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A: Sokoban is a single-player complex game in which a player controls an agent whose goal is to place boxes on target locations solely by pushing them; without crossing any obstacles or wallsB: Sokoban is known to be hard [10], mainly due to its combinatorial complexity and the existence of irreversible states...	ACB	ABC	CBA	ABC	Selection 1
A: Using character substitution to generate new named entities becomes a common linguistic phenomenon which is a big challenge for NERB: Nowadays, the informal language environment created by social media has deeply changed the way that people express their thoughtsC: In this paper, we propose a lightweight...	CAB	ACB	CAB	BAC	Selection 4
A: See Supplementary Note 2 for additional qualitative comparisons and for comparisons against uniform random expanders.B: To characterize the hologram reconstruction with the proposed neural étendue expander we simulate a Fourier holographic setup that has been augmented with a neural étendue expanderC: F...	CAB	ABC	CBA	ACB	Selection 1
A: Besides well-studied NLP tasks, joint MTL is also widely applied in various downstream tasksB: One major problem of such tasks is the lack of sufficient labeled dataC: Through joint MTL, one could take advantage of data-rich domains via implicit knowledge sharing. In addition, abundant unlabeled data cou...	ACB	ACB	ABC	CBA	Selection 3
A: The array environment allows you some options for matrix-like equationsB: You will have to manually key the fences, but you’ll have options for alignment of the columns and for setting horizontal and vertical rulesC: The argument to array controls alignment and placement of vertical rules.	BAC	CBA	ABC	CAB	Selection 3
A: Furthermore, the leaves we have attached toB: for which no w′∈Wi′superscript𝑤′subscript𝑊superscript𝑖′w^{\prime}\in W_{i^{\prime}}italic_w start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT ∈ italic_W start_POSTSUBSCRIPT italic_i start_POSTSUPERSCRIPT ′ end_POSTSUPERSCRIPT end_POSTSUBSCRIPT has N⁢(w)∩S=N⁢(w′)∩S𝑁...	BCA	CAB	BAC	ACB	Selection 2
A: Prior extensions of public goods provision to environments with endogenous linking include Galeotti and Goyal (2010), which furthers the specialization result of Bramoullé et alB: (2007)C: These papers emphasize the prevalence of core-periphery architectures as equilibrium networks, but in a setting wher...	CBA	BCA	ABC	ACB	Selection 3
A: Channel Attention: In SISR, we mainly want to recover as much valuable high-frequency information as possibleB: To solve this problem, many methods (Zhang et al., 2018b; MeiC: However, common CNN-based methods treat channel-wise features equally, which lacks flexibility in dealing with different types of...	BCA	BCA	ACB	BAC	Selection 3
A: However, the architecture relies on a convolutional feature encoder, applies a fixed downsampling operation, and is trained to generate images based on a selected dataset. Our architecture is purely based on networks, requires no pretraining, and directly maximizes self-similarity between the synthesized and kn...	BCA	BAC	CAB	BCA	Selection 2
A: The PG-TS algorithm necessarily samples from an approximation of the posterior, to maintain a reasonable computational overheadB: Recent work of Phan et al., (2019) has identified conditions under which sampling from an approximate posterior can lead to linear regret in multi-armed bandit problems. On the ot...	BAC	ABC	CAB	BCA	Selection 4
A: As in [12], we consider each unfairness category individuallyB: For a given unfairness category, we consider as positive examples those that have been labeled as being unfair for the given category, while the remaining sentences are viewed as not unfair.222The dataset labeling distinguishes between potential...	BAC	BAC	ABC	CBA	Selection 3
A: We then introduce the Bayesian predictive probability of satisfaction and posterior predictive robustness as quantities of interest and show how these measures can be used for comparing a collection of spatio-temporal Bayesian modelsB: This property-related comparison can complement common predictive evaluat...	ACB	BCA	ABC	ABC	Selection 2
