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we propose to combine the reconstruction loss with
training
image fusion
we propose to combine the reconstruction loss with training for dynamic correspondence along with a visibility head and fine-tuning mast3r for point tracking using a relatively small amount of synthetic data
these findings show that transferring proprioceptive experiences into
working
brain activity
these findings show that transferring proprioceptive experiences into working memory introduces systematic temporal and structural distortions
the main objective is to study the interactions of large
systems
complex systems
the main objective is to study the interactions of large systems of living entities mathematically
these findings underscore a key role for confidence in interactions with
genai
ai use
these findings underscore a key role for confidence in interactions with genai shaped by both prior beliefs about oneself and the reliability of ai and context-dependent exposure to advice
dynamic beamforming and power allocation in isac via deep
reinforcement
reinforcement learning
dynamic beamforming and power allocation in isac via deep reinforcement learning
in this paper our goal is to evaluate this efficiency in the case of the maximum
likelihood
maximum likelihood
in this paper our goal is to evaluate this efficiency in the case of the maximum likelihood estimator mle when the noise distribution belongs to a scale family
we demonstrate the capabilities of this laser-arpes system by investigating several prototypical materials showcasing its potential for elucidating
complex
optical properties
we demonstrate the capabilities of this laser-arpes system by investigating several prototypical materials showcasing its potential for elucidating complex phenomena in quantum materials
to address this imbalance we present lifesync-games a framework leveraging simplified digital twins to connect
virtual
physical virtual
to address this imbalance we present lifesync-games a framework leveraging simplified digital twins to connect virtual gameplay with real-life activities
this unified framework naturally reproduces the observed evolution of luminosity the core mass
function
massive stars
this unified framework naturally reproduces the observed evolution of luminosity the core mass function the mass growth of the most massive protostars and the dense gas star formation law on clump scales establishing a coherent picture of accelerating star formation across scales
while optical flow a computer vision technique for estimating pixel wise
motion
optical flow
while optical flow a computer vision technique for estimating pixel wise motion between consecutive images has advanced rapidly in computer vision its applicability to geophysical problems and to satellite sar imagery remains underexplored
however when a food web representing predator-prey relationships is given finding a set of species that optimizes
phylogenetic
phylogenetic diversity
however when a food web representing predator-prey relationships is given finding a set of species that optimizes phylogenetic diversity subject to the condition that each saved species should be able to find food among the preserved species is np-hard spillner et al
as an alternative to established hole-based photonic crystal cavities we introduce corrugated triangular dinosaur
photonic
photonic devices
as an alternative to established hole-based photonic crystal cavities we introduce corrugated triangular dinosaur photonic crystal cavities and develop a tapered quasi loss-free cavity-waveguide interface to adiabatically interconvert bloch and waveguide modes
coal-fired power plants demonstrates strong exponential spatial
decay
spatial decay
coal-fired power plants demonstrates strong exponential spatial decay kappa_s 0
our work significantly extends the existing results on the
convergence
gradient descent
our work significantly extends the existing results on the convergence of gd and sgd by guaranteeing that they apply to practical neural network settings and has the potential to unlock further exploration of learning dynamics
our analysis loosely favours local starburst
activity
star-forming region
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
in this article we present the derivation of the theoretical foundations for cooperative task spaces of multi-arm robotic systems based on geometric primitives defined using conformal
geometric
geometric primitives
in this article we present the derivation of the theoretical foundations for cooperative task spaces of multi-arm robotic systems based on geometric primitives defined using conformal geometric algebra
aiming for biological plausibility each network has a small
receptive
receptive fields
aiming for biological plausibility each network has a small receptive field thus receiving a fixed part of the external input and the networks do not share weights
we devise a new tree embedding construction framework that operates on an arbitrary metric decomposition with bounded diameter offering a tradeoff between
distortion
spanning trees
we devise a new tree embedding construction framework that operates on an arbitrary metric decomposition with bounded diameter offering a tradeoff between distortion and the locality of its algorithmic steps
while interventional data require direct perturbations of variables interventional constraints encode high-level causal knowledge in the form of inequality constraints on
causal
interventional constraints
while interventional data require direct perturbations of variables interventional constraints encode high-level causal knowledge in the form of inequality constraints on causal effects
we address this gap by directly investigating what must fail for
inconsistency
theoretical guarantees
