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as an alternative to established hole-based photonic crystal cavities we introduce corrugated triangular dinosaur photonic crystal cavities and develop a tapered quasi loss-free cavity-waveguide interface to adiabatically interconvert bloch and | waveguide | waveguide modes | as an alternative to established hole-based photonic crystal cavities we introduce corrugated triangular dinosaur photonic crystal cavities and develop a tapered quasi loss-free cavity-waveguide interface to adiabatically interconvert bloch and waveguide modes |
our work not only reveals the key role of anisotropic epc in controlling the thermal and optical properties of tairte4 but also provides insights into designing polarization-sensitive optoelectronic | devices | photonic circuits | our work not only reveals the key role of anisotropic epc in controlling the thermal and optical properties of tairte4 but also provides insights into designing polarization-sensitive optoelectronic devices based on topological semimetals |
motivated by practical applications we use this baseline to develop a new framework for fast approximate matrix multiplication | amm | approximation factor | motivated by practical applications we use this baseline to develop a new framework for fast approximate matrix multiplication amm via low-degree approximations of the cksu polynomials |
our key idea is to decouple visual and linguistic adaptation by introducing two lightweight modules a domain classifier to identify the input image type and a dual adapter mechanism comprising a prompt adapter for | language | vision-language models vlms | our key idea is to decouple visual and linguistic adaptation by introducing two lightweight modules a domain classifier to identify the input image type and a dual adapter mechanism comprising a prompt adapter for language modulation and a visual adapter for vision feature adjustment |
the orbital angular momentum oam of light is a versatile degree of freedom with transformative impact across optical | communication | optical communication | the orbital angular momentum oam of light is a versatile degree of freedom with transformative impact across optical communication imaging and micromanipulation |
we conducted a simulation study to examine confounding bias in ite estimates generated by | causal | causal effect | we conducted a simulation study to examine confounding bias in ite estimates generated by causal forest and x-learner models under varying conditions including the presence or absence of true heterogeneity |
adapting large language models llms via reinforcement learning rl is often bottlenecked by the | generation | large language | adapting large language models llms via reinforcement learning rl is often bottlenecked by the generation stage which can consume over 75 of the training time |
we propose a functional evaluation metric for | generative | generative models | we propose a functional evaluation metric for generative models based on the relative density ratio rdr designed to characterize distributional differences between real and generated samples |
self-supervised synthetic pretraining for inference of stellar mass embedded in | dense | dense gas | self-supervised synthetic pretraining for inference of stellar mass embedded in dense gas |
our results provide fundamental insights into light-matter interactions in | solids | optical properties | our results provide fundamental insights into light-matter interactions in solids at the nanoscale and are vital for optimally designing the new generation of absorption-based flexible optoelectronic devices |
we theoretically analyze the convergence behavior of the proposed scheme and quantify its gains in expected | communication | channel estimation | we theoretically analyze the convergence behavior of the proposed scheme and quantify its gains in expected communication efficiency and training accuracy |
the price-pareto growth model of networks with | community | mobility networks | the price-pareto growth model of networks with community structure |
we show that a subtle modification of standard bifurcation analysis identifies such | critical | phase transition | we show that a subtle modification of standard bifurcation analysis identifies such critical numbers including those associated with discreteness- and noise-induced transitions |
to solve this high-dimensional non-convex problem under uncertain channels we develop a deep | reinforcement | reinforcement learning | to solve this high-dimensional non-convex problem under uncertain channels we develop a deep reinforcement learning solution framework based on the proximal policy optimization ppo algorithm that integrates distribution-aware action modeling and a multi-branch actor network |
although the evaluation was limited to simulation these results establish predictive | processing | 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 uncerta... |
in this work we propose a flow decomposition-and-aggregation framework built upon an | inversion-free | flow matching | in this work we propose a flow decomposition-and-aggregation framework built upon an inversion-free formulation to address these limitations |
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 | world models | 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 |
discrete dynamics arise naturally in systems with broken temporal translation | symmetry | quantum walk | discrete dynamics arise naturally in systems with broken temporal translation symmetry and are typically described by first-order recurrence relations representing classical or quantum markov chains |
modulating the free-electron wave function with light brings new opportunities to create attosecond electron pulse trains to probe the | quantum | quantum dot | modulating the free-electron wave function with light brings new opportunities to create attosecond electron pulse trains to probe the quantum coherence of systems with significantly improved spatial resolution and to generate classical and non-classical states of light with wide tunability |
