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to illustrate this we construct a class of structured datasets where incremental
adam
deep learning
to illustrate this we construct a class of structured datasets where incremental adam provably converges to the ell_2 -max-margin classifier in contrast to the ell_ infty -max-margin bias of full-batch adam
while ai-assisted participants completed several tasks
faster
task performance
while ai-assisted participants completed several tasks faster and more accurately no significant pre-post differences emerged in standardized measures of problem solving or verbal comprehension
diffusion models for wireless transceivers from pilot-efficient
channel
channel estimation
diffusion models for wireless transceivers from pilot-efficient channel estimation to ai-native 6g receivers
we also explore alternatives including the shooting method and linearization with the iterative
linear
linear control
we also explore alternatives including the shooting method and linearization with the iterative linear quadratic regulator ilqr
to generate physically and semantically plausible supervision signals we introduce a spatial prior labeling method that guides a
vision-language
vision-language models
to generate physically and semantically plausible supervision signals we introduce a spatial prior labeling method that guides a vision-language model to produce reasonable manipulation orders for distillation
few-shot examples substantially improve performance indicating potential for targeted enhancement of llms
vr
virtual reality
few-shot examples substantially improve performance indicating potential for targeted enhancement of llms vr manipulation capabilities
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
uplink 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
this energy is believed to impact the star formation activity and contribute to the
quenching
quiescent galaxies
this energy is believed to impact the star formation activity and contribute to the quenching of galaxies
approximately 80 of the emission of a region
originates
emission line
approximately 80 of the emission of a region originates from the halo component
these findings suggest that resting-state
eeg
electroencephalography eeg
these findings suggest that resting-state eeg connectivity patterns can index stable cognitive traits such as creativity
we experimentally demonstrate vortex beams spanning eight oam orders from -3 to 4 and achieve selective excitation of distinct
topological
vortex phase
we experimentally demonstrate vortex beams spanning eight oam orders from -3 to 4 and achieve selective excitation of distinct topological charges at a fixed telecommunication wavelength by tuning the interlayer separation and twist angle
existing vision-language navigation vln approaches are mostly designed for ground robots and struggle to generalize to aerial tasks that require full 3d
spatial
vision-language-action vla
existing vision-language navigation vln approaches are mostly designed for ground robots and struggle to generalize to aerial tasks that require full 3d spatial reasoning
this formulation leads to a point to set type of optimization problem which relaxes the requirement on
controllability
control systems
this formulation leads to a point to set type of optimization problem which relaxes the requirement on controllability of the system compared to the classic lap framework
self-localization on a 3d map by fusing global and local features from a
monocular
point tracking
self-localization on a 3d map by fusing global and local features from a monocular camera
furthermore real-world experiments confirm that the
robot
robotic systems
furthermore real-world experiments confirm that the robot can safely pass through narrow passages while maintaining rapid planning performance
results show that unlike all other computational processes
consciousness
cognitive science
results show that unlike all other computational processes consciousness is not independent of its substrate and possessing it is an evolutionary advantage for intelligent entities
validated in high-fidelity simulation with realistic quadrotor dynamics the resulting policies significantly outperform both a standard reinforcement
learning
multi-drone racing
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
these discoveries were heavily driven by migdal- e liashberg theory and its first-principles computational implementations for electron-phonon
interactions
quantum materials
these discoveries were heavily driven by migdal- e liashberg theory and its first-principles computational implementations for electron-phonon interactions the key concept of phonon-mediated superconductivity
82 10 8 m _ sun kpc -2 - values close to those of nearby
quiescent
stellar population
82 10 8 m _ sun kpc -2 - values close to those of nearby quiescent galaxies
we present a unified field-theoretic framework for the dynamics of activity and
connectivity
functional connectivity
we present a unified field-theoretic framework for the dynamics of activity and connectivity in interacting neuronal systems
dissecting the mass quenching in tng50 galaxy size determines the
quenching
host galaxy
dissecting the mass quenching in tng50 galaxy size determines the quenching mode
