prompt
stringlengths
41
511
target
stringlengths
1
25
keyword
stringclasses
697 values
full_sentence
stringlengths
48
1.25k
the proposed method extends to nonlinear systems by treating nonlinear terms as bounded
disturbances
bounded disturbances
the proposed method extends to nonlinear systems by treating nonlinear terms as bounded disturbances with rigorous approximation bounds
to address this challenge researchers have recently introduced the concept of
context
context engineering
to address this challenge researchers have recently introduced the concept of context engineering
the ability to use random objects as tools in a generalizable manner is a missing piece in
robots
mobile robots
the ability to use random objects as tools in a generalizable manner is a missing piece in robots intelligence today to boost their versatility and problem-solving capabilities
this study demonstrates that providing language models with
pragmatic
vision-language models
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
bell inequality violation is the phenomenon where multiple non-communicating parties can exhibit correlations using quantum
resources
multipartite entanglement
bell inequality violation is the phenomenon where multiple non-communicating parties can exhibit correlations using quantum resources that are impossible if they can only use classical resources
surprisingly given its proximity to the quasar in redshift the absorber has strong cold gas characteristics including
ci
absorption line
surprisingly given its proximity to the quasar in redshift the absorber has strong cold gas characteristics including ci and h _2
evaluated on a comprehensive dataset from the canadian prairies cypress demonstrates superior performance over existing
deep
deep learning
evaluated on a comprehensive dataset from the canadian prairies cypress demonstrates superior performance over existing deep learning-based yield prediction models highlighting the effectiveness of fine-tuning foundation models for specialized agricultural applications
topological protection of photon-pair generation in nonlinear
waveguide
photonic devices
topological protection of photon-pair generation in nonlinear waveguide arrays
we present high-resolution simulations up to 10 10 particles of the disruption of a solar-like star by a 10 6m_sun black hole with the new gpu-based smoothed-particle hydrodynamics code sph-exa including the relativistic apsidal precession of the stellar debris orbits our simulations run from initial
disruption
massive stars
we present high-resolution simulations up to 10 10 particles of the disruption of a solar-like star by a 10 6m_sun black hole with the new gpu-based smoothed-particle hydrodynamics code sph-exa including the relativistic apsidal precession of the stellar debris orbits our simulations run from initial disruption to the ...
we establish consistency convergence rate and
asymptotic
efficiency bound
we establish consistency convergence rate and asymptotic distribution for the estimator of the bounds
additionally the dynamics features the periodic transfer of the
spin
spin readout
additionally the dynamics features the periodic transfer of the spin to the maximally stretched state starting from a superposition state
adaptive context length optimization with low-frequency truncation for multi-agent
reinforcement
continual learning
adaptive context length optimization with low-frequency truncation for multi-agent reinforcement learning
focusing on a regime in which all candidates prefer the same institution we characterize the large-market equilibrium and derive a closed-form expression for the resulting
representation
representation ratio
focusing on a regime in which all candidates prefer the same institution we characterize the large-market equilibrium and derive a closed-form expression for the resulting representation ratio
to better control the structures of generated layouts we disentangle the
structural
layout generation
to better control the structures of generated layouts we disentangle the structural information from the element placements
occupancy analysis of two butterfly species further
confirmed
butterfly species
occupancy analysis of two butterfly species further confirmed these results
this paper proposes a debiased estimator for
causal
causal inference
this paper proposes a debiased estimator for causal effects in high-dimensional generalized linear models with binary outcomes and general link functions
our results lay a fundamental understanding of how pre-trained llms manipulate numbers and outline the potential of more accurate probing techniques in addressed refinements of
llms
large language models llms
our results lay a fundamental understanding of how pre-trained llms manipulate numbers and outline the potential of more accurate probing techniques in addressed refinements of llms architectures
we present results from crocodile-dwarf a suite of cosmological zoom-in hydrodynamic simulations of isolated field dwarf galaxies with halo
masses
quiescent galaxies
we present results from crocodile-dwarf a suite of cosmological zoom-in hydrodynamic simulations of isolated field dwarf galaxies with halo masses of sim10 10 m_ odot at z 0 performed with the textsc gadget4-osaka code
with the current progress of artificial intelligence ai technology and its
increasingly
artificial intelligence