normal curves in sub-finsler lie groups branching for strongly | convex | strongly convex | normal curves in sub-finsler lie groups branching for strongly convex norms and face stability for polyhedral norms |
programming assistants powered by large language | models | large language | programming assistants powered by large language models llms have become widely available with conversational assistants like chatgpt proving particularly accessible to less experienced programmers |
in this paper we show new strongly polynomial work-depth tradeoffs for computing single-source shortest paths sssp in non-negatively weighted directed | graphs | polynomial time | in this paper we show new strongly polynomial work-depth tradeoffs for computing single-source shortest paths sssp in non-negatively weighted directed graphs in parallel |
we combine deep photometric data in the cosmos and xmm-lss fields with high-resolution | cosmological | host galaxy | we combine deep photometric data in the cosmos and xmm-lss fields with high-resolution cosmological hydrodynamical simulations to explore two key questions 1 how does the galaxy stellar mass function particularly in the dwarf mstar 10 9 |
finally type iii-d galaxies have low mass surface density | disks | circumgalactic medium | finally type iii-d galaxies have low mass surface density disks sigma delta r_ mathrm exp sim 0 |
in this paper we investigate this idea in the classical paradigm of the ultimatum | game | game theory | in this paper we investigate this idea in the classical paradigm of the ultimatum game which we theoretically modify to introduce prejudice at the level of players terming its intensity as prejudicity |
using numerical simulations we quantify the degradation in performance due to disorder and identify single-qubit rotations two-qubit entangling gates and quantum information transport as | particularly | qubit readout | using numerical simulations we quantify the degradation in performance due to disorder and identify single-qubit rotations two-qubit entangling gates and quantum information transport as particularly susceptible |
the fact that our algorithm works for typical uniformly random constant degree regular graphs rather than for all constant degree graphs is unavoidable thanks to the following impossibility result that we obtain for every fixed k in n the approximation factor of any algorithm for average distance that works for all con... | graphs | -approximation algorithm | the fact that our algorithm works for typical uniformly random constant degree regular graphs rather than for all constant degree graphs is unavoidable thanks to the following impossibility result that we obtain for every fixed k in n the approximation factor of any algorithm for average distance that works for all con... |
in the data-scarce regime generalization occurs via benign overfitting or fails via harmful | overfitting | machine learning | in the data-scarce regime generalization occurs via benign overfitting or fails via harmful overfitting depending on the amount of data and we characterize the transition boundary |
despite recent advances in 3d human motion | generation | video generation | despite recent advances in 3d human motion generation mogen on standard benchmarks existing models still face a fundamental bottleneck in their generalization capability |
to overcome the potential non-smoothness of the hyper-objective and the computational challenges associated with the hessian matrix we utilize penalty and augmented lagrangian methods to reformulate the original | problem | minimax optimal | to overcome the potential non-smoothness of the hyper-objective and the computational challenges associated with the hessian matrix we utilize penalty and augmented lagrangian methods to reformulate the original problem as a single-level one |
it introduces two key capabilities automated feedback generation using a fine-tuned large language model and visualization of student | code | code review | it introduces two key capabilities automated feedback generation using a fine-tuned large language model and visualization of student code submissions to uncover learning patterns |
we show that if the system is controllable then incorporating this as prior knowledge does not relax the conditions required for | data-driven | data-driven stabilization | we show that if the system is controllable then incorporating this as prior knowledge does not relax the conditions required for data-driven stabilization |
specifically we propose an additive instrumental variable framework to identify mean potential | outcomes | potential outcomes | specifically we propose an additive instrumental variable framework to identify mean potential outcomes and the average treatment effect with a weighting function |
while these machine learning models boast impressive accuracy a related concern is how to assess and maintain | calibration | machine learning | while these machine learning models boast impressive accuracy a related concern is how to assess and maintain calibration in the predictions these models make |
we design polynomial-time approximations to the optimum online algorithm achieving guarantees of 7 8 for vertex-weighted | graphs | -approximation algorithm | we design polynomial-time approximations to the optimum online algorithm achieving guarantees of 7 8 for vertex-weighted graphs and 2 sqrt 2 -2 approx 0 |
the results establish the first unified baseline of | photonic | single photons | the results establish the first unified baseline of photonic machine-learning performance revealing complementary strengths between variational hardware-native and hybrid approaches |
this work introduces steervlm a lightweight steering module designed to guide | vision-language | vision-language models vlms | this work introduces steervlm a lightweight steering module designed to guide vision-language models vlms towards outputs that better adhere to desired instructions |