A: It shows an adjoint situation between 𝐏𝐃𝐏𝐃\mathbf{PD}bold_PD and 𝐄𝐃𝐄𝐃\mathbf{ED}bold_ED, i.eB: the 2-categories of primary doctrines and that of elementary ones that is, primary doctrines with equalityC: That adjoint situation is comonadic. This fact not only reveals the coalgebraic nature of equ...	CBA	BCA	BAC	ABC	Selection 4
A: ForestSimSearch can handle a top-k query in O⁢(k)𝑂𝑘O(k)italic_O ( italic_k ) time once the precomputation is finishedB: Efficient top-k similarity search algorithm : We devise ForestSimSearch for the top-k similarity searchC: Furthermore, we use the fast approximate algorithm to compute the diagonal e...	CBA	BAC	BCA	ABC	Selection 2
A: Table 6: The examples for aspect sentiment coherency found by LSAB: The target aspects are denoted in bold and the underlined words indicates the aspects with coherent sentimentsC: “Pos”, “Neg” and “Neu” represent positive, negative and neutral, respectively.	ABC	BAC	CAB	BCA	Selection 1
A: The operator 𝐋𝐋\mathbf{L}bold_L and 𝐖𝐖\mathbf{W}bold_W are constructed from a multilevel decomposition of the location of predictorsB: This process is somewhat elaborate and the reader is referred to [31] and [32] for all of the detailsC: However, for the exposition in this section it sufficient to k...	CBA	ABC	ACB	BAC	Selection 2
A: QuantumNAT is fundamentally different from existing methods: (i) Prior work focuses on low-level numerical correction in inference only; QuantumNAT embraces more optimization freedom in both training and inferenceB: (ii) PQC has a good built-in error-tolerance which motivates QuantumNAT’s post-measurement qu...	ACB	BCA	BCA	CAB	Selection 1
A: From the results, we can see that the second stage of the TSW algorithm contributes significantly on improving the performance. By using the second stage of the TSW algorithm, the majority of pseudo-outliers are removed. This effectively reduces the ambiguity in the model selection process.B: The AOR and AR...	CBA	CAB	BAC	ABC	Selection 2
A: We now prove our main result, that there are no ugly perfect graphsB: Our proof is a generalization of the proof of the latter result by Bonamy, Groenland, Muller, Narboni, Pekárek andC: This generalizes the same fact which was previously proved for Meyniel graphs [22] (a class which contains chordal gr...	BAC	CBA	ACB	CAB	Selection 3
A: We adopt linear evaluation on the CIFAR-10 in 64×\times×64 resolutions with 1600-epoch pre-trained ResNet-50 on STL-10, and other settings are the same as Sec. V-B. GenURL achieves the highest accuracy among all methods: +3.36%/+3.29%/+2.99% for GenURL pre-training 400/800/1600 epochs over the second-best method...	CAB	BAC	BAC	BCA	Selection 1
A: Under 512kB SRAM/2MB Flash, MCUNetV2 achieves a new record ImageNet accuracy of 71.8% on commercial microcontrollers, which is 3.3% compared to the best solution under the same quantization policy. Lower-bit (int4) or mixed-precision quantization can further improve the accuracy (marked in gray in the table). We...	ACB	CBA	BAC	CAB	Selection 2
A: Experiments show our framework outperforms baseline methods even when its encoder module uses a randomly initialized BERT encoder, showing the power of the new tagging frameworkB: In this competition, we introduce a fresh perspective to revisit the relational event-cause extraction task and propose a novel ...	BCA	CBA	BAC	BCA	Selection 3
A: As shown in Figure 2, for example, Graph Encoder 1 uses embeddings learned by itself as query graphs and embeddings learned by all others as key graphs to compute Encoder 1 contrastive loss. After learning, each trained graph encoder can be utilized to extract graph latent representations from a graph when prese...	CAB	ABC	CBA	ACB	Selection 3
A: In the machine learning literature, this idea was explored by Li and Bowling, (2019), Cogswell et al., (2019) and Ren et al., (2020) with the generation transfer typically implemented as reinitializing the weights of agents’ neural networks. Such an approach inevitably introduces noise into the learning process*...	BAC	CBA	ABC	ACB	Selection 3
A: Control barrier functions (CBFs) were introduced in [3, 4] to render a safe set controlled forward invariantB: Many variations and extensions of CBFs appeared in the literature, e.g., composition of CBFs [5], CBFs for multi-robot systems [6], CBFs encoding temporal logic constraints [7], and CBFs for systems...	BAC	CBA	CBA	ACB	Selection 4
