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this survey provides an analysis of current methodologies integrating legal and logical specifications into the perception prediction and
planning
collision avoidance
this survey provides an analysis of current methodologies integrating legal and logical specifications into the perception prediction and planning modules of automated driving systems
adaptive surrogate gradients for sequential reinforcement
learning
reinforcement learning
adaptive surrogate gradients for sequential reinforcement learning in spiking neural networks
for instances with more than 100 jobs exact methods such as
mip
practical performance
for instances with more than 100 jobs exact methods such as mip and dynamic programming become computationally intractable
in this work we investigate how and at which stage value
alignment
test-time alignment
in this work we investigate how and at which stage value alignment arises during the course of a model s post-training
this integrated approach offers a general mathematical framework for designing and evaluating
control
control strategies
this integrated approach offers a general mathematical framework for designing and evaluating control strategies in infectious disease outbreaks with applications to low resource settings and beyond
to evaluate the system-level performance of nonlinear sis we present a case study where sis structures are optimized to minimize the symbol error rate ser in an mimo system with
sis
wireless systems
to evaluate the system-level performance of nonlinear sis we present a case study where sis structures are optimized to minimize the symbol error rate ser in an mimo system with sis deployed at both the transmitter and receiver sides using only statistical channel information
larger holes as narrower degree distributions in
complex
complex networks
larger holes as narrower degree distributions in complex networks
while generative models especially large language models
llms
large language
while generative models especially large language models llms are ubiquitous in today s world principled mechanisms to assess their in correctness are limited
typically an sis is modelled as a surface that imparts phase shifts on impinging electromagnetic signals to achieve desired
communication
nonlinear sis
typically an sis is modelled as a surface that imparts phase shifts on impinging electromagnetic signals to achieve desired communication objectives
public opinion on environmental issues remains polarized in many countries posing a significant barrier to the implementation of
effective
environmental change
public opinion on environmental issues remains polarized in many countries posing a significant barrier to the implementation of effective policies
by providing a scalable and effective training methodology cruise advances the development of
autonomous
autonomous driving
by providing a scalable and effective training methodology cruise advances the development of autonomous systems for dynamic competitive tasks and serves as a blueprint for future real-world deployment
furthermore to manage the high-dimensional gradients of
llms
models llms
furthermore to manage the high-dimensional gradients of llms we employ sparse random projection to reduce dimensionality and improve storage and computation efficiency
the picard-lagrange framework for higher-order
langevin
langevin dynamics
the picard-lagrange framework for higher-order langevin monte carlo
accurate channel state information csi is essential for reliable multiuser
mimo
channel state information csi
accurate channel state information csi is essential for reliable multiuser mimo operation
saber symbolic regression-based angle of arrival and
beam
channel estimation
saber symbolic regression-based angle of arrival and beam pattern estimator
inspired by this principle we introduce a hierarchical multimodal recurrent neural network grounded in
predictive
neural representations
inspired by this principle we introduce a hierarchical multimodal recurrent neural network grounded in predictive processing under the free-energy principle capable of directly integrating over 30 000-dimensional visuo-proprioceptive inputs without dimensionality reduction
experiments on synthetic and real-world datasets
demonstrate
real-world datasets
experiments on synthetic and real-world datasets demonstrate that our method effectively mitigates spurious correlation issues and yields more robust reward models
inverse reinforcement learning irl aims to explain observed
behavior
policy learning
inverse reinforcement learning irl aims to explain observed behavior by uncovering an underlying reward
this constraint naturally gives rise to spatial correlations between the states of neighboring nodes as the
infection
viral replication
this constraint naturally gives rise to spatial correlations between the states of neighboring nodes as the infection status of connected individuals becomes interdependent
consequently we contribute a versatile scalable and self-improving learning framework to the field of
autonomous
autonomous driving
consequently we contribute a versatile scalable and self-improving learning framework to the field of autonomous drone racing