by examining the challenges in data-efficient llm | post-training | training data | by examining the challenges in data-efficient llm post-training we highlight open problems and propose potential research avenues |
while many studies rely on branch length information the topology of | phylogenetic | phylogenetic tree | while many studies rely on branch length information the topology of phylogenetic trees particularly their degree of imbalance offers a robust framework for inferring evolutionary dynamics when timing data is uncertain |
one experiment is robustly more informative than another if the decision maker s maxmin expected utility after observing the output of the former is always at least her maxmin expected | utility | randomized experiments | one experiment is robustly more informative than another if the decision maker s maxmin expected utility after observing the output of the former is always at least her maxmin expected utility after observing the latter |
our results demonstrate that roboos-next achieves superior performance across heterogeneous embodiments validating its effectiveness in enabling lifelong scalable and robust | multi-robot | robotic systems | our results demonstrate that roboos-next achieves superior performance across heterogeneous embodiments validating its effectiveness in enabling lifelong scalable and robust multi-robot collaboration |
non-monotone submodular maximization subject to a matroid | constraint | submodular maximization | non-monotone submodular maximization subject to a matroid constraint under noise |
a unified framework for spatial and temporal treatment effect | boundaries | treatment effect | a unified framework for spatial and temporal treatment effect boundaries theory and identification |
consequently the average performance achieved by llms remains | considerably | superior performance | consequently the average performance achieved by llms remains considerably below the human baseline |
recent advances in data collection and technology enable a deeper understanding of complex urban commuting yet few studies have rigorously analyzed the temporal stability and origin-destination od heterogeneity of | route | route choice | recent advances in data collection and technology enable a deeper understanding of complex urban commuting yet few studies have rigorously analyzed the temporal stability and origin-destination od heterogeneity of route choice |
the tip density reaches sim 2 mathrm cm -3 implying an ambient medium density of sim 10 -3 | mathrm | interstellar medium | the tip density reaches sim 2 mathrm cm -3 implying an ambient medium density of sim 10 -3 mathrm cm -3 in agreement with the galactic warm ionized medium at a distance of sim 5 kpc |
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 | numerical simulations | 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 |
we find that dwarf agn selected by infrared colors are the most distinct | population | active galactic | we find that dwarf agn selected by infrared colors are the most distinct population with the highest star formation rates and lowest stellar masses |
to mitigate the prohibitive overhead associated with full | channel | channel state information csi | to mitigate the prohibitive overhead associated with full channel state information at the transmitter csit we propose a partial-csit-based beamforming scheme that leverages randomized steering vectors and limited user-side feedback based on signal quality measurements |
we show that such collections of relation decoders can be highly compressed by simple order-3 tensor networks without significant loss in | decoding | sparse autoencoders | we show that such collections of relation decoders can be highly compressed by simple order-3 tensor networks without significant loss in decoding accuracy |
we investigate whether large language models | llms | language models | we investigate whether large language models llms can act as in-context meta-learners for this task |
the focus is on the mathematical description of these interactions and their role in deriving differential | systems | complex systems | the focus is on the mathematical description of these interactions and their role in deriving differential systems that describe the aforementioned dynamics |
these results highlight the significant room for improving the mathematical | reasoning | reasoning curriculum | these results highlight the significant room for improving the mathematical reasoning in current llms |
firstly our deep learning model predicts correspondence probabilities and reliabilities for every pair of a | trajectory | autonomous driving | firstly our deep learning model predicts correspondence probabilities and reliabilities for every pair of a trajectory and sensor measurements |
the evolutionary mechanisms of cooperative behavior represent a fundamental topic in complex systems and | evolutionary | game theory | the evolutionary mechanisms of cooperative behavior represent a fundamental topic in complex systems and evolutionary dynamics |
for bounded treewidth permutation classes which include the above-mentioned separable class we further reduce the | space | tree embedding | for bounded treewidth permutation classes which include the above-mentioned separable class we further reduce the space overhead to a lower order additive term making our data structure succinct |
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 learning | 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 |
by varying the parameters within the objective function and the constraints we determine how the optimal | spatial | spatial structure | by varying the parameters within the objective function and the constraints we determine how the optimal spatial structure may vary when individuals differ in their information gathering ability and how this variation differs in the context of resource constraints |
