Split (1)

train · 2.93k rows

shuffled_text stringlengths 267 3.16k	A stringclasses 6 values	B stringclasses 6 values	C stringclasses 6 values	D stringclasses 6 values	label stringclasses 4 values
A: Since then, the computational complexity of finding diverse solutions in many other combinatorial problems has been studied. For instance, diverse variants of Vertex Cover, Matching and Hitting Set have been shown to be NP-hard, even when considering simple diversity measures like the pairwise-sum of Hamming dis...	ABC	CAB	BAC	ABC	Selection 2
A: Given a measurement apparatus E𝐸Eitalic_E, there is only a tiny fraction of quantum pure states on which E𝐸Eitalic_E’s application produces coherent information. This is independent of the number of measurement outcomes of E𝐸Eitalic_E. B: This section shows the limitations of the algorithmic content of [u...	BAC	ACB	ACB	CBA	Selection 4
A: Training employed early stopping based on validation performance, and images were pre-processed by normalizing them with respect to the dataset’s mean and standard deviation. Data augmentation techniques such as horizontal flipping and random cropping were applied to enhance the dataset. The AdamW optimizer with...	CBA	BCA	CAB	ABC	Selection 3
A: † indicates that the results are taken from the original paper, and other methods are reproduced using the same network architectureB: Four post-hoc foreground OOD detection methods are respectively plugged into our method ‘X’-DFB, where improved results are highlighted in red and they are in blue otherwise....	BCA	BAC	ABC	CBA	Selection 1
A: Despite denoisers significantly reducing noise, they often introduce blurriness into the denoised output. As a result, removing the amplified noise in a brightened low-light image often comes at the cost of removing detail, especially in high-frequency regions of the image.B: These denoising techniques range...	CAB	ABC	ACB	CBA	Selection 4
A: All subjects gave their informed consent for inclusion before they participated in the studyB: The protocol of the study was approved by the Ethics Committee of Central European University (reference number: 2022-2023/1/EX)C: All methods of the study were carried out following the principles of the Belmo...	BCA	ABC	ACB	ACB	Selection 2
A: Designr), while there is no significant disparity between the residue-level and protein-level pretrained modules in downstream tasks, Designr slightly outperforms Designp overallB: Furthermore, regarding different levels (Designp vsC: This observation suggests that any small gaps between the two levels o...	CAB	ABC	CAB	BAC	Selection 4
A: MRR is the average inverse rank for all test triples, and H@k is the percentage of ranks lower than or equal to kB: The maximum values of MRR and H@k are both 1, and the higher MRR or H@k, the better the performance. We adopt the filtered setting [9] to exclude candidate triples that have been seen in traini...	ACB	ACB	ACB	BCA	Selection 4
A: Note that we did not specify how the priority value of each node is computed simply because we do not know what the optimal way to compute such a value isB: Prioritizing paths with a low likelihood of being dominated will reduce the number of recomputations and paths added to the priority queue. C: This ...	BAC	ABC	BCA	BAC	Selection 3
A: 8 are shown in Table III.B: FigC: 8 provides the BLER performance of (512,256)512256\left(512,256\right)( 512 , 256 ) and (512,384)512384\left(512,384\right)( 512 , 384 ) polar codes with different construction methods. The MWDs of the polar codes in Fig	CBA	BAC	CAB	BAC	Selection 3
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	BCA	BAC	CAB	CBA	Selection 4
A: (2021)B: To explore the potential benefits of a diffusion-based approach over a GAN-based approach, we include the state-of-the-art StyleGAN3 as a baseline Karras et alC: To allow a fair comparison, we fine-tune a pre-trained StyleGAN3 on the same hardware for the same number of steps. A blind compariso...	CBA	CAB	BAC	CAB	Selection 3
A: Plus, cameras are oriented to look toward the objectsB: The camera distance can also be scaled in the way discussed in the main paperC: During optimization, the camera field of view is randomly sampled between 40 and 70 degrees. At test time, the field of view is fixed at 60 degrees.	BCA	BAC	BCA	CBA	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: Table 3 separately li...	CBA	ACB	BAC	BCA	Selection 3
A: One challenge of the sentence-level event extraction is that a sentence may contain more than one event record (Si et al., 2022; Subburathinam et al., 2019) (e.g., the example in Figure 1), and event specific templates can help the model to identify and extract events in a targeted manner. Prior approaches tackl...	ACB	ACB	CAB	CBA	Selection 3
