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in this work we investigate how choice homophily and triadic closure shape the emergence of the spiral of
silence
opinion dynamics
in this work we investigate how choice homophily and triadic closure shape the emergence of the spiral of silence the phenomenon whereby minority views are progressively silenced due to fear of isolation
6 films of thickness ranging from 5 nm to 65
nm
film thickness
6 films of thickness ranging from 5 nm to 65 nm using 7 kev 10 kev and 13 kev incident photon energies with inelastic electron mean free paths ranging from 7
motion imitation is a promising approach for humanoid
locomotion
motion planning
motion imitation is a promising approach for humanoid locomotion enabling agents to acquire humanlike behaviors
aeolus supports a broad range of tasks including regression classification temporal structure modeling and graph learning serving as a unified benchmark across tabular sequential and
graph
graph neural
aeolus supports a broad range of tasks including regression classification temporal structure modeling and graph learning serving as a unified benchmark across tabular sequential and graph modalities
while traditional approaches rely on data to reveal causal links a recently developed method assimilative
causal
causal effects
while traditional approaches rely on data to reveal causal links a recently developed method assimilative causal inference aci integrates observations with dynamical models
neural networks tended to outperform in larger
datasets
neural network
neural networks tended to outperform in larger datasets and in those with more predictors but this advantage narrowed over time
reasoning about reasoning towards informed and reflective use of
llm
llm responses
reasoning about reasoning towards informed and reflective use of llm reasoning in hci
in terms of graph size we obtain a lower bound of 2 tilde
omega
lower bound
in terms of graph size we obtain a lower bound of 2 tilde omega sqrt log log n
to evaluate our method we developed a task oriented
virtual
physical virtual
to evaluate our method we developed a task oriented virtual environment for a user study
in this paper we systematically evaluate llms
reasoning
reasoning curriculum
in this paper we systematically evaluate llms reasoning capabilities in the normative domain from both logical and modal perspectives
through these principles our method achieves image reconstructions from fmri that faithfully reconstruct the seen
images
image reconstruction
through these principles our method achieves image reconstructions from fmri that faithfully reconstruct the seen images and surpass current sota approaches both visually and by standard objective metrics
to mitigate the high-dimensional challenges of humanoid control thor introduces a reinforcement
learning
reinforcement learning
to mitigate the high-dimensional challenges of humanoid control thor introduces a reinforcement learning architecture that decouples the upper body waist and lower body
additionally we prove local convergence guarantees for
weak
superlinear convergence
additionally we prove local convergence guarantees for weak minty operators
however these approaches only add constraints upon refinement
failure
existing approaches
however these approaches only add constraints upon refinement failure expending significant search effort on infeasible branches
each simulated agent is assigned demographic attributes a personal political stance and an
llm
llm agents
each simulated agent is assigned demographic attributes a personal political stance and an llm variant texttt gpt-4
2 mm continuum emission and velocity differences estimated from hco and h 13 co molecular
line
emission line
2 mm continuum emission and velocity differences estimated from hco and h 13 co molecular line data
reinforcement learning rl fine-tuning of large language models llms often suffers from instability due to the numerical mismatch between the
training
reinforcement learning
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
our approach leverages the action-value q-
function
reinforcement learning
our approach leverages the action-value q- function to balance efficiency and fairness without requiring additional training
graph-theoretical mapping of resting-state
eeg
brain decoding
graph-theoretical mapping of resting-state eeg reveals neural signatures of creativity
this dataset establishes a foundation for advancing research in streaming video understanding complex
temporal
temporal understanding
this dataset establishes a foundation for advancing research in streaming video understanding complex temporal reasoning and multimodal inference
the emergence of spite driven by prejudice is also found to persist when one considers long-term
evolutionary
evolutionary dynamics
the emergence of spite driven by prejudice is also found to persist when one considers long-term evolutionary dynamics in the mutation-selection dominated regime
to further balance performance and automated effort we then develop a minimal intervention controller mic that retains acceptable
stability
predictive control
to further balance performance and automated effort we then develop a minimal intervention controller mic that retains acceptable stability while limiting automation
despite the simplicity of this bath we uncover rich dynamical phase
transitions
phase transitions