A: Our random restriction lemma shows that if one randomly fixes most of the inputs to a quantum query algorithm, then the algorithm’s behavior on the unrestricted inputs can be approximated by a “simple” function (say, a small decision tree or small DNF formula)B: We then use this random restriction lemma to g...	CBA	BAC	BCA	ABC	Selection 3
A: Furthermore, we also plot adjacency matrices for Bernoulli distribution, Poisson distribution and Signed network. B: Meanwhile, since A𝐴Aitalic_A and Z𝑍Zitalic_Z are known here, one can run DFA and nDFA directly to A𝐴Aitalic_A in Figure 2 with two communities to check the error rates of DFA and nDFAC:...	CBA	CAB	CAB	ABC	Selection 1
A: This, at least partially, can be explained by its on-policy natureB: MA-Trace exhibits lower sample efficiency than the other methods we used for comparisonsC: Adapting the importance correction to accommodate more off-policy data would be an important achievement.	CBA	CBA	BAC	CAB	Selection 3
A: On the one hand, their trust in such decisions could be low due to a lack of in-depth knowledge on how models are learning from the training data. On the other hand, ML experts often have little prior knowledge about the data from particular domainsB: In the InfoVis/VA communities, most of the research in e...	BAC	CAB	CBA	CBA	Selection 1
A: In particular, several recent research works present the benefit of utilizing the polarization domain in recently proposed communication schemes including, but not limited to, MIMO spatial multiplexing [1]; spatial modulation (SM) [2, 3, 4]; non-orthogonal multiple access (NOMA) [5]; and beamforming [6, 7]B...	BAC	ACB	CBA	BAC	Selection 2
A: In other words, online algorithms exists which produce solutions that are only a constant factor worse than the offline optimumB: If the arriving pieces are convex polygons that may be arbitrarily rotated, the task reduces to packing axis-parallel rectangles by first rotating each piece so that a diameter of...	ACB	BCA	ABC	CBA	Selection 2
A: A classic method is mean teacher [17, 34], which aggregates multiple predictions of unlabeled data by a teacher model pre-trained from labeled dataB: The aggregated results work as more reliable pseudo labels for unlabeled data in rest part of the method.C: To alleviate this problem, many researchers [3,...	ABC	BCA	ABC	ACB	Selection 2
A: This section conducts extensive experiments to demonstrate that DFSP is effective for mixed membership community detection and our fuzzy weighted modularity is capable of the estimation of the number of communities for mixed membership weighted networks generated from our MMDF modelB: We conducted all experi...	ABC	CAB	BAC	BAC	Selection 1
A: In this way, the knowledge of previously learned classes can be preserved.B: In these methods, when learning at a new phase, the model of the previous phase is used as the teacher, and the CIL Learner is regularized to produce similar outputs as the teacherC: Many CIL methods mitigate forgetting through...	ACB	CBA	CAB	BAC	Selection 2
A: This adjustment enabled the utilization of visual cues across different modalities. The image similarity was computed by defining the local normalized cross correlation (LNCC) as an average over the LNCCs for each modality (channel). The second modification consisted of a new training strategy to alleviate overf...	ACB	CAB	ABC	BAC	Selection 4
A: a tuple of database values) is entailed by all repairs, or is not entailed by some repair. But, as discussed in [8], the former is too strict, while the latter is not very useful in a practical contextB: Example 1, despite its simplicity, illustrates one of the limitations of the CQA approach. The notion of...	BAC	CBA	ACB	BCA	Selection 1
A: Inspired by their exploration, we examine different node-absorption rates (instead of rewiring edges) to consider different community structures, andB: Salathé and Jones [38] explored the effect of differences in community structure on the outbreak duration, final size, and outbreak peak in simulations of an...	CBA	BAC	ACB	CAB	Selection 4