our study addresses the challenges inherent in calculating mixed fermion-boson systems and explores the potential of quantum
computing
quantum error correction
our study addresses the challenges inherent in calculating mixed fermion-boson systems and explores the potential of quantum computing to advance their analysis
finally we relate our approach to the information bottleneck one and we exhibit a
bias-variance
fisher information
finally we relate our approach to the information bottleneck one and we exhibit a bias-variance decomposition of the bayes cost of interest on its own
magnetic phase transitions between ordered phases are often understood on the basis of semi-classical
spin
magnetic anisotropy
magnetic phase transitions between ordered phases are often understood on the basis of semi-classical spin models
together these results suggest that nearly all correlations are not needed to predict neural activity and we provide the tools to uncover the key
correlations
predictive processing
together these results suggest that nearly all correlations are not needed to predict neural activity and we provide the tools to uncover the key correlations that are
the core of fm agent integrates several key innovations 1 a cold-start initialization phase incorporating expert guidance 2 a novel
evolutionary
fm agent
the core of fm agent integrates several key innovations 1 a cold-start initialization phase incorporating expert guidance 2 a novel evolutionary sampling strategy for iterative optimization 3 domain-specific evaluators that combine correctness effectiveness and llm-supervised feedback and 4 a distributed asynchronous e...
simulation of the time-dynamics of fermionic
many-body
quantum mechanics
simulation of the time-dynamics of fermionic many-body systems has long been predicted to be one of the key applications of quantum computers
text prompt is the most common way for human-generative ai
genai
ai use
text prompt is the most common way for human-generative ai genai communication
we validate the properties of our estimators and showcase their broad
applicability
ate estimation
we validate the properties of our estimators and showcase their broad applicability through an extensive simulation study
furthermore as long as the degree delta is not very small namely as long as
delta
poly log
furthermore as long as the degree delta is not very small namely as long as delta geq text poly 1 epsilon this dependence is only logarithmic in 1 epsilon
chemical separation of stellar populations analytic solutions for
chemical
stellar mass
chemical separation of stellar populations analytic solutions for chemical evolution models with metallicity-dependent yields
in addition to detailing the system we also share the empirical
mode
waveguide modes
in addition to detailing the system we also share the empirical mode transfer matrices enabling future work in astrophotonic design computational imaging device fabrication feedback loops and beam shaping
we introduce rlmeval an evaluation suite for these tasks focusing on research-level mathematics from
real-world
evaluation metrics
we introduce rlmeval an evaluation suite for these tasks focusing on research-level mathematics from real-world lean formalization projects
as an example of applications we solve a class of wasserstein and sinkhorn dro problems using the recently-discovered
wasserstein
gromov-wasserstein distance
as an example of applications we solve a class of wasserstein and sinkhorn dro problems using the recently-discovered wasserstein fisher-rao and stein variational gradient flows
the key message in the current work is how high temperatures sim10 11
k
heat conduction
the key message in the current work is how high temperatures sim10 11 k pop out as essential
posterior sampling provides an accurate and fair framework for tasks such as inpainting deblurring and mri reconstruction and several heuristics attempt to
approximate
approximate posterior
posterior sampling provides an accurate and fair framework for tasks such as inpainting deblurring and mri reconstruction and several heuristics attempt to approximate it
local overidentification and efficiency gains in modern
causal
causal effects
local overidentification and efficiency gains in modern causal inference and data combination
an understanding of the assembly history of the complex star cluster omega centauri has long been sought after with many studies separating the
stars
star formation
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
by incorporating a novel two-stage inference workflow the benchmark can further evaluate
vlms
models vlms
by incorporating a novel two-stage inference workflow the benchmark can further evaluate vlms capability to align and compare elements attributes across two charts
specifically braincognizer introduces two modules the cognitive integration module which incorporates prior human knowledge to extract hierarchical region semantics and the
cognitive
brain decoding
specifically braincognizer introduces two modules the cognitive integration module which incorporates prior human knowledge to extract hierarchical region semantics and the cognitive correlation module which captures contextual semantic relationships across regions
graph approach for observability analysis in
power
power systems