despite the simplicity of this bath we uncover rich dynamical phase transitions i
results show that active ris yields higher spectral efficiency se by eliminating the
multiplicative
active ris
results show that active ris yields higher spectral efficiency se by eliminating the multiplicative fading inherent in passive riss and allocating more resources to data transmission
reinforcement learning with verifiable rewards
rlvr
reinforcement learning
reinforcement learning with verifiable rewards rlvr is a promising approach for enhancing agentic deep search
numerical simulations corroborate the analytical results demonstrating that infection levels decrease monotonically with higher protection adoption and highlight the impact of mutation rates and protection cost on
infection
infectious individuals
numerical simulations corroborate the analytical results demonstrating that infection levels decrease monotonically with higher protection adoption and highlight the impact of mutation rates and protection cost on infection state trajectories
interestingly we also identify 4 -dtc phases that cannot be explained by the system s mathbb z _2 symmetry these
phases
-dtc phases
interestingly we also identify 4 -dtc phases that cannot be explained by the system s mathbb z _2 symmetry these phases become stable for higher values of angular momentum
in the state-of-the-art photonic quantum computers pqcs phase-shift and displacement
gates
quantum dot
in the state-of-the-art photonic quantum computers pqcs phase-shift and displacement gates can be implemented in an electrically-programmable way
next-generation interferometry with gauge-invariant
linear
nonlinear optical
next-generation interferometry with gauge-invariant linear optical scatterers
we show here that in models equipped with a learning rule inferred from neurobiological data spurious overlaps collectively reduce the mean synaptic inputs to
neurons
neural representations
we show here that in models equipped with a learning rule inferred from neurobiological data spurious overlaps collectively reduce the mean synaptic inputs to neurons and that this mean reduction causes in turn an increase in storage capacity through a sparsening of network activity
stress in chromium thin films deposited by dc
magnetron
film thickness
stress in chromium thin films deposited by dc magnetron sputtering on grounded cupper and stainless-steel substrate holders
our findings connect entanglement dissipation-enhanced scaling laws and superabsorption outlining a pathway towards scalable quantum
batteries
quantum batteries
our findings connect entanglement dissipation-enhanced scaling laws and superabsorption outlining a pathway towards scalable quantum batteries offering practical quantum advantage
large language models llms face significant inference latency challenges stemming from their autoregressive design and
large
large language models llms
large language models llms face significant inference latency challenges stemming from their autoregressive design and large size
additionally it offers insights into sensing performance effects on
beam
near-field beam
additionally it offers insights into sensing performance effects on beam patterns as well as communicationsensing trade-offs in multi-target scenarios
we focus on the efficiency of building tree
embedding
tree embedding
we focus on the efficiency of building tree embedding in various computational settings under high-dimensional euclidean mathbb r d
beyond lamno _ 3 our work opens an avenue for studying a wider range of
correlated
quantum materials
beyond lamno _ 3 our work opens an avenue for studying a wider range of correlated materials
graph-enhanced policy optimization in llm
agent
llm agents
graph-enhanced policy optimization in llm agent training
lastly we also provide a tight zcdp bound for the worst
case
lower bound
lastly we also provide a tight zcdp bound for the worst case bounded range mechanism
our two-stage approach first scales the relative depth
map
depth estimation
our two-stage approach first scales the relative depth map with the sparse depth points then refines the final metric prediction with our proposed cascade conv-deformable transformer blocks
overcoming this challenge advances key applications such as creating reliable reward models for
reinforcement
reinforcement learning rl
overcoming this challenge advances key applications such as creating reliable reward models for reinforcement learning from human feedback rlhf and building effective routing systems that select the best-suited model for a given user query
experimental results demonstrate that our approach significantly improves manipulation accuracy reduces system latency and achieves single-pass intention and
object
object recall
experimental results demonstrate that our approach significantly improves manipulation accuracy reduces system latency and achieves single-pass intention and object recognition accuracy greater than 88 across multiple real-world scenarios
the stellar mass-size analysis reveals that star-forming members are more compact at higher
masses
black hole mass
the stellar mass-size analysis reveals that star-forming members are more compact at higher masses than their field counterparts
passive fatigue during conditional automated
driving
automated driving
passive fatigue during conditional automated driving can compromise driver readiness and safety
