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<|MaskedSetence|> It suffices to compute its gradient with respect to the state and verify if this gradient belongs to 𝒪𝒪\mathcal{O}caligraphic_O. This holds for any physical quantity that can be analytically expressed in terms of the state. In particular, it holds for the unknown constant parameters, which were inc... | **A**:
Once 𝒪𝒪\mathcal{O}caligraphic_O is computed, we can easily check whether a given physical quantity, which can be analytically expressed in terms of the state, is observable or not.
**B**: This is trivial.
**C**: To check their identifiability it suffices to compute their gradient.
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There are various similarity or distance measures to define a loss function for enforcing invariant representations. <|MaskedSetence|> (2017) and Meng et al. (2018) minimize the KL-divergence and Lee et al. <|MaskedSetence|> (2018) minimize the Wasserstein distance. <|MaskedSetence|> Long et al. (2015) minimize Max... | **A**: Sun and Saenko (2016) minimize the ℓ2subscriptℓ2\ell_{2}roman_ℓ start_POSTSUBSCRIPT 2 end_POSTSUBSCRIPT distance between the covariance matrices of the source and target domain representations.
**B**: For example, Zhuang et al.
**C**: (2019) and Damodaran et al.
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For the U-Net, we modify an available PyTorch implementation [50]. <|MaskedSetence|> <|MaskedSetence|> Further details are presented in Appendix C.2. <|MaskedSetence|> The Adam optimizer [51] is used in all experiments.. | **A**: To address this concern, we conduct bootstrapping experiments for the U-Net architecture, offering detailed insights into the impact of sample size on model performance.
**B**: We use a 10-fold CV over our training data and grid search to select parameters such as learning rate, weight decay, batch size, and nu... | CAB | CAB | CAB | CAB | Selection 4 |
<|MaskedSetence|> When popular repositories are formed or influencers act, the structure of the social network alters, affecting network metrics. The TTERGM technique build upon previous statistical models by incorporating information flow across hierarchical configuration features. We represent social network learnin... | **A**: The new parameters are then approximated via Monte Carlo maximum likelihood estimation.
**B**: Future work may include expanding this approach to model the influence of more "distant" users in the network, or those that do not directly follow an influencer..
**C**:
We implemented a social-theory driven tempor... | CAB | BCA | CAB | CAB | Selection 3 |
A primary objective of on-device training is to uphold or even enhance the accuracy of deployed models while operating under computational constraints. <|MaskedSetence|> Existing studies assess the accuracy gains achieved by on-device training systems across a spectrum of representative ML tasks encompassing computer ... | **A**: Despite the utilization of diverse neural network architectures and benchmark datasets, we noticed that on-device training can contribute to accuracy enhancements.
**B**: Consequently, accuracy improvement stands as a crucial performance metric for on-device training.
**C**: Data drift is a prominent challenge... | ABC | BAC | BAC | BAC | Selection 2 |
<|MaskedSetence|> In [chen2020traveling, victor2019measuring], they use the ABI interfaces to check for ERC-20 mandatory functions and events in the bytecode of smart contracts. Di Angelo et al. [di2021identification] use the same technique to identify ERC-20 as well as ERC-721 and others. These approaches are somewha... | **A**: Furthermore, it is crucial to notice that, for our study, we don’t need to collect ERC-721 assets that have not been transferred between addresses.
**B**: Different approaches have been proposed to collect Ethereum assets, in particular ERC-20.
**C**: Indeed, since we want to measure wash trading events, asset... | CBA | BAC | BAC | BAC | Selection 4 |
<|MaskedSetence|> <|MaskedSetence|> [15], Han et al. [14], Li et al. [16], we test our proposed method and baselines on CIFAR-10, CIFAR-100 [30], and F-MNIST [31] forming many comparisons with the literature. <|MaskedSetence|> | **A**: Along with Tiny-Imagenet and Imagenet [32], these five datasets form well-studied computer vision tasks, easing reproducibility.
Additionally, we use a human labelled version of CIFAR-10, titled CIFAR-10N [33], for which we use the “worst labels" allowing us flexibility in our experiments..
**B**: [17], Wang et... | CBA | BCA | CBA | CBA | Selection 1 |
A small number of SDC tools have been produced to assist in the process of achieving ‘safe outputs’, such as sdcTable [18] and tauArgus [19] by Statistics Netherlands; however they require expert knowledge of SDC to use effectively. <|MaskedSetence|> They are predominantly used for regularly repeating reports in Nati... | **A**: However, for scenarios where the same tables are repeatedly generated and secondary differencing is considered a significant problem, the investment in setting up the tools can be cost-effective..
**B**: The need to rewrite the metadata for each table makes these tools poorly suited for research use.
**C**: Mo... | CBA | CBA | CBA | ACB | Selection 2 |
<|MaskedSetence|> This extension is achieved based on the understanding that the companion matrix of a polynomial in power basis with degree n𝑛nitalic_n can represent an endomorphism of the spaces consisting of polynomials with degree less than n𝑛nitalic_n defined by the multiplication of the involved variable in th... | **A**: Their only difference is that we use Newton basis this time.
**B**: The companion matrix of a polynomial in Newton basis possesses a similar property.
**C**: To develop the formula of subresultant polynomial for multiple univariate polynomials in Newton basis, we use the extended version of the well-known comp... | CBA | CBA | CBA | BCA | Selection 1 |
Table 5: Correlation results for the different tasks, with OPT (different sizes) and Bloom. <|MaskedSetence|> <|MaskedSetence|> Dark and light blue colored cells stand for negative correlations <−0.2absent0.2<-0.2< - 0.2 and >−0.2absent0.2>-0.2> - 0.2, respectively. <|MaskedSetence|> Average accuracy across all pro... | **A**: Dark and light orange colored cells stand for positive correlations >0.2absent0.2>0.2> 0.2 and <0.2absent0.2<0.2< 0.2, respectively.
