prompt stringlengths 41 511 | target stringlengths 1 25 | keyword stringclasses 697
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the third example has a discrete multivalued treatment that can increase or | decrease | treatment assignment | the third example has a discrete multivalued treatment that can increase or decrease multiple times over time |
orchvis advances human-centered design for multi-agent | systems | human-ai interaction | orchvis advances human-centered design for multi-agent systems by combining transparent visualization with adaptive autonomy |
we demonstrate that the precession of the disk and wind drive time-dependent obscuration and reprocessing of | x-ray | gamma -ray | we demonstrate that the precession of the disk and wind drive time-dependent obscuration and reprocessing of x-ray radiation |
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 | 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 |
interaction-augmented instruction modeling the synergy of prompts and | interactions | human-ai interaction | interaction-augmented instruction modeling the synergy of prompts and interactions in human-genai collaboration |
model and hyperparameter selection are critical but challenging in machine learning typically | requiring | variable selection | model and hyperparameter selection are critical but challenging in machine learning typically requiring expert intuition or expensive automated search |
advancing interdisciplinary approaches to online | safety | online safety | advancing interdisciplinary approaches to online safety research |
even when these global minima are aligned to the hidden configuration there can be exponentially many higher | energy | global minima | even when these global minima are aligned to the hidden configuration there can be exponentially many higher energy local minima that are all unaligned with the hidden solution |
while successful in language and vision their adoption in | eeg | electroencephalography eeg | while successful in language and vision their adoption in eeg has lagged due to the heterogeneity of public datasets which are collected under varying protocols devices and electrode configurations |
we then apply it to a higher-order spin-glass hamiltonian with 156 | qubits | quantum computing | we then apply it to a higher-order spin-glass hamiltonian with 156 qubits executed on ibm quantum processors |
the state of brain emulation report 2025 provides a comprehensive reassessment of the field s progress since sandberg and bostrom s 2008 whole brain | emulation | surrogate brain | the state of brain emulation report 2025 provides a comprehensive reassessment of the field s progress since sandberg and bostrom s 2008 whole brain emulation roadmap |
we study the impact of static disorder on a globally-controlled superconducting quantum | computing | super-heisenberg scaling | we study the impact of static disorder on a globally-controlled superconducting quantum computing architecture based on a quasi-two-dimensional ladder geometry r |
stage 1 performs a brief cold start and then math-only | rl | reinforcement learning rl | stage 1 performs a brief cold start and then math-only rl with verifiable rewards to develop reasoning skills |
large language models llms such as chatgpt are | increasingly | language models | large language models llms such as chatgpt are increasingly integrated into high-stakes decision-making yet little is known about their susceptibility to social influence |
these subclumps exhibit parabolic morphologies consistent with ram-pressure-confined droplets with their heads tending to point toward the | galactic | quiescent galaxies | these subclumps exhibit parabolic morphologies consistent with ram-pressure-confined droplets with their heads tending to point toward the galactic plane |
contribution of task-irrelevant stimuli to | drift | receptive fields | contribution of task-irrelevant stimuli to drift of neural representations |
kinematic elemental and structural dependences on | metallicity | bulge stars | kinematic elemental and structural dependences on metallicity in the galactic bulge |
we investigate potential heating mechanisms including direct agn photoionisation uv fluorescent excitation from young star | clusters | star formation rates | we investigate potential heating mechanisms including direct agn photoionisation uv fluorescent excitation from young star clusters and shock excitation |
reinforcement learning rl is widely used to produce robust robotic manipulation policies but fine-tuning vision-language-action vla | models | vision-language models vlms | 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 |
the results illustrate how safety-first opl provides an implementable interpretable tool for risk-sensitive | policy | policy evaluation | the results illustrate how safety-first opl provides an implementable interpretable tool for risk-sensitive policy design quantifying the efficiency-insurance trade-off that policymakers face when outcomes are volatile |
in this work we present a fully unsupervised machine learning ml workflow that detects and classifies these defects directly from | molecular | molecular dynamics | in this work we present a fully unsupervised machine learning ml workflow that detects and classifies these defects directly from molecular dynamics data |
