Split (3)

train · 9.78k rows

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.

prompt stringlengths 41 511	target stringlengths 1 25	keyword stringclasses 697 values	full_sentence stringlengths 48 1.25k
cooperative task spaces for multi-arm manipulation	control	multi-robot collaboration	cooperative task spaces for multi-arm manipulation control based on similarity transformations
this design incorporates a temporal attention in vision encoder enabling the model to better capture the progression of	actions	temporal understanding	this design incorporates a temporal attention in vision encoder enabling the model to better capture the progression of actions and the relationships between frames before passing visual tokens to the llm
for a simple mutation model we find exact solutions for the	equilibrium	evolutionary dynamics	for a simple mutation model we find exact solutions for the equilibrium moments of the fitness distribution
classical optical flow methods rely on mathematical models and strong assumptions about	motion	optical flow	classical optical flow methods rely on mathematical models and strong assumptions about motion which limit their accuracy in complex scenarios
we study attention in mobile augmented reality	ar	augmented reality	we study attention in mobile augmented reality ar using object recall as a proxy outcome
we open-source our complete data generation pipeline and	training	real-world datasets	we open-source our complete data generation pipeline and training code providing a reproducible foundation for future research
moreover with only 1-hour of fmri data from a new subject we achieve results comparable to current	methods	brain decoding	moreover with only 1-hour of fmri data from a new subject we achieve results comparable to current methods trained on full 40-hour recordings
artificial intelligence has advanced significantly through deep learning	reinforcement	deep learning	artificial intelligence has advanced significantly through deep learning reinforcement learning and large language and vision models
identifying geometric third-order nonlinear	transport	third-order nonlinear	identifying geometric third-order nonlinear transport in disordered materials
our method is interpretable and can easily be adapted to other	datasets	dataset comprising	our method is interpretable and can easily be adapted to other datasets offering many future directions for research and practical applications
here we study continual learning and the compositional reuse of learned computations in	recurrent	artificial neural	here we study continual learning and the compositional reuse of learned computations in recurrent neural network rnn models using a novel two-system approach one system that infers what computation to perform and one that implements how to perform it
given r as an input we present a polynomial-time o n r-1 2 -approximation algorithm for this	maximization	submodular maximization	given r as an input we present a polynomial-time o n r-1 2 -approximation algorithm for this maximization problem which does not require prior knowledge of the specific decomposition
the current advancements in beam shaping techniques their	impact	beam shaping	the current advancements in beam shaping techniques their impact on the nanoparticle characteristics and their broader implications for scaling pulsed laser ablation in liquids to meet industrial demands are highlighted offering a comprehensive perspective on the future of this dynamic field
however its application is often hindered by low	textbf	reinforcement learning	however its application is often hindered by low textbf reward density in deep search scenarios where agents expend significant exploratory costs for infrequent and often null final rewards
this is a concise pedagogical introduction to the dynamic field of	open	quantum computing	this is a concise pedagogical introduction to the dynamic field of open quantum systems governed by markovian master equations
this paper proposes a fully prior-free model of experimentation in which the decision maker observes the entire distribution of signals	generated	randomized experiments	this paper proposes a fully prior-free model of experimentation in which the decision maker observes the entire distribution of signals generated by a known experiment under an unknown distribution of the state of the world
in this work we show that the quantum walk technique fails to produce a fast	algorithm	open quantum	in this work we show that the quantum walk technique fails to produce a fast algorithm improving the known or even the trivial upper bound on the query complexity
we evaluate our method across a large dataset of real-life	autonomous	autonomous driving	we evaluate our method across a large dataset of real-life autonomous navigation scenarios demonstrating that it maintains high accuracy while significantly reducing computational cost
this study experimentally tested whether short-term exposure to narrow ai tools enhances core	cognitive	ai assistance	this study experimentally tested whether short-term exposure to narrow ai tools enhances core cognitive abilities or simply optimizes task performance
shortcuts spurious rules that perform well during training but fail to generalize present a major challenge to the reliability of	deep	deep learning	shortcuts spurious rules that perform well during training but fail to generalize present a major challenge to the reliability of deep networks geirhos et al
we apply this design space to three distinct human-agent	collaboration	human-machine teaming	we apply this design space to three distinct human-agent collaboration scenarios a bystander interaction b cooperative tasks and c shared control demonstrating its capacity to generate adaptable scalable and cross-domain communication strategies
shortcuts spurious rules that perform well during training but fail to generalize present a major challenge to the reliability of	deep	deep learning	shortcuts spurious rules that perform well during training but fail to generalize present a major challenge to the reliability of deep networks geirhos et al