**B**: Correlations with p<0.00625𝑝0.00625p<0.00625italic_p < 0.00625 (according to Bonferroni correction for multiple hypotheses) are marked with **.
**C**: Correlations with p... | CAB | CBA | CBA | CBA | Selection 2 |
We conduct dense experiments on two public datasets: PEMS-BAY [10] and METR-LA [31]. PEMS-BAY is collected by California Transportation Agencies (CalTrans) Performance Measurement System (PeMS). <|MaskedSetence|> For METR-LA, 207 loop detectors on the highway of Los Angeles County are selected from Mar 1st 2012 to Ju... | **A**: It contains 325 highway sensors of the Bay Area from Jan 1st 2017 to Jun 30th 2017.
**B**: For both datasets, traffic speed readings are aggregated into 5 minutes windows.
**C**: With pairwise road network distances between sensors, the adjacency matrix representing connection from any sensor i𝑖iitalic_i to a... | ABC | ABC | BAC | ABC | Selection 2 |
<|MaskedSetence|> An alternative approach is self-supervised learning (SSL), which allows one to learn and extract meaningful feature representations without manually labeling data [18]. It has demonstrated remarkable progress across diverse facets of medical image analysis, including but not limited to anatomical loc... | **A**: [21] employed U-Net and holistically-nested edge detector (HED) to extract useful semantic features from unlabeled prostate 2D MRI.
**B**: Recently, Bolous et al.
**C**:
All the studies mentioned earlier relied on supervised learning (SL) algorithms, and large-scale labeled data was required to train the DL m... | CBA | CBA | CBA | BAC | Selection 3 |
On MS COCO and BDD100K datasets, the success rates of TOG on YOLOv5 are close to zero while the success rates of TOG for FasterRCNN are 17.2 and 60.9 respectively. As mentioned above, TOG attacks the final output layer by maximizing the classification score and objectness score. For the one-stage detector YOLOv5, the c... | **A**: We conjecture that this is mainly because the features extracted by YOLOv5 are more vulnerable to adversarial attack than that of FasterRCNN.
**B**: The following experiments with respect to the perturbation degree in Fig. 9 also show that the features extracted by YOLOv5 can be easily changed by TFA even with ... | CBA | CAB | CAB | CAB | Selection 4 |
Notable black-box methods are:
LIME Ribeiro et al. <|MaskedSetence|> (2022) approximate the vicinity of the input with a linear function that is interpretable. But depending on the choice of the size of the vicinity, LIME can lead to very disparate results. Methods like RISE Petsiuk et al. <|MaskedSetence|> <|Masked... | **A**: (2016) and its multimodal adaptation DIME Lyu et al.
**B**: SHAP exhibits great theoretical properties that enable us to define a MM score, as.
**C**: (2018) and SHAP Lundberg and Lee (2017) compute importance scores by randomly masking parts of the input and determining the effect this has on the output.
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Training Data:
To generate augmented query-document data (AugQ), we utilize two large text datasets: Wikipedia222enwiki-20211020-pages-articles-multistream.xml.bz2 and CommonCrawl by Pile (pile) (Pile-CC). <|MaskedSetence|> This results in a total of 22.6 million paragraphs available for training. <|MaskedSetence|> F... | **A**: For Wikipedia, we process the original text dump by segmenting articles into paragraphs by line breaks and reserving titles and anchor texts (texts with hyperlinks, italics, or boldface).
**B**: Pile-CC consists of 52.4 million web documents, but it does not provide structure information, making Doc-Anchor unav... | BAC | ABC | ABC | ABC | Selection 4 |
Song et al. <|MaskedSetence|> This model not only captures document graphs but also preserves their inherent structure, mitigating information loss arising from graph fragmentation. <|MaskedSetence|> [214] leverage GCN to extract entity dependencies in text based on the underlying dependency tree. <|MaskedSetence|> ... | **A**: Simultaneously, Zhang et al.
**B**: To uphold the precision of information extraction, a novel pruning strategy is introduced.
**C**: [213] present a novel graph-state LSTM model.
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This work has been developed in the context of deep-sea applications. However, the image formation model described by Eq. 2, which we extended in a multi-view setting in Eq. 6, was conceived for natural light conditions. <|MaskedSetence|> We show that while the employed model does not capture some specific characteri... | **A**: Taking these factors into consideration, the design and application of deep-sea image formation models requires further research and remains in the scope of future works..
**B**: For more details, Appendix B provides empirical examples that illustrate how the natural light model fits deep-sea images.
**C**: In... | CBA | CBA | BAC | CBA | Selection 2 |
<|MaskedSetence|> <|MaskedSetence|> The y-axis shows the FID metric, and the x-axis shows the index of the current training task. <|MaskedSetence|> The plots show that the best architecture for each CL method is SR, our approach. . | **A**:
Figure 6: The results show the quality of the constructed images for different continual learning methods and AD architectures.
**B**: Each value represents the average FID across all tasks seen so far, with a lower value indicating a higher reconstruction quality.
**C**: Each plot represents a different CL t... | ACB | ACB | ACB | ACB | Selection 4 |
The presented method can take two versions of inputs. <|MaskedSetence|> <|MaskedSetence|> This version allows one to adapt to the real propagation phenomena, when e.g. <|MaskedSetence|> Note that, in both cases, RadioUNet can yield very accurate results, in previously unseen city environment and Tx deployment scenar... | **A**: In the first case, only the city map and the Tx location image are given as inputs, similar to a simulation setting of a ray-tracing software.