we address this gap by directly investigating what must fail for inconsistency to arise aiming to identify a substantive necessary condition for hellinger inconsistency
this hybrid approach enhances both sampling and entanglement
efficiency
quantum coherence
this hybrid approach enhances both sampling and entanglement efficiency enabling more resource-practical implementations of distributed quantum computation
monte carlo simulations demonstrate that our approach exhibits excellent finite sample performance for both oos prediction and
policy
policy optimization
monte carlo simulations demonstrate that our approach exhibits excellent finite sample performance for both oos prediction and policy evaluation
we evaluate the model in simulation with up to 14 qubits on sentiment analysis mnist permuted mnist copying
memory
memory effects
we evaluate the model in simulation with up to 14 qubits on sentiment analysis mnist permuted mnist copying memory and language modeling adopting projective measurements as a limiting case to obtain mid-circuit readouts while maintaining a coherent recurrent quantum memory
focusing on scientific topics at the secondary education level we explore the potential of large
language
large language
focusing on scientific topics at the secondary education level we explore the potential of large language models to generate chains of hints that scaffold learners without revealing answers
these results highlight the substantial room for improvement and underscore the
challenges
llm raters
these results highlight the substantial room for improvement and underscore the challenges of applying llms in education
because observational inputs may be biased in ways unknown ex ante we develop a minimax proportional regret
objective
policy optimization
because observational inputs may be biased in ways unknown ex ante we develop a minimax proportional regret objective that evaluates any candidate design relative to an oracle that knows the bias and jointly chooses the design and estimator
we find that the gaussian beams gouy phase not only plays a crucial role in the interaction but also enables straight-forward generation of valuable free-electron states including comb-shape spectra with similar amplitudes and
states
quantum dot
we find that the gaussian beams gouy phase not only plays a crucial role in the interaction but also enables straight-forward generation of valuable free-electron states including comb-shape spectra with similar amplitudes and states with high degree of coherence
this paper explores the implementation of intelligent robotic manipulating agents based on
vision-language
vision-language models
this paper explores the implementation of intelligent robotic manipulating agents based on vision-language models vlms in the physical world
interestingly we reveal that the beam pattern not only captures the receiver s location
information
channel estimation
interestingly we reveal that the beam pattern not only captures the receiver s location information but also implicitly encodes the spatial relationship between the receiver and obstacle which facilitates identifying the optimal airy beam configuration
early-assembling high-concentration halos form
stars
star-forming region
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 find a relation between narrower degree distributions and longer loops in investigating the lengths of the shortest loops in various networks with continuously changing
degree
scale-free networks
we find a relation between narrower degree distributions and longer loops in investigating the lengths of the shortest loops in various networks with continuously changing degree distributions including three typical types of realistic scale-free networks classical erd os-r enyi random graphs and regular networks
experimental conditions replicate the informational and
social
social media
experimental conditions replicate the informational and social mobilization treatments of the original facebook study
we propose a taxonomy of data-efficient llm post-training methods covering data selection data quality enhancement
synthetic
synthetic data
we propose a taxonomy of data-efficient llm post-training methods covering data selection data quality enhancement synthetic data generation data distillation and compression and self-evolving data ecosystems
our experiments show that current video large
language
large language
our experiments show that current video large language model video-llm architectures have critical limitations in temporal understanding struggling with tasks that require detailed comprehension of action sequences and temporal progression
through iterative decomposition of the problem into tractable subgoals selection of appropriate analytical methods and validation of intermediate results we reveal how
human
mathematical reasoning
through iterative decomposition of the problem into tractable subgoals selection of appropriate analytical methods and validation of intermediate results we reveal how human intuition and machine computation can complement one another
with the increasing integration of intelligent
driving
autonomous driving
with the increasing integration of intelligent driving functions into serial-produced vehicles ensuring their functionality and robustness poses greater challenges
this is an exponential improvement over previous results and only a polylogarithmic factor away from the
lower
upper bound
this is an exponential improvement over previous results and only a polylogarithmic factor away from the lower bound
incorporating causal knowledge and mechanisms is essential for refining
causal
treatment effect
incorporating causal knowledge and mechanisms is essential for refining causal models and improving downstream tasks such as designing new treatments
for the variant condition we enforce a robust decrease over a parameterized
disturbance
disturbance observer
