DREAM: Efficient Dataset Distillation by Representative Matching

Dataset distillation aims to synthesize small datasets with little information loss from original large-scale ones for reducing storage and training costs. Recent state-of-the-art methods mainly constrain the sample synthesis process by matching synthetic images and the original ones regarding gradients, embedding distributions, or training trajectories. Although there are various matching objectives, currently the strategy for selecting original images is limited to naive random sampling. We argue that random sampling overlooks the evenness of the selected sample distribution, which may result in noisy or biased matching targets. Besides, the sample diversity is also not constrained by random sampling. These factors together lead to optimization instability in the distilling process and degrade the training efficiency. Accordingly, we propose a novel matching strategy named as \textbf{D}ataset distillation by \textbf{RE}present\textbf{A}tive \textbf{M}atching (DREAM), where only representative original images are selected for matching. DREAM is able to be easily plugged into popular dataset distillation frameworks and reduce the distilling iterations by more than 8 times without performance drop. Given sufficient training time, DREAM further provides significant improvements and achieves state-of-the-art performances.Comment: Efficient matching for dataset distillatio

GUDN: A novel guide network with label reinforcement strategy for extreme multi-label text classification

In natural language processing, extreme multi-label text classification is an emerging but essential task. The problem of extreme multi-label text classification (XMTC) is to recall some of the most relevant labels for a text from an extremely large label set. Large-scale pre-trained models have brought a new trend to this problem. Though the large-scale pre-trained models have made significant achievements on this problem, the valuable fine-tuned methods have yet to be studied. Though label semantics have been introduced in XMTC, the vast semantic gap between texts and labels has yet to gain enough attention. This paper builds a new guide network (GUDN) to help fine-tune the pre-trained model to instruct classification later. Furthermore, GUDN uses raw label semantics combined with a helpful label reinforcement strategy to effectively explore the latent space between texts and labels, narrowing the semantic gap, which can further improve predicted accuracy. Experimental results demonstrate that GUDN outperforms state-of-the-art methods on Eurlex-4k and has competitive results on other popular datasets. In an additional experiment, we investigated the input lengths' influence on the Transformer-based model's accuracy. Our source code is released at https://t.hk.uy/aFSH.Comment: 12 pages, 6 figure

DREAM+: Efficient Dataset Distillation by Bidirectional Representative Matching

Dataset distillation plays a crucial role in creating compact datasets with similar training performance compared with original large-scale ones. This is essential for addressing the challenges of data storage and training costs. Prevalent methods facilitate knowledge transfer by matching the gradients, embedding distributions, or training trajectories of synthetic images with those of the sampled original images. Although there are various matching objectives, currently the strategy for selecting original images is limited to naive random sampling. We argue that random sampling overlooks the evenness of the selected sample distribution, which may result in noisy or biased matching targets. Besides, the sample diversity is also not constrained by random sampling. Additionally, current methods predominantly focus on single-dimensional matching, where information is not fully utilized. To address these challenges, we propose a novel matching strategy called Dataset Distillation by Bidirectional REpresentAtive Matching (DREAM+), which selects representative original images for bidirectional matching. DREAM+ is applicable to a variety of mainstream dataset distillation frameworks and significantly reduces the number of distillation iterations by more than 15 times without affecting performance. Given sufficient training time, DREAM+ can further improve the performance and achieve state-of-the-art results. We have released the code at github.com/NUS-HPC-AI-Lab/DREAM+.Comment: This is an extension of the ICCV conference versio

The Constraints of Unitary on ππ\pi\pi Scattering Dispersion Relations

A new dispersion relation for the partial wave $\pi\pi$ scattering $S$ matrix is set up. Using the dispersion relation we generalize the single channel unitarity condition, $SS^+=1$, to the entire complex $s$ plane, which is equivalent to the generalized unitarity condition in quantum mechanics. The pole positions of the $\sigma$ resonance and the $f_0(980)$ resonance are estimated based on the theoretical relations we obtained. The central value of the $\sigma$ pole position is $M_\sigma\simeq 410$MeV, $\Gamma_\sigma\simeq 550$MeV, obtained after including the the constraint of the Adler zero condition.Comment: 10 pages with 4 figures, revised version to appear in Phys. Lett.