**B**: the available simulation method (used for the initial supervision) or the environment map is not accurate enough.
**C**: In the second version, samples from the ... | ACB | ACB | ACB | ACB | Selection 1 |
<|MaskedSetence|> However, the main issue is that no obstacle is considered. <|MaskedSetence|> This method is not feasible in this paper. Although obstacles are static, the robots are actually faced with the dynamic obstacle avoidance problem due to the existence of the reference velocity command 𝐯∗superscript𝐯∗\ma... | **A**:
In the last section, the swarm controller (23) is designed for the trapezoid virtual tube under speed constraints.
**B**: For obstacle avoidance inside 𝒯𝒯\mathcal{T}caligraphic_T, a common idea is to introduce a potential-based obstacle avoidance term into the swarm controller.
**C**: The detailed descripti... | CAB | ABC | ABC | ABC | Selection 4 |
Methodological bias: The project presentation order is predetermined. <|MaskedSetence|> While this is inherent to the problem setting and cannot be altered, it may influence student evaluations and, consequently, the final project rankings. <|MaskedSetence|> In Section 5.1, we analyzed the presentation order bias, w... | **A**: In Section 5.2, we investigated primacy and recency bias, wherein students, when asked to choose between two projects to which they assigned the same grade, may preferentially select the first or latter project..
**B**: Students evaluate the projects iteratively after each presentation.
**C**: We examined two ... | BCA | CAB | BCA | BCA | Selection 1 |
<|MaskedSetence|> Firstly, we analyze the internal components of WDIB in Table II, including our proposed WRDC (Case 1), SCF (Case 2), and ⊗tensor-product\otimes⊗ (adaptive multiplier, Case 4). <|MaskedSetence|> The SCF module further improves the PSNR value by 0.18 dB with a parametric gain of less than 10K. <|Mask... | **A**:
The effectiveness of WDIB.
**B**: The adaptive multiplier improves the PSNR by 0.04 dB compared to the baseline and does not introduce additional computational load or slow down the inference process.
**C**: By comparing case 1, case 2, and the baseline, we observe that our proposed WRDC module achieves sligh... | ACB | ACB | ACB | ABC | Selection 2 |
<|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> Green arrows mean input (come from the previous stage) while Red arrows represent current stage output (used for the next stage). The outputs in the Red arrows are the inputs in the Green arrows. We take the last stage outputs as final output [20, 24].. | **A**: (Yellow area), (c) A cascaded transformer decoder will conduct the reasoning between the query and query features (Green area).
**B**:
Figure 3: Our proposed Panoptic-PartFormer.
**C**: It contains three parts: (a) a backbone to extract features (Red area), (b) a decoupled decoder to generate scene features a... | BCA | BCA | BCA | BCA | Selection 1 |
The generator of our GAN receives a 512×512512512512\times 512512 × 512 pixel FLM of the facial landmarks as input. <|MaskedSetence|> In addition, the discriminator receives five feature maps as input instead of only four. <|MaskedSetence|> 3. One of our early hypotheses in [LPG20] was that a higher number of FLMs (e... | **A**: Compared to the Pix2Pix GAN, the output has been extended by a fourth feature map to be able to generate depth images.
**B**: Changing the number of FLMs does not change the quality of the results but only increases the training time.
.
**C**: While the first four correspond to the four channels of the RGBD im... | BCA | ACB | ACB | ACB | Selection 4 |
<|MaskedSetence|> <|MaskedSetence|> Specifically, the improvement for the random case is statistically significantly better than for the worst-case scenario (p<0.005𝑝0.005p<0.005italic_p < 0.005), obtained using an ANOVA test. Nevertheless, for both the random and worst case, the optimal seeding configuration is sta... | **A**:
Most importantly, Fig.
**B**: Interestingly, while the relationship between the average basic reproduction number and the economic profit for both cases is complex and non-linear, the figure reveals a somewhat linear decreasing trend.
**C**: 5 reveals that the optimal seeding strategy indeed increases the ave... | ACB | ACB | ACB | ACB | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> In addition, several methods with complexity guarantees have also been proposed for nonconvex optimization with relatively simple constraints. For example, interior-point method [10], log-barrier method [58], and projected gradient descent method [69] were proposed for nonconvex op... | **A**:
In recent years, there has been considerable research on designing algorithms with complexity guarantees for finding an approximate SOSP of nonconvex optimization problems.
**B**: In particular, numerous algorithms were developed for nonconvex unconstrained optimization, such as cubic regularized Newton method... | ABC | ABC | ACB | ABC | Selection 4 |
<|MaskedSetence|> To this end, we extend the method of influence balance (IB) [19] to CIL setting and propose the incremental influence-balanced (IIB) method for CIL. Specifically, we first derive a metric that measures how much each sample influences the biased decision boundaries. Then, we decompose the metric into ... | **A**: Finally, we design the incremental influence-balanced (IIB) loss function for CIL, which adaptively assigns different weights to samples according to their influence on decision boundaries (c.f.
**B**: Fig. 1, IIB Method).
.
**C**: In order to deal with the imbalanced data learning problem, we attempt to atten... | CAB | BAC | CAB | CAB | Selection 3 |
X.Z. <|MaskedSetence|> <|MaskedSetence|> L.B. supervised the project. <|MaskedSetence|> | **A**: constructed the overall idea, designed the experiment, and prepared the manuscript.
