approaches require costly numerical
solvers
existing methods
traditional approaches require costly numerical solvers to sample between arbitrary time points
adam is the de facto optimizer in deep learning yet its theoretical
understanding
neural network
adam is the de facto optimizer in deep learning yet its theoretical understanding remains limited
the accretion is viscosity-limited when q alpha xi 1 mathcal m 2 3 3 1 2 h 3 where q is the mass ratio between the co and the
supermassive
black hole mass
the accretion is viscosity-limited when q alpha xi 1 mathcal m 2 3 3 1 2 h 3 where q is the mass ratio between the co and the supermassive black hole alpha the viscosity parameter mathcal m the mach number of the bulk relative motion and h the aspect ratio of the agn disc
swiech stochastic optimal control in infinite dimensions dynamic
programming
dynamic programming
swiech stochastic optimal control in infinite dimensions dynamic programming and hjb equations springer 2017
in this control algorithm each host vehicle negotiates with other agents in a control zone of the highway network and enacts its own action to perform
safe
control strategy
in this control algorithm each host vehicle negotiates with other agents in a control zone of the highway network and enacts its own action to perform safe and energy-efficient merge maneuvers
furthermore the moving mass dynamics are expressed as an extension to the manoeuvring model for
underwater
moving mass
furthermore the moving mass dynamics are expressed as an extension to the manoeuvring model for underwater vehicles originally introduced by fossen 1991
in decode we grow galaxies with their sfr linked to halo accretion rate distributions via
abundance
stellar population
in decode we grow galaxies with their sfr linked to halo accretion rate distributions via abundance matching
to overcome the potential non-smoothness of the
hyper-objective
objective function
to overcome the potential non-smoothness of the hyper-objective and the computational challenges associated with the hessian matrix we utilize penalty and augmented lagrangian methods to reformulate the original problem as a single-level one
multimodal large language models mllms have advanced
vision-language
vision-language models vlms
multimodal large language models mllms have advanced vision-language reasoning and are increasingly deployed in embodied agents
the growing complexity of integrated photonics necessitates compact low-power
devices
photonic circuits
the growing complexity of integrated photonics necessitates compact low-power devices that transcend traditional material-centric design approaches
this setting motivates us to align semantic information in unstructured text with the structured
normative
normative reasoning
this setting motivates us to align semantic information in unstructured text with the structured normative elements of regulations
the determination of the phase diagram of water ice under extreme conditions remains a fundamental
challenge
phase transition
the determination of the phase diagram of water ice under extreme conditions remains a fundamental challenge in high-pressure physics
further enhancement of the breakdown voltage was achieved by tunneling leakage management using composite pt cap ptox
pt
ptox pt
further enhancement of the breakdown voltage was achieved by tunneling leakage management using composite pt cap ptox pt 1
notably the learned policies transfer directly from simulation to hardware without fine-tuning achieving
stable
reinforcement learning
notably the learned policies transfer directly from simulation to hardware without fine-tuning achieving stable real-world locomotion
ops problems are computationally challenging mixed-integer
linear
quadratic programming
ops problems are computationally challenging mixed-integer linear programs milps that must be solved rapidly and frequently in operational settings
the latter is decomposed into individual and coupling costs with the distinctive feature that the
coupling
predictive control
the latter is decomposed into individual and coupling costs with the distinctive feature that the coupling term is a pairwise interaction function between the controls
unveiling intrinsic text bias in multimodal large
language
large language
unveiling intrinsic text bias in multimodal large language models through attention key-space analysis
we demonstrate that a nonlinear sis can improve communication reliability compared to a linear sis by forming complex signal patterns across the
sis
wireless systems
we demonstrate that a nonlinear sis can improve communication reliability compared to a linear sis by forming complex signal patterns across the sis surface which provide higher diversity against noise disturbances while still allowing the receiver to discern these patterns
in subsequent years a host of new methods was introduced that measured both the synchrony among neuronal
spike
spike train
in subsequent years a host of new methods was introduced that measured both the synchrony among neuronal spike trains and the directional component e
braincognizer brain decoding with human visual
cognition
brain decoding
braincognizer brain decoding with human visual cognition simulation for fmri-to-image reconstruction
modern vision-language models vlms excel at many
multimodal
vision-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
these contributions highlight domain-specific insights that have shaped the design of an immersive
ar
augmented reality
these contributions highlight domain-specific insights that have shaped the design of an immersive ar theater system
yet an important question still remains are video models ready to serve as zero-shot reasoners in challenging visual
reasoning
spatial reasoning
yet an important question still remains are video models ready to serve as zero-shot reasoners in challenging visual reasoning scenarios
additionally we introduce securebleu a new evaluation metric designed to assess the effectiveness of
review
review comments
additionally we introduce securebleu a new evaluation metric designed to assess the effectiveness of review comments in addressing security issues
early-assembling high-concentration halos form
stars
stellar mass
early-assembling high-concentration halos form stars efficiently and become gas-poor by z 0 while late-assembling low-concentration halos remain gas-rich due to delayed star formation and rejuvenated gas accretion
we model financial distress propagation as a diffusion process on weighted networks deriving a network diffusion equation from first principles that predicts contagion decay depends on the
network
network fragility
we model financial distress propagation as a diffusion process on weighted networks deriving a network diffusion equation from first principles that predicts contagion decay depends on the network s algebraic connectivity through the relation kappa sqrt lambda_2 d where lambda_2 is the second-smallest eigenvalue of the...