with the current progress of artificial intelligence ai technology and its increasingly broader applications trust is seen as a required criterion for ai usage acceptance and deployment
despite the language s high degree of ambiguity when unvocalized recent machine learning approaches have
significantly
natural language processing
despite the language s high degree of ambiguity when unvocalized recent machine learning approaches have significantly advanced performance on this task
first hclfuse investigates the quantification theory of
information
dual encoder
first hclfuse investigates the quantification theory of information mapping in unsupervised fusion networks which leads to the design of a multi-scale mask-regulated variational bottleneck encoder
finally we discuss how multiplex networks fit within the broader framework of decorated
graphs
correlation network
finally we discuss how multiplex networks fit within the broader framework of decorated graphs and how the convergence results can be recovered from the limit theory of decorated graphs
this further inspires a practical method that uses variational inference to recover these variables and leverages them to train
reward
reward models
this further inspires a practical method that uses variational inference to recover these variables and leverages them to train reward models
emergent behaviors are a defining feature of complex
systems
emergent behaviors
emergent behaviors are a defining feature of complex systems yet their quantitative characterization remains an open challenge as traditional classifications rely mainly on visual inspection of spatio-temporal patterns
4 the siren x-ray and optical emissions take over each other twice per
cycle
emission line
4 the siren x-ray and optical emissions take over each other twice per cycle possibly with two different peak x-ray fluxes within one cycle
to address these limitations we propose securereviewer a new approach designed for enhancing llms ability to identify and resolve security-related issues during
code
code review
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
while recent breakthroughs in computer vision cv and artificial intelligence ai have driven remarkable progress the field still faces a critical challenge as knowledge remains fragmented across
multimodal
computer vision
while recent breakthroughs in computer vision cv and artificial intelligence ai have driven remarkable progress the field still faces a critical challenge as knowledge remains fragmented across multimodal perception contextual reasoning and cooperative intelligence
this paper proposes a noncoherent low probability of detection lpd
communication
wireless communication
this paper proposes a noncoherent low probability of detection lpd communication system based on direct sequence spread spectrum dsss and grassmannian signaling
our findings thus interpret linear relational decoding in transformer
language
language models
our findings thus interpret linear relational decoding in transformer language models as primarily property-based rather than relation-specific
we develop a direct debiased machine learning framework comprising neyman targeted estimation and generalized
riesz
debiased machine learning
we develop a direct debiased machine learning framework comprising neyman targeted estimation and generalized riesz regression
to unlock further sis potential we propose a nonlinear
sis
nonlinear sis
to unlock further sis potential we propose a nonlinear sis that can mimic the behaviour of nonlinear neural networks
linearly transforming stimulus representations of deep neural networks yields
high-performing
deep learning
linearly transforming stimulus representations of deep neural networks yields high-performing models of behavioral and neural responses to complex stimuli
this study constructs financial networks using the local gaussian
correlation
correlation network
this study constructs financial networks using the local gaussian correlation coefficients between tail regions of stock returns in the shanghai stock exchange
this formulates the problem as a co-optimization setup to i optimize the data processing and ii
optimally
efficiently solving
this formulates the problem as a co-optimization setup to i optimize the data processing and ii optimally allocate the computing resources
our focus is on theory and reproducible algorithms
empirical
practical performance
our focus is on theory and reproducible algorithms empirical benchmarking is optional
their structural configuration as well as on the presence and nature of
atomic
electronic structure
their structural configuration as well as on the presence and nature of atomic defects
these findings demonstrate the potential of ai
agents
human-ai interaction
these findings demonstrate the potential of ai agents to move beyond process partners toward colleagues that share intent strengthen group dynamics and collaborate with humans to advance ideas
furthermore we use our bounds to investigate the problem of data memorization raised in those works and which asserts that there are learning problem instances for which any learning algorithm that has good
prediction
policy learning
furthermore we use our bounds to investigate the problem of data memorization raised in those works and which asserts that there are learning problem instances for which any learning algorithm that has good prediction there exist distributions under which the algorithm must memorize a big fraction of the training datas...
