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this work represents the theoretical foundations of this cooperative
manipulation
manipulation ordering
this work represents the theoretical foundations of this cooperative manipulation control framework and thus the experiments are presented in an abstract way while giving pointers towards potential future applications
cypress leverages a pre-trained large-scale geospatial
foundation
foundation models
cypress leverages a pre-trained large-scale geospatial foundation model prithvi-eo-2
recently deep multi-agent reinforcement learning marl has demonstrated promising
performance
reinforcement learning
recently deep multi-agent reinforcement learning marl has demonstrated promising performance for solving challenging tasks such as long-term dependencies and non-markovian environments
the kerr rotation associated with orbital accumulation has been studied in previous works and is largely due to the dc electric
field-induced
kerr rotation
the kerr rotation associated with orbital accumulation has been studied in previous works and is largely due to the dc electric field-induced change of the electron distribution function
a flexible block-coordinate forward-backward
algorithm
accelerated gradient
a flexible block-coordinate forward-backward algorithm for non-smooth and non-convex optimization
because each round of qec depends on measurement long
readout
qubit readout
because each round of qec depends on measurement long readout times increase cycle duration and slow down program execution
this work introduces a dynamic context-aware scene
reasoning
multimodal reasoning
this work introduces a dynamic context-aware scene reasoning framework that leverages vision-language alignment to address zero-shot real-world scenarios
our results suggest the need to conduct user-centered studies on measuring
llms
llm responses
our results suggest the need to conduct user-centered studies on measuring llms ability to help users while preserving privacy
estimation and inference in boundary discontinuity designs
distance-based
effect boundaries
estimation and inference in boundary discontinuity designs distance-based methods
cosmic vine high abundance of massive galaxies and
dark
dark matter
cosmic vine high abundance of massive galaxies and dark matter halos in a forming cluster at z 3
this involves jointly optimizing active beamforming
power
power allocation
this involves jointly optimizing active beamforming power allocation receiving filters and ma position configurations which is a highly non-convex problem
artificial intelligence systems based on large
language
language models
artificial intelligence systems based on large language models llms can now generate coherent text music and images yet they operate without a persistent state each inference reconstructs context from scratch
the measurement of the optical power propagating in a waveguide is achieved by leveraging the photo-thermal resistance variation of one of the resistors that comprise a bridge which is either part of the
waveguide
waveguide modes
the measurement of the optical power propagating in a waveguide is achieved by leveraging the photo-thermal resistance variation of one of the resistors that comprise a bridge which is either part of the waveguide or in close contact with the waveguide
the tip density reaches sim 2 mathrm cm -3 implying an ambient medium density of sim 10 -3 mathrm cm -3 in agreement with the
galactic
circumgalactic medium
the tip density reaches sim 2 mathrm cm -3 implying an ambient medium density of sim 10 -3 mathrm cm -3 in agreement with the galactic warm ionized medium at a distance of sim 5 kpc
existing approaches from vision-language-action vla
models
vision-language models
existing approaches from vision-language-action vla models to hierarchical frameworks fall short due to their reliance on limited or dividual-agent memory
the pde model also displays a biologically infeasible short-wave instability in the case of payoff-driven motion and equal diffusivities indicating that we need to be careful about the mathematical properties of pde models with payoff-driven directed motion and indicating potential use for nonlocal pde models for spati...
evolutionary
game theory
the pde model also displays a biologically infeasible short-wave instability in the case of payoff-driven motion and equal diffusivities indicating that we need to be careful about the mathematical properties of pde models with payoff-driven directed motion and indicating potential use for nonlocal pde models for spati...
