eamag/beyond_benchmarks · Datasets at Hugging Face

modeling epidemics on multiplex networks epidemic threshold and

basic

disease transmission

modeling epidemics on multiplex networks epidemic threshold and basic reproduction number

slideagent employs specialized agents and decomposes reasoning into three specialized levels-global page and element-to construct a

structured

reasoning capabilities

slideagent employs specialized agents and decomposes reasoning into three specialized levels-global page and element-to construct a structured query-agnostic representation that captures both overarching themes and detailed visual or textual cues

distributed quantum computing dqc provides a promising route toward scalable quantum

computation

quantum walk

distributed quantum computing dqc provides a promising route toward scalable quantum computation where entanglement-assisted locc and circuit knitting represent two complementary approaches

this study experimentally tested whether short-term exposure to narrow ai tools enhances core

cognitive

ai use

this study experimentally tested whether short-term exposure to narrow ai tools enhances core cognitive abilities or simply optimizes task performance

these findings demonstrate that post-covid-19 regulatory reforms effectively reduced network interconnectedness and systemic vulnerability in the european

banking

european banking

these findings demonstrate that post-covid-19 regulatory reforms effectively reduced network interconnectedness and systemic vulnerability in the european banking system

empirically our algorithms consistently outperform existing baselines in terms of size-accuracy tradeoffs and runtime even when

data

real-world datasets

empirically our algorithms consistently outperform existing baselines in terms of size-accuracy tradeoffs and runtime even when data assumptions are violated across a wide range of datasets

we propose a taxonomy of data-efficient llm

post-training

training data

we propose a taxonomy of data-efficient llm post-training methods covering data selection data quality enhancement synthetic data generation data distillation and compression and self-evolving data ecosystems

structural vulnerability assessment in urban

transport

mobility networks

structural vulnerability assessment in urban transport networks a network-wide geometric approach using gromov-wasserstein

this can potentially help to reduce bias in

causal

causal effect

this can potentially help to reduce bias in causal effect estimation arising from hidden confounders

improving classification of occluded objects through

scene

computer vision

improving classification of occluded objects through scene context

our findings suggest the smc has a higher production of eu with respect to the alpha -elements than the

milky

galactic disk

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

furthermore political and institutional support was identified as critical to the civic

tool

civic tool

furthermore political and institutional support was identified as critical to the civic tool s success

considering structured data with an underlying feature space of small dimension we show that maximizing the mutual information implies i finding an appropriate projection space and ii building a neural representation with the

appropriate

abstract representations

considering structured data with an underlying feature space of small dimension we show that maximizing the mutual information implies i finding an appropriate projection space and ii building a neural representation with the appropriate metric

simulation results demonstrate that the proposed approach significantly outperforms some baseline approaches and other state-of-the-art deep

reinforcement

reinforcement learning

simulation results demonstrate that the proposed approach significantly outperforms some baseline approaches and other state-of-the-art deep reinforcement learning algorithms

existing automated approaches though increasingly leveraging large

language

large language

existing automated approaches though increasingly leveraging large language models llms remain largely confined to structured tabular data and cannot adequately address the heterogeneity of social media analysis

the minimum cardinality any subset of the

tree

tree embedding

the minimum cardinality any subset of the tree s vertices must have so that all clusters of vertices further away than some l do not exceed a cardinality threshold

767 by feng niazadeh and saberi for unweighted

graphs

regular graphs

767 by feng niazadeh and saberi for unweighted graphs whose second batch consists of independently arriving nodes

our data structure supports tau i and tau -1 i

queries

query complexity

our data structure supports tau i and tau -1 i queries in o 1 time sidestepping the lower bound of golynski soda 2009 that holds for general permutations

climate and land use change impact perceptions were

analysed

land use

climate and land use change impact perceptions were analysed with machine learning to quantify their influence

behind this polarization empirical studies have identified social susceptibility personal prejudice and personal experience as dominant factors in

opinion

opinion formation

behind this polarization empirical studies have identified social susceptibility personal prejudice and personal experience as dominant factors in opinion formation on environmental issues

we thus confirm that adaptive higher-order methods achieve superlinear convergence for certain degenerate problems as long as p is large enough and provide sharp bounds on the order of

convergence

superlinear convergence

we thus confirm that adaptive higher-order methods achieve superlinear convergence for certain degenerate problems as long as p is large enough and provide sharp bounds on the order of convergence one can expect in the limit