in addition to the vertical excitation the effect of structural relaxation is also estimated using analytical
atomic
atomic force
in addition to the vertical excitation the effect of structural relaxation is also estimated using analytical atomic forces
our key insight is to reframe the offline policy
learning
reinforcement learning rl
our key insight is to reframe the offline policy learning problem by leveraging the textbf observed future of each expert trajectory
using this framing we derive bounds on the success of
collective
collective action
using this framing we derive bounds on the success of collective action
grounded in the theory of neural dynamics we derive closed-form expressions for the duration of perceptual dominance and
suppression
human cognition
grounded in the theory of neural dynamics we derive closed-form expressions for the duration of perceptual dominance and suppression and for the degree of hysteresis i
because ground-truth his are unavailable a semi-supervised and an unsupervised approach are proposed i a diversity
deep
deep learning
because ground-truth his are unavailable a semi-supervised and an unsupervised approach are proposed i a diversity deep semi-supervised anomaly detection diversity-deepsad approach augmented with continuous auxiliary labels used as hypothetical damage proxies which overcomes the limitation of prior binary labels that o...
our work provides a framework for determining when
fitness
population genetics
our work provides a framework for determining when fitness inference is feasible from population-wide whole-genome time-stratified data and highlights settings where it is not
low-rank adaptation lora has become a popular technique for parameter-efficient fine-tuning of large
language
large language
low-rank adaptation lora has become a popular technique for parameter-efficient fine-tuning of large language models llms
5 spectroscopically-confirmed quiescent galaxies in the uds and egs fields at 3 z 5 with nirspec prism spectroscopy from rubies and other public jwst
nirspec
host galaxy
5 spectroscopically-confirmed quiescent galaxies in the uds and egs fields at 3 z 5 with nirspec prism spectroscopy from rubies and other public jwst nirspec programs
while these deployments of ai in the street have attracted significant media attention and public controversy in recent years the presence of ai in the
street
everyday publics
while these deployments of ai in the street have attracted significant media attention and public controversy in recent years the presence of ai in the street often remains inscrutable and many everyday publics are unaware of it
solving power system capacity expansion planning cep problems at realistic
spatial
expansion planning
solving power system capacity expansion planning cep problems at realistic spatial resolutions is computationally challenging
to address this problem we present a vision-based reinforcement
learning
reinforcement learning
to address this problem we present a vision-based reinforcement learning approach that incorporates a stress-penalized reward to discourage damage to the object explicitly
we track the stellar populations in bulges back in time to their birth location classifying them as bulge-born in-situ and disk-born
stars
stellar population
we track the stellar populations in bulges back in time to their birth location classifying them as bulge-born in-situ and disk-born stars and accreted
beyond this proof of concept empathic prompting points to applications in chatbot-mediated communication particularly in domains like healthcare or education where users
emotional
empathic prompting
beyond this proof of concept empathic prompting points to applications in chatbot-mediated communication particularly in domains like healthcare or education where users emotional signals are critical yet often opaque in verbal exchanges
tensor network methods strike a middle ground between fully-fledged quantum computing and classical computing as they take inspiration from
quantum
quantum dot
tensor network methods strike a middle ground between fully-fledged quantum computing and classical computing as they take inspiration from quantum systems to significantly speed up certain classical operations
the phase transition is quite robust and becomes progressively conspicuous in the limit of large population
size
phase transition
the phase transition is quite robust and becomes progressively conspicuous in the limit of large population size where deterministic evolutionary game dynamics viz
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
super-eddington accretion is a crucial phase in the growth of
supermassive
black hole
super-eddington accretion is a crucial phase in the growth of supermassive black holes
the primary outcome was a composite z-score combining four
cognitive
cognitive science
the primary outcome was a composite z-score combining four cognitive tests
in this paper we investigate the asymptotic behavior of some sir models incorporating demography bounded random
transmission
disease transmission
in this paper we investigate the asymptotic behavior of some sir models incorporating demography bounded random transmission coefficient and a time-dependent vaccination strategy targeting the susceptible population
we close by distinguishing these qualitative changes from density-dependent phase transitions and by discussing how our approach could generalize to broader classes of
collective
collective systems
we close by distinguishing these qualitative changes from density-dependent phase transitions and by discussing how our approach could generalize to broader classes of collective behaviors
spiral features appear across stellar populations of different ages confirming their density-wave nature and producing coherent spirals in both metallicity and mean stellar age distributions-consistent with recent gaia observations of the
