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our hybrid plasmonic waveguide architecture capable of supporting both strong and weak coupling regimes between plasmonic and dielectric
waveguide
waveguide modes
our hybrid plasmonic waveguide architecture capable of supporting both strong and weak coupling regimes between plasmonic and dielectric waveguide modes is precisely engineered to reach an ep where eigenmodes coalesce
the performance of large language models llms often degrades when
crucial
large language
the performance of large language models llms often degrades when crucial information is in the middle of a long context a lost-in-the-middle phenomenon that mirrors the primacy and recency effects in human memory
the derived results suggest that the mechanism for
ionic
ionic conduction
the derived results suggest that the mechanism for ionic conduction is the correlated barrier hopping cbh process
in this paper we combine adaptation and control barrier functions into a real-time control architecture that guarantees stability ensures
control
control systems
in this paper we combine adaptation and control barrier functions into a real-time control architecture that guarantees stability ensures control performance and remains safe even with the parametric uncertainties
sir models with demography random transmission coefficient and non-autonomous
vaccination
disease transmission
sir models with demography random transmission coefficient and non-autonomous vaccination rate
steervlm robust model control through lightweight activation steering for vision
language
vision-language models vlms
steervlm robust model control through lightweight activation steering for vision language models
as autonomous agents from self-driving cars to virtual assistants become increasingly present in everyday life safe and effective collaboration depends on human understanding of
agents
automated driving
as autonomous agents from self-driving cars to virtual assistants become increasingly present in everyday life safe and effective collaboration depends on human understanding of agents intentions
working in a suitable space of trajectories where a partial smoothing property of the linear part of the
hjb
hjb equation
working in a suitable space of trajectories where a partial smoothing property of the linear part of the hjb equations holds
in particular we highlight how deterministic approximations of
stochastic
stochastic differential
in particular we highlight how deterministic approximations of stochastic models can fail near critical numbers
large language models llms have demonstrated exceptional
capabilities
large language models llms
large language models llms have demonstrated exceptional capabilities across multiple domains by leveraging massive pre-training and curated fine-tuning data
existing automated approaches though increasingly leveraging large
language
language models
existing automated approaches though increasingly leveraging large language models llms remain largely confined to structured tabular data and cannot adequately address the heterogeneity of social media analysis
in decode we grow galaxies with their sfr linked to halo accretion rate distributions via
abundance
stellar mass function
in decode we grow galaxies with their sfr linked to halo accretion rate distributions via abundance matching
the growing success of vision-language-action vla models stems from the promise that pretrained vision-language models vlms can endow
agents
learning agents
the growing success of vision-language-action vla models stems from the promise that pretrained vision-language models vlms can endow agents with transferable world knowledge and vision-language vl grounding laying a foundation for action models with broader generalization
we investigate the relationship between disc winds radio jets accretion rates and black hole
masses
stellar mass
we investigate the relationship between disc winds radio jets accretion rates and black hole masses of a sample of sim 100k quasars at z approx 2
the growing complexity of integrated photonics necessitates compact low-power
devices
photonic crystal
the growing complexity of integrated photonics necessitates compact low-power devices that transcend traditional material-centric design approaches
we formulate the problem as a markov decision process and analyze the structure of the optimal
policy
state estimation
we formulate the problem as a markov decision process and analyze the structure of the optimal policy pi star for l 3 extending insights to arbitrary l
however existing methods often rely on prior knowledge of problem parameters-such as smoothness
convexity
first-order methods
however existing methods often rely on prior knowledge of problem parameters-such as smoothness convexity or communication network topologies-to determine appropriate stepsizes
deep reinforcement learning approach to qosaware load balancing in 5g cellular networks under user
mobility
reinforcement learning
deep reinforcement learning approach to qosaware load balancing in 5g cellular networks under user mobility and observation uncertainty
existing approaches often assume linear relationships between covariates and parameters oversimplifying the complex non-monotonic
interactions
traffic dynamics
existing approaches often assume linear relationships between covariates and parameters oversimplifying the complex non-monotonic interactions among different road users
defining the urban local with low dimensional manifolds of human
mobility
large cities
defining the urban local with low dimensional manifolds of human mobility networks
momentum-resolved reflectivity of a 2d photonic
crystal
optical properties
momentum-resolved reflectivity of a 2d photonic crystal in the near-infrared
validated in high-fidelity simulation with realistic quadrotor dynamics the resulting policies significantly outperform both a standard