however classical fixed-position antenna fpa

isac

communication isac

however classical fixed-position antenna fpa isac systems fail to fully utilize spatial degrees of freedom dofs resulting in limited gains for both radar sensing and communication functionalities

reconfigurable intelligent surfaces ris reshape wave

propagation

reconfigurable intelligent surface

reconfigurable intelligent surfaces ris reshape wave propagation and extend coverage but they enlarge the beam search space at the base station making exhaustive sweeps inefficient due to control overhead and latency

the model elucidates how capacity constraints shape the fidelity and memorability of experiences how semantic processing introduces systematic distortions in episodic recall and how

episodic

working memory

the model elucidates how capacity constraints shape the fidelity and memorability of experiences how semantic processing introduces systematic distortions in episodic recall and how episodic replay can recombine previous experiences

this work establishes a clean dichotomy the optimal time

complexity

time complexity

this work establishes a clean dichotomy the optimal time complexity to support central string queries in compressed space is either theta log n log log n or theta log log n

the results expose limitations in current llms capacity for representation alignment highlighting the need for further research on robust alignment between

language

vision-language-action vla

the results expose limitations in current llms capacity for representation alignment highlighting the need for further research on robust alignment between language and internal agent representations

maximal load shedding verification for neural network models of ac

line

line switching

maximal load shedding verification for neural network models of ac line switching

experimenting with llama-3 and qwen-3 models of different sizes and popular supervised fine-tuning sft and preference optimization datasets and algorithms we find that the sft phase generally establishes a model s values and subsequent

preference

preference data

experimenting with llama-3 and qwen-3 models of different sizes and popular supervised fine-tuning sft and preference optimization datasets and algorithms we find that the sft phase generally establishes a model s values and subsequent preference optimization rarely re-aligns these values

yet the classic theoretical results of population

genetics

population size

yet the classic theoretical results of population genetics e

randomizing the structure of a network is a classic procedure used to estimate the statistical

significance

correlation network

randomizing the structure of a network is a classic procedure used to estimate the statistical significance of properties of the network such as transitivity centrality and community structure

such a latched state can provide a superior charge sensing signal for qubit readout and it can have a lifetime chosen to be long enough that the charge sensed

readout

qubit readout

such a latched state can provide a superior charge sensing signal for qubit readout and it can have a lifetime chosen to be long enough that the charge sensed readout can be high fidelity

score-based constrained generative modeling via

langevin

diffusion models

score-based constrained generative modeling via langevin diffusions with boundary conditions

however the practical use of phonon polaritons remains limited in part due to the lack of precise control over the

phonon

phonon polaritons

however the practical use of phonon polaritons remains limited in part due to the lack of precise control over the phonon polariton dispersion as crystal lattice vibrations are often inert to external stimuli

in some cases late-time mergers induce the formation of

extended

dense gas

in some cases late-time mergers induce the formation of extended gas disks by delivering fresh gas and angular momentum

building new end-effectors in simulation the robot can identify the general

tool

tool usage

building new end-effectors in simulation the robot can identify the general tool geometries most beneficial for a task

we present maps masked attribution-based probing of strategies a behaviorally validated computational tool that tests whether explanations derived from artificial neural networks

anns

neural networks

we present maps masked attribution-based probing of strategies a behaviorally validated computational tool that tests whether explanations derived from artificial neural networks anns can also explain human vision

based on the data we associate each patient to one or more diseases and construct complex

comorbidity

comorbidity networks

based on the data we associate each patient to one or more diseases and construct complex comorbidity networks associated with large patient cohorts characterized by an age interval and sex

furthermore we introduce vnia visual narrative intent alignment a

multimodal

vision-language models

furthermore we introduce vnia visual narrative intent alignment a multimodal dataset specifically created to facilitate the development and evaluation of vlm steering techniques

pilot distortion design for toa obfuscation in

uplink

uplink communication

pilot distortion design for toa obfuscation in uplink ofdm communication

inputdsa demixing then comparing recurrent and externally

driven

dynamical systems

inputdsa demixing then comparing recurrent and externally driven dynamics

the model is trained on heterogeneous qps to minimize the

expected

reinforcement learning

the model is trained on heterogeneous qps to minimize the expected objective value evaluated on the projected solutions

our analysis highlights an intrinsic separation between asymptotic and non-asymptotic

guarantees

theoretical guarantees

our analysis highlights an intrinsic separation between asymptotic and non-asymptotic guarantees with the latter suffering from an unavoidable overhead