A: Although polynomial-time and provably optimal, the LP-based approach has a very high time-complexity for it to be practically usefulB: Here, we develop an efficient heuristicC: The general QNR problem can be formulated in terms of hypergraph flows and solved using LP (see Appendix A)	CAB	BCA	ABC	CAB	Selection 2
A: There exist reviews on XAI for AVs, which provide valuable insights from various perspectivesB: These studies expose a variety of approaches, from a universal look to an algorithmic point of viewC: In this sense, the first noteworthy review on XAI for AVs is	BAC	BAC	ABC	BCA	Selection 3
A: The proposed GhostCNN consists of a convolution operation and five stagesB: After each step, the size of the output feature maps are reduced by half till the stage 4C: There are at least two Ghost bottlenecks [7] in each stage, and each bottleneck contains two Ghost modules (its architecture is shown in ...	ABC	BAC	CAB	CBA	Selection 1
A: The design defenses against these types of attacks rely on choosing nonlinear components with specific properties, such as high nonlinearity [7] and high correlation immunity[17]B: Traditionally, stream ciphers are attacked with two approaches: correlation attacks, that exploit possible correlations between ...	BAC	CBA	CAB	CBA	Selection 1
A: Finally, we empirically evaluate the algorithms on multiple games. We show that CDBR outperforms LBR in both Leduc and HUNL and we show that CDBR performs significantly better against SlumBot than any other previous method. Finally, we show that CDRNR outperforms SES in any game and can achieve over half of the ...	ACB	CBA	ABC	ABC	Selection 2
A: In Ecological networks each interaction observed reveals that an edge is present in the underlying network, and the effect of sampling effort can be modelled by taking the observed network after varying numbers of observationsB: It was noted in multiple papers on ecological networks that a lower sampling eff...	ABC	BAC	CAB	CAB	Selection 1
A: Many authors highlight the importance of variables of political, economic, social, and historical nature, in influencing the impact of climatic anomalies on migration processes, emphasi-zing the role of important channels of transmission of the environmental effect to migrationsB: We include in the multiple ...	BAC	BAC	BCA	ABC	Selection 4
A: We remark that, in the fixed learning rate case, one can show that the Optimistic Hedge (24) is identical to Optimistic OMD with the negative-entropy regularizer. However, the adaptive learning rate version (54) can only be interpreted as an FTRL algorithmB: While this can be remedied by the dual stabilizat...	ACB	BAC	CBA	CAB	Selection 1
A: Since φ⁢(A∗)𝜑superscript𝐴\varphi(A^{})italic_φ ( italic_A start_POSTSUPERSCRIPT ∗ end_POSTSUPERSCRIPT ) is a finiteB*: Let ψn=φ∘σnsubscript𝜓𝑛𝜑superscript𝜎𝑛\psi_{n}=\varphi\circ\sigma^{n}italic_ψ start_POSTSUBSCRIPT italic_n end_POSTSUBSCRIPT = italic_φ ∘ italic_σ start_POSTSUPERSCRIPT italic_n end_POS...	CBA	CBA	ACB	CAB	Selection 4
A: The result in Theorem 4 for s≥1/2𝑠12s\geq 1/2italic_s ≥ 1 / 2 (that is, 2⁢k+2≥d2𝑘2𝑑2k+2\geq d2 italic_k + 2 ≥ italic_d) was already derived in Sadhanala et alB: More precisely, these authors established the third term on the right-hand side inC: (2017)	BCA	ACB	BAC	BCA	Selection 2
A: In our framework, rather than directly using the connectivity strength, we decomposed networks into discrete topological states and computed heritability for each state. This granular analysis provides a more accurate estimation of heritability across different functional states of the brain. The resting state m...	CBA	ABC	CBA	BAC	Selection 4
A: ∙∙\bullet∙B: As the iner-event time function τs⁢(θ)subscript𝜏𝑠𝜃\tau_{s}(\theta)italic_τ start_POSTSUBSCRIPT italic_s end_POSTSUBSCRIPT ( italic_θ ) is periodic with period π𝜋\piitalic_π, ϕ⁢(θ+π)=arg⁡(G⁢(τs⁢(θ+π))⁢xθ+π)=arg⁡(−G⁢(τs⁢(θ))⁢xθ)=ϕ⁢(θ)+πitalic-ϕ𝜃𝜋𝐺subscript𝜏𝑠𝜃𝜋subscript𝑥𝜃𝜋𝐺subscript...	CBA	ABC	CAB	BAC	Selection 3
A: In [29], safety verification using barrier functionals for homogeneous distributed parameter systems has been considered. In this work, numerical strategies based on semi-definite programming has been used for the construction of barrier functionals. However, control performance under disturbances has not been c...	CAB	CBA	CBA	BCA	Selection 4
