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in this work we introduce a dynamic environment feedback mechanism into the stochastic nonlinear pgg framework establishing a coevolutionary model that couples
environmental
ecological interactions
in this work we introduce a dynamic environment feedback mechanism into the stochastic nonlinear pgg framework establishing a coevolutionary model that couples environmental states and individual cooperative strategies
finally we derive electronic structure descriptions from a series of representative chemical models and compute the energetics from quantum experiments on quantinuum s h-series
ion
trapped ions
finally we derive electronic structure descriptions from a series of representative chemical models and compute the energetics from quantum experiments on quantinuum s h-series ion trap devices using up to 19 qubits
randomization of weighted networks has traditionally been done via the
weighted
scale-free networks
randomization of weighted networks has traditionally been done via the weighted configuration model wcm a simple extension of the configuration model where weights are interpreted as bundles of edges
specifically we focus on downlink dl bistatic sensing where the user equipment ue performs measurements from reflected
sensing
communication systems
specifically we focus on downlink dl bistatic sensing where the user equipment ue performs measurements from reflected sensing signals and provides feedback to the network nw
we provide theoretical results for the estimation and inference of a class of welfare and value functionals of the nonparametric conditional
average
average treatment
we provide theoretical results for the estimation and inference of a class of welfare and value functionals of the nonparametric conditional average treatment effect cate function under optimal treatment assignment i
we show that 1 this isolated reasoning embedding exhibits unique predictive power accounting for variance in neural activity not explained by other linguistic features and even extending to the recruitment of visual
regions
human cognition
we show that 1 this isolated reasoning embedding exhibits unique predictive power accounting for variance in neural activity not explained by other linguistic features and even extending to the recruitment of visual regions beyond classical language areas
evontree ontology rule-guided self-evolution of large
language
natural language
evontree ontology rule-guided self-evolution of large language models
to reduce such bias debiased machine learning employs
neyman
debiased machine
to reduce such bias debiased machine learning employs neyman orthogonal estimating equations
beyond reasoning benchmarks srl generalizes effectively to agentic
software
software engineering
beyond reasoning benchmarks srl generalizes effectively to agentic software engineering tasks establishing it as a robust and versatile training framework for reasoning-oriented llms
in this work we investigate the ashkin--teller at model on random
scale-free
scale-free networks
in this work we investigate the ashkin--teller at model on random scale-free networks using mean-field theory which extends the traditional ising framework by coupling two spin systems via both pairwise and four-spin interactions
a novel two-stage optimization approach mitigates numerical issues arising from the structure of the resulting optimal
control
optimal control
a novel two-stage optimization approach mitigates numerical issues arising from the structure of the resulting optimal control problem
the interaction between optical interference fringes and the vacuum electromagnetic field inside the phc
cavity
optical interference
the interaction between optical interference fringes and the vacuum electromagnetic field inside the phc cavity improves the linewidth and noise characteristics of lasers
this study of the m81 complex and its hubble flow delivers new and improved tip of the red giant branch trgb -based distances for nine member galaxies yielding a total of 58 galaxies with high-precision
trgb
galaxy cgm
this study of the m81 complex and its hubble flow delivers new and improved tip of the red giant branch trgb -based distances for nine member galaxies yielding a total of 58 galaxies with high-precision trgb distances
compared to traditional road testing scenario-based virtual
testing
scenario coverage
compared to traditional road testing scenario-based virtual testing offers significant advantages in terms of time and cost efficiency reproducibility and exploration of edge cases
many domains of human intellectual labour have to adapt to the new ai tools that give
humans
ai assistance
many domains of human intellectual labour have to adapt to the new ai tools that give humans new functionality and opportunity but also question the viability and necessity of some human work that used to be considered intellectual yet has now become an easily automatable commodity
we deliver a tutorial on rl covering fundamental concepts and key algorithmic families including value-based policy-based and
actor-critic
deep reinforcement learning
we deliver a tutorial on rl covering fundamental concepts and key algorithmic families including value-based policy-based and actor-critic methods
during massive star formation dense gas undergoes
chemical
star-forming region
during massive star formation dense gas undergoes chemical evolution producing both simple and complex organic molecules coms characteristic of hot molecular cores
a closed-form approximation-free control law is derived to ensure that each agent remains within its evolving stt thereby avoiding dynamic
obstacles
collision avoidance
a closed-form approximation-free control law is derived to ensure that each agent remains within its evolving stt thereby avoiding dynamic obstacles while also preventing inter-agent collisions in a socially aware manner and reaching the target within a prescribed time