this enables dynamic and real-time tasks that were previously believed to be unattainable by
large
vision-language models vlms
this enables dynamic and real-time tasks that were previously believed to be unattainable by large vla models
second users recalled fewer physical objects than
virtual
physical virtual
second users recalled fewer physical objects than virtual objects in the environment suggesting reduced awareness of the physical environment
normative reasoning is a type of reasoning that involves
normative
normative reasoning
normative reasoning is a type of reasoning that involves normative or deontic modality such as obligation and permission
using a brain encoder as a digital twin offers a powerful data-driven framework for generating and testing hypotheses about visual selectivity in the human brain - hypotheses that can guide future
fmri
cognitive neuroscience
using a brain encoder as a digital twin offers a powerful data-driven framework for generating and testing hypotheses about visual selectivity in the human brain - hypotheses that can guide future fmri experiments
people tend to walk in groups and interactions with those
groups
group size
people tend to walk in groups and interactions with those groups have a significant impact on crowd behavior and pedestrian traffic dynamics
the polarized thermal emission from interstellar dust offers a valuable tool for probing both the dust and the magnetic field in the
interstellar
interstellar medium
the polarized thermal emission from interstellar dust offers a valuable tool for probing both the dust and the magnetic field in the interstellar medium ism
machine learning ml models meanwhile can be trained to predict near-optimal decisions at a
fraction
machine learning
machine learning ml models meanwhile can be trained to predict near-optimal decisions at a fraction of the speed
we present a proper agnostic learner for the class of triangles that has optimal sample
complexity
time complexity
we present a proper agnostic learner for the class of triangles that has optimal sample complexity and runs in time tilde o epsilon -6 improving on the algorithm of dobkin and gunopulos colt 95 that runs in time tilde o epsilon -10
empathic prompting non-verbal context integration for
multimodal
empathic prompting
empathic prompting non-verbal context integration for multimodal llm conversations
reinforcement learning rl is widely used to produce robust robotic manipulation policies but fine-tuning vision-language-action vla models with
rl
reinforcement learning rl
reinforcement learning rl is widely used to produce robust robotic manipulation policies but fine-tuning vision-language-action vla models with rl can be unstable due to inaccurate value estimates and sparse supervision at intermediate steps
unfortunately in too many cases today s ai is not
accountable
ai assistance
unfortunately in too many cases today s ai is not accountable -- we cannot question it enter into a discussion with it let alone sanction it
combined with the distribution of serial intervals or generation times the rate gives basic and instantaneous values of the
reproduction
reproduction number
combined with the distribution of serial intervals or generation times the rate gives basic and instantaneous values of the reproduction number that govern development and ultimate outcome of the epidemic
many believe that intracortical axons conduct signals too slowly to bring the
contextual
human brain
many believe that intracortical axons conduct signals too slowly to bring the contextual information from receptive fields of other neurons
this framework offers a practical analytical tool for traffic engineers and planners to design adaptive signal control and pedestrian
safety
crash risk
this framework offers a practical analytical tool for traffic engineers and planners to design adaptive signal control and pedestrian safety interventions before crashes occur
structures that support various queries on an input text t in sigma n using
space
data structure
structures that support various queries on an input text t in sigma n using space proportional to the size of t in compressed form
extensions to longitudinal data dynamic treatment
regimes
treatment regimes
extensions to longitudinal data dynamic treatment regimes and multiplicative instrumental variables are further developed
we investigate the impact of synthetic data generation and lightweight fine-tuning techniques on the ability of large
language
language models
we investigate the impact of synthetic data generation and lightweight fine-tuning techniques on the ability of large language models llms to recognize fallacious arguments using the missci dataset and framework
spg-cdenet spatial prior-guided cross dual
encoder
dual encoder
spg-cdenet spatial prior-guided cross dual encoder network for multi-organ segmentation
spiking patches asynchronous sparse and efficient tokens for
event
spiking patches
spiking patches asynchronous sparse and efficient tokens for event cameras
specifically we propose an approach in which an overview of
pragmatic
pragmatic theories
specifically we propose an approach in which an overview of pragmatic theories such as gricean pragmatics and relevance theory is presented as a prompt to the language model guiding it through a step-by-step reasoning process to derive a final interpretation