A: [40] show that wearables can predict workplace activity passively, which has the potential to be used as the foundation of systems to automatically block distractions during focus hours and to suggest breaks. Kucukozer-Cavdar et al. [41] also create a model for predicting office workers’ availability and inclina...	ACB	CBA	CAB	ABC	Selection 2
A: We thus assume a single channel and instant for now, and discuss multiple channels and request duration in §III-F. B: The general spectrum allocation problem is to allocate optimal power to an SU’s request across spatial, frequency, and temporal domainsC: We focus on the core function approximation probl...	CBA	BAC	CAB	BCA	Selection 3
A: This group is called the special Euclidean group and is denoted by S⁢E⁢(2)𝑆𝐸2SE(2)italic_S italic_E ( 2 ). In many applications, the congruence with respect to other groups is consideredB: To a human eye, two figures look the same if they are related by a rigid motion. However, since a reflection changes ...	ABC	ABC	BAC	CBA	Selection 3
A: Obviously, this is not guaranteed for each instance of the algorithm. The Gauss-Southwell method leads to faster convergence at the cost of extra computations and evaluations of gradients during the selection of coordinates which can be an issue in large-scale problems [25].B: On the other hand, the use of ...	CBA	BCA	BCA	ABC	Selection 1
A: The Memristor model is significantly more accurate than the Memristor without STP and the two single decay HOTS models. Enabling STP results in the largest increase in accuracy. B: (Fig 6) shows the results. For brevity, we only show results with the Euclidean classifierC: Suppl. Table 3 contains additio...	CAB	BAC	BCA	ABC	Selection 1
A: For these systems, we prove the following:B: We study the convergence time to a δ𝛿\deltaitalic_δ-stable state in Hegselmann-Krause systems with an arbitrary initial state and an arbitrary given social network, where we update one uniformly at random chosen agent in each stepC: To the best of our knowle...	BCA	ACB	ACB	CAB	Selection 4
A: This test set comprised 500 images randomly selected from the test datasetB: To evaluate the model’s performance and assess its generalization capabilities, we created a separate test setC: We applied the trained model to the test set and measured various evaluation criteria as explained in Section 4.2.	ACB	BAC	CAB	CBA	Selection 2
A: The fact that the Bayes optimal algorithm is suboptimal means that even if we enhance KG and EI to plan more than one step ahead, their performance in a frequentist measure might not improve.B: On the contrary, we show that the Bayes optimal algorithm performs sub-optimally with some of the worst model para...	CAB	CBA	ACB	BCA	Selection 1
A: We also run experiments on the ShapeNet dataset Chang et al. (2015). We utilized 3D Steerable CNNs proposed by Weiler et al. (2018b) as equivariant encoder for the 3d voxel input spaceB: In Figure 6 we visualize a TSNE projection of the embeddings of both models. We can see a well structured embedding space ...	BCA	BAC	BCA	ACB	Selection 4
A: Secondly, the measurements are treated as ground-truth readingsB: The subsets are kept because there are published results to compare to. Because of how the data was split up it is not straightforward to generate a new Strong subset, but a new Selection subset was generated and the method evaluated on it. Th...	CBA	BAC	BCA	ACB	Selection 4
A: Training binary latent VAEs with K=2,3𝐾23K=2,3italic_K = 2 , 3 (except for RELAX which uses 3333 evaluations) on MNIST, Fashion-MNIST, and OmniglotB: We report the average ELBO (±1plus-or-minus1\pm 1± 1 standard error) on the training set after 1M steps over 5 independent runsC: Test data bounds are rep...	CBA	ABC	ACB	BAC	Selection 2
A: This is complemented by both analytical results and corresponding simulations. In Section VI, we discuss the deficiencies of the Random selection approach and the challenges wrtB: its practical implementation.C: Then, in Section V we consider different receiver processing techniques and provide their tho...	ACB	ABC	BCA	CBA	Selection 3