this work establishes a theoretical framework for evaluating the statistical properties of physics-informed estimators in convex classes of functions contributing to closing the gap between
statistical
density-ratio estimation
this work establishes a theoretical framework for evaluating the statistical properties of physics-informed estimators in convex classes of functions contributing to closing the gap between statistical theory and practical pisl with potential applications to cases not yet explored in the literature
decomposing prediction uncertainty into its aleatoric irreducible and epistemic reducible components is critical for the development and deployment of
machine
machine learning
decomposing prediction uncertainty into its aleatoric irreducible and epistemic reducible components is critical for the development and deployment of machine learning systems
modeling the transport dynamics of natural
processes
diffusion models
modeling the transport dynamics of natural processes from population-level observations is a ubiquitous problem in the natural sciences
the copolymer s swelling behavior was characterized using dynamic vapor sorption dvs and in-situ atomic force
microscopy
atomic force microscopy
the copolymer s swelling behavior was characterized using dynamic vapor sorption dvs and in-situ atomic force microscopy afm
numerical studies subsequently provide qualitative evidence of the practical performance achieved for the full recursion using the algorithms and theory
developed
zeroth-order methods
numerical studies subsequently provide qualitative evidence of the practical performance achieved for the full recursion using the algorithms and theory developed for the single-step error bounds
in task and motion planning high-level task
planning
multi-robot collaboration
in task and motion planning high-level task planning is done over an abstraction of the world to enable efficient search in long-horizon robotics problems
this photogrammetry-based calibration process involves multiple high-resolution images from different angles to measure the position and orientation of the
platform
calibration plate
this photogrammetry-based calibration process involves multiple high-resolution images from different angles to measure the position and orientation of the platform center in the three-dimensional space
the vulnerability of cyclists exacerbated by the rising popularity of faster e-bikes
motivates
wheel-to-wheel racing
the vulnerability of cyclists exacerbated by the rising popularity of faster e-bikes motivates adapting automotive perception technologies for bicycle safety
the local gaussian correlation networks among return tails in the chinese
stock
correlation network
the local gaussian correlation networks among return tails in the chinese stock market
this means that individuals within communities do not behave as independent demographic units as their lives are correlated through cooperation shared subsistence practices overlapping land use and exposure to
common
ecological communities
this means that individuals within communities do not behave as independent demographic units as their lives are correlated through cooperation shared subsistence practices overlapping land use and exposure to common shocks such as disease outbreaks or failed harvests
focusing on simpler statistical methods we examine the design-based properties of regression-based methods for estimating
treatment
treatment effect
focusing on simpler statistical methods we examine the design-based properties of regression-based methods for estimating treatment effects in time-series experiments
accurate real-time wireless signal prediction is essential for
next-generation
wireless networks
accurate real-time wireless signal prediction is essential for next-generation networks
these results highlight the significant room for improving the mathematical reasoning in
current
models llms
these results highlight the significant room for improving the mathematical reasoning in current llms
by examining the challenges in data-efficient llm post-training we
highlight
llm raters
by examining the challenges in data-efficient llm post-training we highlight open problems and propose potential research avenues
quantum illumination with nonsimultaneous phase-insensitive coincidence measurements can provide jamming resilience compared to identical
measurements
optical interference
quantum illumination with nonsimultaneous phase-insensitive coincidence measurements can provide jamming resilience compared to identical measurements for classical illumination
we introduce perception learning pel a paradigm that optimizes an agent s sensory interface f_ phi mathcal x to mathcal z using task-agnostic signals decoupled from downstream decision learning g_ theta mathcal z to
mathcal
policy learning
we introduce perception learning pel a paradigm that optimizes an agent s sensory interface f_ phi mathcal x to mathcal z using task-agnostic signals decoupled from downstream decision learning g_ theta mathcal z to mathcal y
we propose an ml based user localization framework for ris assisted
communication
wireless communication
we propose an ml based user localization framework for ris assisted communication at 27 ghz
large language models llms are increasingly shaping creative work and problem-solving however
prior
llm reasoning