angular steering behavior control via rotation in
activation
angular steering
angular steering behavior control via rotation in activation space
west nile virus wnv is a mosquito-borne virus of the genus flaviviridae circulating between mosquitoes and birds while
humans
infectious individuals
west nile virus wnv is a mosquito-borne virus of the genus flaviviridae circulating between mosquitoes and birds while humans equids and other mammals are dead-end hosts
by linking behavioral attributes with environmental context
mobilitygen
mobility networks
by linking behavioral attributes with environmental context mobilitygen reproduces key patterns such as scaling laws for location visits activity time allocation and the coupled evolution of travel mode and destination choices
we then train a transformer-based planner on a dataset of skill compositions to
act
predictive processing
we then train a transformer-based planner on a dataset of skill compositions to act as a high-level scheduler simultaneously predicting the discrete schedule of skills as well as their continuous parameters
we observe that the ability to recall an object physical or virtual that was encountered in a mobile
ar
augmented reality
we observe that the ability to recall an object physical or virtual that was encountered in a mobile ar experience depends on many possible impact factors and attributes with some objects being readily recalled while others are not and some people recalling objects overall much better or worse than others
the optimization problem aims to maximize the communication sum-rate which is critical for ensuring high-quality service to users while also maintaining accurate sensing performance for detection tasks and adhering to maximum power constraints for efficient
resource
resource allocation
the optimization problem aims to maximize the communication sum-rate which is critical for ensuring high-quality service to users while also maintaining accurate sensing performance for detection tasks and adhering to maximum power constraints for efficient resource usage
deep neural networks dnns have been used to model complex
optimization
deep learning
deep neural networks dnns have been used to model complex optimization problems in many applications yet have difficulty guaranteeing solution optimality and feasibility despite training on large datasets
among possible strategies to meet this challenge is exploiting the twist degree of freedom in layered structures which enables both emerging moire physics and unprecedented reconfigurability of
photonic
integrated photonics
among possible strategies to meet this challenge is exploiting the twist degree of freedom in layered structures which enables both emerging moire physics and unprecedented reconfigurability of photonic and electronic properties
this paper studies group target trajectory intent as the outcome of a
cooperative
cooperative game
this paper studies group target trajectory intent as the outcome of a cooperative game where the complex-spatio trajectories are modeled using an nlp-based generative model
we conduct comprehensive experiments with llama 2-7b llama 2-13b and mistral 7b models on mathematical
reasoning
reasoning capabilities
we conduct comprehensive experiments with llama 2-7b llama 2-13b and mistral 7b models on mathematical reasoning coding and summarization tasks
next-generation interferometry with gauge-invariant
linear
optical interference
next-generation interferometry with gauge-invariant linear optical scatterers
enhancing the spatial awareness of underwater
vehicles
autonomous driving
enhancing the spatial awareness of underwater vehicles is key to reducing piloting risks and enabling greater autonomy
neyman targeted estimation also yields tmle as a
special
maximum likelihood
neyman targeted estimation also yields tmle as a special case for regression function estimation
as such while small-scale societies may be demographically fragile large-scale
societies
population size
as such while small-scale societies may be demographically fragile large-scale societies should be much more stable
through regret analysis we demonstrate that difference-in-differences and synthetic control with differencing are complementary the former dominates the latter if and only if the latter s extrapolation error exceeds the former
s
policy optimization
through regret analysis we demonstrate that difference-in-differences and synthetic control with differencing are complementary the former dominates the latter if and only if the latter s extrapolation error exceeds the former s matching error up to a term vanishing at the parametric rate
first an equivalence between klyachko-can-binicio u g lu-shumovsky kcbs vectors and the pyramid upb is shown and then by constructing a one parameter family of upb vectors a quantitative connection between contextuality strength and bound entanglement of
states
quantum channels
first an equivalence between klyachko-can-binicio u g lu-shumovsky kcbs vectors and the pyramid upb is shown and then by constructing a one parameter family of upb vectors a quantitative connection between contextuality strength and bound entanglement of states associated with the corresponding upb is demonstrated
for some example applications distributed support-vector-machine svm and regression are
considered
machine learning
for some example applications distributed support-vector-machine svm and regression are considered as the ml training models
omnix from unified panoramic generation and
perception
computer vision
omnix from unified panoramic generation and perception to graphics-ready 3d scenes
we show that for every learning algorithm there exists an auxiliary
algorithm
debiased machine learning