A: As we are concerned only with finite sets here, our algorithm already produces computable curves. B: This variant of the problem characterizes the sets which are contained in a rectifiable computable curveC: An interesting connection to the Jones-Scul algorithm was given by Gu, Lutz, and Mayordomo [GLM06...	BAC	CBA	CAB	BAC	Selection 2
A: For the remainder of the section, the chief example of a polymatroid to us is the support of a multiprojective variety (and its downward closure)B: an interesting (and proper) subclass of polymatroids. C: The polymatroids of this form are now called Chow polymatroids,333This naming is unfortunate for us ...	BCA	CBA	ACB	BAC	Selection 3
A: Self-reported annotations [19]: They contain the emotional labeling reported by the participants after watching each of the 14141414 videos in the experimentB: The data are stored in one CSV file, that contains 14141414 columns and 1,40014001,4001 , 400 rows (100100100100 volunteers ×\times× 14141414 clips)...	ABC	CAB	BAC	CAB	Selection 1
A: Refer to Table 1 for an overview of machine learning models and selected relevant works. B: In this section, we discuss several such algorithms used for malware classificationC: Machine learning models can detect new, unseen malware through the understanding of underlying behavioral patterns or structura...	BCA	CBA	BCA	ABC	Selection 2
A: We use the minimax theorem to establish that the statistician has a strategy that guarantees high payoff. However, for the minimax theorem to apply, we need to make some modifications to the game.111Blackwell [5] gives an example of a statistical game without a value.B: A strategy for the statistican in this...	ACB	CBA	BAC	BAC	Selection 2
A: Existing attacks aim to hide the STOP sign to cause STOP sign violations [37, 18, 26]. Traffic light detection attack can cause the AD system to recognize a red light as green light, which may lead to red light violations [80]. In addition, the attacks on lane detection, localization, and end-to-end driving mode...	BCA	BCA	CAB	ABC	Selection 3
A: Alexey Barsukov is funded by the European Union (ERC, POCOCOP, 101071674)B: Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive AgencyC: Neither the European Union nor the granting auth...	CAB	ABC	CAB	BAC	Selection 2
A: Finally, ConvNeXt [50] is a CNN competitive with Vision Transformers [17]. It replaces BatchNorm with LayerNorm although this was not the focus of the paper. B: [9] discuss disadvantages of BN and propose a class of normalizer-free networks NFNet. They, however, require custom optimizers and are sensitive to...	CAB	ABC	CBA	BCA	Selection 3
A: We adopted the same training and test splits used in MixFace [41]. The training split was composed of 3.8 M images with 370 persons. In particular, the test split, including the remaining 30 persons, was partitioned into Q1, Q2, Q3, and Q4B: The number next to Q indicates the variance of conditions where it ...	ABC	ABC	ACB	BCA	Selection 4
A: Bellemo et al. [28] described the possible advantages and limitations towards synthetic retina image generation using GANs. The authors highlighted the potential clinical applications of GANs concerning early- and late-stage AMD classification. Burlina et al. [8] trained a Progressive GAN [29] on 133,82113382113...	BCA	ABC	BAC	BCA	Selection 2
A: Moreover, U-Net is employed to generate feature maps where each pixel has large receptive field and the local region also contains the global information.B: In LNLAttenNet, the local and the non-local information of facial expressions are simultaneously considered to construct two parts of the network respec...	ABC	BCA	CAB	ABC	Selection 3
A: this is indeed the best we can doB: However, there’s a robust version of the strategy that works for every other σ𝜎\sigmaitalic_σ: first fix some δ>0𝛿0\delta>0italic_δ > 0 for which σ⁢(−δ)>0𝜎𝛿0\sigma(-\delta)>0italic_σ ( - italic_δ ) > 0.C: If all players have slightly different ratings, no Elo can ...	CBA	ACB	CAB	CAB	Selection 2
A: Tightly connected views—such as the UMAP projection and the inverse polar chart—share identical encodings, i.e., label class mapped to filled-in color, data type as outline color, and US/OS represented with symbols. The inverse polar chart is compact and uses the available space effectively due to its inherent d...	ABC	BAC	ABC	BCA	Selection 4