A: For details of interpolation of Banach spaces through the real method, we refer to Sawano (2018, Chapter 4.2.2)B: It is worth pointing out the relation between the definition (5) and the interpolation space defined through the real method (real interpolation)C: Specifically, Steinwart and Scovel (2012, ...	ACB	BAC	CBA	CAB	Selection 2
A: and Lv et al. do not provide open-source implementations of their curvature-sensitive simplification techniques, which poses a challenge for reproducibility and benchmarking. However, we thank the authors of Potamias et al. for directly providing some simplified point clouds; their results are included later in ...	ACB	CAB	BCA	ACB	Selection 3
A: In this section, we first introduce the preliminaries regarding the standard FL model in Section III-AB: Then, we formulate our FL optimization problem by considering the local model deviation of each client in Section III-BC: The workflow of our proposed FL framework with aggregated gradient is present...	ACB	ABC	BCA	BCA	Selection 2
A: This is because, LLaVA requires fine-tuning the entire 7B LLM, and Mini-GPT4 adopts Vicuna (Chiang et al., 2023) that also fully fine-tunes LLaMA with 13B parameters.B: By further injecting visual conditions with a 0.6M projection network, our multi-modal ‘LLaMA-Adapter’ improves +6.88% accuracy, attaining l...	ACB	ACB	CBA	BAC	Selection 3
A: We evaluate the performance on ActivityNet (Heilbron et al., 2015), an action understanding dataset of 19,994 temporally annotated untrimmed videos with 200 action categories.B: TAL aims at predicting the temporal extent and the labels of action instancesC: Temporal action localization (TAL)	BAC	BAC	CBA	BCA	Selection 3
A: Centered Kernel Alignment (CKA): Proposed by Kornblith et alB: (2019), CKA computes a kernel matrix for each matrix representation input, and defines the scalar similarity index as the two kernel matrices’ alignmentC: We use a linear kernel for CKA evaluation, as the original paper reveals similar resul...	ACB	BAC	ABC	CAB	Selection 3
A: In keypoint metrics, the VP estimator trained using our loss function improved the average precision (AP), average recall (AR)50, and AR75 by 0.01 points, compared with the VP estimator trained using the HRNet loss function. The mean distance errors of all VP/ADPs in the VP estimator trained using our loss funct...	CAB	CBA	ACB	ACB	Selection 2
A: Then, we prove the following chain of implications: (iii) ⟹⟹\Longrightarrow⟹ (iv), followed by (iv) ⟹\implies⟹ (v), (v) ⟹\implies⟹ (vi), and finally (vi) ⟹\implies⟹ (ii). This ensures that all the six statements are equivalent.B: We first prove the equivalence among statements (i), (ii) and (iii)C: To sh...	CBA	BAC	ACB	CAB	Selection 1
A: studied behavioral issues resulting from framework-to-framework conversion (Louloudakis et al., 2023a). They found failures in 10 out of 36 conversionsB: Louloudakis et alC: They created a fault localization and repair pipeline to localize and fix discrepancies (Louloudakis et al., 2023b).	BCA	CBA	BAC	ACB	Selection 3
A: Although our initial experiments involved only two drones simultaneously, the results confirm the framework’s fundamental capabilities.B: These features have been validated through a series of experiments in both simulated and real-world scenarios, demonstrating the effectiveness of the frameworkC: This...	ACB	BAC	ACB	CBA	Selection 4
A: It consists of three steps: fine-tuning the pre-trained model in a supervised fashion on human-produced answers to sampled questions; training a reward model to predict which text among different options is the most appropriate based on human-labeled rankings; and fine-tuning the language model to maximize the l...	ABC	BCA	BCA	BAC	Selection 4
A: We also analyze the impact of various EMA rate β𝛽\betaitalic_β on the model performanceB: This can be seen from the recall rates at the large average numbers of false positives per CT image in Table VI. However, if the β𝛽\betaitalic_β is too large, then the teacher model will barely change. These results d...	CAB	BCA	ACB	CAB	Selection 3
A: 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. However, many of the existing algorithms are not suitable in a two-stage problemB: In this paper, we use an NN policy that is construct...	BCA	ABC	ACB	CBA	Selection 3
A: We thus also expect these augmentation schemes to preserve the unknown downstream labels of different inputs. The challenge is now to transfer the beliefs—implicitly defined through our data augmentation scheme—into our model.B: Indeed, such approaches that use data augmentation provide effective means for m...	CBA	ACB	CBA	CAB	Selection 4
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...	CAB	CAB	ABC	CAB	Selection 3

Subsets and Splits

No community queries yet

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