The Ginger-shaped Asteroid 4179 Toutatis: New Observations from a Successful Flyby of Chang'e-2

On 13 December 2012, Chang'e-2 conducted a successful flyby of the near-Earth asteroid 4179 Toutatis at a closest distance of 770 $\pm$ 120 meters from the asteroid's surface. The highest-resolution image, with a resolution of better than 3 meters, reveals new discoveries on the asteroid, e.g., a giant basin at the big end, a sharply perpendicular silhouette near the neck region, and direct evidence of boulders and regolith, which suggests that Toutatis may bear a rubble-pile structure. Toutatis' maximum physical length and width are (4.75 $\times$ 1.95 km) $\pm$10$\%$, respectively, and the direction of the +$z$ axis is estimated to be (250$\pm$5$^\circ$, 63$\pm$5$^\circ$) with respect to the J2000 ecliptic coordinate system. The bifurcated configuration is indicative of a contact binary origin for Toutatis, which is composed of two lobes (head and body). Chang'e-2 observations have significantly improved our understanding of the characteristics, formation, and evolution of asteroids in general.Comment: 21 pages, 3 figures, 1 tabl

Observation of nonrelativistic plaid-like spin splitting in a noncoplanar antiferromagnet

Spatial, momentum and energy separation of electronic spins in condensed matter systems guides the development of novel devices where spin-polarized current is generated and manipulated. Recent attention on a set of previously overlooked symmetry operations in magnetic materials leads to the emergence of a new type of spin splitting besides the well-studied Zeeman, Rashba and Dresselhaus effects, enabling giant and momentum dependent spin polarization of energy bands on selected antiferromagnets independent of relativistic spin-orbit interaction. Despite the ever-growing theoretical predictions, the direct spectroscopic proof of such spin splitting is still lacking. Here, we provide solid spectroscopic and computational evidence for the existence of such materials. In the noncoplanar antiferromagnet MnTe$_2$, the in-plane components of spin are found to be antisymmetric about the high-symmetry planes of the Brillouin zone, comprising a plaid-like spin texture in the antiferromagnetic ground state. Such an unconventional spin pattern, further found to diminish at the high-temperature paramagnetic state, stems from the intrinsic antiferromagnetic order instead of the relativistic spin-orbit coupling. Our finding demonstrates a new type of spin-momentum locking with a nonrelativistic origin, placing antiferromagnetic spintronics on a firm basis and paving the way for studying exotic quantum phenomena in related materials.Comment: Version 2, 30 pages, 4 main figures and 8 supporting figure

Single-cell RNA sequencing reveals cancer stem-like cells and dynamics in tumor microenvironment during cholangiocarcinoma progression

Cholangiocarcinoma is a malignancy of the bile ducts that is driven by activities of cancer stem-like cells and characterized by a heterogeneous tumor microenvironment. To better understand the transcriptional profiles of cancer stem-like cells and dynamics in the tumor microenvironment during the progression of cholangiocarcinoma, we performed single-cell RNA analysis on cells collected from three different timepoints of tumorigenesis in a YAP/AKT mouse model. Bulk RNA sequencing data from TCGA (The Cancer Genome Atlas program) and ICGC cohorts were used to verify and support the finding. In vitro and in vivo experiments were performed to assess the stemness of cancer stem-like cells. We identified Tm4sf1high malignant cells as cancer stem-like cells. Across timepoints of cholangiocarcinoma formation in YAP/AKT mice, we found dynamic change in cancer stem-like cell/stromal/immune cell composition. Nevertheless, the dynamic interaction among cancer stem-like cells, immune cells, and stromal cells at different timepoints was elaborated. Collectively, these data serve as a useful resource for better understanding cancer stem-like cell and malignant cell heterogeneity, stromal cell remodeling, and immune cell reprogramming. It also sheds new light on transcriptomic dynamics during cholangiocarcinoma progression at single-cell resolution

The Effect of Damping Coefficient, Spring Coefficient, and Mass Ratio on the Power Extraction Performance of a Semiactive Flapping Wing

The effect of varying damping coefficient C∗, spring coefficient K∗, and mass ratio M∗ on the semiactive flapping wing power extraction performance was numerically studied in this paper. A numerical code based on Finite Volume method to solve the two-dimensional Navier-Stokes equations and coupled with Finite Center Difference method to solve the passive plunging motion equation is developed. At a Reynolds number of 3400 and the pitching axis at quarter chord from the leading edge of the wing, the power extraction performance of the semiactive flapping wing with different damping coefficient, spring coefficient, and mass ratio is systematically investigated. The optimal set of spring coefficient is found at a value of 1.00. However, the variation of mass ratio M∗ cannot increase the maximum mean power coefficient and power efficiency, but it can influence the value of damping coefficient C∗ at which the wing achieves the maximum mean power coefficient and power efficiency. Moreover, insensitivity of the mean power coefficient and power efficiency to the variation of damping coefficient C∗ is observed for the wing with smaller mass ratio, which indicates the wing with smaller M∗ has better working stability