reinforcement
deep reinforcement learning
validated in high-fidelity simulation with realistic quadrotor dynamics the resulting policies significantly outperform both a standard reinforcement learning baseline and a state-of-the-art game-theoretic planner
while a tight conversion from epsilon -dp to zcdp
exists
approximation guarantee
while a tight conversion from epsilon -dp to zcdp exists for the worst-case mechanism many common algorithms satisfy stronger guarantees
kagome metals are an intriguing class of quantum materials as the presence of both flat bands and dirac points provides access to functional
properties
quantum materials
kagome metals are an intriguing class of quantum materials as the presence of both flat bands and dirac points provides access to functional properties present in strongly correlated and topological materials
urban transportation networks are inherently vulnerable to
disruptions
traffic dynamics
urban transportation networks are inherently vulnerable to disruptions that affect connectivity and passenger mobility
constructing a quantum algorithm for this problem with a query complexity improving the upper bound o n 7 4 is an
open
open quantum
constructing a quantum algorithm for this problem with a query complexity improving the upper bound o n 7 4 is an open problem
we present combined jwst nirspec and miri mrs integral field spectroscopy data of the nuclear and circumnuclear regions of the highly dust obscured seyfert 2 galaxy ngc 7582 which is part of the
sample
massive galaxies
we present combined jwst nirspec and miri mrs integral field spectroscopy data of the nuclear and circumnuclear regions of the highly dust obscured seyfert 2 galaxy ngc 7582 which is part of the sample of agn in the galaxy activity torus and outflow survey gatos
solving for globally optimal line switching decisions in
ac
optimal power flow
solving for globally optimal line switching decisions in ac transmission grids can be intractability slow
we present a quantum-enhanced protocol for detecting wave-like dark matter using an array of
n
quantum correlations
we present a quantum-enhanced protocol for detecting wave-like dark matter using an array of n entangled superconducting cavities initialized in an m -photon fock state
bridging prediction and attribution identifying forward and backward causal influence ranges using assimilative
causal
causal inference
bridging prediction and attribution identifying forward and backward causal influence ranges using assimilative causal inference
this study develops a real-time framework for estimating pedestrian
crash
crash risk
this study develops a real-time framework for estimating pedestrian crash risk at signalized intersections under heterogeneous non-lane-based traffic
however due to the high penetration loss at high-frequencies blockage becomes a serious problem in thz communications especially in near-field indoor
communications
wireless communication
however due to the high penetration loss at high-frequencies blockage becomes a serious problem in thz communications especially in near-field indoor communications with numerous obstacles
to realize this vision we introduce asynchronous thinking asyncthink as a new paradigm of reasoning with large
language
large language
to realize this vision we introduce asynchronous thinking asyncthink as a new paradigm of reasoning with large language models which organizes the internal thinking process into concurrently executable structures
we evaluate our hierarchical reconstruction approach on three examples 1d translational motion 2d rotational
motion
optical flow
we evaluate our hierarchical reconstruction approach on three examples 1d translational motion 2d rotational motion and dynamic 3d scene deformation via gaussian splatting
to further progress our understanding of how algorithms work in
practice
online algorithm
to further progress our understanding of how algorithms work in practice we propose a new algorithm analysis framework that we call by the book analysis
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 materials
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
the end-to-end system couples free-space path loss beer--lambert atmospheric extinction pixel-level diffraction and optical efficiency with a unitary-pilot least-squares
channel
channel estimation
the end-to-end system couples free-space path loss beer--lambert atmospheric extinction pixel-level diffraction and optical efficiency with a unitary-pilot least-squares channel estimator and quantized phase feedback
this paper also considers energy consumption in the path
planning
obstacle avoidance
this paper also considers energy consumption in the path planning of automated guided vehicles agvs
arbitrary-scale video super-resolution avsr aims to enhance the resolution of
video
video generation
arbitrary-scale video super-resolution avsr aims to enhance the resolution of video frames potentially at various scaling factors which presents several challenges regarding spatial detail reproduction temporal consistency and computational complexity
conformal prediction beyond the horizon distribution-free inference for
policy
policy learning
conformal prediction beyond the horizon distribution-free inference for policy evaluation
moreover under specific assumptions on the adaptive momentum parameters we prove that the algorithm achieves an o 1 k 1 2
convergence
convergence rate
moreover under specific assumptions on the adaptive momentum parameters we prove that the algorithm achieves an o 1 k 1 2 convergence rate in terms of the distance between successive iterates
we first present a benchmark algorithm and then introduce a locally
adaptive
existing methods
we first present a benchmark algorithm and then introduce a locally adaptive refinement and split-sample procedures that broaden applicability