milky
quiescent galaxies
spiral features appear across stellar populations of different ages confirming their density-wave nature and producing coherent spirals in both metallicity and mean stellar age distributions-consistent with recent gaia observations of the milky way
the language of thought lot hypothesis posits that at least some important
cognitive
working memory
the language of thought lot hypothesis posits that at least some important cognitive processes involve language-like representations
we successfully generate a three-photon genuinely entangled state from two bi-separable states via local operations and classical communication
demonstrating
single photons
we successfully generate a three-photon genuinely entangled state from two bi-separable states via local operations and classical communication demonstrating superactivation of genuine multipartite entanglement
this paper also considers energy consumption in the path planning of automated guided
vehicles
autonomous driving
this paper also considers energy consumption in the path planning of automated guided vehicles agvs
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
reasoning tasks
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
effective-hamiltonian reconstruction through bloch-wave interferometry in
bulk
bulk gaas
effective-hamiltonian reconstruction through bloch-wave interferometry in bulk gaas driven by strong thz fields
this opens up a potential cognitive attack in which adversaries might create conditions that make an ar user not
recall
object recall
this opens up a potential cognitive attack in which adversaries might create conditions that make an ar user not recall certain potentially mission-critical objects
it has been proven that super-heisenberg scaling can be achieved when the
hamiltonian
super-heisenberg scaling
it has been proven that super-heisenberg scaling can be achieved when the hamiltonian of the system involves many-body interactions or the time-dependent terms
we show that at these stages the full spectral
energy
spectral energy distribution
we show that at these stages the full spectral energy distribution - x-ray spectra and uv optical photometry - is well described by a compact yet standard accretion disk the same disk which powers the x-rays at all times
we evaluate 15 foundation models across 79 problems spanning eight
academic
foundation models
we evaluate 15 foundation models across 79 problems spanning eight academic domains physics mathematics chemistry economics biology statistics calculus and optimization through three experimental phases 1 baseline establishment six models mixtral-8x7b phi-3 llama 3
however deploying deep learning models for automated analysis in resource-constrained environments faces
reliability
deep learning
however deploying deep learning models for automated analysis in resource-constrained environments faces reliability challenges due to inevitable out-of-distribution ood data
to this end inas qds are integrated in a hybrid photon-phonon patterned microcavity where the density of optical
states
quantum technologies
to this end inas qds are integrated in a hybrid photon-phonon patterned microcavity where the density of optical states is tailored by the lateral confinement of photons in um-sized traps defined lithographically in the microcavity spacer
evolutionary systems must learn to generalize often extrapolating from a limited set of selective conditions to anticipate future
environmental
ecological interactions
evolutionary systems must learn to generalize often extrapolating from a limited set of selective conditions to anticipate future environmental changes
zip codes demonstrates exponential spatial
decay
spatial decay
zip codes demonstrates exponential spatial decay for healthcare access kappa 0
keywords small language models factual grounding directed
reasoning
ai literacy
keywords small language models factual grounding directed reasoning fine-tuning model alignment cost-efficient ai
the analytical calculation of suitable precodings for perfect
channel
channel state information
the analytical calculation of suitable precodings for perfect channel information is well studied however their performance can quickly deteriorate when faced with e
adasdbo leverages adaptive stepsizes based on cumulative
gradient
gradient descent
adasdbo leverages adaptive stepsizes based on cumulative gradient norms to update all variables simultaneously dynamically adjusting its progress and eliminating the need for problem-specific hyperparameter tuning
formation planning provides better performance by minimizing a surrogate cost function that closely approximates the original
cost
optimal control
formation planning provides better performance by minimizing a surrogate cost function that closely approximates the original cost function instead of relying on a shape abstraction
the source code used to conduct the experiments
presented
extensive experiments
the source code used to conduct the experiments presented in this paper is made freely available
understanding how individual learning behavior and structural dynamics interact is essential to modeling
emergent
emergent behaviors
understanding how individual learning behavior and structural dynamics interact is essential to modeling emergent phenomena in socioeconomic networks
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
optimal control
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
reducing the readout duration speeds up cycles and reduces decoherence errors that accumulate while
qubits
qubit readout
reducing the readout duration speeds up cycles and reduces decoherence errors that accumulate while qubits idle but it also lowers the number of collected photons making measurements noisier and more error-prone
in this work we attempt to add robustness into existing region proposal network-deep convolutional neural network rpn-dcnn object