there are two main problems in the task of predicting the dynamic evolution of complex networks on the one hand existing methods usually use simple graphs to describe the relationships in complex networks however this approach can only capture pairwise relationships while there may be rich non-pairwise structured | relationships | correlation network | there are two main problems in the task of predicting the dynamic evolution of complex networks on the one hand existing methods usually use simple graphs to describe the relationships in complex networks however this approach can only capture pairwise relationships while there may be rich non-pairwise structured relationships in the network |
ct reconstruction provides radiologists with | images | image reconstruction | ct reconstruction provides radiologists with images for diagnosis and treatment yet current deep learning methods are typically limited to specific anatomies and datasets hindering generalization ability to unseen anatomies and lesions |
although most related studies have focused on prediction methods research on the predictability of complex | systems | complex systems | although most related studies have focused on prediction methods research on the predictability of complex systems has received increasing attention across disciplines--aiming to provide theories and tools to address a key question what are the limits of prediction accuracy |
score-based generative models based on stochastic differential equations sdes achieve impressive performance in sampling from unknown | distributions | generative models | score-based generative models based on stochastic differential equations sdes achieve impressive performance in sampling from unknown distributions but often fail to satisfy underlying constraints |
in this study we investigate how the ai mathematician aim system can operate as a research | partner | mathematical reasoning | in this study we investigate how the ai mathematician aim system can operate as a research partner rather than a mere problem solver |
this real-time control strategy is then benchmarked against an offline | optimal | control strategy | this real-time control strategy is then benchmarked against an offline optimal dispatch to evaluate flexibility performance |
this work tackles the problem of identifying asymptomatic individuals considering a classic si susceptible-infected network epidemic model where a fraction of the infected nodes are not observed as | infected | viral replication | this work tackles the problem of identifying asymptomatic individuals considering a classic si susceptible-infected network epidemic model where a fraction of the infected nodes are not observed as infected i |
we develop a stochastic variational expectation-maximization | algorithm | debiased machine learning | we develop a stochastic variational expectation-maximization algorithm to jointly optimize the neural and probabilistic components |
on the limitation of evaluating machine unlearning using only a single | training | machine learning | on the limitation of evaluating machine unlearning using only a single training seed |
in the cold dark environments of pre-stellar cores where the temperatures are below 10 k ne can condense onto the surface of | interstellar | star formation | 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 |
dual-channel technology diffusion spatial decay and network contagion in supply | chain | supply chain | dual-channel technology diffusion spatial decay and network contagion in supply chain networks |
furthermore for specific pairs of models and riesz representer estimation methods we can automatically obtain the covariate balancing property without explicitly solving the covariate | balancing | covariate balancing | furthermore for specific pairs of models and riesz representer estimation methods we can automatically obtain the covariate balancing property without explicitly solving the covariate balancing objective |
0 and sample-efficient reinforcement learning on | continuous | reinforcement learning | 0 and sample-efficient reinforcement learning on continuous control tasks without replay buffers |
quantum computing could greatly aid in this understanding as it can potentially provide exponential speedups over classical approaches thereby | offering | quantum batteries | quantum computing could greatly aid in this understanding as it can potentially provide exponential speedups over classical approaches thereby offering insights into the complex electronic structure of actinide compounds |
the dataset allows for a clearer analysis of road conditions by compiling essential | data | autonomous driving | the dataset allows for a clearer analysis of road conditions by compiling essential data including vehicle speed acceleration rotation rates and magnetic field intensity along with the visual and spatial context provided by gis weather and video data |
we further establish unconditional lower bounds demonstrating that the time and query complexities of our algorithms are optimal up to mathrm polylog n | factors | lower bound | we further establish unconditional lower bounds demonstrating that the time and query complexities of our algorithms are optimal up to mathrm polylog n factors hidden within the tilde o cdot notation below |
in this paper we study the problem of continuous-time | reinforcement | optimal control | in this paper we study the problem of continuous-time reinforcement learning where the unknown system dynamics are represented using nonlinear ordinary differential equations odes |
a problem of achieving minimum time consensus for a | set | optimal control | a problem of achieving minimum time consensus for a set of n second-order lti system agents with bounded inputs and fuel constraints is considered |