bayesian nonlinear pde inference via gaussian process	collocation	langevin dynamics	bayesian nonlinear pde inference via gaussian process collocation with application to the richards equation
experimental results showed that compared to the baseline which prompts intermediate reasoning without presenting	pragmatic	mathematical reasoning	experimental results showed that compared to the baseline which prompts intermediate reasoning without presenting pragmatic theories 0-shot chain-of-thought our methods enabled language models to achieve up to 9
in this work we aim to explain this conflict by exploring how language models manipulate	numbers	vision-language models	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
these findings support a clear takeaway improving	representation	representation learning	these findings support a clear takeaway improving representation learning is a direct and useful path to robust world models delivering reliable long-horizon predictions without enlarging the dynamics module
many existing genuine multipartite entanglement gme witnesses for continuous-variable cv quantum systems typically rely on quadrature	measurements	entanglement entropy	many existing genuine multipartite entanglement gme witnesses for continuous-variable cv quantum systems typically rely on quadrature measurements which is challenging to implement in platforms where the cv degrees of freedom can be indirectly accessed only through qubit readouts
however conventional methods such as closed-circuit television dashcam footage and sensor-based detection separate	detection	event cameras	however conventional methods such as closed-circuit television dashcam footage and sensor-based detection separate detection from verification suffer from limited flexibility and require dense infrastructure or high penetration rates restricting adaptability and scalability to shifting incident hotspots
with the increasing number of flexible energy devices in distribution grids coordination between transmission system operators tsos and distribution system operators dsos becomes critical for	optimal	optimal power flow	with the increasing number of flexible energy devices in distribution grids coordination between transmission system operators tsos and distribution system operators dsos becomes critical for optimal system operation
despite recent progress enabled by diffusion models current methods often lack	faithfulness	diffusion models	despite recent progress enabled by diffusion models current methods often lack faithfulness to the actual seen images
dynamic dyck and tree edit distance decompositions and reductions to string	edit	tree embedding	dynamic dyck and tree edit distance decompositions and reductions to string edit distance
unifiedfl introduces i a common gnn to parameterize all architectures ii distance-driven clustering via euclidean distances between	clients	federated learning	unifiedfl introduces i a common gnn to parameterize all architectures ii distance-driven clustering via euclidean distances between clients parameters and iii a two-tier aggregation policy balancing convergence and diversity
we investigate predator-prey school interactions in aquatic environments using a stochastic differential equation sde -based particle-level model that incorporates attraction repulsion alignment and	environmental	ecological interactions	we investigate predator-prey school interactions in aquatic environments using a stochastic differential equation sde -based particle-level model that incorporates attraction repulsion alignment and environmental noise
enrichment from feedback is necessary to mix with the inflowing gas and allow it to	glow	ionized gas	enrichment from feedback is necessary to mix with the inflowing gas and allow it to glow in o vi
we model different scenarios of competition between tumor cells using a static	evolutionary	evolutionary game	we model different scenarios of competition between tumor cells using a static evolutionary game in which cells compete for nutrients and oxygen and might choose to stay and proliferate in the primary tumor or opt to a motility strategy in order to find resources in a metastatic site
length or sycophancy automatically extracting relevant	features	findings highlight	length or sycophancy automatically extracting relevant features without pre-specifying hypotheses remains challenging
we study a bi-virus susceptible-infected-susceptible sis epidemic model in which individuals are either susceptible or	infected	viral replication	we study a bi-virus susceptible-infected-susceptible sis epidemic model in which individuals are either susceptible or infected with one of two virus strains and consider mutation-driven transitions between strains
in this work we show that the quantum walk technique fails to produce a fast algorithm improving the known or even the trivial upper bound on the	query	query complexity	in this work we show that the quantum walk technique fails to produce a fast algorithm improving the known or even the trivial upper bound on the query complexity
despite multiple efforts to understand the problem in these simple graph families the computational complexity of the problem had remained unsettled and our hardness results answer open questions by bhabak and harutyunyan and harutyunyan and hovhannisyan concerning the problem s complexity in k -cycle and k -path	graphs	bipartite graphs	despite multiple efforts to understand the problem in these simple graph families the computational complexity of the problem had remained unsettled and our hardness results answer open questions by bhabak and harutyunyan and harutyunyan and hovhannisyan concerning the problem s complexity in k -cycle and k -path graph...
we propose that this behavior is not simply a flaw indicative of information loss but an adaptation to different information retrieval demands during pre-training some tasks require uniform recall across the entire input a long-term memory	demand	memory demand	we propose that this behavior is not simply a flaw indicative of information loss but an adaptation to different information retrieval demands during pre-training some tasks require uniform recall across the entire input a long-term memory demand while others prioritize the most recent information a short-term memory d...