we show that for every learning algorithm there exists an auxiliary algorithm that does not memorize and which yields comparable generalization error for any data distribution
we deliver a tutorial on rl covering fundamental concepts and key algorithmic families including value-based policy-based and
actor-critic
reinforcement learning
we deliver a tutorial on rl covering fundamental concepts and key algorithmic families including value-based policy-based and actor-critic methods
this study proves that nearest neighbor nn matching can be interpreted as an instance of riesz regression for automatic debiased
machine
machine learning
this study proves that nearest neighbor nn matching can be interpreted as an instance of riesz regression for automatic debiased machine learning
the architecture incorporates a brain-region to image-feature cross-attention mechanism enabling
nonlinear
neural codes
the architecture incorporates a brain-region to image-feature cross-attention mechanism enabling nonlinear mappings between high-dimensional deep network features and semantic patterns encoded in the brain activity
experiments on real-world datasets support our theoretical findings and
demonstrate
real-world datasets
experiments on real-world datasets support our theoretical findings and demonstrate the practical advantages of our approach
in the scope of this work we assume a narrowband and static scenario aiming to focus on the beamforming and
power
power allocation
in the scope of this work we assume a narrowband and static scenario aiming to focus on the beamforming and power allocation strategies
this paper explores how we can leverage ai to
improve
human-ai interaction
this paper explores how we can leverage ai to improve the quality of human oversight
in particular we recover the convergence rate of optimally tuned versions of these
algorithms
convergence rate
in particular we recover the convergence rate of optimally tuned versions of these algorithms up to logarithmic factors in both nonsmooth and smooth settings
while generative models especially large language models llms are ubiquitous in today s world principled mechanisms to assess their in
correctness
generative models
while generative models especially large language models llms are ubiquitous in today s world principled mechanisms to assess their in correctness are limited
moreover we show how this technique can also be used in the
context
approximation guarantee
moreover we show how this technique can also be used in the context of the weighted ring loading problem showing that cost-unaware approximation algorithms can be transformed into approximation algorithms with additional cost guarantees
guided by a bottom-up taxonomy that connects insight types with suitable mining and visualization techniques sia enables
agents
ai agents
guided by a bottom-up taxonomy that connects insight types with suitable mining and visualization techniques sia enables agents to plan and execute coherent analysis strategies
most classical visual navigation methods are restricted to single-goal single-modality and closed set
goal
visual navigation
most classical visual navigation methods are restricted to single-goal single-modality and closed set goal settings
existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning capabilities of large
language
large language models llms
existing benchmarks have widely leveraged high school math competitions for evaluating mathematical reasoning capabilities of large language models llms
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
bulge stars
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
the rapid advancement of large language models
llms
large language
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
in this work we investigate the temporal evolution of
key
massive galaxies
in this work we investigate the temporal evolution of key indicators of dynamical relaxation with particular emphasis on the secular growth of the diffuse intragroup light igl the four major group galaxies and the mass distributions of their progenitors
additionally we introduce securebleu a new evaluation metric designed to assess the effectiveness of
review
security issues
additionally we introduce securebleu a new evaluation metric designed to assess the effectiveness of review comments in addressing security issues
previous algorithms with hat o m work required omega m depth even for special cases of mincost flow with only edge capacities or max
flow
maximum flow
previous algorithms with hat o m work required omega m depth even for special cases of mincost flow with only edge capacities or max flow with vertex capacities
we present a statistical framework that establishes an accelerating star formation scenario for
dense
massive stars
we present a statistical framework that establishes an accelerating star formation scenario for dense clumps using atlasgal and almagal samples
experiments on real-world datasets support our
theoretical
theoretical findings
experiments on real-world datasets support our theoretical findings and demonstrate the practical advantages of our approach
enhancing the reachability of variational quantum
algorithms
quantum key distribution
enhancing the reachability of variational quantum algorithms via input-state design
we also provide a proof-of-concept case study of further adapting dms for better
wireless
wireless systems
we also provide a proof-of-concept case study of further adapting dms for better wireless receiver performance
the samples are acquired through sweeping multiple beams of an
isac
communication isac
the samples are acquired through sweeping multiple beams of an isac proof of concept poc in the industrial scenario of the arena2036
our results demonstrate that acer offers a scalable and
effective
models llms
our results demonstrate that acer offers a scalable and effective recipe for closing critical domain gaps in llms