on the randomized locality of matching problems in | regular | bipartite graphs | on the randomized locality of matching problems in regular graphs |
by dynamically adjusting the coding sequence the metasurface could enable multi-mode orbital angular momentum oam beam generation dynamic | beam | beam pattern | by dynamically adjusting the coding sequence the metasurface could enable multi-mode orbital angular momentum oam beam generation dynamic beam scanning and precise direction finding |
nanovla routing decoupled vision-language understanding for nano-sized generalist | robotic | vision-language models vlms | nanovla routing decoupled vision-language understanding for nano-sized generalist robotic policies |
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 |
through numerical simulations validated with real population and temperature data it is possible to understand the | disease | disease transmission | through numerical simulations validated with real population and temperature data it is possible to understand the disease dynamics under many different scenarios and make future projections offering insights for potential effective control strategies as well as addressing the timing for these strategies to be adopted |
while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle | normative | llm inference | while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle normative reasoning remains underexplored |
while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle | normative | reasoning tasks | while large language models llms have demonstrated remarkable performance across various reasoning tasks their ability to handle normative reasoning remains underexplored |
certification and classification of linear quantum | error | quantum error correction | certification and classification of linear quantum error mitigation methods |
simultaneously strongly aligning with human | visual | computer vision | simultaneously strongly aligning with human visual attention |
such simulations -- for which classical methods are often inaccurate -- are critical to advancing our knowledge and understanding of | quantum | classical simulation | such simulations -- for which classical methods are often inaccurate -- are critical to advancing our knowledge and understanding of quantum chemistry and materials underpinning a wide range of fields from biochemistry to clean-energy technologies and chemical synthesis |
bridging the gap between empirical welfare maximization and conditional average treatment effect estimation in | policy | policy learning | bridging the gap between empirical welfare maximization and conditional average treatment effect estimation in policy learning |
in this work we aim to explain this conflict by exploring how | language | large language | in this work we aim to explain this conflict by exploring how language models manipulate numbers and quantify the lower bounds of accuracy of these mechanisms |
vision-language models vlms such as clip which are pre-trained on large image-text pairs offer a promising solution by enhancing robustness and data efficiency in | medical | sparse autoencoders | vision-language models vlms such as clip which are pre-trained on large image-text pairs offer a promising solution by enhancing robustness and data efficiency in medical imaging tasks |
extensive experiments demonstrate the effectiveness of our model in panoramic visual perception and graphics-ready 3d scene | generation | image generation | extensive experiments demonstrate the effectiveness of our model in panoramic visual perception and graphics-ready 3d scene generation opening new possibilities for immersive and physically realistic virtual world generation |
in network-based sis models of infectious disease transmission | infection | viral replication | in network-based sis models of infectious disease transmission infection can only occur between directly connected individuals |
we give the first super-constant bound to this problem demonstrating an example with a coding advantage of | omega | upper bound | we give the first super-constant bound to this problem demonstrating an example with a coding advantage of omega log k |
to address these challenges we argue that post-hoc attribution can be reframed as a reasoning problem where | answers | question answering | to address these challenges we argue that post-hoc attribution can be reframed as a reasoning problem where answers are decomposed into constituent units each tied to specific context |
a unified theory for causal inference direct debiased | machine | machine learning | a unified theory for causal inference direct debiased machine learning via bregman-riesz regression |
however in recent years with the rise of generative ai especially large | language | large language models llms | however in recent years with the rise of generative ai especially large language models llm and particularly with the widespread popularity of the chatgpt model that concern became practical |
in this paper we explore the stellar mass profiles of a sample of disk galaxies with similar stellar | masses | bulge stars | in this paper we explore the stellar mass profiles of a sample of disk galaxies with similar stellar masses sim 10 10 m _ odot using iac stripe82 legacy project data |
here we introduce a topological framework that defines and detects localities in human | mobility | human mobility | here we introduce a topological framework that defines and detects localities in human mobility networks |