graph approach for observability analysis in power system dynamic state estimation
the benchmark and analysis expose critical limitations in current llm capabilities for class-level engineering offering actionable insights for enhancing
context
context engineering
the benchmark and analysis expose critical limitations in current llm capabilities for class-level engineering offering actionable insights for enhancing context modelling documentation strategies and retrieval integration in production code assistance tools
an event study around covid-19 reveals that
network
network fragility
an event study around covid-19 reveals that network fragility increased 24
a prevailing theory in cognitive neuroscience proposes that the human brain operates through hierarchical predictive processing which underlies flexible
cognition
cognitive neuroscience
a prevailing theory in cognitive neuroscience proposes that the human brain operates through hierarchical predictive processing which underlies flexible cognition and behavior by integrating multimodal sensory signals
inverse-free quantum state estimation with
heisenberg
super-heisenberg scaling
inverse-free quantum state estimation with heisenberg scaling
through a comprehensive evaluation across various configurations we demonstrate that the system effectively performs diacritization without relying on
complex
language agents
through a comprehensive evaluation across various configurations we demonstrate that the system effectively performs diacritization without relying on complex explicit linguistic analysis
the modelling is based on a susceptible-infected-recovered sir - model and on a susceptible-exposed-infected-recovered seir - model through a kernel that dampens the activity based on the recent history of
infectious
disease transmission
the modelling is based on a susceptible-infected-recovered sir - model and on a susceptible-exposed-infected-recovered seir - model through a kernel that dampens the activity based on the recent history of infectious individuals
we propose reasoning curriculum a simple two-stage
curriculum
mathematical reasoning
we propose reasoning curriculum a simple two-stage curriculum that first elicits reasoning skills in pretraining-aligned domains such as math then adapts and refines these skills across other domains via joint rl
maxvstar maximally adaptive vision-guided csi
sensing
activity recognition
maxvstar maximally adaptive vision-guided csi sensing with closed-loop edge model adaptation for robust human activity recognition
improving human verification of llm reasoning through
interactive
large language models llms
improving human verification of llm reasoning through interactive explanation interfaces
understanding how learning algorithms shape the computational strategies that
emerge
deep learning
understanding how learning algorithms shape the computational strategies that emerge in neural networks remains a fundamental challenge in machine intelligence
the rapid advancement of large language models
llms
vision-language models
the rapid advancement of large language models llms has marked a significant breakthrough in artificial intelligence ai ushering in a new era of human-centered artificial intelligence hai
analyzing parametric oscillator ising machines through the
kuramoto
ising machines
analyzing parametric oscillator ising machines through the kuramoto lens
in this work we present a novel scheme dynamic fragmentation-mac dyfrag-mac that offers
dynamic
heterogeneous traffic
in this work we present a novel scheme dynamic fragmentation-mac dyfrag-mac that offers dynamic differentiated channel access to the traffic of various priorities
the land use-climate change-biodiversity nexus in european
islands
climate change
the land use-climate change-biodiversity nexus in european islands stakeholders
our simulations show that our procedures work well in all cases considered having excellent power versus several types of distributional changes and
appearing
simulation studies
our simulations show that our procedures work well in all cases considered having excellent power versus several types of distributional changes and appearing to be particularly suited to the analysis of multivariate data
in this work we answer it positively by providing both computational and statistical convergence
guarantees
theoretical guarantees
in this work we answer it positively by providing both computational and statistical convergence guarantees of sgd
next we propose a novel training approach that leverages a privileged guiding policy to bootstrap the
learning
learning agents
next we propose a novel training approach that leverages a privileged guiding policy to bootstrap the learning process while still exploiting online environment interactions with the spiking policy
these relationships generalize fisher s fundamental theorem of natural
selection
evolutionary game
these relationships generalize fisher s fundamental theorem of natural selection and also make clear some of its limitation
using network gradients it is possible to identify regions where the
network
deep network
using network gradients it is possible to identify regions where the network pays attention during image recognition tasks
to address these limitations a brain-computer interface bci system is developed using a non-invasive electroencephalogram