for the variant condition we enforce a robust decrease over a parameterized disturbance ball with nonzero probability and encode the constraints via an s-procedure with polynomial multipliers
instead the model must have somehow synthesized its own geometry of atomic facts
encoding
world models
instead the model must have somehow synthesized its own geometry of atomic facts encoding global relationships between all entities including non-co-occurring ones
we introduce multicolleagues a multi-agent conversational system that shows how ai
agents
ai systems
we introduce multicolleagues a multi-agent conversational system that shows how ai agents can act as colleagues by conversing with each other sharing new ideas and actively involving users in collaborative ideation
in this setting stochastic gradient descent
sgd
gradient descent
in this setting stochastic gradient descent sgd based solvers have demonstrated strong empirical performance in recent machine learning applications yet their theoretical guarantee to approximate the ot map is an open question
trainium an ai accelerator recently developed by amazon web services aws provides an attractive option for llm training and
inference
models llms
trainium an ai accelerator recently developed by amazon web services aws provides an attractive option for llm training and inference through its heterogeneous architecture
in this work we study data-driven stabilization of linear time-invariant systems using
prior
predictive control
in this work we study data-driven stabilization of linear time-invariant systems using prior knowledge of system-theoretic properties specifically stabilizability and controllability
hard xray photoemission spectroscoy haxpes was used to
analyze
photoemission spectroscopy
hard xray photoemission spectroscoy haxpes was used to analyze the composition and distribution of cobalt and neodymium at the top layers region of ndco _ 4
generate with low randomness and adjusts its predicted temperature and top-p on a token-by-token basis opening a new paradigm for steerable and interactive
llm
models llms
generate with low randomness and adjusts its predicted temperature and top-p on a token-by-token basis opening a new paradigm for steerable and interactive llm decoding
the recent advancement of multimodal large
language
large language
the recent advancement of multimodal large language models mllms is transforming human-computer interaction hci from surface-level exchanges into more nuanced and emotionally intelligent communication
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
galactic disk
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
in the single-user scenario it is proved that the optimal
pinching
pinching antenna
in the single-user scenario it is proved that the optimal pinching antenna pa positions are independent of the transmit beamforming
we use the full-disk vlt-muse mosaic of ngc 253 to identify 2492 hii regions and study their
resolved
star-forming region
we use the full-disk vlt-muse mosaic of ngc 253 to identify 2492 hii regions and study their resolved structure
instrumental variable methods are fundamental to
causal
treatment effect boundaries
instrumental variable methods are fundamental to causal inference when treatment assignment is confounded by unobserved variables
our numerical results show that our regularized one-step approach is the most robust in terms of noise and
experimental
numerical simulations
our numerical results show that our regularized one-step approach is the most robust in terms of noise and experimental setup
wod-e2e waymo open dataset for end-to-end
driving
autonomous driving
wod-e2e waymo open dataset for end-to-end driving in challenging long-tail scenarios
taken together our study revealed a novel difference of functional property in response to task performance in the
sensorimotor
working memory
taken together our study revealed a novel difference of functional property in response to task performance in the sensorimotor areas versus the association areas
our results demonstrate that roboos-next achieves superior performance across heterogeneous embodiments validating its effectiveness in enabling lifelong scalable and robust
multi-robot
multi-robot collaboration
our results demonstrate that roboos-next achieves superior performance across heterogeneous embodiments validating its effectiveness in enabling lifelong scalable and robust multi-robot collaboration
moreover adapting existing code review approaches to target security
issues
code review
moreover adapting existing code review approaches to target security issues faces substantial challenges including data scarcity and inadequate evaluation metrics
however most existing isac designs prioritize
sensing
communication isac
however most existing isac designs prioritize sensing accuracy and communication throughput treating all targets uniformly and overlooking the impact of critical obstacles on motion efficiency
this evaluation is the first step to demonstrate the accuracy and efficiency of time series classification algorithms for
anomaly
anomaly detection
this evaluation is the first step to demonstrate the accuracy and efficiency of time series classification algorithms for anomaly detection and represents a strong baseline that can then be used to guide the model selection step in general automl pipelines
an understanding of the assembly history of the complex star cluster omega centauri has long been sought after with many studies separating the
stars
stellar mass
an understanding of the assembly history of the complex star cluster omega centauri has long been sought after with many studies separating the stars on the color-magnitude diagram into multiple groupings across small magnitude ranges
these results have implications for amplified oversight -- the challenge of combining humans and ai to supervise
ai
artificial intelligence