our approach leverages variable importance of each channel inside machine-learning-based decoders and we trial this methodology across three
applications
neural codes
our approach leverages variable importance of each channel inside machine-learning-based decoders and we trial this methodology across three applications seizure detection gesture recognition and force regression
this study demonstrates that providing language models with pragmatic theories as prompts is an effective in-context learning approach for tasks to
understand
context engineering
this study demonstrates that providing language models with pragmatic theories as prompts is an effective in-context learning approach for tasks to understand implied meanings
in this paper we leverage stochastic projection and lossy compression to establish new conditional
mutual
loss functions
in this paper we leverage stochastic projection and lossy compression to establish new conditional mutual information cmi bounds on the generalization error of statistical learning algorithms
we investigate potential heating mechanisms including direct agn photoionisation uv fluorescent excitation from young star
clusters
star-forming region
we investigate potential heating mechanisms including direct agn photoionisation uv fluorescent excitation from young star clusters and shock excitation
o vi emission is brightest surrounding small
clumpy
dense gas
o vi emission is brightest surrounding small clumpy structures near the galaxy where the gas density is high
these locations were subsequently characterized using a range of spatial and environmental indicators pertinent to urban heat island effects
urban
urban systems
these locations were subsequently characterized using a range of spatial and environmental indicators pertinent to urban heat island effects urban health and climate resilience
our framework thus provides a unified foundation for analyzing and improving the efficiency of fundamental
string-processing
pattern matching
our framework thus provides a unified foundation for analyzing and improving the efficiency of fundamental string-processing problems through the lens of prefix queries
in particular we show that narrower degree distributions contain longer shortest
loops
network structures
in particular we show that narrower degree distributions contain longer shortest loops as a universal property in a wide class of random networks
experimenting with llama-3 and qwen-3 models of different sizes and popular supervised fine-tuning sft and preference optimization datasets and algorithms we find that the sft phase generally establishes a model s values and subsequent
preference
preference optimization
experimenting with llama-3 and qwen-3 models of different sizes and popular supervised fine-tuning sft and preference optimization datasets and algorithms we find that the sft phase generally establishes a model s values and subsequent preference optimization rarely re-aligns these values
it first derives the bounding box layout through an implicit box vector-set diffusion process a task that implicit
diffusion
diffusion models
it first derives the bounding box layout through an implicit box vector-set diffusion process a task that implicit diffusion handles effectively since box tokens contain little geometric detail
assessing scenario coverage is crucial for evaluating the robustness of
autonomous
scenario coverage
assessing scenario coverage is crucial for evaluating the robustness of autonomous agents yet existing methods rely on expensive human annotations or computationally intensive large vision-language models lvlms
the proposed framework uses a simple and effective rejection sampling method to reconstruct these
traces
thinking traces
the proposed framework uses a simple and effective rejection sampling method to reconstruct these traces at scale
additionally the relatively low sensitivity of non-invasive neural measures limits the interpretation of null findings in
studies
surrogate brain
additionally the relatively low sensitivity of non-invasive neural measures limits the interpretation of null findings in studies targeting proper nccs
by having two parties transmit phase encoded weak coherent pulses wcp to an untrusted central node the tf-qkd exploits
single-photon
single photons
by having two parties transmit phase encoded weak coherent pulses wcp to an untrusted central node the tf-qkd exploits single-photon interference to achieve secret key rates scaling as square-root of channel length enabling quantum-secured communication over unprecedented distances
drawing on recent research into the neural basis of visual
awareness
visual stimuli
drawing on recent research into the neural basis of visual awareness we propose that spatial simulation and perceptual experience depend on shared representational geometries captured by higher-order indices of perceptual relations
ofdm is widely adopted in modern wireless communication systems but its
power
transmit power
ofdm is widely adopted in modern wireless communication systems but its power efficiency is limited by high envelope fluctuations
these results clarify when cpa modifies amplitudes versus spectral poles offer practical guidance for data presentation and indicate that cpa alone is not a route to linewidth suppression or polaromechanical
mode
waveguide modes
these results clarify when cpa modifies amplitudes versus spectral poles offer practical guidance for data presentation and indicate that cpa alone is not a route to linewidth suppression or polaromechanical mode splitting in the linear weak-probe regime
while current models show promise it remains an open
question
abstract representations
while current models show promise it remains an open question whether this alignment is superficial or reflects a deeper correspondence in the underlying dimensions of representation
simultaneously strongly aligning with human
visual
vision-language models
