Split (1)

train · 2.93k rows

shuffled_text stringlengths 267 3.44k	A stringclasses 6 values	B stringclasses 6 values	C stringclasses 6 values	D stringclasses 6 values	label stringclasses 4 values
A: We now briefly motivate why finding diverse minimum s𝑠sitalic_s-t𝑡titalic_t cuts in a graph can be of interestB: In general, to solve a real-world problem, one typically formulates the problem as an instance of a computational problem and proceeds to find a solution with the help of an optimization algori...	ABC	ACB	CAB	ACB	Selection 1
A: The only assumption needed is that the topology needs to have the T0subscript𝑇0T_{0}italic_T start_POSTSUBSCRIPT 0 end_POSTSUBSCRIPT property and a computable countable basisB: The advantage to the topological approach used in this paper is that a very general topology can be usedC: Typical requirements...	BAC	ACB	ABC	ABC	Selection 1
A: The goal of this approach is to improve the performance of the model on a target dataset by training the model on the combined dataset and then applying the trained model to the target dataset. In this framework, the proposed normalization technique allows to obtain a domain adaptation. B: However, current a...	ACB	ABC	CAB	CBA	Selection 4
A: Their results are shown at the bottom of TabsB: Enhancing Different OOD Detection Methods. Four different SotA methods – MSP, ODIN, Energy, and ViM – are used as foreground-based OOD detection baseline models and plugged into DFB to perform joint foreground and background OOD detectionC: 1 and 2.	ACB	BCA	ABC	BAC	Selection 4
A: In many cases, the SSIM is greatly improved by adding the LPDM. Adding the LPDM to LIME, RetinexNet, EnlightenGAN, ZeroDCE, ZeroDCE++ and LLFormer boasts up to a 53.5%, 78.65%, 16.8%, 24.08%, 23.82%, 4.92% SSIM improvement, respectively. LLFormer yields new state-of-the-art color SSIM results on the LOL dataset ...	BAC	BCA	CBA	ABC	Selection 3
A: To get a balanced population, we applied the following prescreening conditions: i) participants are from the United States, ii) an equal number of female and male participants, iii) participants with White, Asian, Hispanic, and African ethnicity consist ∼similar-to\sim∼50%, ∼similar-to\sim∼17%, ∼similar-to\sim∼1...	ACB	CAB	BAC	CBA	Selection 4
A: Additionally, we provide residue-level and protein-level results for comprehensive analysisB: The retrieval alignment evaluation on the CATH, trRosetta, Ts50/Ts500, and CASP14 test sets is presented in Group 2 of Table 3C: It’s noteworthy that the protein-level pretrained model exhibits a higher ease in ...	BAC	ABC	BCA	CBA	Selection 1
A: The structure of LiftNet is shown in Fig. 2.B: A TC layer broadcasts the input elements via kernels, thus increasing the dimension of the output. Different from traditional upsampling methods (e.g., nearest-neighbor, bilinear, and bicubic interpolation [29]), TC can capture the interactions among the paramet...	BAC	BCA	BAC	CBA	Selection 4
A: Assuming that we already found the optimal fidelity curves between any two nodes in the network, one can easily find the fidelity curve associated with multipartite entanglement distribution for a given source node and any tree nodes [6]B: Fig. 5 shows the run time as a function of the number of nodes in our...	ACB	CBA	CBA	BAC	Selection 1
A: II describes the preliminaries of polar codes, MWD and SCL decodingB: The ECBS algorithm is proposed in Section V. Section VI shows the performance of polar codes constructed by the MWD sequence and the ECBS algorithm. Section VII concludes this paper.C: The properties of MWUB are shown in Section III. I...	ACB	CBA	BAC	ABC	Selection 1
A: So for this tree we have that the mean depth is given byB: Thus we see that when there are signals the weights on leaf nodes are no longer proportional, but skewed further towards the longer branchesC: where the inequality follows from our assumption 1/2<p<112𝑝11/2<p<11 / 2 < italic_p < 1	ACB	CBA	ABC	BCA	Selection 2
A: (2022) have trained diffusion models from scratch on 3D data or even on 4D data Kim and Ye (2022), and Han et al. (2023) use diffusion models conditioned on anatomical masks to generate labeled images for segmentation.B: Pre-trained models are often trained on 2D RGB datasets, but many medical imaging modali...	BCA	CBA	ABC	CAB	Selection 4
A: Nevertheless, the direct rendering of NeRFs often results in incorrect occlusions within their overlapping regions, indicating a deficiency in global refinement. To improve it, as detailed in (d), we refine sampling points that were originally guided by texts corresponding to individual objects, now with the inc...	BAC	ABC	CAB	BAC	Selection 2
A: First, as a density-based algorithm, HDBSCAN cannot make use of the true number of clusters, putting it at a disadvantage. Second, HDBSCAN reports a large number of noise points (≈\approx≈60% on average), so that its results are not directly comparable to that of the other algorithmsB: We report the performa...	BCA	CAB	CAB	ACB	Selection 1
A: The triggers and arguments missed by the baselines but captured by COFFEE are highlightedB: It is evident that COFFEE is generally more effective in detecting the events.C: Table 3: Event extraction examples from the test set using COFFEE, COFFEE without ranking and TANL+COFFEE	CBA	BCA	BAC	BAC	Selection 2