A: To successfully frontrun a target user in the system, an adversary not only needs commensurately larger computational resources than the norm to compute the VDF proof faster, but the adversary also needs to delay the target user’s transaction in the mempool for the duration of time it takes to compute a valid VD...	ABC	CAB	ACB	ACB	Selection 1
A: In Section 5, we aim to learn the selection criterion that maximizes the equilibrium policy valueB: Adapting the approach of Wager and Xu (2021), we estimate gradients by applying symmetric, mean-zero perturbations to the selection criterion and the threshold for receiving treatment for each unit and runnin...	ACB	ABC	BCA	CAB	Selection 1
A: In summary, the proposed OccamNets have architectural inductive biases favoring simpler solutionsB: ConclusionC: The experiments show improvements over state-of-the-art bias mitigation techniques. Furthermore, existing methods tend to do better with OccamNets as compared to the standard architectures.	BCA	ABC	BAC	ABC	Selection 3
A: More importantly, VSPW has dense annotations with a high frame rate of 15fps, making itself the best benchmark for VSS till now. In contrast, previous datasets used for VSS only have very sparse annotation, i.e., only one frame out of many consecutive frames is annotated. Both training and validation sets of VSP...	BCA	CAB	BAC	BAC	Selection 1
A: Naive Embedding Tracking: Due to a large number of sparse parameters in recommender models, per-entry frequency counters would require gigabytes of on-chip storageB: AC: Alternatively, storing the frequencies in CPU/GPU memory would require three accesses: one to obtain the embeddings, one to read the f...	ABC	ACB	BAC	CBA	Selection 3
A: While we believe the above results are useful more generally, our main motivation for proving them here is to extend existing results in the literature adapting Morse-theoretic ideas to the PL setting so that they apply to some noncompact settingsB: 4.13], which applies only to polytopal complexes, to all po...	BAC	ACB	BAC	BAC	Selection 2
A: In order to solve the ground state and the time evolution of the system, the stochastic reconfiguration (SR) method and time-dependent variational Monte Carlo (VMC) approach [43] are utilized, respectively. We find that time evolutions of the energy expectation value from the neural networks are perfectly consis...	CBA	ACB	BAC	CAB	Selection 4
A: Table 2 shows the result of different hℎhitalic_h. B: First, we choose different space interval hℎhitalic_h to observe the performance of our modelC: In order to show the effect of different space intervals and time intervals, two groups of comparison tests have been done	CBA	CAB	BAC	ABC	Selection 1
A: We design an exponential search strategy for constructing large enough samples for training the estimators.B: We also propose proper preprocessing and algorithms that enable sub-linear query answering that scales to very large and high-dimensional data sets. Furthermore, to enable no-data access during the q...	ABC	ACB	CBA	ABC	Selection 3
A: They did not appreciate the fact that CO-oPS allowed their teens to have the same level of privacy in their app usage as they didB: 68% of the parents (N=13) explicitly said that they would not want their teens to have the ability to hide apps, but they want do want that privacy feature for themselves.C:...	ABC	BCA	CAB	ACB	Selection 2
A: Rather, it is averaged over a positive mass, and hence it is more robust. The distance-to-measure filtration is the sublevel filtration of the distance-to-measure function.B: As opposed to the distance to the support of μ𝜇\muitalic_μ, it is not estimated by a minimumC: The distance-to-measure (DTM) func...	ABC	CBA	BCA	BAC	Selection 2
A: Each subject is asked to finish 8 tasks, and 324 videos containing around 140,000 images are captured. Each frame is annotated with binary AU occurrence labels by two FACS coders independently. DISFA involves 26 adults, and to record their spontaneous facial behaviors, they are asked to watch specific videos. Ea...	BCA	ABC	CBA	ABC	Selection 3
A: As pointed out in [15], block validation time cannot be neglected and is the bottleneck of block propagation for large block sizesB: To shorten block validation time, [16] proposed to probabilistically validate received new blocks. Not validating all blocks, however, may compromise securities. Also, selectiv...	BCA	CAB	CBA	ABC	Selection 1
