252 research outputs found
Action-Conditioned Contrastive Policy Pretraining
Deep visuomotor policy learning achieves promising results in control tasks
such as robotic manipulation and autonomous driving, where the action is
generated from the visual input by the neural policy. However, it requires a
huge number of online interactions with the training environment, which limits
its real-world application. Compared to the popular unsupervised feature
learning for visual recognition, feature pretraining for visuomotor control
tasks is much less explored. In this work, we aim to pretrain policy
representations for driving tasks using hours-long uncurated YouTube videos. A
new contrastive policy pretraining method is developed to learn
action-conditioned features from video frames with action pseudo labels.
Experiments show that the resulting action-conditioned features bring
substantial improvements to the downstream reinforcement learning and imitation
learning tasks, outperforming the weights pretrained from previous unsupervised
learning methods. Code and models will be made publicly available
Chiral Dirac-like fermion in spin-orbit-free antiferromagnetic semimetals
Dirac semimetal is a phase of matter, whose elementary excitation is
described by the relativistic Dirac equation. In the limit of zero mass, its
parity-time symmetry enforces the Dirac fermion in the momentum space, which is
composed of two Weyl fermions with opposite chirality, to be non-chiral.
Inspired by the flavor symmetry in particle physics, we theoretically propose a
massless Dirac-like equation yet linking two Weyl fields with the identical
chirality by assuming SU(2) isospin symmetry, independent of the space-time
rotation exchanging the two fields. Dramatically, such symmetry is hidden in
certain solid-state spin-1/2 systems with negligible spin-orbit coupling, where
the spin degree of freedom is decoupled with the lattice. Therefore, the
existence of the corresponding quasiparticle, dubbed as flavor Weyl fermion,
cannot be explained by the conventional (magnetic) space group framework. The
four-fold degenerate flavor Weyl fermion manifests linear dispersion and a
Chern number of 2, leading to a robust network of topologically protected Fermi
arcs throughout the Brillouin zone. For material realization, we show that the
transition-metal chalcogenide CoNb3S6 with experimentally confirmed collinear
antiferromagnetic order is ideal for flavor Weyl semimetal under the
approximation of vanishing spin-orbit coupling. Our work reveals a counterpart
of the flavor symmetry in magnetic electronic systems, leading to further
possibilities of emergent phenomena in quantum materials.Comment: 27 pages and 5 figure
Sudowoodo: a Chinese Lyric Imitation System with Source Lyrics
Lyrics generation is a well-known application in natural language generation
research, with several previous studies focusing on generating accurate lyrics
using precise control such as keywords, rhymes, etc. However, lyrics imitation,
which involves writing new lyrics by imitating the style and content of the
source lyrics, remains a challenging task due to the lack of a parallel corpus.
In this paper, we introduce \textbf{\textit{Sudowoodo}}, a Chinese lyrics
imitation system that can generate new lyrics based on the text of source
lyrics. To address the issue of lacking a parallel training corpus for lyrics
imitation, we propose a novel framework to construct a parallel corpus based on
a keyword-based lyrics model from source lyrics. Then the pairs \textit{(new
lyrics, source lyrics)} are used to train the lyrics imitation model. During
the inference process, we utilize a post-processing module to filter and rank
the generated lyrics, selecting the highest-quality ones. We incorporated audio
information and aligned the lyrics with the audio to form the songs as a bonus.
The human evaluation results show that our framework can perform better lyric
imitation. Meanwhile, the \textit{Sudowoodo} system and demo video of the
system is available at
\href{https://Sudowoodo.apps-hp.danlu.netease.com/}{Sudowoodo} and
\href{https://youtu.be/u5BBT_j1L5M}{https://youtu.be/u5BBT\_j1L5M}.Comment: 7 pages,3 figures, submit to emnlp 2023 demo trac
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