large language models llms have demonstrated exceptional capabilities across multiple
domains
large language
large language models llms have demonstrated exceptional capabilities across multiple domains by leveraging massive pre-training and curated fine-tuning data
when two-dimensional atomic layers of different materials are brought into close proximity to form van
der
van der waals
when two-dimensional atomic layers of different materials are brought into close proximity to form van der waals vdw heterostructures interactions between adjacent layers significantly influence their physicochemical properties
our approach makes it possible to relate the formulation of
parallel
parallel trends
our approach makes it possible to relate the formulation of parallel trends violation to empirical evidence from 1 pre-testing 2 covariate benchmarking and 3 standard reporting statistics and visualizations
user perceptions of privacy and helpfulness in
llm
llm responses
user perceptions of privacy and helpfulness in llm responses to privacy-sensitive scenarios
the discriminator is trained using a combination of real-world data and simulation
data
autonomous driving
the discriminator is trained using a combination of real-world data and simulation data executed by the agent which is designed to train a policy that generates realistic motion trajectories that match the statistical properties of human motion
5 cdot mathrm polylog frac w delta time algorithm for solving the generalized maximum flow and generalized minimum cost
flow
maximum flow
5 cdot mathrm polylog frac w delta time algorithm for solving the generalized maximum flow and generalized minimum cost flow problems in this setting where delta is the target accuracy and w is the maximum of all costs capacities and loss factors and their inverses
therefore this paper proposes retrieval augmented generation rag -enhanced distributed
llm
llm agents
therefore this paper proposes retrieval augmented generation rag -enhanced distributed llm agents with emergency response for generalizable tsc reg-tsc
to solve this high-dimensional non-convex problem under uncertain channels we develop a deep
reinforcement
deep reinforcement
to solve this high-dimensional non-convex problem under uncertain channels we develop a deep reinforcement learning solution framework based on the proximal policy optimization ppo algorithm that integrates distribution-aware action modeling and a multi-branch actor network
on multiple robustness of proximal dynamic
treatment
treatment regimes
on multiple robustness of proximal dynamic treatment regimes
generating networks that more accurately reflect
real-world
mobility networks
generating networks that more accurately reflect real-world patterns is a significant topic within complex network research
for training purposes we prepared a set of 1 730 annotated
images
image generation
for training purposes we prepared a set of 1 730 annotated images that were captured under various traffic conditions
to solve this high-dimensional non-convex problem under uncertain channels we develop a deep
reinforcement
deep reinforcement learning
to solve this high-dimensional non-convex problem under uncertain channels we develop a deep reinforcement learning solution framework based on the proximal policy optimization ppo algorithm that integrates distribution-aware action modeling and a multi-branch actor network
here we implement an efficient quantum simulation algorithm on quantinuum s system model h2 trapped-ion
quantum
quantum technologies
here we implement an efficient quantum simulation algorithm on quantinuum s system model h2 trapped-ion quantum computer for the time dynamics of a 56-qubit system that is too complex for exact classical simulation
lastly we apply inputdsa to neural data recorded from rats performing a
cognitive
human brain
lastly we apply inputdsa to neural data recorded from rats performing a cognitive task demonstrating that it identifies a transition from input-driven evidence accumulation to intrinsically-driven decision-making
stellar abundances of elements with production channels that are metallicity-dependent most notably aluminium have provided an empirical route for separating different
galactic
stellar mass
stellar abundances of elements with production channels that are metallicity-dependent most notably aluminium have provided an empirical route for separating different galactic components
our framework allows for deriving analytically the conditions for favoring a specific behavior in any network
structure
collective systems
our framework allows for deriving analytically the conditions for favoring a specific behavior in any network structure strongly affected by non-social environments frequent exogenous forcing fef which contrasts with previous computationally prohibitive methods
all you need for object detection from pixels points and prompts to next-gen fusion and
multimodal
computer vision
all you need for object detection from pixels points and prompts to next-gen fusion and multimodal llms vlms in autonomous vehicles
object binding the brain s ability to bind the many features that collectively represent an
object
visual stimuli
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
normative reasoning is a type of reasoning that involves
normative
reasoning tasks
normative reasoning is a type of reasoning that involves normative or deontic modality such as obligation and permission
extreme equivalent width-selected low-mass starbursts at z 4-9 insights into their
role
stellar mass function
extreme equivalent width-selected low-mass starbursts at z 4-9 insights into their role in cosmic reionization
efficient collision-avoidance constraints for ellipsoidal
obstacles
obstacle avoidance
efficient collision-avoidance constraints for ellipsoidal obstacles in optimal control application to path-following mpc and uavs
