arxiv_id float64 1.5k 2.51k | title stringlengths 9 178 ⌀ | authors stringlengths 2 22.8k | categories stringlengths 4 146 | summary stringlengths 103 1.92k ⌀ | published stringdate 2015-02-06 10:44:00 2025-07-10 17:59:58 ⌀ | comments stringlengths 2 417 ⌀ | journal_ref stringclasses 321
values | doi stringclasses 398
values | ss_title stringlengths 8 159 ⌀ | ss_authors stringlengths 11 8.38k ⌀ | ss_year float64 2.02k 2.03k ⌀ | ss_venue stringclasses 281
values | ss_citationCount float64 0 134k ⌀ | ss_referenceCount float64 0 429 ⌀ | ss_fieldsOfStudy stringclasses 47
values |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,211.08233 | Temporal Modeling Matters: A Novel Temporal Emotional Modeling Approach
for Speech Emotion Recognition | ['Jiaxin Ye', 'Xin-cheng Wen', 'Yujie Wei', 'Yong Xu', 'Kunhong Liu', 'Hongming Shan'] | ['cs.SD', 'cs.CL', 'eess.AS'] | Speech emotion recognition (SER) plays a vital role in improving the
interactions between humans and machines by inferring human emotion and
affective states from speech signals. Whereas recent works primarily focus on
mining spatiotemporal information from hand-crafted features, we explore how to
model the temporal pa... | 2022-11-14T13:35:01Z | ICASSP 2023 | IEEE ICASSP 2023 | 10.1109/ICASSP49357.2023.10096370 | null | null | null | null | null | null | null |
2,211.08332 | Versatile Diffusion: Text, Images and Variations All in One Diffusion
Model | ['Xingqian Xu', 'Zhangyang Wang', 'Eric Zhang', 'Kai Wang', 'Humphrey Shi'] | ['cs.CV'] | Recent advances in diffusion models have set an impressive milestone in many
generation tasks, and trending works such as DALL-E2, Imagen, and Stable
Diffusion have attracted great interest. Despite the rapid landscape changes,
recent new approaches focus on extensions and performance rather than capacity,
thus requiri... | 2022-11-15T17:44:05Z | ICCV 2023; Github link:
https://github.com/SHI-Labs/Versatile-Diffusion | null | null | Versatile Diffusion: Text, Images and Variations All in One Diffusion Model | ['Xingqian Xu', 'Zhangyang Wang', 'Eric Zhang', 'Kai Wang', 'Humphrey Shi'] | 2,022 | IEEE International Conference on Computer Vision | 198 | 117 | ['Computer Science'] |
2,211.08609 | R-Pred: Two-Stage Motion Prediction Via Tube-Query Attention-Based
Trajectory Refinement | ['Sehwan Choi', 'Jungho Kim', 'Junyong Yun', 'Jun Won Choi'] | ['cs.CV'] | Predicting the future motion of dynamic agents is of paramount importance to
ensuring safety and assessing risks in motion planning for autonomous robots.
In this study, we propose a two-stage motion prediction method, called R-Pred,
designed to effectively utilize both scene and interaction context using a
cascade of ... | 2022-11-16T01:43:39Z | null | null | null | null | null | null | null | null | null | null |
2,211.08769 | RetroMAE v2: Duplex Masked Auto-Encoder For Pre-Training
Retrieval-Oriented Language Models | ['Shitao Xiao', 'Zheng Liu'] | ['cs.CL', 'cs.IR'] | To better support retrieval applications such as web search and question
answering, growing effort is made to develop retrieval-oriented language
models. Most of the existing works focus on improving the semantic
representation capability for the contextualized embedding of [CLS] token.