**B**: X.C., D.L., R.Y., and Y.Z performed the algorithm study and data analysis.
**C**: All the authors participated in discussions during the project..
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Some commonly used match-based CEMs treat code as text, such as BLEU (Papineni et al., 2002) and Accuracy, which focus on basic and lexical-level features. <|MaskedSetence|> <|MaskedSetence|> However, the preceding CEMs have deficiencies in identifying code relationships, because code is mainly evaluated based on fun... | **A**: They compute scores mainly based on n-gram co-occurrence statistics.
**B**: CodeBLEU (Ren et al., 2020) additionally takes into account the structure of code, i.e., abstract syntax tree and data flow.
**C**: 1, code (a) and code (b) have a much higher similarity of tokens or structures than code (c).
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<|MaskedSetence|> <|MaskedSetence|> Therefore, in Figure 3b we evaluate the attack success at fixed test accuracies. <|MaskedSetence|> We observe tough that as the training runs for longer to convergence and the test accuracy is higher, the backdoor is also learned better by the model and the attack becomes more suc... | **A**: In practice, the training may stop after a certain accuracy has been reached.
**B**: We notice a significant difference between the four attack strategies for accuracy in the low 90s (i.e., 0.9, 0.93), with the centrality-based methods Degree, ENS and PageRank being consistently on top, generally twice more suc... | CBA | CAB | CAB | CAB | Selection 3 |
Furthermore, we used a statistical approach and a search algorithm, in order to collect news related to six different domains (e.g. politics, world, daily, sports, science, and culture) from periods 2006-2007 and 2021-2022. Therefore, in accordance with relevant literature of the area, we selected three news articles f... | **A**: (2020); Fan et al.
**B**: (2021); Baly et al.
**C**: (2019).
.
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There are works using ideas from RL to train GANs (Yu et al., 2017; Wang et al., 2017; Sarmad et al., 2019; Bai et al., 2019). <|MaskedSetence|> <|MaskedSetence|> First, different GAN objectives are used: SeqGAN uses the JS divergence while we use IPM. <|MaskedSetence|> Besides, in our work, rewards are mathematica... | **A**: The most relevant work is SeqGAN (Yu et al., 2017), which uses policy gradient to train the generator network.
**B**: There are several main differences between their settings and ours.
**C**: In SeqGAN, the next token is dependent on tokens generated from all previous steps, while in diffusion models the next... | ABC | ABC | BAC | ABC | Selection 4 |
The concept of a ZKP was first introduced in 1989 by Goldwasser et al. [7]. It has been proved that every NP problem has a ZKP [6], so a computational ZKP for any NP puzzle can be constructed via a reduction to another problem. <|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> They are also easy to understand a... | **A**: These card-based protocols have benefits that they require only portable objects easily found in everyday life and do not require computers.
**B**: Therefore, many researchers instead focused on constructing physical ZKPs using a deck of playing cards.
**C**: Such construction, however, is unintuitive and look... | CBA | CBA | CBA | CBA | Selection 1 |
The authors would like to thank Benjamin Grimmer for helpful conversations surrounding minimax optimization, Jacob Steinhardt and Adam Sealfon for useful discussions on robust statistics, and Jason Gaitonde for advice on high-dimensional probability. <|MaskedSetence|> Nietert was supported by the National Science Foun... | **A**: S.
**B**: R.
**C**: Goldfeld was supported in part by the NSF CAREER award under Grant CCF-2046018, an NSF Grant DMS-2210368, and the
IBM Academic Award..
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<|MaskedSetence|> This not only reduces the number of equations in the stress solution, but also maintains the advantages of the stress method. <|MaskedSetence|> <|MaskedSetence|> Therefore, the stress function solution plays a significant role in solving problems in elastic mechanics, especially stress. To better u... | **A**: The advantages of the stress method yield more precise stress results, like in equilibrium elements.
**B**: However, the stress method necessitates higher-order trial functions and complex integration processes to determine the displacement field, which is more complicated than taking derivatives.
**C**: In th... | CAB | CAB | CAB | CAB | Selection 4 |
Figure 1: (a) Left: An encoder trained with the standard contrastive loss can exhibit inconsistency, as different views of an instance are encouraged to be represented similarly in the feature space, irrespective of the actual difference between them. Right: A consistent encoder positions the vector of more strongly a... | **A**: (2020); Chen & He (2021), which enforce invariance to all data augmentations, may inadvertently cluster dissimilar data closely in the feature space.
**B**: (2011) and Flowers102 Nilsback & Zisserman (2008) using pre-trained encoders.
**C**: Existing contrastive methods He et al.
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<|MaskedSetence|> <|MaskedSetence|> Typically, customers in the low-mid range of risk opened notifications more often compared to customers at high risk. As part of the test analysis customers were divided into three groups: high ability to respond, positive balances in accounts and few overdrafts; medium ability to ... | **A**:
Another goal of the test was understanding the customer’s ability to respond to an overdraft notification.
**B**: The model predicted a customer’s risk but cannot predict if a customer has the means to prevent an overdraft when they are notified.
**C**: If certain customers receive email interventions and oth... | ABC | ABC | ABC | BCA | Selection 3 |
<|MaskedSetence|> <|MaskedSetence|> For some datasets in [41], there was no metadata. We excluded such datasets from consideration. Therefore, the number of datasets has decreased to 19191919 datasets with one-dimensional data and one dataset with single multi-dimensional time series. <|MaskedSetence|> | **A**:
Original paper [41] provides a detailed description of each dataset.
**B**: From each dataset with one-dimensional data, the first two time series were taken..
**C**: All the metadata for building the model (prediction horizon, context length, periodicity, etc.) follow the settings from this project.