82 10 8 m _ sun kpc -2 - values close to those of nearby
quiescent
galaxy cgm
82 10 8 m _ sun kpc -2 - values close to those of nearby quiescent galaxies
our general interaction framework which reduces to several previously studied models as special cases provides a versatile platform for engineering quantum
correlations
quantum correlations
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
reinforcement learning rl fine-tuning of large
language
language models
reinforcement learning rl fine-tuning of large language models llms often suffers from instability due to the numerical mismatch between the training and inference policies
protected ion beam fabrication of two-dimensional transition metal dichalcogenides based
photonic
photonic devices
protected ion beam fabrication of two-dimensional transition metal dichalcogenides based photonic devices
in the cold dark environments of pre-stellar
cores
stellar mass
in the cold dark environments of pre-stellar cores where the temperatures are below 10 k ne can condense onto the surface of interstellar grains
microresonators are essential in integrated
photonics
photonic circuits
microresonators are essential in integrated photonics enabling optical filters modulators sensors and frequency converters
modern vision-language models vlms excel at many multimodal tasks yet their grasp of temporal information in video
remains
language models
modern vision-language models vlms excel at many multimodal tasks yet their grasp of temporal information in video remains weak and crucially under-evaluated
however when researchers have access to many covariates at the experiment design stage they often face challenges in effectively selecting or weighting
covariates
covariate balancing
however when researchers have access to many covariates at the experiment design stage they often face challenges in effectively selecting or weighting covariates when creating their strata
this paper develops a unified framework for identifying spatial and temporal
boundaries
effect boundaries
this paper develops a unified framework for identifying spatial and temporal boundaries of treatment effects in difference-in-differences designs
these results have implications for amplified oversight -- the challenge of combining humans and ai to supervise ai
systems
ai use
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
this work lays out the architectural blueprint for extending hpcqc integration to support pulse-level quantum
operations
quantum algorithm
this work lays out the architectural blueprint for extending hpcqc integration to support pulse-level quantum operations without disrupting state-of-the-art classical workflows
in extensive simulations we demonstrate that such an approach reliably recovers true
covariates
covariate balancing
in extensive simulations we demonstrate that such an approach reliably recovers true covariates under diverse noise scenarios and improves both selection accuracy and stability
experimental demonstration of multi-object tracking in integrated
sensing
integrated sensing
experimental demonstration of multi-object tracking in integrated sensing and communication
in this aspect we formulate a sum rate optimization problem that jointly optimizes the antenna activation factor the bs transmit power and the ue s transmit power subject to
power
power allocation
in this aspect we formulate a sum rate optimization problem that jointly optimizes the antenna activation factor the bs transmit power and the ue s transmit power subject to power budget constraints for the bs and the ues as well as minimum rate requirements for the ues
test-time alignment of llms via sampling-based optimal
control
test-time alignment
test-time alignment of llms via sampling-based optimal control in pre-logit space
gaussian processes gps on the other hand are often
preferred
gaussian process
gaussian processes gps on the other hand are often preferred in uncertainty quantification tasks due to their interpretability
from the perspective of dynamical systems theory visual
rivalry
higher-order visual
from the perspective of dynamical systems theory visual rivalry offers an experimentally tractable window into the dynamical mechanisms governing perceptual awareness
we develop an efficient algorithm to solve this bilevel
optimization
bilevel optimization
we develop an efficient algorithm to solve this bilevel optimization problem which computes parameter gradients without backpropagating through the solver
to standardize this study we curate the evaluation data into mme-cof a compact
benchmark
reasoning curriculum
to standardize this study we curate the evaluation data into mme-cof a compact benchmark that enables in-depth and thorough assessment of chain-of-frame cof reasoning
in the presence of disturbances this improvement idea renders inverse
optimal
optimal control
in the presence of disturbances this improvement idea renders inverse optimal issf controllers robust to gain variations with the same gain margin of 1 2 inf
here we report how four-dimensional scanning transmission electron
microscopy
atomic force microscopy