simultaneously strongly aligning with human visual attention
to address these limitations we propose securereviewer a new approach designed for enhancing llms ability to identify and resolve security-related
issues
security issues
to address these limitations we propose securereviewer a new approach designed for enhancing llms ability to identify and resolve security-related issues during code review
magnetic phase transitions between ordered phases are often understood on the basis of semi-classical
spin
hidden spin
magnetic phase transitions between ordered phases are often understood on the basis of semi-classical spin models
intuitively the answer appears straightforward when a particular mode is both temporally well
confined
coherent control
intuitively the answer appears straightforward when a particular mode is both temporally well confined i
recently researchers have been cautioned against using preliminary tests which aim to detect violations of
parallel
parallel trends
recently researchers have been cautioned against using preliminary tests which aim to detect violations of parallel trends in the pre-treatment period
beyond identifying causal connections an equally important challenge is determining the associated causal influence range cir indicating when
causal
causal effects
beyond identifying causal connections an equally important challenge is determining the associated causal influence range cir indicating when causal influences emerged and for how long they persist
the local gaussian correlation networks among return
tails
local gaussian
the local gaussian correlation networks among return tails in the chinese stock market
focusing on simpler statistical methods we examine the design-based properties of regression-based methods for estimating treatment effects in
time-series
time-series experiments
focusing on simpler statistical methods we examine the design-based properties of regression-based methods for estimating treatment effects in time-series experiments
enabling continual learning in llms remains a
key
federated learning
enabling continual learning in llms remains a key unresolved research challenge
in this paper we systematically evaluate llms
reasoning
llm agents
in this paper we systematically evaluate llms reasoning capabilities in the normative domain from both logical and modal perspectives
this paper develops a unified framework for identifying
spatial
treatment effect
this paper develops a unified framework for identifying spatial and temporal boundaries of treatment effects in difference-in-differences designs
we find that most of the stars in our bulges are formed in-situ but 33 of our
bulges
bulge stars
we find that most of the stars in our bulges are formed in-situ but 33 of our bulges show a non-negligible contribution of stellar accretion from satellites which could add to about 35 of the population
we believe the most compelling evidence arises when the model itself
freely
extensive experiments
we believe the most compelling evidence arises when the model itself freely reproduces the target content
differentially private two-stage gradient descent for
instrumental
instrumental variable
differentially private two-stage gradient descent for instrumental variable regression
time division duplexing tdd has become the dominant duplexing mode in 5g and beyond due to its ability to exploit channel reciprocity for efficient downlink
channel
channel estimation
time division duplexing tdd has become the dominant duplexing mode in 5g and beyond due to its ability to exploit channel reciprocity for efficient downlink channel state information csi acquisition
we determine the asymptotic type distribution observed in a single host in the limit of large host and virus
populations
population size
we determine the asymptotic type distribution observed in a single host in the limit of large host and virus populations under asymptotic rate assumptions by tracing back the ancestry of the sample
certification and classification of linear quantum
error
quantum coherence
certification and classification of linear quantum error mitigation methods
angular steering generalizes existing addition and orthogonalization techniques under a unified
geometric
angular steering
angular steering generalizes existing addition and orthogonalization techniques under a unified geometric rotation framework simplifying parameter selection and maintaining model stability across a broader range of adjustments
star quasiconvexity an unified approach for linear
convergence
convergence guarantees
star quasiconvexity an unified approach for linear convergence of first-order methods beyond convexity
this paper proposes a novel paradigm for machine
learning
machine learning
this paper proposes a novel paradigm for machine learning that moves beyond traditional parameter optimization
in retrospect k -errata trees appear very well optimized even though a large body of work has adapted k -errata
trees
-errata trees
in retrospect k -errata trees appear very well optimized even though a large body of work has adapted k -errata trees to various settings throughout the past two decades the original time-space trade-off for k -mismatch indexing has not been improved in the general case
in particular k -errata trees yield an elegant solution to k -mismatch queries where we are to report all substrings of the text with hamming distance at most k to the
query
-errata trees
in particular k -errata trees yield an elegant solution to k -mismatch queries where we are to report all substrings of the text with hamming distance at most k to the query pattern
optimal bidding and coordinated dispatch of hybrid
energy
optimal power
optimal bidding and coordinated dispatch of hybrid energy systems in regulation markets
the local convergence of such optimization algorithms on functions that have lipschitz continuous
p
local convergence