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MKGAT (Sun et al., 2020) is the first model to introduce a knowledge graph into the multimodal recommendation. MKGAT proposes a multimodal graph attention technique to model multimodal knowledge graph from two aspects of entity information aggregation and entity relationship reasoning, respectively. <|MaskedSetence|> ... | **A**: Furthermore, a novel graph attention network is adopted to aggregate neighboring entities while considering the relations in the knowledge graph.
**B**: CMCKG (Cao et al., 2022) treats information from descriptive attributes and structural connections as two modals and learns node representation by maximizing c... | ACB | ABC | ACB | ACB | Selection 1 |
A key question for researchers is which meta-parameters to use to achieve the best possible performance. <|MaskedSetence|> For baseline models, we used the parameters suggested by their respective authors. For our model, we used a 9-layer architecture with a kernel size of 3 and a hidden size of 512 to balance the lim... | **A**: Inner experiments with Optuna optimization [49] indicated that this setup is the best or close to the best across several datasets.
**B**: However, there were two datasets where we deviated from this setup:
.
**C**: Our goal was to develop a model that is universal and performs well with default parameters or ... | CAB | CAB | CAB | CAB | Selection 3 |
Third, ambiguous contracts can be a burden for agents, either because they are more difficult to evaluate and enforce or because they are a weapon for extracting surplus from agents. Circumstances may accordingly restrict attention to ambiguity-proof classes of contracts. Our results show that insisting on ambiguity pr... | **A**: We note that commission contracts are common, and in their simplest form are linear.333A contract may include a base payment plus a commission, making it affine rather than linear.
**B**: Ordered contracts, with linear contracts as a leading example, are straightforward to process.
**C**: Section 5 notes that ... | BAC | BAC | BAC | BAC | Selection 3 |
<|MaskedSetence|> <|MaskedSetence|> Instead, when they wish to ask a query φ𝜑\varphiitalic_φ, they pass it to the mechanism. The mechanism answers φ𝜑\varphiitalic_φ without revealing too much information about the dataset; e.g. <|MaskedSetence|> [DFH+15a, DFH+15b, DK22, FS18, FS17, SU15a].. | **A**: In those works, analysts do not have direct access to the data.
**B**: by adding noise to the output of φ𝜑\varphiitalic_φ applied to the dataset.
**C**:
Much prior work has focused on the design of mechanisms, a layer between the analyst and dataset.
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Figure 3: Design of the experiment: 1) OptiTrack Cameras, 2) Spot Trajectory. <|MaskedSetence|> <|MaskedSetence|> The Spot will always face the participant in gaze conditions. 3) Participants’ original orientation. <|MaskedSetence|> | **A**: Without gaze, in forward conditions, the Spot is facing A point; in sideways conditions, the Spot is vertical to line AB, facing the participant side, and in backward conditions, the Spot is facing B point.
**B**: The Spot will always move from B to A if not still.
**C**: The participants will always face the ... | CBA | BAC | BAC | BAC | Selection 3 |
Regarding the Levenberg-Marquardt Damped Least Squares (LMDLS) technique, the simulation results are shown in Figures 9 and 10. <|MaskedSetence|> Figure 11 displays the angular joint values obtained using the optimization algorithm. Figure 12 indicates that the position error is nearly zero, demonstrating the high ac... | **A**: This method incurs a high computational cost, primarily due to the complexity of the human leg’s structure.
**B**: As shown in Figure 16, the neural network technique achieves high accuracy with an error of less than 1.6×10−61.6superscript1061.6\times 10^{-6}1.6 × 10 start_POSTSUPERSCRIPT - 6 end_POSTSUPERSCRIP... | ACB | ACB | CBA | ACB | Selection 1 |
In order to obtain a representative sample over the state-of-the-art we employed a keyword-based search in academic search engines (e.g. SemanticScholar) and Github to gather all papers and approaches (systems and toolsets) that might fit our criteria. <|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> After clos... | **A**: This methodology is in line with other surveys [17].
**B**: We also relied on existing surveys to gather potentially missed approaches.
**C**: After a manual selection process via the paper titles and abstracts and comparison with our requirements we created a list of 64 candidate sytems.
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<|MaskedSetence|> Subsequently, the artificial neural networks method is used to solve the inverse kinematics problem. The efficiency of the artificial neural networks method is verified using the jerk energy criteria. The rest of this paper is organized as follows: Section 2 provides a brief mathematical background o... | **A**: In this paper, the dual quaternion-based theory is applied to the kinematics and dynamics study of the 7-DOF human lower limbs in 3D space.
**B**: Section 3 elaborates on the forward kinematics of the human lower limb in 3D space using dual quaternions.
**C**: In Section 5, the dynamical model of the lower lim... | ABC | ABC | CAB | ABC | Selection 1 |
In practice, multiple network operators co-exist in a given geographical area, each operating in different frequency band. As a consequence, at a given point in time, multiple UEs are served by different operators in the system. <|MaskedSetence|> In particular, since the IRS elements are passive, they will reflect the... | **A**: More fundamentally, none of these works address the question of the out-of-band (OOB) performance even in the scenario of two operators operating in non-overlapping bands and the IRS is optimized for only one operator.
**B**: In such a scenario, if an IRS is optimized to cater to the needs of one of the operato... | BCA | BCA | BCA | BCA | Selection 2 |
To this end, previous studies used the gap of the loss (Neyshabur et al. <|MaskedSetence|> 2020, 2021) or the smoothness of the loss landscape (Keskar et al. 2016; Li et al. <|MaskedSetence|> 2021; Kwon et al. <|MaskedSetence|> | **A**: 2018; Foret et al.