here we report how four-dimensional scanning transmission electron microscopy 4d-stem can address critical challenges in swcnt structural analysis
while diffusion language models dlms enable fine-grained refinement their practical controllability
remains
language models
while diffusion language models dlms enable fine-grained refinement their practical controllability remains fragile
using high-quality bilateral exposure data from the european banking authority transparency exercise 2014-2023 we estimate the causal impact of the covid-19 pandemic on
network
network fragility
using high-quality bilateral exposure data from the european banking authority transparency exercise 2014-2023 we estimate the causal impact of the covid-19 pandemic on network fragility using spatial difference-in-differences methods adapted from our previous studies
we establish a practical and easy-to-implement sequential
stopping
stopping rules
we establish a practical and easy-to-implement sequential stopping rule for the martingale central limit theorem focusing on monte carlo methods for estimating the mean of a non-iid sequence of martingale difference type
while decllm is overall more compute-optimal during pretraining
redllm
llm post-training
while decllm is overall more compute-optimal during pretraining redllm demonstrates comparable scaling and context length extrapolation capabilities
using this result and the replica trick we find that the entanglement entropy of highly excited
states
multipartite entanglement
using this result and the replica trick we find that the entanglement entropy of highly excited states assumes a thermal form providing a concrete realization of the eigenstate thermalization hypothesis eth
here we introduce a topological framework that defines and detects localities in human
mobility
urban systems
here we introduce a topological framework that defines and detects localities in human mobility networks
dc transport number studies reveal that the
total
nonlinear transport
dc transport number studies reveal that the total conductivity is dominated by ionic conduction 95
coherent control of quantum emitters is essential for scalable
quantum
optical communication
coherent control of quantum emitters is essential for scalable quantum photonic technologies
moreover in the same settings in which our uniqueness theorem applies we also design and analyze an efficient
randomized
randomized algorithm
moreover in the same settings in which our uniqueness theorem applies we also design and analyze an efficient randomized algorithm to compute the unique minimum matrix-vector decomposition and thus a tensor rank decomposition of minimum rank
we introduce a new analytical framework for modelling degree sequences in
individual
mobility networks
we introduce a new analytical framework for modelling degree sequences in individual communities of real-world networks e
we introduce human ai collaborative uncertainty quantification a framework that formalizes how an ai model can refine a human
expert
ai assistance
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...
echo-conditioned denoising diffusion probabilistic models for multi-target
tracking
multi-object tracking
echo-conditioned denoising diffusion probabilistic models for multi-target tracking in rf sensing
we formulate the problem as a markov decision process and analyze the structure of the
optimal
optimal control
we formulate the problem as a markov decision process and analyze the structure of the optimal policy pi star for l 3 extending insights to arbitrary l
this paper focuses on the transceiver design of ofdm systems based on dms provides an illustration of the potential of
dms
communication systems
this paper focuses on the transceiver design of ofdm systems based on dms provides an illustration of the potential of dms in wireless transceivers and points out the related research directions brought by dms
we show that the cavity reflection approach enables high-fidelity spin
readout
qubit readout
we show that the cavity reflection approach enables high-fidelity spin readout even when the t center only has a modest cyclicity
these findings highlight the potential of shared control strategies to balance stability efficiency and
driver
collision avoidance
these findings highlight the potential of shared control strategies to balance stability efficiency and driver acceptance
large language models llms are catalyzing the development of
autonomous
models llms
large language models llms are catalyzing the development of autonomous ai research agents for scientific and engineering discovery
a limiting case of this scheme utilizing two pulses with identical gaussians envelopes and tuned delay and relative phase is also explored revealing experimentally accessible pathways for manipulating
quantum
quantum dot
a limiting case of this scheme utilizing two pulses with identical gaussians envelopes and tuned delay and relative phase is also explored revealing experimentally accessible pathways for manipulating quantum coherence
our experimental evaluation shows that models achieved the same performance with a compression ratio of 4-16x compared to lightgbm models using an adapted training process and an
alternative
rgb fundus