However, recent study shows that... | 2022-11-16T08:57:55Z | null | null | null | RetroMAE v2: Duplex Masked Auto-Encoder For Pre-Training Retrieval-Oriented Language Models | ['Shitao Xiao', 'Zheng Liu'] | 2,022 | arXiv.org | 2 | 35 | ['Computer Science'] |
2,211.09085 | Galactica: A Large Language Model for Science | ['Ross Taylor', 'Marcin Kardas', 'Guillem Cucurull', 'Thomas Scialom', 'Anthony Hartshorn', 'Elvis Saravia', 'Andrew Poulton', 'Viktor Kerkez', 'Robert Stojnic'] | ['cs.CL', 'stat.ML'] | Information overload is a major obstacle to scientific progress. The
explosive growth in scientific literature and data has made it ever harder to
discover useful insights in a large mass of information. Today scientific
knowledge is accessed through search engines, but they are unable to organize
scientific knowledge ... | 2022-11-16T18:06:33Z | null | null | null | null | null | null | null | null | null | null |
2,211.0911 | Holistic Evaluation of Language Models | ['Percy Liang', 'Rishi Bommasani', 'Tony Lee', 'Dimitris Tsipras', 'Dilara Soylu', 'Michihiro Yasunaga', 'Yian Zhang', 'Deepak Narayanan', 'Yuhuai Wu', 'Ananya Kumar', 'Benjamin Newman', 'Binhang Yuan', 'Bobby Yan', 'Ce Zhang', 'Christian Cosgrove', 'Christopher D. Manning', 'Christopher Ré', 'Diana Acosta-Navas', 'Dre... | ['cs.CL', 'cs.AI', 'cs.LG'] | Language models (LMs) are becoming the foundation for almost all major
language technologies, but their capabilities, limitations, and risks are not
well understood. We present Holistic Evaluation of Language Models (HELM) to
improve the transparency of language models. First, we taxonomize the vast
space of potential ... | 2022-11-16T18:51:34Z | Authored by the Center for Research on Foundation Models (CRFM) at
the Stanford Institute for Human-Centered Artificial Intelligence (HAI).
Project page: https://crfm.stanford.edu/helm/v1.0 | Published in Transactions on Machine Learning Research (TMLR),
2023 | null | null | null | null | null | null | null | null |
2,211.0926 | Task-aware Retrieval with Instructions | ['Akari Asai', 'Timo Schick', 'Patrick Lewis', 'Xilun Chen', 'Gautier Izacard', 'Sebastian Riedel', 'Hannaneh Hajishirzi', 'Wen-tau Yih'] | ['cs.CL'] | We study the problem of retrieval with instructions, where users of a
retrieval system explicitly describe their intent along with their queries. We
aim to develop a general-purpose task-aware retrieval system using multi-task
instruction tuning, which can follow human-written instructions to find the
best documents fo... | 2022-11-16T23:13:22Z | Code, data and pretrained model checkpoints are available at
https://github.com/facebookresearch/tart | null | null | null | null | null | null | null | null | null |
2,211.09552 | UniFormerV2: Spatiotemporal Learning by Arming Image ViTs with Video
UniFormer | ['Kunchang Li', 'Yali Wang', 'Yinan He', 'Yizhuo Li', 'Yi Wang', 'Limin Wang', 'Yu Qiao'] | ['cs.CV'] | Learning discriminative spatiotemporal representation is the key problem of
video understanding. Recently, Vision Transformers (ViTs) have shown their
power in learning long-term video dependency with self-attention.