we focus on an important safety problem that is already challenging for

humans

trustworthy ai

we focus on an important safety problem that is already challenging for humans fact-verification of ai outputs

as a result the gromov-wasserstein distance can be used to rank edges depending on their criticality with respect to their individual impact on the overall infrastructure and level allowing for prioritizing maintenance emergency planning and enhancing the resilience of the

urban

mobility networks

as a result the gromov-wasserstein distance can be used to rank edges depending on their criticality with respect to their individual impact on the overall infrastructure and level allowing for prioritizing maintenance emergency planning and enhancing the resilience of the urban transport network

socio-cognitive agent-oriented evolutionary

algorithm

genetic algorithm

socio-cognitive agent-oriented evolutionary algorithm with trust-based optimization

this study aims to analyze the impact of expanding the search space of the optimization phase and the

robustness

object detection

this study aims to analyze the impact of expanding the search space of the optimization phase and the robustness of the adaptability of the detector in identifying edges of a set of natural images and specialized subsets extracted from the same image set

5 nm separating nonmagnetic nanoflakes from larger ones with a

magnetic

magnetic ground

5 nm separating nonmagnetic nanoflakes from larger ones with a magnetic ground state emerging from several energetically competing spin configurations

meanwhile the resource allocation problem is solved using a successive

convex

resource allocation

meanwhile the resource allocation problem is solved using a successive convex approximation sca -based algorithm

in this work we propose cola-world which for the first time successfully realizes this synergistic paradigm resolving the core

challenge

deep learning

in this work we propose cola-world which for the first time successfully realizes this synergistic paradigm resolving the core challenge in joint learning through a critical warm-up phase that effectively aligns the representations of the from-scratch lam with the pre-trained world model

additionally we connect for the first time the chromosome diagram to the two-stream age-metallicity relation allowing us to link the p1 and p2

stars

stellar population

additionally we connect for the first time the chromosome diagram to the two-stream age-metallicity relation allowing us to link the p1 and p2 stars to the distinct star formation tracks proposed to be in-situ and ex-situ contributions to the cluster s assembly

although per-iteration cost can exceed that of classical multilevel schemes the method is efficient and consistently outperforms newton s method

gradient

zeroth-order methods

although per-iteration cost can exceed that of classical multilevel schemes the method is efficient and consistently outperforms newton s method gradient descent and the multilevel newton method indicating that second-order methods can outperform first-order methods even when newton s method is initially slow

phylogenetic trees capture evolutionary relationships among

isolates

phylogenetic tree

phylogenetic trees capture evolutionary relationships among isolates and provide a natural framework for detecting such adaptive signals

comparative evaluations show that these proposed methods perform better than existing approaches in both collision

avoidance

collision avoidance

comparative evaluations show that these proposed methods perform better than existing approaches in both collision avoidance and task assignment

autonomous vehicles avs are transforming the future of transportation through advances in intelligent

perception

autonomous driving

autonomous vehicles avs are transforming the future of transportation through advances in intelligent perception decision-making and control systems

accurate world models are essential for enabling agents to think plan and reason effectively in

complex

real-world scenarios

accurate world models are essential for enabling agents to think plan and reason effectively in complex dynamic settings

although recent advances have introduced real-world stochasticity in nonlinear public goods

game

game theory

although recent advances have introduced real-world stochasticity in nonlinear public goods game pgg such stochasticity remains static neglecting its origin in the external environment as well as the coevolution of system stochasticity and cooperative behavior driven by environmental dynamics

the era of agentic organization learning to organize with

language

natural language

the era of agentic organization learning to organize with language models

while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle normative

reasoning

language models

while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle normative reasoning remains underexplored

one recurring problem in this task is the weaknesses found in some detectors such as the difficulty in detecting loose edges and the lack of context to

extract

object detection

one recurring problem in this task is the weaknesses found in some detectors such as the difficulty in detecting loose edges and the lack of context to extract relevant information from specific problems

this research presents a novel racing and

overtaking

collision avoidance

this research presents a novel racing and overtaking agent capable of learning to reliably navigate a track and overtake opponents in both simulation and reality

finally numerical comparisons among a dynamic programming solutions for the markovian sis model b transnn-based optimal control and c the proposed transnn-based receding horizon

control

predictive control

finally numerical comparisons among a dynamic programming solutions for the markovian sis model b transnn-based optimal control and c the proposed transnn-based receding horizon control are presented

robust non-negative proximal gradient algorithm for

inverse

gradient flow

robust non-negative proximal gradient algorithm for inverse problems

geohabnet incorporates key factors such as dispersal probabilities and habitat availability in a network framework for better understanding habitat connectivity for host-dependent

species

ecological communities

geohabnet incorporates key factors such as dispersal probabilities and habitat availability in a network framework for better understanding habitat connectivity for host-dependent species such as pathogens arthropod pests or pollinators

the growing complexity of integrated photonics necessitates compact low-power

devices

integrated photonics

the growing complexity of integrated photonics necessitates compact low-power devices that transcend traditional material-centric design approaches