by moving from monolithic models to orchestrated intelligence this approach seeks to align medical | ai | artificial intelligence | by moving from monolithic models to orchestrated intelligence this approach seeks to align medical ai with the first principle of medicine care that is transparent equitable and centered on the individual |
large language models llms are increasingly used as | raters | llm raters | large language models llms are increasingly used as raters for evaluation tasks |
to test this we conducted a randomized controlled experiment n 486 comparing a two variants of reflective human-led modes in which the llm elicits elaboration through suggestions or questions against b a proactive model-led mode in which the | llm | llm responses | to test this we conducted a randomized controlled experiment n 486 comparing a two variants of reflective human-led modes in which the llm elicits elaboration through suggestions or questions against b a proactive model-led mode in which the llm independently rewrites ideas |
the coordination game payoff structure captures the insight that mutualistic | strategies | control strategies | the coordination game payoff structure captures the insight that mutualistic strategies lead to robust advantages only after such biological markets reach a certain scale |
our framework unifies riesz regression for automatic | debiased | debiased machine learning | our framework unifies riesz regression for automatic debiased machine learning covariate balancing targeted maximum likelihood estimation tmle and density-ratio estimation |
a view-conditional video inpainting model is trained to learn a robust geometry prior by denoising realistically synthesized warped | images | computer vision | a view-conditional video inpainting model is trained to learn a robust geometry prior by denoising realistically synthesized warped images and to inpaint occluded or missing regions across virtual viewpoints eliminating the need for explicit 3d annotations |
high-resolution x-ray data are best suited for outflow s studies and the observed | absorption | ionized gas | high-resolution x-ray data are best suited for outflow s studies and the observed absorption lines on heavy elements are evidence of the physical properties of an absorbing gas |
along the way we also develop improved indexes for short patterns offering | better | pattern matching | along the way we also develop improved indexes for short patterns offering better trade-offs in this practically relevant special case |
these results demonstrate that spiral density waves can persist in fully cosmological | disks | circumgalactic medium | these results demonstrate that spiral density waves can persist in fully cosmological disks linking internal dynamical processes to galaxy assembly and offering testable predictions for present and future surveys such as jwst and roman |
we conduct a comprehensive comparison between redllm pretrained with prefix language | modeling | large language models llms | we conduct a comprehensive comparison between redllm pretrained with prefix language modeling lm and decllm pretrained with causal lm at different model scales ranging from sim 150m to sim 8b |
we further establish a strong baseline solution that outperforms prior | approaches | existing methods | we further establish a strong baseline solution that outperforms prior approaches under these challenging conditions |
while large language models have been applied to energy systems as code generators and parameter extractors no existing implementation deploys llms as autonomous coordinators managing the complete workflow from natural | language | language models | while large language models have been applied to energy systems as code generators and parameter extractors no existing implementation deploys llms as autonomous coordinators managing the complete workflow from natural language input to multi-appliance scheduling |
while a multi-agent approach based on large language models llms represents a promising strategy to surpass the | capabilities | large language models llms | while a multi-agent approach based on large language models llms represents a promising strategy to surpass the capabilities of single models its success is critically dependent on synergistic team composition |
however the fundamental question of emph which problems with a deterministic | complexity | time complexity | however the fundamental question of emph which problems with a deterministic complexity of omega log n can be solved exponentially faster using randomization still remains wide open |
we release the code and data for aot-psyphybench to encourage further progress in the physical and temporal | reasoning | models vlms | we release the code and data for aot-psyphybench to encourage further progress in the physical and temporal reasoning capabilities of vlms |
to ensure reward fidelity our automated grader calibration pipeline systematically purges noise from the llm-based | reward | human feedback | to ensure reward fidelity our automated grader calibration pipeline systematically purges noise from the llm-based reward model with minimal human supervision |
to this end we introduce a novel metric for comparing both intrinsic | recurrent | dynamical systems | to this end we introduce a novel metric for comparing both intrinsic recurrent and input-driven dynamics called inputdsa idsa |
while deep learning dominates recent mtl research support vector machines svms and twin | svms | machine learning | while deep learning dominates recent mtl research support vector machines svms and twin svms twsvms remain relevant due to their interpretability theoretical rigor and effectiveness with small datasets |
1 pc the magnetic field lines appear roughly perpendicular to the | filament | magnetic field | 1 pc the magnetic field lines appear roughly perpendicular to the filament s long axis in contrast to the smaller-scale structure sim 0 |
metacognition and confidence dynamics in advice taking from | generative | ai use | metacognition and confidence dynamics in advice taking from generative ai |