detection
object detection
in this work we attempt to add robustness into existing region proposal network-deep convolutional neural network rpn-dcnn object detection networks through two distinct scene-based information fusion techniques
approximate nearest neighbor ann search and approximate kernel density
estimation
machine learning
approximate nearest neighbor ann search and approximate kernel density estimation a-kde are fundamental problems at the core of modern machine learning with broad applications in data analysis information systems and large-scale decision making
our results reveal an unambiguous detection of faint
extended
emission line
our results reveal an unambiguous detection of faint extended emission in the f444w band with a typical size of 200 parsecs and magnitude of 27
we apply inputdsa on recurrent neural networks rnns trained with deep
reinforcement
reinforcement learning
we apply inputdsa on recurrent neural networks rnns trained with deep reinforcement learning identifying that high-performing networks are dynamically similar to one another while low-performing networks are more diverse
actions are equally fundamental in the modeling of stochastic
processes
diffusion models
actions are equally fundamental in the modeling of stochastic processes as they trigger discontinuous state transitions and enable the flow of information through large complex systems
our theoretical results highlight the crucial role played by the regularity of the boundary a one-dimensional manifold over which
identification
nonparametric identification
our theoretical results highlight the crucial role played by the regularity of the boundary a one-dimensional manifold over which identification estimation and inference are conducted
yet in the domain of tool learning the lack of rms specifically
designed
reinforcement learning rl
yet in the domain of tool learning the lack of rms specifically designed for function-calling tasks has limited progress toward more capable agentic ai
large language models llms commonly boost reasoning via sample-evaluate-ensemble decoders achieving
label
large language
large language models llms commonly boost reasoning via sample-evaluate-ensemble decoders achieving label free gains without ground truth
our results include that finding a solution is fixed-parameter tractable with respect to the vertex cover number of the food web assuming the
phylogenetic
phylogenetic diversity
our results include that finding a solution is fixed-parameter tractable with respect to the vertex cover number of the food web assuming the phylogenetic tree is a star
this review highlights the critical role of beam shaping encompassing spatial shaping of the
beam
beam shaping
this review highlights the critical role of beam shaping encompassing spatial shaping of the beam to influence laser-material interaction and temporal modification to optimize pulse duration and energy delivery
this work provides a robust and adaptable framework to support transparent evidence-based policymaking for mitigating public
health
public health
this work provides a robust and adaptable framework to support transparent evidence-based policymaking for mitigating public health crises
ai predictive systems are increasingly embedded in
decision
artificial intelligence
ai predictive systems are increasingly embedded in decision making pipelines shaping high stakes choices once made solely by humans
spiking patches asynchronous sparse and efficient tokens for
event
event cameras
spiking patches asynchronous sparse and efficient tokens for event cameras
the learned features enable effective data
curation
data curation
the learned features enable effective data curation re-labeling the harmful examples in arena yields large safety gains 37 with no cost to general performance
despite its longstanding presence and significant attention within the optimization community most works focusing on understanding its
convergence
linear convergence
despite its longstanding presence and significant attention within the optimization community most works focusing on understanding its convergence guarantees assume the strong l-lipschitz condition
when such estimates are insufficient to extrapolate effects for broader policy questions such as external
validity
causal inference
when such estimates are insufficient to extrapolate effects for broader policy questions such as external validity and general-equilibrium ge effects researchers combine trials with external evidence from reduced-form or structural observational estimates or prior experiments
this allows us to infer a dense turn-by-turn
reward
reward density
this allows us to infer a dense turn-by-turn reward signal grounded in the expert s revealed strategy decomposing the intractable long-horizon problem into a series of supervised learning tasks and training a policy to output a structured texttt action state_assessment tuple governing both textbf what to ask and crucia...
however by reducing complex cost functions to formations discrepancies arise between maintaining the shape and minimizing the original
cost
cost function
however by reducing complex cost functions to formations discrepancies arise between maintaining the shape and minimizing the original cost function
lateral ventricular brain-computer interface system with lantern-inspired
electrode
electroencephalography eeg
lateral ventricular brain-computer interface system with lantern-inspired electrode for stable performance and memory decoding
our results highlight the need for simpler models that align with the available data and propose a distribution-based approach to better capture ecosystem
diversity
ecological communities
our results highlight the need for simpler models that align with the available data and propose a distribution-based approach to better capture ecosystem diversity stability and competition