these results have implications for amplified oversight -- the challenge of combining humans and ai to supervise ai systems even as they surpass human expert performance
through source analyses localized to anterior- and posterior cingulate cortex acc pcc we found that pcc alpha activity showed heightened sensitivity to
disruptions
sensorimotor disruptions
through source analyses localized to anterior- and posterior cingulate cortex acc pcc we found that pcc alpha activity showed heightened sensitivity to disruptions exclusively in visuo-haptic immersion
we present a systematic analysis of estimation errors for a class of optimal
transport
optimal transport
we present a systematic analysis of estimation errors for a class of optimal transport based algorithms for filtering and data assimilation
minimax robust method of estimation is applied in the case where the spectral densities are not known exactly while some sets of admissible spectral
densities
maximum likelihood
minimax robust method of estimation is applied in the case where the spectral densities are not known exactly while some sets of admissible spectral densities are given
we show that ecological interactions between parents and mutants result in frequency-dependent
selection
population genetics
we show that ecological interactions between parents and mutants result in frequency-dependent selection and can be characterized by a single emergent parameter that measures the strength of ecological feedbacks
our findings reveal that while current video models demonstrate promising reasoning patterns on short-horizon spatial coherence fine-grained grounding and locally consistent dynamics they remain limited in long-horizon causal
reasoning
spatial reasoning
our findings reveal that while current video models demonstrate promising reasoning patterns on short-horizon spatial coherence fine-grained grounding and locally consistent dynamics they remain limited in long-horizon causal reasoning strict geometric constraints and abstract logic
understanding how creativity is represented in the brain s intrinsic functional architecture remains a central challenge in
cognitive
human cognition
understanding how creativity is represented in the brain s intrinsic functional architecture remains a central challenge in cognitive neuroscience
a shared step across different trajectories receives the same
reward
reward density
a shared step across different trajectories receives the same reward while different steps under the same fork receive different rewards
the functionality of the proposed deep network is assessed on the two
different
deep network
the functionality of the proposed deep network is assessed on the two different databases
in this work we propose missynth a pipeline that applies retrieval-augmented generation rag to produce synthetic fallacy samples which are then used to fine-tune an
llm
models llms
in this work we propose missynth a pipeline that applies retrieval-augmented generation rag to produce synthetic fallacy samples which are then used to fine-tune an llm model
along the way we present an online algorithm for 1 varepsilon -hypergraph sparsification which is
optimal
mathrm polylog
along the way we present an online algorithm for 1 varepsilon -hypergraph sparsification which is optimal up to poly-logarithmic factors
as a by-product we get the first deterministic
poly
time complexity
as a by-product we get the first deterministic poly n log lambda -time algorithm requiring no common knowledge to gather any team when all labels are distinct
we present a quantum-enhanced protocol for detecting wave-like dark matter using an array of
n
quantum algorithm
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
we introduce human ai collaborative uncertainty
quantification
human-machine teaming
we introduce human ai collaborative uncertainty quantification a framework that formalizes how an ai model can refine a human expert s proposed prediction set with two goals avoiding counterfactual harm ensuring the ai does not degrade correct human judgments and complementarity enabling recovery of correct outcomes th...
while humans intuitively perform this translation based on common sense and embodied understanding whether large
language
large language
while humans intuitively perform this translation based on common sense and embodied understanding whether large language models llms can effectively replicate this ability remains underexplored
source code will be publicly available at
https
publicly available
source code will be publicly available at https github
the core challenge arises from the complex coupling between communication sinr requirements and
sensing
integrated sensing
the core challenge arises from the complex coupling between communication sinr requirements and sensing performance metrics
in contrast the plug-in approach is based on regression where one first estimates the conditional average treatment effect cate and then recommends the
treatment
average treatment effect
in contrast the plug-in approach is based on regression where one first estimates the conditional average treatment effect cate and then recommends the treatment with the highest estimated outcome
with the rapid development of large language models llms various llm-based works have been
widely
large language
with the rapid development of large language models llms various llm-based works have been widely applied in educational fields
we obtain three main results a a conceptually simple tilde o nk -time algorithm for pmwed very different from that of landau and vishkin for pmed b a significantly more complicated
tilde
-time algorithm
we obtain three main results a a conceptually simple tilde o nk -time algorithm for pmwed very different from that of landau and vishkin for pmed b a significantly more complicated tilde o n k 3
a quadratic speedup of the quantum adiabatic