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

fault-tolerant quantum

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

developing a multi-task ensemble geometric deep network for

supply

supply chain

developing a multi-task ensemble geometric deep network for supply chain sustainability and risk management

our initial approach uses solve_bvp to approximate optimal

control

optimal control

our initial approach uses solve_bvp to approximate optimal control trajectories

in the absence of disturbances we find that standard inverse optimal safe controllers have a certain degree of

gain

bounded disturbances

in the absence of disturbances we find that standard inverse optimal safe controllers have a certain degree of gain margin

we present results from crocodile-dwarf a suite of cosmological zoom-in hydrodynamic simulations of isolated field dwarf galaxies with halo

masses

stellar mass function

we present results from crocodile-dwarf a suite of cosmological zoom-in hydrodynamic simulations of isolated field dwarf galaxies with halo masses of sim10 10 m_ odot at z 0 performed with the textsc gadget4-osaka code

edges between isolates separated by more than seven internal nodes were pruned to emphasise local

evolutionary

phylogenetic tree

edges between isolates separated by more than seven internal nodes were pruned to emphasise local evolutionary structure

24 96 pc the b-fields in the dusty and molecular outflows of arp 220 the closest 78 mpc ultra-luminous infrared galaxy hosting two interacting

nuclei

galactic nuclei

24 96 pc the b-fields in the dusty and molecular outflows of arp 220 the closest 78 mpc ultra-luminous infrared galaxy hosting two interacting nuclei denoted as east and west

more broadly they point to an intrinsic neural signature of adaptive brain function marked by efficient yet flexible network

organization

functional connectivity

more broadly they point to an intrinsic neural signature of adaptive brain function marked by efficient yet flexible network organization that may support creative and adaptive cognition

though being dynamically equivalent our results also explain why location-dependent variations in feedback strength cause differences in the propagation of

traveling

traveling waves

though being dynamically equivalent our results also explain why location-dependent variations in feedback strength cause differences in the propagation of traveling waves between both adaptation mechanisms

our work which strives to induct the essence of behavioural

game

game theory

our work which strives to induct the essence of behavioural game theory into the world of ants is first ever report of realizing sampling equilibrium in scenarios not involving human players

in this work we propose a framework for modeling diverse

persona-based

preference optimization

in this work we propose a framework for modeling diverse persona-based preferences by learning to aggregate outputs from multiple rubric-conditioned judges

we establish the first update-time separation between dynamic algorithms against oblivious adversaries and those against adaptive adversaries in natural dynamic graph problems based on popular fine-grained

complexity

time complexity

we establish the first update-time separation between dynamic algorithms against oblivious adversaries and those against adaptive adversaries in natural dynamic graph problems based on popular fine-grained complexity hypotheses

unlike conventional compressing approaches that address only a subset of these requirements limited numerical precision and limited number of neurons in the network

spikefit

spike train

unlike conventional compressing approaches that address only a subset of these requirements limited numerical precision and limited number of neurons in the network spikefit treats the allowed weights discrete values themselves as learnable parameters co-optimized with the model allowing for optimal clusterization-aware training cat of the model s weights at low precision 2- 4- or 8-bit which results in higher network compression efficiency as well as limiting the number of unique synaptic connections to a value required by neuromorphic processor

we propose basis voting a plurality-rule estimator - novel in the spatial literature - that consistently identifies

causal

causal effects

we propose basis voting a plurality-rule estimator - novel in the spatial literature - that consistently identifies causal effects only under the assumption that in a spatial basis expansion of the exposure and confounder there exist several basis functions in the support of the exposure but not the confounder

we introduce two new city population datasets that use consistent

city

urban systems

we introduce two new city population datasets that use consistent city definitions across countries and over time