particularly we design an additional control input using
reinforcement
reinforcement learning
particularly we design an additional control input using reinforcement learning rl to be applied to the vehicle powertrain along with the input commanded by the battery
finally drawing on literature from both nlp ml and hci as a constructive step forward we develop reflection prompts to support hci practitioners engage with
llm
llm responses
finally drawing on literature from both nlp ml and hci as a constructive step forward we develop reflection prompts to support hci practitioners engage with llm reasoning in an informed and reflective way
we conduct a comprehensive comparison between redllm pretrained with prefix language
modeling
language models
we conduct a comprehensive comparison between redllm pretrained with prefix language modeling lm and decllm pretrained with causal lm at different model scales ranging from sim 150m to sim 8b
a hamilton-jacobi reachability framework with soft
constraints
soft constraints
a hamilton-jacobi reachability framework with soft constraints for safety-critical systems
this potential molecular gas supply however does not correlate with the current accretion efficiency of the smbhs suggesting that only a fraction of the observed
non-rotating
dense gas
this potential molecular gas supply however does not correlate with the current accretion efficiency of the smbhs suggesting that only a fraction of the observed non-rotating gas is currently reaching the smbh
we outline a multi-phase research methodology focused on preparing re datasets fine-tuning ai models and designing collaborative
human-ai
ai agents
we outline a multi-phase research methodology focused on preparing re datasets fine-tuning ai models and designing collaborative human-ai workflows
a persistent challenge however is maintaining robust target
tracking
multi-object tracking
a persistent challenge however is maintaining robust target tracking under partial or full occlusions
on the other hand global indices such as those based on spectral analysis of the networks
graph
network structures
on the other hand global indices such as those based on spectral analysis of the networks graph fail in identifying critical elements
simulation results demonstrate that the proposed approach significantly outperforms some baseline approaches and other state-of-the-art deep
reinforcement
deep reinforcement
simulation results demonstrate that the proposed approach significantly outperforms some baseline approaches and other state-of-the-art deep reinforcement learning algorithms
bootstrap consistency for empirical likelihood in
density
density estimation
bootstrap consistency for empirical likelihood in density ratio models
many biological populations exhibit diversity in their strategy for survival and
reproduction
basic reproduction
many biological populations exhibit diversity in their strategy for survival and reproduction in a given environment and microbes are an example
our results demonstrate that ssf significantly improves sensing quality while preserving
communication
signal-to-noise ratio
our results demonstrate that ssf significantly improves sensing quality while preserving communication efficiency
aligning llm-based judges with human preferences is a significant challenge as they are difficult to
calibrate
llm raters
aligning llm-based judges with human preferences is a significant challenge as they are difficult to calibrate and often suffer from rubric sensitivity bias and instability
through experiments on synthetic and real-world
datasets
synthetic data
through experiments on synthetic and real-world datasets we show that our algorithm outperforms existing anytime algorithms as well as fixed-budget algorithms
finally we empirically validate our approach against
existing
local calibration
finally we empirically validate our approach against existing multiclass calibration techniques
typically an sis is modelled as a surface that imparts phase shifts on impinging electromagnetic signals to achieve desired
communication
communication systems
typically an sis is modelled as a surface that imparts phase shifts on impinging electromagnetic signals to achieve desired communication objectives
we resolve this question by presenting the first bidirectional reduction showing that suffix array queries are up to an additive o log log n term in
query
query time
we resolve this question by presenting the first bidirectional reduction showing that suffix array queries are up to an additive o log log n term in query time equivalent to prefix-select queries in all parameters
we conduct experiments to study the effects of noise on
collective
collective action
we conduct experiments to study the effects of noise on collective action
wigner negativity and genuine multipartite entanglement gme are
key
quantum channels
wigner negativity and genuine multipartite entanglement gme are key nonclassical resources that enable computational advantages and broader quantum-information tasks
code review serves as an effective practice that enables developers to check their teammates
code
code review
code review serves as an effective practice that enables developers to check their teammates code before integration into the codebase
while significant computational challenges remain the neural differential manifold represents a fundamental shift towards geometrically structured interpretable and efficient
deep
deep learning
while significant computational challenges remain the neural differential manifold represents a fundamental shift towards geometrically structured interpretable and efficient deep learning systems
inference-cost-aware dynamic tree construction for efficient inference in large
language
large language models llms
inference-cost-aware dynamic tree construction for efficient inference in large language models
by using a lattice model with high-dimensional state agents and evolution under a fitness that depends on an
agent
emergent behaviors
by using a lattice model with high-dimensional state agents and evolution under a fitness that depends on an agent s local neighborhood and global dissimilarity clusters of diverse communities with different fitness are organized by equalizing the finesses on the boundaries where their numbers and sizes are robust to p...