the local convergence of such optimization algorithms on functions that have lipschitz continuous p th derivatives and are uniformly convex of order q has been studied by doikov and nesterov math
we investigate the chemical content of 22 well-studied massive protostars from the sofia massive soma star formation survey aiming to identify correlations between
chemical
stellar mass
we investigate the chemical content of 22 well-studied massive protostars from the sofia massive soma star formation survey aiming to identify correlations between chemical and physical parameters
our findings suggest that multilingual data when balanced appropriately can enhance language model
capabilities
vision-language models
our findings suggest that multilingual data when balanced appropriately can enhance language model capabilities without compromising performance even in low-resource settings
outdated channel state information or as is particularly relevant for satellite channels when position
estimates
channel state
outdated channel state information or as is particularly relevant for satellite channels when position estimates are erroneous
semantic representations emerge in biologically inspired ensembles of
cross-supervising
neural networks
semantic representations emerge in biologically inspired ensembles of cross-supervising neural networks
metric entropy and minimax risk of ellipsoids with an
application
minimax risk
metric entropy and minimax risk of ellipsoids with an application to pinsker s theorem
combined with lightweight classifiers and a pipelined
readout
qubit readout
combined with lightweight classifiers and a pipelined readout design our approach both reduces logical error rate by up to 35x and overall qec cycle time up to 1
this dataset serves two key purposes 1 enabling robust training of deep learning models on extensive heterogeneous data and 2 facilitating rigorous evaluation of model generalization for
ct
image reconstruction
this dataset serves two key purposes 1 enabling robust training of deep learning models on extensive heterogeneous data and 2 facilitating rigorous evaluation of model generalization for ct reconstruction
samples were subjected to varied thermal and vibrational conditions and their crystallization onset and morphological evolution were examined through optical microscopy scanning electron microscopy sem energy dispersive x-ray spectroscopy eds and atomic force
microscopy
atomic force microscopy
samples were subjected to varied thermal and vibrational conditions and their crystallization onset and morphological evolution were examined through optical microscopy scanning electron microscopy sem energy dispersive x-ray spectroscopy eds and atomic force microscopy afm
we hope our results show the potential of looplm as a novel
scaling
mathematical reasoning
we hope our results show the potential of looplm as a novel scaling direction in the reasoning era
we further show that abstention is a versatile tool with direct applications to other core problems in policy learning it yields improved guarantees under margin conditions without the common realizability assumption connects to distributionally robust policy learning by hedging against small data shifts and supports s...
policy
policy learning
we further show that abstention is a versatile tool with direct applications to other core problems in policy learning it yields improved guarantees under margin conditions without the common realizability assumption connects to distributionally robust policy learning by hedging against small data shifts and supports s...
in this study we investigate the wavelength dependence of the self-diffracted signal generated by a femtosecond pulsed laser in a dye solution to directly evaluate the electronic third-order
nonlinear
nonlinear optical
in this study we investigate the wavelength dependence of the self-diffracted signal generated by a femtosecond pulsed laser in a dye solution to directly evaluate the electronic third-order nonlinear susceptibility spectrum
accurate and timely travel information is an asset for enhancing passenger travel experience during normal
traffic
traffic dynamics
accurate and timely travel information is an asset for enhancing passenger travel experience during normal traffic and for mitigating the discomforts during disruptions
we present a theoretical framework for quantum-coherent nonlinear interferometry in which the
nonlinear
quantum dot
we present a theoretical framework for quantum-coherent nonlinear interferometry in which the nonlinear medium is modeled as active electron-phonon quantum systems rather than a passive chi 2 converter
while many studies rely on branch length information the topology of
phylogenetic
phylogenetic diversity
while many studies rely on branch length information the topology of phylogenetic trees particularly their degree of imbalance offers a robust framework for inferring evolutionary dynamics when timing data is uncertain
finding a computational model has proven elusive particularly because of conflation of consciousness with other cognitive capabilities exhibited by humans such as
intelligence
artificial intelligence
finding a computational model has proven elusive particularly because of conflation of consciousness with other cognitive capabilities exhibited by humans such as intelligence and physiological sensations
ultimately we analyze cutting-edge detection methodologies ranging from 2d and 3d pipelines to hybrid sensor fusion with particular attention to emerging transformer-driven approaches powered by vision transformers vits large and small
language
vision-language models vlms
ultimately we analyze cutting-edge detection methodologies ranging from 2d and 3d pipelines to hybrid sensor fusion with particular attention to emerging transformer-driven approaches powered by vision transformers vits large and small language models slms and vlms