in numerous experiments the results reveal the importance of the proposed method in hierarchical networks in the visual tasks and also validate the hypothesis that the | hierarchical | higher-order visual | in numerous experiments the results reveal the importance of the proposed method in hierarchical networks in the visual tasks and also validate the hypothesis that the hierarchical information content in brain regions of the visual system can be quantified by decoding outcomes to reflect an information hierarchy |
for a graph g the parameter treedepth measures the minimum depth among all forests f called elimination | forests | tree edit distance | for a graph g the parameter treedepth measures the minimum depth among all forests f called elimination forests such that g is a subgraph of the ancestor-descendant closure of f |
previous work established one-way reductions showing how suffix array queries can be answered using for example rank | queries | compressed indexing | previous work established one-way reductions showing how suffix array queries can be answered using for example rank queries on the burrows-wheeler transform |
this study proposes to quantify the structural modifications implied by the disruption of single elements in a transportation network through the | gromov-wasserstein | gromov-wasserstein distance | this study proposes to quantify the structural modifications implied by the disruption of single elements in a transportation network through the gromov-wasserstein distance |
nearest neighbor matching as least squares | density | density estimation | nearest neighbor matching as least squares density ratio estimation and riesz regression |
to effectively learn from these enriched alignments molbridge employs substructure-aware contrastive learning coupled with a self-refinement mechanism that filters out noisy | alignment | test-time alignment | to effectively learn from these enriched alignments molbridge employs substructure-aware contrastive learning coupled with a self-refinement mechanism that filters out noisy alignment signals |
researchers often use specifications that correctly estimate the | average | treatment effect boundaries | researchers often use specifications that correctly estimate the average treatment effect under the assumption of constant effects |
our empirical analysis shows that contractionary monetary policy shocks have significant negative effects on the | macroeconomic | monetary policy | our empirical analysis shows that contractionary monetary policy shocks have significant negative effects on the macroeconomic stars highlighting the nonzero long-run effects of transitory monetary policy shocks |
this framework significantly broadens the set of tools available for analyzing selection in categorical and other discrete | outcomes | potential outcomes | this framework significantly broadens the set of tools available for analyzing selection in categorical and other discrete outcomes offering substantial relevance for empirical work across economics health sciences and social sciences |
to this end we introduce a novel metric for comparing both intrinsic | recurrent | recurrent neural | to this end we introduce a novel metric for comparing both intrinsic recurrent and input-driven dynamics called inputdsa idsa |
artificial intelligence ai systems increasingly match or surpass human experts in | biomedical | physiological signals | artificial intelligence ai systems increasingly match or surpass human experts in biomedical signal interpretation |
we describe this simulation method and compare it with | alternative | classical simulation | we describe this simulation method and compare it with alternative approaches |
our findings introduce a new paradigm in integrated | photonics | photonic circuits | our findings introduce a new paradigm in integrated photonics paving the way for ultracompact modulators and highly tunable on-chip communication systems with reduced power consumption |
beyond lamno _ 3 our work opens an avenue for studying a wider range of | correlated | electronic structure | beyond lamno _ 3 our work opens an avenue for studying a wider range of correlated materials |
in this work we propose a strategy that exploits the principles of non-hermitian physics--specifically the concept of exceptional | points | exceptional points | in this work we propose a strategy that exploits the principles of non-hermitian physics--specifically the concept of exceptional points eps --to transcend these limitations and pave the way for the next generation of versatile high-performance photonic devices |
in particular we show that narrower degree distributions contain longer shortest | loops | scale-free networks | in particular we show that narrower degree distributions contain longer shortest loops as a universal property in a wide class of random networks |
to generate physically and semantically plausible supervision signals we introduce a spatial prior labeling method that guides a | vision-language | vision-language-action vla | to generate physically and semantically plausible supervision signals we introduce a spatial prior labeling method that guides a vision-language model to produce reasonable manipulation orders for distillation |
reasoning about reasoning towards informed and reflective use of | llm | llm reasoning | reasoning about reasoning towards informed and reflective use of llm reasoning in hci |