**B**: 2021) to investigate the generalization power of a DNN.
.
**C**: 2017; Bousquet, Klochkov, and Zhivotovskiy 2020; Deng, He, and Su 2021; Haghifam et al.
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<|MaskedSetence|> In classification, ordinarilly more layers is better in deep learning. On datasets such as MNIST, even simple CNNs with three layers can achieve high classification performance. <|MaskedSetence|> <|MaskedSetence|> However, in [5], ResNet with more than 1000 layers deeper than 152 layers show the lo... | **A**: However, for more challenging datasets such as CIFAR10, shallow networks have limitations.
**B**: ReLU (Rectified Linear Units) is mainly used in the fields of vision classification.
**C**: As is well known, ResNet won the 2015 ILSVRC competition with 152 layers.
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<|MaskedSetence|> We then tested combinations of two tasks (e.g., VA & AUs), and finally, we utilized the affective representations from all three tasks concurrently. The results are summarized in Table 3, where we present only the best performance for each experiment to avoid cluttering of the results. Notably, even ... | **A**: Initially, we used only single-task affective representations (extracted from MMA) as input to the RNN.
**B**: In the two-task experiments, we observed a further increase in the Pearson’s correlation coefficient ranging from 1% to 1.5%.
**C**: The model’s performance improved substantially when incorporating a... | ACB | ACB | ACB | ABC | Selection 2 |
<|MaskedSetence|> Considering that the point-wise relationship of events is susceptible to noise signal [31], voxel-wise GNNs [11, 12] first convert an event stream into a voxel set and then aggregate vertices’ information for feature representation. The voxel-wise representations keep more local semantics than the po... | **A**:
Recent graph-based approaches [16, 9, 10] construct point-wise graphs on downsampled event streams and exploit graph neural networks (GNNs) to extract event features.
**B**: As stated in Section I, existing point-based methods still have some limitations that need to be improved, mainly the defective design of... | ABC | ABC | ACB | ABC | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> First, the most effective will be faster contact detection. In the current setup, collisions are detected from the joint torque sensors in the manipulator and its dynamic model and their remapping onto the end effector. <|MaskedSetence|> A remedy would be a force/torque sensor at ... | **A**: In our setup, this leads to delayed and noisy estimation of the collision and significant movement of the object.
**B**: The results in the real setup are negatively affected by the noise induced by the contact events—the collision is detected with a certain delay, the object moves, and the new pose is not re-e... | BCA | ABC | BCA | BCA | Selection 1 |
Many efforts have been devoted to finding diverse solutions in combinatorial problems. <|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> Since then, the computational complexity of finding diverse solutions in many other combinatorial problems has been studied. For instance, diverse variants of Vertex Cover, Mat... | **A**: were the first to explore this problem from a complexity-theoretic perspective.
**B**: In their seminal paper [KGD93], Kuo et al.
**C**: They showed that the basic problem of maximizing a distance norm over a set of elements is already NP-hard.
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<|MaskedSetence|> <|MaskedSetence|> As shown in Table VIII, models with context normalization technique achieve good results on the blended dataset. <|MaskedSetence|> More precisely, the model with CN-Patches achieves 55.04% accuracy and 81.83% top-5 accuracy, which exceeds the results of all baseline models (ref. F... | **A**: It is also interesting to notice that this performance in terms of accuracy is biased by the MNIST digits dataset, which is less difficult to learn than CIFAR-100.
**B**: Context normalization, on the other hand, gives an adaptive representation per dataset (according to the contexts), which makes training poss... | CBA | BAC | CBA | CBA | Selection 1 |
<|MaskedSetence|> We aim to understand the effectiveness of DFB from two perspectives, including the foreground and background OOD scoring, and the latent features learned in DFB, with the results on the Textures dataset reported in Figs. <|MaskedSetence|> We can see in Fig. <|MaskedSetence|> From the feature repres... | **A**: 4 and 5 respectively.
**B**: 4 that the background OOD scores in DFB enable a significantly better ID and OOD separation than the foreground OOD scores, indicating that the ID and OOD samples can be easier to be separated by looking from the background features than the semantic features since there can be more... | CAB | CAB | CAB | BCA | Selection 3 |
LLIE techniques have existed for many decades and can be divided into non-learning-based methods and learning-based methods. <|MaskedSetence|> HE adjusts the global contrast of an image via a single transformation function. <|MaskedSetence|> <|MaskedSetence|> Despite achieving reasonable results, the abovementioned ... | **A**: However, low-light images often require contrast enhancements that vary dynamically depending on local regions of the image.
**B**: Popular examples of traditional techniques which do not require learning from data include variants of histogram equalization (HE) [6, 20] and gamma correction (GC) [21].
**C**: T... | BCA | BAC | BAC | BAC | Selection 3 |
<|MaskedSetence|> For instance, it has been demonstrated that information-seeking performance is not solely contingent upon internet-related knowledge but is also impacted by key cognitive abilities, resulting in a disadvantage for older adults [13, 14]. Sex is another factor contributing to diverse information-seekin... | **A**: Previous research has shown that individuals exhibit distinct cognitive patterns and abilities when engaging in online information-seeking activities, with several characteristics identified as influential factors.
**B**: Bi/multilingualism, though not directly linked to information-seeking, has been associated... | ACB | BAC | ACB | ACB | Selection 1 |
<|MaskedSetence|> Proteins with similar folds typically share significant structural similarities, even if their sequences and functions differ. Fold classification can offer insights into evolutionary relationships among proteins.