eeg
brain activity
to address these limitations a brain-computer interface bci system is developed using a non-invasive electroencephalogram eeg headband focuscalm to record brainwave activity under attentive and non-attentive states
this paper introduces a benchmark combobench evaluating llms capability to translate semantic actions into vr device manipulation sequences across 262 scenarios from four popular
vr
virtual reality
this paper introduces a benchmark combobench evaluating llms capability to translate semantic actions into vr device manipulation sequences across 262 scenarios from four popular vr games half-life alyx into the radius moss book ii and vivecraft
for typical cortical stimuli tens of milliseconds this places the
functional
human cognition
for typical cortical stimuli tens of milliseconds this places the functional plasticity window in the few-second range a testable prediction that identifies seconds-scale eligibility traces as necessary for error-driven learning in biological circuits
while resting-state fmri studies have revealed large-scale network correlates of creative potential electroencephalography
eeg
brain regions
while resting-state fmri studies have revealed large-scale network correlates of creative potential electroencephalography eeg offers a temporally precise and scalable approach to capture the fast oscillatory dynamics that underlie spontaneous neural organization
to solve the formulated problem we proposed a two-timescale multi-agent
deep
deep reinforcement
to solve the formulated problem we proposed a two-timescale multi-agent deep deterministic policy gradient tts-maddpg algorithm based on the centralized training and distributed execution paradigm
leveraging this dataset we fine-tune llms to generate code
review
code review
leveraging this dataset we fine-tune llms to generate code review comments that can effectively identify security issues and provide fix suggestions with our proposed secure-aware fine-tuning strategy
hybrid dqn-td3 reinforcement learning for
autonomous
policy learning
hybrid dqn-td3 reinforcement learning for autonomous navigation in dynamic environments
a logic-based algorithmic meta-theorem for treedepth single exponential fpt time and
polynomial
polynomial time
a logic-based algorithmic meta-theorem for treedepth single exponential fpt time and polynomial space
we introduce behavior-adaptive connectivity estimation bace an end-to-end framework that learns phase-specific directed inter-regional
connectivity
brain regions
we introduce behavior-adaptive connectivity estimation bace an end-to-end framework that learns phase-specific directed inter-regional connectivity directly from multi-region intracranial local field potentials lfp
numerous mitigation methods exist for quantum noise suppression making it challenging to identify the optimum approach for a specific application especially as ongoing advances in hardware tuning and error correction are expected to reduce logical
error
quantum algorithm
numerous mitigation methods exist for quantum noise suppression making it challenging to identify the optimum approach for a specific application especially as ongoing advances in hardware tuning and error correction are expected to reduce logical error rates
fm agent reaches state-of-the-art results autonomously without human interpretation or
tuning
fm agent
fm agent reaches state-of-the-art results autonomously without human interpretation or tuning -- 1976
in previous modeling works based on neuroscience data we show that this expansion
compression
encoding models
in previous modeling works based on neuroscience data we show that this expansion compression is a necessary outcome of efficient learning
overall our study links the structure of stimuli task and learning rule to representational drift and could pave the way for using
drift
continual learning
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
our analysis reveals that while the recency effect directly aligns with short-term memory demand in the training data the primacy effect is induced by the uniform long-term memory
demand
memory demand
our analysis reveals that while the recency effect directly aligns with short-term memory demand in the training data the primacy effect is induced by the uniform long-term memory demand and is additionally influenced by the model s autoregressive properties and the formation of attention sinks
a review of ai-driven approaches for nanoscale heat
conduction
heat conduction
a review of ai-driven approaches for nanoscale heat conduction and radiation
it is shown however that under control gain variation the
safe
optimal control
it is shown however that under control gain variation the safe set of these controllers is locally asymptotically stable which implies that their safety is sensitive to large but bounded disturbances
these accretion-based m_ bullet values which in this sample span nearly three orders of magnitude are consistent with
galactic
active galactic
these accretion-based m_ bullet values which in this sample span nearly three orders of magnitude are consistent with galactic scaling relations but are significantly more precise 68 credible interval pm 0