A: Our paper further strengthens the integral operator technique, making it the most powerful technique for establishing learning rates of kernel methods (or spectral algorithms). We believe that our technical tools can be used for more related topics. For instance, some literature considers the general source cond...	CBA	BCA	BAC	ABC	Selection 1
A: We report the maximum and mean Hausdorff distances between the original meshes, and the meshes reconstructed from the simplified point cloudsB: Also reported is the average surface variation over each simplified point cloud. Best, second-best and third-best results are in red, green and blue respectively. It...	CAB	BCA	ABC	CAB	Selection 2
A: As depicted in Fig. 12, the decrement of the hyperparameter α𝛼\alphaitalic_α demonstrates that the FL framework accentuates the optimization of the discrepancy between the local model of client i𝑖iitalic_i and the average local model, which in turn, bolsters the precision of the global model and expedites the ...	BAC	CAB	CBA	CAB	Selection 1
A: By further injecting visual conditions with a 0.6M projection network, our multi-modal ‘LLaMA-Adapter’ improves +6.88% accuracy, attaining leading results superior to the GPT series. In Table 3 for the three multi-modal benchmarks, compared to the concurrent works, our approach achieves competitive scores with a...	ACB	CBA	BAC	CAB	Selection 3
A: Both linear probing and fine-tuning the whole model are explored. B: We select HMDB51 (Kuehne et al., 2011) containing 6,766 videos with 51 categories and UCF101 (Soomro et al., 2012) containing 13,320 videos with 101 categoriesC: Video action recognition	ACB	CBA	CAB	BAC	Selection 2
A: The original representations are organized according to the source language (by shape), whereas ContraSim projects translations of the same sentence close to each other (clustered by color).B: The ContraSim encoder was trained on Arabic and English languagesC: To further analyze this, we compare the orig...	ACB	ABC	CAB	CBA	Selection 4
A: Moreover, the tilt angle is 0∘superscript00^{\circ}0 start_POSTSUPERSCRIPT ∘ end_POSTSUPERSCRIPT because the height of a camera mounted on a car is sufficiently small with respect to the distance between the camera and other objects. The horizontal center of the panoramic images corresponds with the travel direc...	BCA	CBA	BCA	CAB	Selection 2
A: Our conditions do not require any assumption on the graph, whose topology is just assumed to be time-invariantB: We have provided necessary and sufficient conditions for the synchronization of identical linear SISO systems, with a guaranteed convergence rate, both in the continuous-time and in the discrete-t...	ABC	BAC	ABC	CAB	Selection 2
A: Quantitatively (Spearman), results are similar. The test yields a weak positive correlation (ρ=0.34𝜌0.34\rho=0.34italic_ρ = 0.34)B: Qualitatively, in Figure 6 we see no discernible increase in the number of failures following larger ONNX updatesC: Similarly, Incompatibility and Type Problems	BCA	BAC	ACB	CAB	Selection 2
A: sensor measurements, values corresponding to state estimation, references for controllers, etcB: The Alphanumeric Viewer is a component that monitors the state of specific variables of the system, e.gC: The information is distributed in different panes to facilitate the search for a specific variable of ...	ABC	BCA	BAC	CBA	Selection 3
A: Due to the large impact LLMs are already having (Bommasani et al., 2021) and the quality of outputs of the systems based on them (Stevenson et al., 2022b), it is possible to argue that the artifacts produced by them are indeed valuable. B: Value refers to utility, performance, and attractiveness (Maher, 2010...	BAC	CAB	CBA	ABC	Selection 2
A: Inspired by the success of the Vision Transformers [37] in natural images, the plug-and-play slice grouped non-local modules [2, 34] are specially designed for the pulmonary nodule detection task, which can enhance the detector’s ability to extract the global information and meanwhile reduce the computation of t...	ABC	CAB	BCA	ABC	Selection 2
A: This is because the affine policy has bad generalization when applied to never-seen instances of load forecasts, and tend to resort to load shedding in the second stage, leading to high costs. B: In comparison, using the affine policy reduces the average running time by half, however, it also performs 20%per...	ACB	ABC	CBA	ACB	Selection 3
A: Others place priors directly over predictive functions (Flam-Shepherd et al., 2017; Sun et al., 2019; Matsubara et al., 2021; Nalisnick et al., 2021; Raj et al., 2023). Both approaches, however, present challenges—the mapping between the network’s parameters and predictive functions is complex, while directly sp...	ABC	CBA	ABC	BAC	Selection 2
A: The need for reliable inference on shape and topological features in applications has led to substantial interest in integrating classical statistical techniques with topological invariantsB: Roughly speaking, TDA provides qualitative multiscale shape descriptors for point clouds, notably persistent homolog...	BAC	ABC	CBA	CAB	Selection 2

Subsets and Splits

No community queries yet

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