large language models llms are increasingly shaping creative work and problem-solving however prior research suggests that they may diminish unassisted creativity
for the case of the payoff-driven motion the
stochastic
stochastic differential
for the case of the payoff-driven motion the stochastic model shows an overall decrease in population size and average payoff but the pde model displays more subtle behavior in this setting and will depend on the relative diffusivities of the two strategies
we implement the how system as an rnn whose
low-rank
recurrent neural
we implement the how system as an rnn whose low-rank components are composed according to the context inferred by the what system
our solution jointly optimizes the transmission power and the
neural
neural network
our solution jointly optimizes the transmission power and the neural network split point
immersive applications call for synthesizing
spatiotemporal
optical flow
immersive applications call for synthesizing spatiotemporal 4d content from casual videos without costly 3d supervision
it however brings up significant computational hurdles that compound those already inherent in
sobolev
sobolev ipm
it however brings up significant computational hurdles that compound those already inherent in sobolev ipm
in this work we develop a mathematical framework for evaluating the theoretical effectiveness of various wnv
control
optimal control
in this work we develop a mathematical framework for evaluating the theoretical effectiveness of various wnv control methods in germany
the era of agentic organization learning to organize with
language
large language models llms
the era of agentic organization learning to organize with language models
incorporating these two modules enhances intra-region semantic consistency and maintains inter-region contextual associations thereby facilitating
fine-grained
fmri data
incorporating these two modules enhances intra-region semantic consistency and maintains inter-region contextual associations thereby facilitating fine-grained brain decoding
our findings suggest the smc has a higher production of eu with respect to the alpha -elements than the milky
way
dwarf galaxies
our findings suggest the smc has a higher production of eu with respect to the alpha -elements than the milky way but in line with what observed in other dwarf systems within the local group
robotic assistant completing collaborative tasks with dexterous
vision-language-action
vision-language models vlms
robotic assistant completing collaborative tasks with dexterous vision-language-action models
even advanced rl algorithms are often limited in their ability to solve
problems
computational cost
even advanced rl algorithms are often limited in their ability to solve problems in these conditions
the nct reframes ai evaluation from performance to persistence outlining conceptual requirements for future benchmarks and architectural designs that could sustain long-term identity and goal coherence in
generative
ai agents
the nct reframes ai evaluation from performance to persistence outlining conceptual requirements for future benchmarks and architectural designs that could sustain long-term identity and goal coherence in generative models
we provide concrete guarantees for the efficiency and correctness of the sampling algorithm complementing the empirical success of
diffusion
diffusion models
we provide concrete guarantees for the efficiency and correctness of the sampling algorithm complementing the empirical success of diffusion models with rigorous theory
finally these step-wise rewards are used to calculate fork-relative advantages blended with trajectory-relative
advantages
models llms
finally these step-wise rewards are used to calculate fork-relative advantages blended with trajectory-relative advantages to train the llm for tool use
this tradeoff leaves neutral atom systems stuck between slow but accurate
readout
spin readout
this tradeoff leaves neutral atom systems stuck between slow but accurate readout and fast but unreliable readout
the question of internal mechanisms that modulate
traveling
traveling waves
the question of internal mechanisms that modulate traveling waves of sos is still unanswered although it is established that it is an adaptation mechanism that mediates them
the optimal control law features a strong low-frequency actuation from the bottom jet which targets the
main
optimal control
the optimal control law features a strong low-frequency actuation from the bottom jet which targets the main vortex shedding while the top and lateral jets address higher-frequency less energetic phenomena
diverse emission patterns from precessing super-eddington disks formed in
tidal
tidal field
diverse emission patterns from precessing super-eddington disks formed in tidal disruption events
a popular opinion is that much of the contextual influences arise from feedback from higher visual
areas
brain regions
a popular opinion is that much of the contextual influences arise from feedback from higher visual areas whose neurons have larger receptive fields
we leverage multi-electrode array recordings from the ventral visual stream--including v1 v4 and inferotemporal it cortex--to investigate how distributed neural populations encode and
represent
receptive fields
we leverage multi-electrode array recordings from the ventral visual stream--including v1 v4 and inferotemporal it cortex--to investigate how distributed neural populations encode and represent visual information