A: In a broader context of reinforcement learning with partial observability, our work is related to several recent works on POMDPs with special structures. For example, Kwon et alB: (2021) considers POMDPs having tree-structured states with their positions in certain partitions being the observations. Compare...	CBA	ACB	CAB	BAC	Selection 2
A: There were 91 unique authors identified from the included studies. The VOSviewer software was used to calculate the most impactful authors, generate co-authorship clusters, and perform co-occurrences of keyword analysis (Van Eck NJ, \APACyear\bibnodate). All the authors were counted irrespective of the authorsh...	ACB	BAC	ACB	ABC	Selection 4
A: Our outlier detection is a simple process inspired by compression ratioB: On the other hand, outliers will have more similar compression ratios with all the other points. This difference can be captured by the variance of the list of compression ratios between one point and all of the other points, with outl...	ABC	ACB	BAC	CBA	Selection 2
A: Fig. 1: The overall architecture of our proposed SI-Dial frameworkB: Note that the dashed lines denote the operations only after the dialog is completed) for the final scene graph generation.C: We first obtain the preliminary objects from the object detector based on the incomplete visual input, and pro...	ACB	CAB	BCA	BCA	Selection 1
A: Figure 9: Example for randomized lower bound 2222 for the maximum costB: The red letters denote the probabilities to locate the facility by the mechanism f⁢(e,⋅)𝑓𝑒⋅f(e,\cdot)italic_f ( italic_e , ⋅ ). The dashed lines represent the deviations of the agents.C: The black dots are agents	ABC	CAB	ACB	ABC	Selection 3
A: All other edges of the chain form part of some induced paw and their incident vertices have degree odd in such paw. Therefore, every pair of consecutive vertices in the chain have different colors in any valid bi-coloring. The number of edges in the chain is exactly 6⁢k2+16subscript𝑘216k_{2}+16 italic_k start_P...	BAC	ACB	CBA	CAB	Selection 3
A: To set the complexity of each ReLU network, we have followed the indications reported in the corresponding rows of Tab. 2, where we have considered the case of equally distributed neurons across the L𝐿Litalic_L hidden layersB: As a consequence, the training time required to determine the values of the unde...	BAC	ABC	ACB	CAB	Selection 3
A: In their seminal work [55] consider objects sliding down a plane. By tracking the objects, they estimate velocity vectors that are used to supervise a rigid body simulation of the respective object.B: While many approaches work with trajectories in state space, there are also several works that operate direc...	ABC	BAC	BAC	CAB	Selection 4
A: To do so, we must the error sources encountered during both the quantum communication errors and the quantum semantic errors present in practical setups in the QSC framework.B: As discussed earlier, the QSC framework ensures minimality of quantum communication resources by extracting and compressing the sem...	ABC	BAC	BCA	CAB	Selection 4
A: We have designed different MARL setups for FD and HD node operationsB: Through the cooperation among MARL agents, the developed resource allocation approach can coordinate link interference and data caching on IAB-nodes, and capture network dynamicsC: Moreover, we have provided a learning framework consi...	BCA	BAC	CAB	ACB	Selection 2
A: With the high-discretion accelerated protocol, incentive alignment is lost even for a typical drug. In the blockbuster scenario, an organization may have an expected value of hundreds of millions or billions of dollars of profit for running a clinical trial on a placebo. B: We report on the expected value of...	CAB	ACB	ACB	BCA	Selection 1
A: FigB: The red frame is the transformed moving image using Clear+URS registration. Green and Yellow frames are the transformed images using respectively PPIR(MPC)+URS and PPIR(FHE)v1+URS.C: A5: Qualitative results for affine registration with SSD between 2D medical images	ACB	BAC	CBA	BAC	Selection 1

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