recent work has shown that different large language models llms converge to similar and accurate | input | vision-language models | recent work has shown that different large language models llms converge to similar and accurate input embedding representations for numbers |
in the limited cases where ground truth is available through exact classical | simulation | quantum mechanics | in the limited cases where ground truth is available through exact classical simulation we find that it agrees with the results we obtain from the quantum device |
however the performance of all previous digital quantum simulations has been matched by classical methods and it has thus far remained unclear whether near-term intermediate-scale quantum hardware could offer any computational | advantage | quantum batteries | however the performance of all previous digital quantum simulations has been matched by classical methods and it has thus far remained unclear whether near-term intermediate-scale quantum hardware could offer any computational advantage in this area |
experimental results on multiple benchmark | datasets | real-world datasets | experimental results on multiple benchmark datasets demonstrate the superior performance of the proposed method in terms of both accuracy and sparsity |
we study integer programs where the constraint matrix a has such a path-like | structure | integer programs | we study integer programs where the constraint matrix a has such a path-like structure every non-zero coefficient appears in at most two consecutive constraints |
this problem is inherently challenging due to its | non-convex | optimization problem | this problem is inherently challenging due to its non-convex nature |
anti gravitron a statistical physics perspective on multidimensional metrics of | polarizing | gromov-wasserstein distance | anti gravitron a statistical physics perspective on multidimensional metrics of polarizing inequality |
notably the phase offsets suggest structurally distinct causes of rural and urban accident | risk | crash risk | notably the phase offsets suggest structurally distinct causes of rural and urban accident risk with urban regions exhibiting increasing acceleration in accident scaling potentially linked to growth in vehicle numbers size and weight |
the key task of machine learning is to minimize the loss function that measures the model fit to the | training | deep learning | the key task of machine learning is to minimize the loss function that measures the model fit to the training data |
we introduce a general diploid population model with self-fertilization and possible overlapping generations and study the genealogy of a sample of n genes as the population | size | population size | we introduce a general diploid population model with self-fertilization and possible overlapping generations and study the genealogy of a sample of n genes as the population size n tends to infinity |
our primary contribution is the novel imposition of explicit constraints directly within the | flow | optical flow | 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 |
current non-invasive neuroimaging techniques trade off between spatial | resolution | temporal resolution | current non-invasive neuroimaging techniques trade off between spatial resolution and temporal resolution |
instrumental variable methods are fundamental to | causal | treatment effect | instrumental variable methods are fundamental to causal inference when treatment assignment is confounded by unobserved variables |
interpreting visual observations and natural | language | vision-language-action vla | interpreting visual observations and natural language instructions for complex task execution remains a key challenge in robotics and ai |
super-heisenberg scaling which scales as n - beta with beta 1 in terms of the number of particles n or t - beta in terms of the evolution time t is better than heisenberg | scaling | super-heisenberg scaling | super-heisenberg scaling which scales as n - beta with beta 1 in terms of the number of particles n or t - beta in terms of the evolution time t is better than heisenberg scaling in quantum metrology |
skeb provides a foundation for assessing unlearning completeness | robustness | llm raters | skeb provides a foundation for assessing unlearning completeness robustness and overall behavior in llms |
however even under this condition classical | proper | proper scoring | however even under this condition classical proper scoring rules fail to elicit correct forecasts |
deep networks have shown remarkable performance across a wide range of tasks yet getting a global concept-level | understanding | convolutional neural | deep networks have shown remarkable performance across a wide range of tasks yet getting a global concept-level understanding of how they function remains a key challenge |
data selection is a critical aspect of reinforcement learning with verifiable rewards rlvr for enhancing the | reasoning | reinforcement learning | data selection is a critical aspect of reinforcement learning with verifiable rewards rlvr for enhancing the reasoning capabilities of large language models llms |
in thisproject we have used machine learning techniques like logistic regression random forest and | support | machine learning | in thisproject we have used machine learning techniques like logistic regression random forest and support vector machines to analyze the health claims data and identify demographic and medical factors that play a crucial role in predicting all-cause readmissions |
this energy is believed to impact the star formation activity and contribute to the | quenching | massive galaxies | this energy is believed to impact the star formation activity and contribute to the quenching of galaxies |
as a consequence the two approaches are interchangeable in several respects and share the same theoretical | guarantees | theoretical guarantees | as a consequence the two approaches are interchangeable in several respects and share the same theoretical guarantees under common conditions |
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