structured layouts are preferable in many 2d visual contents eg guis webpages since the structural information allows convenient
layout
layout generation
structured layouts are preferable in many 2d visual contents eg guis webpages since the structural information allows convenient layout editing
experimental results demonstrate that securereviewer outperforms state-of-the-art baselines in both security issue detection accuracy and the overall quality and practical utility of generated
review
review comments
experimental results demonstrate that securereviewer outperforms state-of-the-art baselines in both security issue detection accuracy and the overall quality and practical utility of generated review comments
through experiments on synthetic and real-world
datasets
real-world datasets
through experiments on synthetic and real-world datasets we show that our algorithm outperforms existing anytime algorithms as well as fixed-budget algorithms
object binding the brain s ability to bind the many features that collectively represent an object into a coherent whole is
central
cognitive science
object binding the brain s ability to bind the many features that collectively represent an object into a coherent whole is central to human cognition
many mendelian randomization mr papers have been conducted only in people of european
ancestry
population genetics
many mendelian randomization mr papers have been conducted only in people of european ancestry limiting transportability of results to the global population
experimental verification is scarce however especially in the telecom range because real
photonic
photonic circuits
experimental verification is scarce however especially in the telecom range because real photonic crystals and experimental methods inherently cannot be homogeneous in the third dimension
the global income distribution was fitted to log-normal and
gamma
income distribution
the global income distribution was fitted to log-normal and gamma functions which are standard tools in econophysics
our methods and findings offer not only practical applications for quantum
networks
quantum dot
our methods and findings offer not only practical applications for quantum networks but also lead to a deeper understanding of multipartite entanglement structures
this improvement allows the inverse optimal safe control to inherit the standard
gain
optimal control
this improvement allows the inverse optimal safe control to inherit the standard gain margin of 1 2 inf without requiring prior knowledge of whether f x or u0 acts safely on the safety boundary while simultaneously ensuring global asymptotic stability of the resulting safe set
recent work has shown that different large
language
large language
recent work has shown that different large language models llms converge to similar and accurate input embedding representations for numbers
the prior network generates coarse localization maps that delineate the approximate roi serving as spatial guidance for the dual
encoder
cross dual encoder network
the prior network generates coarse localization maps that delineate the approximate roi serving as spatial guidance for the dual encoder network
using information geometry to characterize
higher-order
higher-order visual
using information geometry to characterize higher-order interactions in eeg
our model generates thresholds for when reducing costs or emissions is more useful depending on the factors which influence the population s
opinion
opinion formation
our model generates thresholds for when reducing costs or emissions is more useful depending on the factors which influence the population s opinion formation
for dyck edit distance our reduction incurs only polylogarithmic overheads in approximation and
update
edit distance
for dyck edit distance our reduction incurs only polylogarithmic overheads in approximation and update time yielding an n o 1 -approximation with n o 1 updates
the f1tenth competition provides a useful opportunity for developing wheel-to-wheel
racing
wheel-to-wheel racing
the f1tenth competition provides a useful opportunity for developing wheel-to-wheel racing algorithms on a standardised physical platform
by properly learning the bidirectional scattering patterns and complex attenuation profiles based on channel measurements these ellipsoids inherently cap ture the electromagnetic transmission characteristics of
wireless
wireless communication
by properly learning the bidirectional scattering patterns and complex attenuation profiles based on channel measurements these ellipsoids inherently cap ture the electromagnetic transmission characteristics of wireless environments thereby accurately modeling signal transmission under varying transceiver configuration...