The objective of this setup is to predict, within enzymes with mixed folds, the specifi... | **A**: We employ ESM-2 as a language modality input for comparison to confirm its sequence-only representation capabilities.
**B**: Although ESM-2 (11.5%P@1, 24.5%P@2, 36.5%P@3) slightly outperforms the earlier GVP, it significantly lags behind the performance of ours, demonstrating enhanced generalization ability due... | CAB | CAB | CBA | CAB | Selection 4 |
We implement all the methods with OpenKE [33], which is a pytorch-based open-source framework for knowledge embedding111Codes are available at https://github.com/brcai/LiftNet. <|MaskedSetence|> <|MaskedSetence|> In LiftNet, the parameters of the two TC layers as set as {InChan:1, OutChan:4, Kernel:3} and {InChan:4,... | **A**: Meanwhile, we implement a two-layer LiftNet for LiftNet-based methods, which lifts the dimension of entity representations from 16 to 512.
**B**: We fix the random seed for all experiments and use MRR of the validation set to find the optimal learning rate from {0.01, 0.05, 0.1, 0.5}.
**C**: We run TransE, Tra... | CAB | CAB | CAB | CAB | Selection 4 |
<|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> First, consider the setup proposed by [12], where entanglement between qubits is generated using laser pulses. Increasing the duration of these pulses raises the probability of generating an ebit but reduces its quality, as shown in Fig. 1(a,b). Consequently, if ... | **A**: The fidelity of an ebit can be quantified as the distance between the quantum state of the ebit in question and the state of a maximally entangled ebit [2].
**B**: This paper advances the research on quantum networks by introducing an highly versatile routing approach based on fidelity curves, which can be util... | ACB | BAC | BAC | BAC | Selection 4 |
However, practical challenges, such as ethical and legal impediments to sharing medical data, particularly for unstructured radiology reports, complicate this endeavor [Scheibner et al. <|MaskedSetence|> (2020)].
For one of the few public datasets of this caliber that exists, MIMIC-CXR, Chambon et al. have demonstrate... | **A**: (2019), Chambon et al.
**B**: (2021), Bovenberg et al.
**C**: (2022a)]..
| BAC | BAC | CBA | BAC | Selection 1 |
In our study, we employ the CLIP score as the primary evaluation metric to assess the congruence between the generated 3D assets and the associated text prompts. This score, commonly used in text-to-image generation research as noted in studies [38, 65, 55], is derived from the cosine similarity between the embeddings... | **A**: We refer readers to our suppl.
**B**: for additional results..
**C**: As detailed in Table 3, our quantitative comparisons demonstrate the superior alignment of our method with the text prompt compared to the Latent-NeRF and SJC approaches in diverse scene configurations.
| CAB | CAB | CAB | ACB | Selection 1 |
In this paper, we explore generating synthetic data directly from high level descriptions. Our Python package, repliclust, accomplishes this goal by summarizing the overall geometry of probabilistic mixture models with a few high-level parameters. <|MaskedSetence|> <|MaskedSetence|> The first makes clusters non-conve... | **A**: The second makes a p𝑝pitalic_p-dimensional data set directional by wrapping it around the (p+1)𝑝1(p+1)( italic_p + 1 )-dimensional sphere through an inverse stereographic projection.
.
**B**: Although our approach is based on ellipsoidal clusters, we have implemented two post-processing functions for generati... | CBA | CBA | CBA | CBA | Selection 1 |
While impressive results are reported, we identify two major limitations of the current generation-based event extraction methods. <|MaskedSetence|> According to the experiments conducted by Hsu et al. (2022), a slight change in the template might lead to significant performance changes, thus raising the issue of usi... | **A**: Firstly, most of these methods rely on heuristic templates and extensive human knowledge engineering.
**B**: However, obtaining this oracle information, such as event type and schema, is unrealistic for a real-world inference system to achieve automatically.
**C**: Secondly, most of these generation-based appr... | ACB | ACB | ACB | CBA | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> (2009) firstly introduced the embedding property of RKHS for the empirical process technique. <|MaskedSetence|> Our paper further strengthens the integral operator technique, making it the most powerful technique for establishing learning rates of kernel methods (or spectral algor... | **A**: As mentioned in Fischer and Steinwart (2020), the empirical process and the integral operator techniques are the two main techniques used to derive the learning rates of kernel methods.
**B**: Fischer and Steinwart (2020) further combined the embedding property of RKHS with the integral operator technique.
**C... | ACB | ACB | ACB | ACB | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> <|MaskedSetence|> [25]. The former method, termed Hierarchical Clustering (HC), recursively divides the original point cloud into two sets, until each child set attains a size smaller than a threshold size parameter. Moreover, a variation parameter plays an important role in spars... | **A**: Some of the earliest curvature-sensitive simplification techniques were proposed by Pauly et al.
**B**: In this section we will introduce a number of existing point cloud simplification techniques, with a particular focus on works which have a feature-preserving element to their approach.
**C**: [26] and Moenn... | BAC | BAC | CBA | BAC | Selection 2 |
According to [38], other adaptive algorithms such as FedAdagrad and FedYogi are proposed to improve the model convergence rate under the situation of heterogeneous data. FedAdam employs adaptive learning rates and momentum by leveraging local updates from client devices to efficiently update the global model. FedAdagra... | **A**: The experiment results are illustrated in Table V and Fig. 10.
**B**: Compared with other adaptive FL algorithms, our proposed FedAgg still performs better with higher accuracy and a faster convergence rate.
.