building on this inpainting core we design a spatiotemporal autoregressive inference pipeline that traverses virtual-camera splines and extends videos with overlapping windows enabling coherent
generation
image fusion
building on this inpainting core we design a spatiotemporal autoregressive inference pipeline that traverses virtual-camera splines and extends videos with overlapping windows enabling coherent generation at bounded per-step complexity
more specifically the study relates to the complex features of living systems and the
mathematical
statistical physics
more specifically the study relates to the complex features of living systems and the mathematical tools inspired by statistical physics
1b and 3b parameter llms on diverse multilingual corpora varying the number of
languages
multilingual data
1b and 3b parameter llms on diverse multilingual corpora varying the number of languages from 25 to 400
augmentation density impacted behavior and reduced awareness of uncommon
objects
object recall
augmentation density impacted behavior and reduced awareness of uncommon objects in the environment
one recurring problem in this task is the weaknesses found in some detectors such as the difficulty in
detecting
spatial reasoning
one recurring problem in this task is the weaknesses found in some detectors such as the difficulty in detecting loose edges and the lack of context to extract relevant information from specific problems
ellipsoidal set-theoretic design of robust
safety
safety filter
ellipsoidal set-theoretic design of robust safety filters for constrained linear systems
our general interaction framework which reduces to several previously studied
models
quantum networks
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
self-localization on a 3d map by using an inexpensive monocular
camera
point tracking
self-localization on a 3d map by using an inexpensive monocular camera is required to realize autonomous driving
for the variant condition we enforce a robust decrease over a parameterized disturbance ball with nonzero probability and encode the
constraints
optimal control
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
the coordination of multiple autonomous agents in high-speed
competitive
multi-drone racing
the coordination of multiple autonomous agents in high-speed competitive environments represents a significant engineering challenge
look at that distractor dynamic translation gain under low perceptual load in
virtual
physical virtual
look at that distractor dynamic translation gain under low perceptual load in virtual reality
identifying treatment effects on categorical
outcomes
categorical outcomes
identifying treatment effects on categorical outcomes in iv models
undirected multicast network coding gaps via
locally
network coding
undirected multicast network coding gaps via locally decodable codes
large language models llms have demonstrated exceptional
capabilities
large language
large language models llms have demonstrated exceptional capabilities across multiple domains by leveraging massive pre-training and curated fine-tuning data
recent causality-based methods address this challenge by learning invariant
causal
causal effects
recent causality-based methods address this challenge by learning invariant causal relationships in the underlying data-generating process
for example existing studies often employ maximum likelihood or covariate
balancing
covariate balancing
for example existing studies often employ maximum likelihood or covariate balancing to estimate e_0 but these approaches may not be optimal for accurately estimating h_0 or the ate
strain engineering is a powerful strategy for controlling the structural and
electronic
electronic structure
strain engineering is a powerful strategy for controlling the structural and electronic properties of two-dimensional materials particularly in systems hosting charge density wave cdw order
this paper explores how we can leverage ai to
improve
ai assistance
this paper explores how we can leverage ai to improve the quality of human oversight
we introduce a general diploid population model with self-fertilization and possible overlapping
generations
population genetics
we introduce a general diploid population model with self-fertilization and possible overlapping generations and study the genealogy of a sample of n genes as the population size n tends to infinity
control synthesis with reinforcement learning a
modeling
deep reinforcement
control synthesis with reinforcement learning a modeling perspective
swarms evolving from collective behaviors among multiple individuals are commonly seen in nature which enables biological
systems
multi-robot collaboration
swarms evolving from collective behaviors among multiple individuals are commonly seen in nature which enables biological systems to exhibit more efficient and robust collaboration
for specific tasks carefully adding a lightweight structural hint through self-augmented
prompting
human feedback
for specific tasks carefully adding a lightweight structural hint through self-augmented prompting can yield further improvements of 3-4 points on average
based on the results we further propose a full streaming
inference
vision-language models vlms
based on the results we further propose a full streaming inference framework for real-time robot control of vla