twinkle twinkle little star roman sees where you are predicting exoplanet transit | yields | interstellar medium | twinkle twinkle little star roman sees where you are predicting exoplanet transit yields in the rosette nebula with the nancy grace roman space telescope |
the external medium also influences the evolution of circumstellar disks and protostellar outflows with the high-density external medium disks grow rapidly but their mass becomes smaller relative to the | protostellar | interstellar medium | the external medium also influences the evolution of circumstellar disks and protostellar outflows with the high-density external medium disks grow rapidly but their mass becomes smaller relative to the protostellar mass and the outflow is sustained over a long duration |
the conditions for the clt exclude certain canonical examples such as the empirical sub-gaussian norm of normally distributed | random | central limit theorem | the conditions for the clt exclude certain canonical examples such as the empirical sub-gaussian norm of normally distributed random variables |
it further decomposes the evaluation of llm performance into six fundamental | capabilities | llm post-training | it further decomposes the evaluation of llm performance into six fundamental capabilities including opinion consistency memory recall logical reasoning lexical fidelity persona tone and syntactic style |
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 | star clusters | 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 |
the feynman path integral formalism has inspired the development of memory-efficient and parallelizable classical | algorithms | quantum walk | the feynman path integral formalism has inspired the development of memory-efficient and parallelizable classical algorithms for simulating quantum computers |
the probability of vacuum metastability and artificial | vacuum | vacuum decay | the probability of vacuum metastability and artificial vacuum decay expert survey results |
we conclude that this framework can be used in the future to design compare and benchmark | obstacle | dynamic obstacles | we conclude that this framework can be used in the future to design compare and benchmark obstacle avoidance methods |
the problem of optimizing the computing resources for distributed machine learning | ml | machine learning | the problem of optimizing the computing resources for distributed machine learning ml and optimization is considered in this paper |
an analytical model supports our experimental observations by linking this robustness to the | band-structure | coupling regimes | an analytical model supports our experimental observations by linking this robustness to the band-structure properties of the interacting modes |
we finally provide numerical evidence for our | theoretical | theoretical guarantees | we finally provide numerical evidence for our theoretical results |
we further discover that issameobject is encoded in a low-dimensional subspace on top of | object | receptive fields | we further discover that issameobject is encoded in a low-dimensional subspace on top of object features and that this signal actively guides attention |
the goal of policy learning is to train a | policy | policy learning | the goal of policy learning is to train a policy function that recommends a treatment given covariates to maximize population welfare |
we adapt the degree-based mean-field dbmf sir model for single-layered complex networks to the | multiplex | multiplex networks | we adapt the degree-based mean-field dbmf sir model for single-layered complex networks to the multiplex setting where each layer has its own degree distribution and infection rate |
communication impact is quantied by a capacity-motivated lower bound obtained from the linear minimum mean-squared error error covariance with a mismatched | channel | wireless communication | communication impact is quantied by a capacity-motivated lower bound obtained from the linear minimum mean-squared error error covariance with a mismatched channel estimate |
tuning magnetic anisotropy through chemical doping is a powerful strategy for designing functional materials with enhanced | magnetic | magnetic properties | tuning magnetic anisotropy through chemical doping is a powerful strategy for designing functional materials with enhanced magnetic properties |
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 | photonic circuits | 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 |
we introduce a framework that captures regimes of containment mitigation and | failure | control strategies | we introduce a framework that captures regimes of containment mitigation and failure to control |
reinforcement finetuning rft is a key technique for aligning large | language | language models | 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 |
reward models rms play a critical role in aligning large language models llms with | human | reward density | reward models rms play a critical role in aligning large language models llms with human preferences |
experimental results showed that compared to the state-of-the-art method sota the accuracy improvement rate in a cg dataset with dynamic | obstacles | obstacle avoidance | experimental results showed that compared to the state-of-the-art method sota the accuracy improvement rate in a cg dataset with dynamic obstacles is 1 |
2024 develops riesz regression for automatic debiased machine learning which directly estimates the riesz representer or equivalently the | bias-correction | bias-correction term | 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 |
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