boundary vector cells bvcs are a class of

neurons

brain regions

boundary vector cells bvcs are a class of neurons in the brains of vertebrates that encode environmental boundaries at specific distances and allocentric directions playing a central role in forming place fields in the hippocampus

this fully demonstrates the advantages of this generative image

fusion

multimodal reasoning

this fully demonstrates the advantages of this generative image fusion method drawing inspiration from human cognition in enhancing structural consistency and detail quality

using an argument based on schur functions we also show that the newly exhibited coherent

states

quantum correlations

using an argument based on schur functions we also show that the newly exhibited coherent states asymptotically minimize position-momentum uncertainty

in this paper we propose a new test-time alignment method called adaptive importance sampling on pre-logits

aisp

test-time alignment

in this paper we propose a new test-time alignment method called adaptive importance sampling on pre-logits aisp on the basis of the sampling-based model predictive control with the stochastic control input

for this problem we develop a direct debiased machine

learning

debiased machine learning

for this problem we develop a direct debiased machine learning framework with an end-to-end algorithm

test-time alignment of large language models llms attracts attention because fine-tuning

llms

large language

test-time alignment of large language models llms attracts attention because fine-tuning llms requires high computational costs

our recursive algorithm generates each spanning

tree

spanning trees

our recursive algorithm generates each spanning tree in constant amortized time using o n 2 space

the method combines classical preparation of a perturbed

ground

ground state

the method combines classical preparation of a perturbed ground state with short-time quantum evolution of product states sampled from it

2024 develops riesz regression for automatic debiased machine learning which directly estimates the

riesz

riesz representer

2024 develops riesz regression for automatic debiased machine learning which directly estimates the riesz representer or equivalently the bias-correction term by minimizing the mean squared error

stochastic dynamics of urban predator-prey systems integrating human

disturbance

human disturbance

stochastic dynamics of urban predator-prey systems integrating human disturbance and functional responses

the corresponding combinatorial problem is a version of the steiner tree packing problem and the network coding question asks whether the multicast

coding

network coding

the corresponding combinatorial problem is a version of the steiner tree packing problem and the network coding question asks whether the multicast coding rate exceeds the tree-packing rate

unifying regression-based and design-based

causal

causal effects

unifying regression-based and design-based causal inference in time-series experiments

this modification enhances the magnetic anisotropy along the c axis leading to a significant increase in magnetization at low temperatures and under high magnetic fields contrary to conventional expectations for

magnetic

magnetic anisotropy

this modification enhances the magnetic anisotropy along the c axis leading to a significant increase in magnetization at low temperatures and under high magnetic fields contrary to conventional expectations for magnetic dilution

for this reason a lrsga method is proposed where the approximation to

second-order

zeroth-order methods

for this reason a lrsga method is proposed where the approximation to second-order mixed derivatives are obtained by rank-one updates

furthermore increasing the fermi energy of the topological insulator enhances the surface plasmon and

phonon

phonon polaritons

furthermore increasing the fermi energy of the topological insulator enhances the surface plasmon and phonon contributions inducing a blueshift of the dppp branches and bringing them closer to resonance with the magnon mode thereby increasing the hybridization strength

our primary contribution is the novel imposition of explicit constraints directly within the

flow

flow matching

our primary contribution is the novel imposition of explicit constraints directly within the flow matching process ensuring that the generated trajectories adhere to vital safety and kinematic rules

investigation of the intrinsic hidden spin

texture

hidden spin texture

investigation of the intrinsic hidden spin texture and spin-state segregation in centrosymmetric monolayer dichalcogenide effectiveness of the electric-field approach

we validate this model by collapsing several unsteered

robots

robotic manipulation

we validate this model by collapsing several unsteered robots without true shape information

our results demonstrate that a modified monte carlo-based approach significantly outperforms traditional q-learning and two exhaustive search patterns illustrating its potential in adapting

rl

reinforcement learning

our results demonstrate that a modified monte carlo-based approach significantly outperforms traditional q-learning and two exhaustive search patterns illustrating its potential in adapting rl to complex environments

with enough data optimal performance is attained through model s specialisation towards the target but it can be hard to reach for

training

learning algorithm

with enough data optimal performance is attained through model s specialisation towards the target but it can be hard to reach for training algorithms which get attracted by sub-optimal solutions predicted by the theory

fully programmable plasmonic pt-symmetric dimer with epsilon near zero and phase-change materials for

integrated

photonic circuits

fully programmable plasmonic pt-symmetric dimer with epsilon near zero and phase-change materials for integrated photonics