additionally they imply an m 1 o 1 w -time algorithm for solving the problem on graphs with a given
tree
tree embedding
additionally they imply an m 1 o 1 w -time algorithm for solving the problem on graphs with a given tree decomposition of width w
using the next generation matrix method we derive an analytical expression for the
basic
basic reproduction
using the next generation matrix method we derive an analytical expression for the basic reproduction number mathcal r_0
we hypothesize this gap stems from missing core
gui
gui knowledge
we hypothesize this gap stems from missing core gui knowledge which existing training schemes such as supervised fine tuning and reinforcement learning alone cannot fully address
molecule and text representation learning has
gained
representation learning
molecule and text representation learning has gained increasing interest due to its potential for enhancing the understanding of chemical information
this framework learns a stochastic policy to construct circuits sequentially sampling them in proportion to a flexible user-defined
reward
policy learning
this framework learns a stochastic policy to construct circuits sequentially sampling them in proportion to a flexible user-defined reward function that can encode multiple design objectives such as performance depth and gate count
at first glance our lower bound would seem to render
retrieval
lower bound
at first glance our lower bound would seem to render retrieval unusable in many settings that aim to achieve very low redundancy
in recent work it has been shown that this random return can be well approximated by a finite number of random variables which we call truncated
random
truncated random return
in recent work it has been shown that this random return can be well approximated by a finite number of random variables which we call truncated random return
we introduce a taxonomy that classifies approaches by
anomaly
anomaly detection
we introduce a taxonomy that classifies approaches by anomaly type and graph dynamics analyze representative models and map them to key cybersecurity applications
this paper introduce textbf infoflow a systematic framework that
tackles
context engineering
this paper introduce textbf infoflow a systematic framework that tackles this problem from three aspects
after proving some properties of optimal solutions of the convex relaxation we exploit them to develop a dynamic programming approach returning an approximate solution to the
convex
strongly convex
after proving some properties of optimal solutions of the convex relaxation we exploit them to develop a dynamic programming approach returning an approximate solution to the convex relaxation and with time complexity o n 2 where n is the number of points into which the continuous path is discretized
the schottky barrier engineering was performed with a composite pt cap ptox
pt
ptox pt
the schottky barrier engineering was performed with a composite pt cap ptox pt 1
we find that for different types of network architectures and for both visual or neuronal stimuli these
cross-supervising
neural networks
we find that for different types of network architectures and for both visual or neuronal stimuli these cross-supervising networks learn semantic representations that are easily decodable and that decoding accuracy is comparable to supervised networks -- both at the level of single networks and the ensemble
these results suggest lossy compression supports mnemonic
discrimination
encoding models
these results suggest lossy compression supports mnemonic discrimination by discarding redundant and overlapping information
we demonstrate that the treatment effects of interest can be consistently
estimated
average treatment effect
we demonstrate that the treatment effects of interest can be consistently estimated using ordinary least squares with an appropriately specified working model and transformed regressors
we propose a new and more substantively appropriate conditional extrapolation
assumption
average treatment effect
we propose a new and more substantively appropriate conditional extrapolation assumption which requires an analyst to conduct a preliminary test to determine whether the severity of pre-treatment parallel trend violations falls below an acceptable level before extrapolation to the post-treatment period is justified
their quantum cram e r-rao bound saturates the
heisenberg
super-heisenberg scaling
their quantum cram e r-rao bound saturates the heisenberg limit
we argue that accountability mechanisms are needed in
human-ai
trustworthy ai
we argue that accountability mechanisms are needed in human-ai agent relationships to ensure alignment with user and societal interests
distributional assumptions that discipline serially correlated latent
variables
causal effects
distributional assumptions that discipline serially correlated latent variables play a central role in dynamic structural models
experimental results showed that compared to the baseline which prompts
intermediate
reasoning tasks
experimental results showed that compared to the baseline which prompts intermediate reasoning without presenting pragmatic theories 0-shot chain-of-thought our methods enabled language models to achieve up to 9
in the non-adaptive case our lower bounds essentially match the
complexity
query complexity
in the non-adaptive case our lower bounds essentially match the complexity of the algorithm that we provide
while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle normative
reasoning
reasoning capabilities
while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle normative reasoning remains underexplored
a problem of achieving minimum time consensus for a
set
optimal control
a problem of achieving minimum time consensus for a set of n second-order lti system agents with bounded inputs and fuel constraints is considered
in this work we show that the quantum walk technique fails to produce a fast
algorithm
quantum key distribution
in this work we show that the quantum walk technique fails to produce a fast algorithm improving the known or even the trivial upper bound on the query complexity
here we propose and investigate two theoretical protocols for fast single-shot
readout
spin readout
here we propose and investigate two theoretical protocols for fast single-shot readout of cavity-coupled single t center electronic spins
confidence ratings were uniformly high and
resource
retrospective confidence
confidence ratings were uniformly high and resource quality outcomes were comparable across conditions
the model achieved a classification accuracy exceeding previous cnn and lstm-based approaches and was
benchmarked
recurrent neural networks
the model achieved a classification accuracy exceeding previous cnn and lstm-based approaches and was benchmarked against a temporal convolutional network tcn baseline
in the latter case we show that coexistence of both strains is impossible when mutation occurs from the strain with lower
reproduction
basic reproduction
in the latter case we show that coexistence of both strains is impossible when mutation occurs from the strain with lower reproduction number and transmission rate to the other strain
the central sections proceed to apply this framework to two central phenomena first by analyzing the collective dynamics of information spreading with a dedicated focus on the models the main empirical insights and the unique traits characterizing misinformation and second by reviewing current models of
opinion
opinion dynamics
the central sections proceed to apply this framework to two central phenomena first by analyzing the collective dynamics of information spreading with a dedicated focus on the models the main empirical insights and the unique traits characterizing misinformation and second by reviewing current models of opinion dynamic...