our experimental evaluation shows that models achieved the same performance with a compression ratio of 4-16x compared to lightgbm models using an adapted training process and an alternative memory layout
existing causal discovery methods allow enforcing structural constraints for example requiring a causal path from pip3 to akt but they may still produce incorrect
causal
interventional constraints
existing causal discovery methods allow enforcing structural constraints for example requiring a causal path from pip3 to akt but they may still produce incorrect causal conclusions such as learning that pip3 inhibits akt
we give matching lower bounds up to polylogarithmic
factors
lower bound
we give matching lower bounds up to polylogarithmic factors for both results
we study the sobolev ipm problem for measures supported on a graph metric space where critic function is constrained to lie within the unit ball defined by
sobolev
sobolev ipm
we study the sobolev ipm problem for measures supported on a graph metric space where critic function is constrained to lie within the unit ball defined by sobolev norm
quantum illumination with nonsimultaneous phase-insensitive coincidence measurements can provide jamming resilience compared to identical measurements for
classical
quantum emitters
quantum illumination with nonsimultaneous phase-insensitive coincidence measurements can provide jamming resilience compared to identical measurements for classical illumination
joint encoding of what and when predictions through error-modulated plasticity in reservoir
spiking
neural codes
joint encoding of what and when predictions through error-modulated plasticity in reservoir spiking networks
our results have applications across diverse contexts from behavioural ecology to bio-inspired
collective
collective systems
our results have applications across diverse contexts from behavioural ecology to bio-inspired collective systems design
our findings pave the way for the integration of chemically tailored intercalation compounds in scalable
quantum
quantum materials
our findings pave the way for the integration of chemically tailored intercalation compounds in scalable quantum technologies
kolmogorov- arnold networks kans semi-parametric
neural
neural network
kolmogorov- arnold networks kans semi-parametric neural architectures have emerged as a prominent approach for modeling complex functions with structured and efficient representations through spline layers
we use 44 central galaxies from the cielo
cosmological
host galaxy
we use 44 central galaxies from the cielo cosmological simulations
test-time prompt tuning tpt has emerged as a promising technique for adapting large
vision-language
vision-language models
test-time prompt tuning tpt has emerged as a promising technique for adapting large vision-language models vlms to unseen tasks without relying on labeled data
recent quantum machine learning approaches such as quantum kernel methods and variational quantum circuits have shown promise in capturing complex data distributions for
anomaly
anomaly detection
recent quantum machine learning approaches such as quantum kernel methods and variational quantum circuits have shown promise in capturing complex data distributions for anomaly detection but remain constrained by limited qubit counts
reinforcement finetuning rft is a key technique for aligning large language models llms with human preferences and enhancing
reasoning
reinforcement learning rl
reinforcement finetuning rft is a key technique for aligning large language models llms with human preferences and enhancing reasoning yet its effectiveness is highly sensitive to which tasks are explored during training
pvmark enabling public verifiability for llm
watermarking
watermarking schemes
pvmark enabling public verifiability for llm watermarking schemes
we test the compression versus expansion hypotheses by predicting performance on the canonical
mnemonic
working memory
we test the compression versus expansion hypotheses by predicting performance on the canonical mnemonic similarity task
we refer to this riesz representer estimation as generalized
riesz
riesz regression
we refer to this riesz representer estimation as generalized riesz regression
we study attention in mobile augmented reality ar using object
recall
object recall
we study attention in mobile augmented reality ar using object recall as a proxy outcome
the eeg microstate analysis was utilized to explore the relative variations in temporal parameters and brain
functional
fmri data
the eeg microstate analysis was utilized to explore the relative variations in temporal parameters and brain functional connectivity
additionally the dynamics features the periodic transfer of the
spin
quantum walk
additionally the dynamics features the periodic transfer of the spin to the maximally stretched state starting from a superposition state
there are two prevalent ways to constructing 3d scenes procedural
generation
image generation
there are two prevalent ways to constructing 3d scenes procedural generation and 2d lifting
our results suggest the need to conduct user-centered studies on measuring
llms
llm reasoning
our results suggest the need to conduct user-centered studies on measuring llms ability to help users while preserving privacy