while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle normative reasoning
remains
models llms
while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle normative reasoning remains underexplored
5-4b models across visual reasoning tasks demonstrate that our methods consistently improve visual reasoning
capabilities
reasoning capabilities
5-4b models across visual reasoning tasks demonstrate that our methods consistently improve visual reasoning capabilities outperforming vanilla self-improvement by 3
time-resolved atom interferometry as employed in applications such as gravitational wave detection and searches for ultra-light dark matter requires precise
control
atom interferometry
time-resolved atom interferometry as employed in applications such as gravitational wave detection and searches for ultra-light dark matter requires precise control over systematic effects
with the rapid growth of autonomous vehicle technologies effective path-tracking control has become a critical component in ensuring safety and efficiency in complex
traffic
collision avoidance
with the rapid growth of autonomous vehicle technologies effective path-tracking control has become a critical component in ensuring safety and efficiency in complex traffic scenarios
we present lean4phys a comprehensive reasoning framework for college-level
physics
mathematical reasoning
we present lean4phys a comprehensive reasoning framework for college-level physics problems in lean4
as ai capabilities improve and ai is used to tackle more challenging tasks verifying quality and safety becomes
increasingly
ai use
as ai capabilities improve and ai is used to tackle more challenging tasks verifying quality and safety becomes increasingly challenging
we construct a spatial graph using k-nearest neighbors to aggregate geometric information from the local layout and encode both object-object and object-manipulator interactions to support accurate
manipulation
manipulation ordering
we construct a spatial graph using k-nearest neighbors to aggregate geometric information from the local layout and encode both object-object and object-manipulator interactions to support accurate manipulation ordering in real-time
we complement our theoretical results with experiments on various real-world
datasets
real-world datasets
we complement our theoretical results with experiments on various real-world datasets which show that the proposed sketches are lightweight and achieve consistently low error in practice
this demonstrates that previously established conditions for linear systems to be sample-based observable can be utilized to verify or design sampling strategies that satisfy the conditions to guarantee rges of the
sample-based
state estimation
this demonstrates that previously established conditions for linear systems to be sample-based observable can be utilized to verify or design sampling strategies that satisfy the conditions to guarantee rges of the sample-based mhe
the evolution of the maximum core mass further shows that the growth timescales of protoclusters and their
embedded
stellar mass function
the evolution of the maximum core mass further shows that the growth timescales of protoclusters and their embedded most massive protostars are comparable implying a self-similar acceleration of star formation from the stellar to the protocluster scale
in addition practitioners also want confidence that the learned policy has better performance than the incumbent policy according to downstream
policy
policy optimization
in addition practitioners also want confidence that the learned policy has better performance than the incumbent policy according to downstream policy evaluation
the algorithm runs in o log sum_t n_t log m time and o
m
time complexity
the algorithm runs in o log sum_t n_t log m time and o m space independent of k
we present a deep reinforcement learning framework based on proximal policy optimization
ppo
deep reinforcement
we present a deep reinforcement learning framework based on proximal policy optimization ppo for autonomous qos-aware load balancing implemented end-to-end in a lightweight pure-python simulation environment
sensitivity analysis for treatment effects in difference-in-differences models using
riesz
riesz regression
sensitivity analysis for treatment effects in difference-in-differences models using riesz representation
on average across countries the share of urban residents living in
cities
large cities
on average across countries the share of urban residents living in cities with over one million people rose from 18 in 1975 to 39 in 2025
modeling and scheduling of fusion patterns in
autonomous
autonomous driving
modeling and scheduling of fusion patterns in autonomous driving systems extended version
this completes the theoretical foundation of compressed indexing closing a crucial gap between upper and lower bounds and providing a clear target for future data structures seeking either the optimal time in the smallest space or the fastest time in the optimal
space
query time
this completes the theoretical foundation of compressed indexing closing a crucial gap between upper and lower bounds and providing a clear target for future data structures seeking either the optimal time in the smallest space or the fastest time in the optimal space both of which are now known for central string queries
explaining the inherent tradeoffs for suffix
array
suffix array
explaining the inherent tradeoffs for suffix array functionality equivalences between string problems and prefix range queries
finally we present mbench a hierarchical benchmark designed for fine-grained evaluation across
motion
point tracking
finally we present mbench a hierarchical benchmark designed for fine-grained evaluation across motion quality prompt fidelity and generalization ability