algorithm
quantum walk
a quadratic speedup of the quantum adiabatic algorithm qaa for finding independent sets iss in a graph is proven analytically
data-driven exponential framing for pulsive temporal
patterns
temporal patterns
data-driven exponential framing for pulsive temporal patterns without repetition or singularity
from the perspective of dynamical systems theory visual
rivalry
visual rivalry
from the perspective of dynamical systems theory visual rivalry offers an experimentally tractable window into the dynamical mechanisms governing perceptual awareness
in this work we introduce a general form of a two-parameter family of local
interactions
quantum mechanics
in this work we introduce a general form of a two-parameter family of local interactions between quantum walkers conditioned on the internal state of their coins
this paper provides bode-like sensitivity integrals for the quasiperiodic
disturbance
bounded disturbances
this paper provides bode-like sensitivity integrals for the quasiperiodic disturbance observer in both continuous-time and discrete-time representations and clarifies the avoided sensitivity tradeoff with time delays
we show that the dynamical systems are mathematically equivalent under a compensatory external input which depends on the adaptation strength leading to a shift in state space of the otherwise
equivalent
dynamical systems
we show that the dynamical systems are mathematically equivalent under a compensatory external input which depends on the adaptation strength leading to a shift in state space of the otherwise equivalent bifurcation structure
quantum batteries qbs exploit collective quantum
resources
quantum advantage
quantum batteries qbs exploit collective quantum resources to surpass the limits of classical energy storage and power delivery
group based reinforcement learning rl has shown impressive results on complex
reasoning
reinforcement learning
group based reinforcement learning rl has shown impressive results on complex reasoning and mathematical tasks
these results highlight that explicitly modeling environmental structure is a robust generalizable strategy for advancing
llm
llm agents
these results highlight that explicitly modeling environmental structure is a robust generalizable strategy for advancing llm agent training
we finally provide numerical evidence for our
theoretical
theoretical findings
we finally provide numerical evidence for our theoretical results
to capture the long-term dependency and complex dynamics of
eeg
electroencephalography eeg
to capture the long-term dependency and complex dynamics of eeg we propose a hybrid encoder combining a mamba-like linear attention channel encoder and a spatiotemporal dynamics model
the model is based on mechanisms of fast and flat depth-limited goal-directed probabilistic simulation--analogous to those used in monte carlo tree-search models of expert game-play but scaled down to use very few stochastic samples simple goal heuristics for evaluating
actions
reinforcement learning
the model is based on mechanisms of fast and flat depth-limited goal-directed probabilistic simulation--analogous to those used in monte carlo tree-search models of expert game-play but scaled down to use very few stochastic samples simple goal heuristics for evaluating actions and no deep search
using this framework we prove that many successful combinatorial kernels are either related or equivalent to heat
kernels
heat kernels
using this framework we prove that many successful combinatorial kernels are either related or equivalent to heat kernels and validate this theoretical claim in our experiments
the resulting bilinearities are handled by an alternating scheme that
alternates
bilevel optimization
the resulting bilinearities are handled by an alternating scheme that alternates between optimizing multipliers and updating the variant and radius until a positive slack is obtained
6d channel knowledge map construction via bidirectional
wireless
channel estimation
6d channel knowledge map construction via bidirectional wireless gaussian splatting
with reinforcement learning agents and a curriculum learning approach the trained agent may be a stepping stone towards application of reinforcement
learning
learning agents
with reinforcement learning agents and a curriculum learning approach the trained agent may be a stepping stone towards application of reinforcement learning agents in automation of the forestry forwarder
the incorporation of mn repositions the flat bands relative to the
fermi
fermi level
the incorporation of mn repositions the flat bands relative to the fermi level in a manner consistent with hole-doping as revealed by hard x-ray photoemission and density functional theory
the considered scenarios cover both single satellite and cooperative multi-satellite beamforming using either global or local
channel
channel state information
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
self-localization based on a camera often uses a
convolutional
convolutional neural
self-localization based on a camera often uses a convolutional neural network cnn that can extract local features that are calculated by nearby pixels
using this framework we conduct a comprehensive evaluation of nine representative lvg models finding that while current methods
perform
models vlms
using this framework we conduct a comprehensive evaluation of nine representative lvg models finding that while current methods perform well on basic visual and temporal aspects they struggle with inter-event consistency fine-grained alignment and high-level thematic adherence etc
01 pc and follow the gas inflows from the interstellar medium ism to the black hole
bh
black hole
01 pc and follow the gas inflows from the interstellar medium ism to the black hole bh allowing for the self-consistent emergence of circumnuclear discs cnds