we aim to assess what types of sfhs are consistent with the observed present-day star formation rates text sfr _0 and time-averaged star formation rates langle text
sfr
stellar mass function
we aim to assess what types of sfhs are consistent with the observed present-day star formation rates text sfr _0 and time-averaged star formation rates langle text sfr rangle of galaxies in the local volume without assuming any fixed functional form
through expert-centered case studies and quantitative evaluation we show that sia effectively discovers diverse and meaningful insights from social media while supporting human-agent
collaboration
ai use
through expert-centered case studies and quantitative evaluation we show that sia effectively discovers diverse and meaningful insights from social media while supporting human-agent collaboration in complex analytical tasks
the thesis is divided into two main sections methodological and
experimental
findings suggest
the thesis is divided into two main sections methodological and experimental work
dynamic spatial treatment effects as continuous functionals theory and evidence from
healthcare
dynamic spatial
dynamic spatial treatment effects as continuous functionals theory and evidence from healthcare access
we demonstrate an all-photonic terahertz receiver for a data-modulated
signal
ghz ghz
we demonstrate an all-photonic terahertz receiver for a data-modulated signal targeting a 106-ghz 2
our primary contributions include a persona-based method for synthesizing
preference
preference data
our primary contributions include a persona-based method for synthesizing preference labels at scale and two distinct implementations of our aggregator generalized additive model gam and a multi-layer perceptron mlp
as an alternative to established hole-based photonic crystal cavities we introduce corrugated triangular dinosaur
photonic
photonic circuits
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
we formalize the concept of treatment effect
boundaries
average treatment effect
we formalize the concept of treatment effect boundaries as structural parameters characterizing regime transitions where causal effects cease to operate
we first analyse a one-dimensional version of the model and formally show through a hopf-cole transformation that it admits in appropriate asymptotic regimes phenotypically heterogeneous travelling wave solutions wherein the locally prevailing cell phenotype varies across the
wave
traveling waves
we first analyse a one-dimensional version of the model and formally show through a hopf-cole transformation that it admits in appropriate asymptotic regimes phenotypically heterogeneous travelling wave solutions wherein the locally prevailing cell phenotype varies across the wave due to the presence of oxygen gradient...
by first establishing a converse issf-bf theorem we reveal the equivalence among the achievability of issf by feedback the achievability of inverse optimality and the solvability of a hamilton-jacobi-isaacs equation associated with the
inverse
inverse optimal issf
by first establishing a converse issf-bf theorem we reveal the equivalence among the achievability of issf by feedback the achievability of inverse optimality and the solvability of a hamilton-jacobi-isaacs equation associated with the inverse optimal issf gain assignment
we address the problem of localizing the source of
infection
infectious individuals
we address the problem of localizing the source of infection in an undirected tree-structured network under a susceptible-infected outbreak model
we demonstrate this method in simulation and discuss how textit a priori understandings of
obstacle
collision avoidance
we demonstrate this method in simulation and discuss how textit a priori understandings of obstacle risk can be directly incorporated into the safety filter to generate safe behaviors that are risk-aware
we formalize the concept of treatment effect
boundaries
effect boundaries
we formalize the concept of treatment effect boundaries as structural parameters characterizing regime transitions where causal effects cease to operate
social media platforms generate massive volumes of heterogeneous data capturing user behaviors textual content temporal
dynamics
social media
social media platforms generate massive volumes of heterogeneous data capturing user behaviors textual content temporal dynamics and network structures
additionally our system enables object-level editing where physical items in the room can be transformed to their
virtual
physical virtual
additionally our system enables object-level editing where physical items in the room can be transformed to their virtual counterparts in a story
we propose a generative framework that learns latent representations of fund manager strategies without requiring explicit
utility
reinforcement learning
we propose a generative framework that learns latent representations of fund manager strategies without requiring explicit utility specification
we derive formal identification results under staggered treatment adoption and develop a three-stage estimation procedure implementable with standard
panel
panel data
we derive formal identification results under staggered treatment adoption and develop a three-stage estimation procedure implementable with standard panel data