2306.11695] A Simple and Effective Pruning Approach for Large Language Models Skip to

1910.04760] A cost-effective method for improving and re-purposing large, pre-trained GANs

1912.04421] Basis Prediction Networks for Effective Burst Denoising with Large Kernels Skip to main content We

1910.13267] BPE-Dropout: Simple and Effective Subword Regularization Skip to main content We gratefully acknowledge support

1503.05884] Effective equidistribution and property tau Skip to main content We gratefully acknowledge support

0708.4040] Effective equidistribution for closed orbits of semisimple groups on homogeneous spaces Skip to

2311.01378] Vision-Language Foundation Models as Effective Robot Imitators Skip to main content We gratefully acknowledge support from

1901.05555] Class-Balanced Loss Based on Effective Number of Samples Skip to main content We gratefully

algebraic unit. His proof depends on Duke's Equidistribution Theorem and is hence non-effective. In this

1910.12755] Two recent p-adic approaches towards the (effective) Mordell conjecture Skip to main content We

In this paper, we propose novel approaches for unconditional GAN compression. We first introduce effective channel pruning and

to track and verify training data ownership. Previous data watermarking techniques primarily focus on effective memorization during pretraining, while

to theoretically explain the applicability of the proposed framework. 3) Effective: Comprehensive experimental analysis on

reconstructing high-fidelity appearance from images taken under extreme illumination variation. Moreover, our approach is particularly effective at recovering view-dependent

object labels through conditional random fields for collective classification, whereas graph neural networks learn effective object representations for

domain-specific questions. We find that both Reinforced and Unsupervised ICL can be quite effective in the

Learned Discontinuities, by Chenxi Liu and 4 other authors View PDF HTML (experimental) Abstract: Effective representation of 2D

Sohn and 8 other authors View PDF Abstract: Semi-supervised learning (SSL) provides an effective means of leveraging

fine details or excessive training time. In this paper, we propose an efficient yet effective framework, HumanGaussian, that generates

social media, there is a critical need for systems that can provide effective real-time verification of

specific knowledge into the student universal embedding. UDON's distillation approach is not only effective, but also very efficient

and 3 other authors View PDF HTML (experimental) Abstract: Sinusoidal neural networks have been shown effective as implicit neural representations

on six benchmarks spanning pairwise registration and shape assembly. Notably, our unified formulation enables effective joint training on diverse

along with a shadow map, inferred using a simple and effective technique, to spatially

Abstract: Generating realistic human videos remains a challenging task, with the most effective methods currently relying on

rank losses and ensures robust training. Secondly, we use a simple yet effective loss function to

the number of images per class, leading to long-tailed distributions. An effective and simple

In this work, we present pyramid adversarial training (PyramidAT), a simple and effective technique to improve

in models that are capable of extracting image features that are not only effective at encoding image level

on the growth of structure and neutrino masses from SDSS with effective field theory Skip to

the above phenomena by defining a new complexity measure we call the effective model complexity and

weights important for those tasks. We demonstrate our approach is scalable and effective by solving a

a multi-scale discriminator with a text alignment loss to build an effective conditional GAN-based formulation

inefficient. To address this, we propose Inheritune, a simple and effective training recipe for

in better understanding PD motor progression, thus advancing the development of more effective and personalized

the translated goal can be handed to domain-independent AI planners that are very effective at planning. Our empirical

self-supervised learning in several domains. In particular, contrastive methods are most effective where data augmentation can

to reading original paper texts, and the authors viewed our system as an effective way of communicating

faithful brushstrokes, and introduce a nearest neighbor-based loss that is highly effective at capturing style details

not diverse. To address this, we introduce ULIP-2, a simple yet effective tri-modal pre-training

on the analysis of existing exploration methods, we propose a more effective modification of the

task of private GM with an excess error guarantee that scales with the effective diameter of the

class in the $\mathcal{W}$ latent space. With NoisyTwins, we first introduce an effective and inexpensive

Phongthawee and 6 other authors View PDF Abstract: We present a simple yet effective technique to estimate

and 4 other authors View PDF HTML (experimental) Abstract: Physical reasoning is important for effective robot manipulation. Recent work

that improving the visual realism of the images can be more effective than imposing task-specific

Pumacay and 5 other authors View PDF HTML (experimental) Abstract: To realize effective large-scale, real-world

and testing more challenging. In this work we introduce a simple, yet effective Convolutional Random Walk Network

the identity of the input portrait. Experiments show that our method is more effective in resynthesizing

processing. We show that incorporating this information can markedly enhance semantic correspondence performance with simple but effective solutions in both

from N to Z, we define the notion of an effective (or closed) formula. It

This emerges by minimizing the cost of producing a desired effective isotropic radiated power, which

a measurement of $D_A(z)/r_d$ and $H(z)r_d$ at nine effective redshifts with the

space that represents photorealistic image neural fields. We propose a simple and effective method, inspired by several

reduce the required human efforts. To utilize such data, we propose an effective multi-task language-conditioned

assumptions, such as a prior pose distribution or coarse pose initialization, making them less effective in a

in terms of generality. Following the most popular and effective paradigm in this

affordance learning. We then propose a vision-language framework with simple and effective designs that boost the

the accuracy and precision of the derived stellar parameters, considering especially effective temperature, surface gravity, and