**C**: FedYogi, inspired by the Yogi optimizer, incorporates elements of adaptive learning rates and ... | CAB | CAB | CAB | BCA | Selection 2 |
<|MaskedSetence|> To verify the out-of-domain generation ability of our approach, we conduct a two-stage multi-modal training, and then evaluate three benchmarks (MME (Fu et al., 2023), MMBench (Liu et al., 2023c), LVLM-eHub (Xu et al., 2023)) in a zero-shot manner. <|MaskedSetence|> This step is mainly for the align... | **A**: For the first stage, we utilize the raw image-caption data from LAION-400M (Schuhmann et al., 2021) to tune the projection network and zero-initialized attention modules.
**B**: For the second stage, we freeze the projection network, and only tune the zero-initialized attention within LLaMA by a combination of ... | CAB | BAC | CAB | CAB | Selection 1 |
<|MaskedSetence|> <|MaskedSetence|> However, ContraSim shows that the difference in the ability to detect the correct pair dramatically changes from shallow to deep layers. This raises an interesting insight regarding the evolution of representations across layers. For instance, Conneau et al. (2020b) used CKA to mea... | **A**: Our results show that this difference is higher than found before..
**B**: Using previous similarity measures we might infer that there is no difference in the ability to detect the correct pairs across different layers.
**C**:
In the multilingual benchmark (Table 2, FAISS results), we found a much greater di... | CBA | CBA | CBA | CBA | Selection 3 |
To solve this problem concerning the arrangement and number of points, we define additional VP-related points called ADPs based on the spatial symmetry as follows. <|MaskedSetence|> This symmetry means that a regular octahedron has three types of rotational symmetric axes. To estimate a unique camera rotation requiri... | **A**: The supplementary materials describe details of the symmetry and optimal arrangement..
**B**: Therefore, 3D VP/ADP coordinates are the optimal arrangement given a practical number of points.
**C**: We found that six 3D VPs form a regular octahedron that has the symmetry of regular octahedron groups (octahedral... | CBA | CBA | BAC | CBA | Selection 2 |
<|MaskedSetence|> presented a survey of open-source hardware and software comparing their main features [7]. In Table I some relevant flight controller projects are listed. These projects may cover both hardware and software development of these controllers. They range from Open Source Hardware (OSH) and Open Source S... | **A**: Furthermore, most of them allow to simulate their behavior in a fully simulated way or Software-in-the-Loop (SITL) or in a Hardware-in-the-Loop (HITL) way, where the autopilot code actually runs on the specific hardware of the controller.
**B**: This makes it possible to improve the validation of the systems cr... | ACB | CAB | CAB | CAB | Selection 4 |
<|MaskedSetence|> Rhodes (1961) theorizes that four perspectives have to be considered: product (see Section 3) and process (discussed above), but also the so-called press and person.
Press refers to the relationship between the product and the influence its environment has upon it (Rhodes, 1961). Individuals and thei... | **A**: The resulting system model of creativity is a never-ending cycle where individuals always base their works on knowledge from a domain, which constantly changes thanks to new and valuable artifacts (from different individuals).
**B**: Indeed, product and process are not sufficient to explain creativity.
**C**: ... | BAC | BAC | CBA | BAC | Selection 2 |
Qualitative Comparison. We visualize the detection results of the compared SOTA approaches and our SUP-ICI in Fig. 4. <|MaskedSetence|> The true positives (TP), false positives (FP), and false negatives (FN) are denoted by the green boxes, red boxes, and yellow boxes, respectively. We also display the detection scores... | **A**: On the contrary, the compared approaches’ detection results are usually offset or even completely miss the ground truths.
**B**: As shown, compared with other approaches, our SUP-ICI is able to detect the TPs with higher confidences and more precise positions.
**C**: The detection results are displayed based o... | ABC | CBA | CBA | CBA | Selection 3 |
Recently, many machine-learning based algorithms have been proposed to accelerate the computational speed for OPF, please see [19, 29, 30, 31, 32] and the references within. <|MaskedSetence|> <|MaskedSetence|> For feasibility, the solutions need to have feasibility guarantees. In this paper, we use an NN policy that ... | **A**: To enhance computational speed, the proxy of the second stage cannot involve multiple steps (e.g., a neural network followed by a power flow solver).
**B**: However, many of the existing algorithms are not suitable in a two-stage problem.
**C**: At the same time, a neural network is much more expressive than a... | BAC | BAC | BAC | BAC | Selection 3 |
<|MaskedSetence|> We use the CIFAR10 training set as the unlabelled pool set from which to label points. <|MaskedSetence|> We acquire 10 labels per acquisition round up to 500 labels and evaluate using the full test set. We compare self-supervised BNNs to a deep ensemble, the strongest BNN baseline. <|MaskedSetence|... | **A**: We use BALD (Houlsby et al., 2011) as the acquisition function for the deep ensemble and self-supervised BNN, which provide epistemic uncertainty estimates.
**B**: We consider low-budget active learning, which simulates a scenario where labelling examples is extremely expensive.
**C**: We assume an initial tra... | BCA | BAC | BCA | BCA | Selection 3 |
To provide statistical theory which allows for changes in the probabilistic structure, we consider an “infill” asymptotic framework in which more observations become available at a local level as the observation length T𝑇Titalic_T increases. <|MaskedSetence|> <|MaskedSetence|> This paved the way for the development ... | **A**: Nonstationary processes that can be analyzed in such a framework are known as locally stationary time series.
**B**: The theory was introduced in [33] for the linear case, and refined in [81] to nonlinear time series.
**C**: Theory and corresponding inference techniques for Banach space-valued processes were l... | ABC | ABC | ABC | BAC | Selection 1 |
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