the complexity bounds we obtain are confirmed numerically for a specific case with the o n 2 quantum algorithm outperforming the classical greedy
algorithm
quantum walk
the complexity bounds we obtain are confirmed numerically for a specific case with the o n 2 quantum algorithm outperforming the classical greedy algorithm that also runs in o n 2
specifically to assess how well llms reason with normative modals we make a comparison between their reasoning with
normative
reasoning capabilities
specifically to assess how well llms reason with normative modals we make a comparison between their reasoning with normative modals and their reasoning with epistemic modals which share a common formal structure
overall they are not yet reliable as standalone zero-shot reasoners but exhibit encouraging signs as complementary visual engines alongside dedicated
reasoning
reasoning capabilities
overall they are not yet reliable as standalone zero-shot reasoners but exhibit encouraging signs as complementary visual engines alongside dedicated reasoning models
this paper introduces a dual-learning framework that integrates individualized learning
rates
learning rates
this paper introduces a dual-learning framework that integrates individualized learning rates for agents and a rewiring rate for the network reflecting real-world cognitive diversity and structural adaptability
learning a compact representation of history is critical for planning and generalization in
partially
temporal resolution
learning a compact representation of history is critical for planning and generalization in partially observable environments
through a comprehensive evaluation across various configurations we demonstrate that the system effectively performs
diacritization
natural language processing
through a comprehensive evaluation across various configurations we demonstrate that the system effectively performs diacritization without relying on complex explicit linguistic analysis
existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning
capabilities
language models
existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning capabilities of large language models llms
while photonic lanterns efficiently and uniquely map a set of input
modes
waveguide modes
while photonic lanterns efficiently and uniquely map a set of input modes to single-mode outputs or vice versa the optical mode transfer matrix of any particular fabricated device cannot be constrained at the design stage due to manufacturing imperfections
low-altitude uav-carried movable antenna for joint wireless
power
transmit power
low-altitude uav-carried movable antenna for joint wireless power transfer and covert communications
we show that our estimation strategy fully exploits the multidimensional assignment rule and reveals
heterogeneous
treatment effect boundaries
we show that our estimation strategy fully exploits the multidimensional assignment rule and reveals heterogeneous effects along the treatment boundaries
phase shifts switches and beam splits allow for the construction of arbitrary
quantum
quantum dot
phase shifts switches and beam splits allow for the construction of arbitrary quantum gates
these findings highlight challenges in achieving logical consistency in llms normative
reasoning
reasoning capabilities
these findings highlight challenges in achieving logical consistency in llms normative reasoning and provide insights for enhancing their reliability
however these methods assume that only one object is provided and that it is possible with the correct grasp to perform the task they are not capable of identifying grasping and using the best object for a task when many are available especially when the optimal
tool
tool usage
however these methods assume that only one object is provided and that it is possible with the correct grasp to perform the task they are not capable of identifying grasping and using the best object for a task when many are available especially when the optimal tool is absent
we show that scmd is a proper metric and provide a consistent estimator with
theoretical
theoretical guarantees
we show that scmd is a proper metric and provide a consistent estimator with theoretical guarantees
we provide a rigorous theoretical analysis of our proposals and
complement
simulation studies
we provide a rigorous theoretical analysis of our proposals and complement it with supporting simulations
traditional graph_theoretic metrics such as betweenness and degree
centrality
scale-free networks
traditional graph_theoretic metrics such as betweenness and degree centrality offer insights into local network structure but often fail to capture global structural distortions resulting from link failures
here we demonstrate that reinforcement learning rl and supervised learning sl drive
recurrent
continual learning
here we demonstrate that reinforcement learning rl and supervised learning sl drive recurrent neural networks rnns toward fundamentally different computational solutions when trained on identical decision-making tasks
after deriving a non-convex mathematical model of the problem we
prove
strongly convex
after deriving a non-convex mathematical model of the problem we prove that the feasible region of this problem is a lattice
empirically we construct a dataset of math word problems injected with various number of irrelevant axioms that vary in
semantic
question answering
empirically we construct a dataset of math word problems injected with various number of irrelevant axioms that vary in semantic overlap with the goal theorem
empirically our algorithms consistently outperform
existing
real-world datasets
empirically our algorithms consistently outperform existing baselines in terms of size-accuracy tradeoffs and runtime even when data assumptions are violated across a wide range of datasets
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
-approximation algorithm