while resting-state fmri studies have revealed large-scale network correlates of creative potential electroencephalography
eeg
brain-computer interface
while resting-state fmri studies have revealed large-scale network correlates of creative potential electroencephalography eeg offers a temporally precise and scalable approach to capture the fast oscillatory dynamics that underlie spontaneous neural organization
for instances with more than 100 jobs exact methods such as mip and dynamic
programming
dynamic programming
for instances with more than 100 jobs exact methods such as mip and dynamic programming become computationally intractable
by learning continuous-time dynamics directly from data the lnn enables the filters to adapt to complex nonlinear motion and achieve accurate
tracking
multi-object tracking
by learning continuous-time dynamics directly from data the lnn enables the filters to adapt to complex nonlinear motion and achieve accurate tracking of highly maneuvering objects in clutter
msad a deep dive into model selection for time series
anomaly
anomaly detection
msad a deep dive into model selection for time series anomaly detection
we analyse 19 spiral disks from the cosmological rtnscrimhd azahar suite deriving line-of-sight integrated maps to measure median magnetic-field strength b specific energies thermal turbulent magnetic and cosmic-ray and star formation rate sfr star formation surface density sigma_
mathrm
galactic disk
we analyse 19 spiral disks from the cosmological rtnscrimhd azahar suite deriving line-of-sight integrated maps to measure median magnetic-field strength b specific energies thermal turbulent magnetic and cosmic-ray and star formation rate sfr star formation surface density sigma_ mathrm sfr and specific sfr ssfr
inference-cost-aware dynamic tree construction for efficient
inference
large language models llms
inference-cost-aware dynamic tree construction for efficient inference in large language models
evolutionary game theory offers a general framework to study how behaviors evolve by
social
game theory
evolutionary game theory offers a general framework to study how behaviors evolve by social learning in a population
although the evaluation was limited to simulation these results establish
predictive
predictive processing
although the evaluation was limited to simulation these results establish predictive processing as a universal and scalable computational principle pointing toward robust flexible and autonomous caregiving robots while offering theoretical insight into the human brain s ability to achieve flexible adaptation in uncertain real-world environments
we present a mathcal o log 5 m -competitive algorithm for the
mpmd
online algorithm
we present a mathcal o log 5 m -competitive algorithm for the mpmd problem
self-improvement has emerged as a mainstream paradigm for advancing the
reasoning
reasoning capabilities
self-improvement has emerged as a mainstream paradigm for advancing the reasoning capabilities of large vision-language models lvlms where models explore and learn from successful trajectories iteratively
we focus our presentation on a recently proposed method by chernozhukov
et
existing methods
we focus our presentation on a recently proposed method by chernozhukov et al
designing a secure and resilient distributed smartphone participant data
collection
data collection
designing a secure and resilient distributed smartphone participant data collection system
a hybrid genetic algorithm combining a global
search
genetic algorithm
a hybrid genetic algorithm combining a global search with a local gradient-based optimizer was used to determine the optimal jet actuation parameters in an experiment-in-the-loop setup
bridging the gap between empirical welfare maximization and conditional
average
average treatment effect
bridging the gap between empirical welfare maximization and conditional average treatment effect estimation in policy learning
in particular a 4 -additive spanner is a subgraph that preserves all pairwise distances up to an
additive
spanning trees
in particular a 4 -additive spanner is a subgraph that preserves all pairwise distances up to an additive error of 4
lateral ventricular brain-computer interface system with lantern-inspired
electrode
brain-computer interface
lateral ventricular brain-computer interface system with lantern-inspired electrode for stable performance and memory decoding
based on our characterization we design a policy optimization algorithm that uses machine
learning
machine learning
based on our characterization we design a policy optimization algorithm that uses machine learning to predict counterfactual outcomes and then plugs in these predictions to estimate the pareto frontier then the decision-maker can select the policy that optimizes their desired tradeoff after which policy evaluation can be performed on the test set as usual
the main results are the existence and uniqueness of a regular mild solution to the hjb equation a verification theorem and the synthesis of optimal
feedback
linear control
the main results are the existence and uniqueness of a regular mild solution to the hjb equation a verification theorem and the synthesis of optimal feedback controls
symbiosis emergence and abandonment in nature a coordination
game
evolutionary game
symbiosis emergence and abandonment in nature a coordination game approach