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 work underscores the potential of cas as proactive human-machine interface hmi interventions demonstrating how natural language can support context-aware interaction during
automated
automated driving
this work underscores the potential of cas as proactive human-machine interface hmi interventions demonstrating how natural language can support context-aware interaction during automated driving
in addition we propose an marginal likelihood
estimator
maximum likelihood
in addition we propose an marginal likelihood estimator to enable model comparison across alternative specifications
through fourier transform infrared spectroscopy measurement and full-wave photonic simulations we identified a range of optical excitations in the rbs including three sphps two hyperbolic volume
phonon
phonon polaritons
through fourier transform infrared spectroscopy measurement and full-wave photonic simulations we identified a range of optical excitations in the rbs including three sphps two hyperbolic volume phonon polaritons hvphps and one epsilon-near-zero enz mode
while recent llm-based approaches improve over static templates they still generate noisy fragmented graphs with duplicate nodes due to the absence of guided extraction and
coreference
node duplication
while recent llm-based approaches improve over static templates they still generate noisy fragmented graphs with duplicate nodes due to the absence of guided extraction and coreference resolution
a novel two-stage optimization approach mitigates numerical issues arising from the structure of the resulting
optimal
control strategy
a novel two-stage optimization approach mitigates numerical issues arising from the structure of the resulting optimal control problem
overall our study links the structure of stimuli task and learning rule to representational drift and could pave the way for using
drift
recurrent neural
overall our study links the structure of stimuli task and learning rule to representational drift and could pave the way for using drift as a signal for uncovering underlying computation in the brain
leveraging this equivalence we propose a novel regularization method for
policy
reinforcement learning
leveraging this equivalence we propose a novel regularization method for policy learning
in this paper we consider a full-duplex fd integrated sensing and
communication
wireless communication
in this paper we consider a full-duplex fd integrated sensing and communication isac system in which the base station bs performs downlink and uplink communications with multiple users while simultaneously sensing multiple targets
specifically we first construct a dataset tailored for training and evaluating secure code
review
code review
specifically we first construct a dataset tailored for training and evaluating secure code review capabilities
finally we outline open problems in the field and present a roadmap for integrating tf-qkd into scalable quantum
networks
fault-tolerant quantum
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
this represents a paradigm shift long-residence
interstellar
circumgalactic medium
this represents a paradigm shift long-residence interstellar objects primarily reveal gcr-processed material rather than pristine material representative of their primordial formation environments
the output phase is ultimately read out as a
change
optical interference
the output phase is ultimately read out as a change in optical power
the safety filter employs a smooth mixing strategy between
nominal
safety filter
the safety filter employs a smooth mixing strategy between nominal and backup controllers based on distance to the invariant set boundary facilitating minimal intervention when the system operates safely
we hope our results show the potential of
looplm
thinking traces
we hope our results show the potential of looplm as a novel scaling direction in the reasoning era
we provide an inferential framework to assess variable importance for heterogeneous
treatment
causal effects
we provide an inferential framework to assess variable importance for heterogeneous treatment effects
our study establishes a theoretical foundation and physical intuition about the
role
phase transitions
our study establishes a theoretical foundation and physical intuition about the role of the gouy phase
we adopt inverse probability weighting ipw for
identification
nonparametric identification
we adopt inverse probability weighting ipw for identification however ipw-transformed outcomes are known to be noisy even when true propensity scores are used
this allows us to investigate the restoration of particle-number symmetry in the dynamics from initial states with no well-defined particle number and the emergence of the quantum
mpemba
mpemba effect
this allows us to investigate the restoration of particle-number symmetry in the dynamics from initial states with no well-defined particle number and the emergence of the quantum mpemba effect
to optimize this trade-off we pose a non-convex joint ota power-control design and develop an efficient successive
convex
power allocation
to optimize this trade-off we pose a non-convex joint ota power-control design and develop an efficient successive convex approximation sca algorithm that requires only statistical csi at the base station
since multiple transport maps exist we employ conditional optimal
transport
optimal transport
since multiple transport maps exist we employ conditional optimal transport flow matching cot-fm to ensure that the transformation minimally distorts the underlying structure of the data
however the visual clarity of radar charts can be severely compromised when
feature
radar charts
however the visual clarity of radar charts can be severely compromised when feature values alternate drastically in magnitude around the circle causing areas to collapse which misrepresents relative differences
nonetheless this approach typically assumes a deterministic payoff structure for
social
social interactions
nonetheless this approach typically assumes a deterministic payoff structure for social interactions
inverse reinforcement learning using just
classification
machine learning
inverse reinforcement learning using just classification and a few regressions
unlike traditional multimodal interfaces empathic
prompting
empathic prompting
unlike traditional multimodal interfaces empathic prompting requires no explicit user control instead it unobtrusively augments textual input with affective information for conversational and smoothness alignment
the simulations include detailed modeling of star formation
chemical
star formation rates
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 this paper we introduce a novel concept in
causal
interventional constraints
in this paper we introduce a novel concept in causal discovery termed interventional constraints which differs fundamentally from interventional data
our general interaction framework which reduces to several previously studied models as special cases provides a versatile platform for engineering quantum
correlations
quantum key distribution
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
our method is designed for versatility allowing integration with any state-of-the-art deep
reinforcement
deep reinforcement
our method is designed for versatility allowing integration with any state-of-the-art deep reinforcement learning drl algorithms within its self-play framework
this paper investigates whether pretrained language models including large language models possess similar
capabilities
language agents
this paper investigates whether pretrained language models including large language models possess similar capabilities for loanword identification
however when deployed in real-world scenarios such solutions typically face scalability issues and have to address practical requirements such as full access to original
datasets
real-world scenarios
however when deployed in real-world scenarios such solutions typically face scalability issues and have to address practical requirements such as full access to original datasets and model
nonparametric identification of spatial treatment effect boundaries evidence from
bank
european banking
nonparametric identification of spatial treatment effect boundaries evidence from bank branch consolidation
this procedure is extended to broader scenarios with imbalanced data such as
imbalanced
imbalanced data
this procedure is extended to broader scenarios with imbalanced data such as imbalanced multi-task learning and causal inference
this single circuit provides a biologically grounded
flexible
brain-computer interface
this single circuit provides a biologically grounded flexible mechanism for predictive cognition
for small-scale open-source models reinforcement
learning
reinforcement learning rl
for small-scale open-source models reinforcement learning with verifiable rewards rlvr fails when correct solutions are rarely sampled even after many attempts while supervised fine-tuning sft tends to overfit long demonstrations through rigid token-by-token imitation
they do not break network nonlocality which enables one to identify useful quantum
channels
quantum advantage
they do not break network nonlocality which enables one to identify useful quantum channels in networks
we release amo-bench to facilitate further research into advancing the reasoning abilities of
language
language models
we release amo-bench to facilitate further research into advancing the reasoning abilities of language models
a key manifestation is temporal reflection in an unbounded spatial domain where a sudden
temporal
vortex phase
a key manifestation is temporal reflection in an unbounded spatial domain where a sudden temporal discontinuity induces phase-conjugated backward waves alongside anomalous spin conversion
while modern large language models llms are increasingly used to model neural responses to
language
large language models
while modern large language models llms are increasingly used to model neural responses to language their internal representations are highly entangled mixing information about lexicon syntax meaning and reasoning
we establish the asymptotic properties of the
test
test statistics
we establish the asymptotic properties of the test statistics which hold under both fixed- and high-dimensional regimes
understanding how transient dynamics unfold in response to localized
inputs
transient dynamics
understanding how transient dynamics unfold in response to localized inputs is central to predicting and controlling signal propagation in network systems including neural processing epidemic intervention and power-grid resilience
however research on online safety remains fragmented across different hci subfields with
limited
online safety
however research on online safety remains fragmented across different hci subfields with limited communication and collaboration between disciplines
a unified framework for spatial and temporal treatment effect
boundaries
treatment assignment
a unified framework for spatial and temporal treatment effect boundaries theory and identification
our solutions assume a constant star formation efficiency a constant mass-loading factor and that the yields are linearly dependent on the interstellar medium
abundance
stellar mass
our solutions assume a constant star formation efficiency a constant mass-loading factor and that the yields are linearly dependent on the interstellar medium abundance with the option of a saturation of the yields at high metallicity
here our approach aligns motor performance items from different measurement instruments for
mixed-effects
mixed-effects regression
here our approach aligns motor performance items from different measurement instruments for mixed-effects regression and maps estimated effects back to the observed item level to quantify the treatment switch effect
we release code pretrained weights and tutorials to support standardized
eeg
brain activity
we release code pretrained weights and tutorials to support standardized eeg research and accelerate progress in clinical neuroscience