Unfortunately, they exhibit limitations in tackling local video redundancy, due
to the blind global com... | 2022-11-17T14:17:40Z | 24 pages, 4 figures, 20 tables | null | null | UniFormerV2: Spatiotemporal Learning by Arming Image ViTs with Video UniFormer | ['Kunchang Li', 'Yali Wang', 'Yinan He', 'Yizhuo Li', 'Yi Wang', 'Limin Wang', 'Y. Qiao'] | 2,022 | arXiv.org | 113 | 93 | ['Computer Science'] |
2,211.09699 | PromptCap: Prompt-Guided Task-Aware Image Captioning | ['Yushi Hu', 'Hang Hua', 'Zhengyuan Yang', 'Weijia Shi', 'Noah A Smith', 'Jiebo Luo'] | ['cs.CV', 'cs.CL'] | Knowledge-based visual question answering (VQA) involves questions that
require world knowledge beyond the image to yield the correct answer. Large
language models (LMs) like GPT-3 are particularly helpful for this task because
of their strong knowledge retrieval and reasoning capabilities. To enable LM to
understand i... | 2022-11-15T19:07:53Z | Accepted to ICCV 2023 | null | null | PromptCap: Prompt-Guided Task-Aware Image Captioning | ['Yushi Hu', 'Hang Hua', 'Zhengyuan Yang', 'Weijia Shi', 'Noah A. Smith', 'Jiebo Luo'] | 2,022 | arXiv.org | 106 | 108 | ['Computer Science'] |
2,211.09707 | Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion
Models | ['Simon Alexanderson', 'Rajmund Nagy', 'Jonas Beskow', 'Gustav Eje Henter'] | ['cs.LG', 'cs.CV', 'cs.GR', 'cs.HC', 'cs.SD', 'eess.AS', '68T07', 'G.3; I.2.6; I.3.7; J.5'] | Diffusion models have experienced a surge of interest as highly expressive
yet efficiently trainable probabilistic models. We show that these models are
an excellent fit for synthesising human motion that co-occurs with audio, e.g.,
dancing and co-speech gesticulation, since motion is complex and highly
ambiguous given... | 2022-11-17T17:41:00Z | 20 pages, 9 figures. Published in ACM ToG and presented at SIGGRAPH
2023 | ACM Trans. Graph. 42, 4 (August 2023), 20 pages | 10.1145/3592458 | Listen, Denoise, Action! Audio-Driven Motion Synthesis with Diffusion Models | ['Simon Alexanderson', 'Rajmund Nagy', 'J. Beskow', 'G. Henter'] | 2,022 | ACM Transactions on Graphics | 174 | 168 | ['Computer Science', 'Engineering'] |
2,211.0976 | VeLO: Training Versatile Learned Optimizers by Scaling Up | ['Luke Metz', 'James Harrison', 'C. Daniel Freeman', 'Amil Merchant', 'Lucas Beyer', 'James Bradbury', 'Naman Agrawal', 'Ben Poole', 'Igor Mordatch', 'Adam Roberts', 'Jascha Sohl-Dickstein'] | ['cs.LG', 'math.OC', 'stat.ML'] | While deep learning models have replaced hand-designed features across many
domains, these models are still trained with hand-designed optimizers. In this
work, we leverage the same scaling approach behind the success of deep learning
to learn versatile optimizers. We train an optimizer for deep learning which is
itsel... | 2022-11-17T18:39:07Z | null | null | null | VeLO: Training Versatile Learned Optimizers by Scaling Up | ['Luke Metz', 'James Harrison', 'C. Freeman', 'Amil Merchant', 'Lucas Beyer', 'James Bradbury', 'Naman Agrawal', 'Ben Poole', 'Igor Mordatch', 'Adam Roberts', 'Jascha Narain Sohl-Dickstein'] | 2,022 | arXiv.org | 60 | 150 | ['Computer Science', 'Mathematics'] |
2,211.098 | InstructPix2Pix: Learning to Follow Image Editing Instructions | ['Tim Brooks', 'Aleksander Holynski', 'Alexei A. Efros'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.GR', 'cs.LG'] | We propose a method for editing images from human instructions: given an
input image and a written instruction that tells the model what to do, our
model follows these instructions to edit the image. To obtain training data for
this problem, we combine the knowledge of two large pretrained models -- a
language model (G... | 2022-11-17T18:58:43Z | Project page with code:
https://www.timothybrooks.com/instruct-pix2pix | null | null | null | null | null | null | null | null | null |
2,211.09807 | Towards All-in-one Pre-training via Maximizing Multi-modal Mutual
Information | ['Weijie Su', 'Xizhou Zhu', 'Chenxin Tao', 'Lewei Lu', 'Bin Li', 'Gao Huang', 'Yu Qiao', 'Xiaogang Wang', 'Jie Zhou', 'Jifeng Dai'] | ['cs.CV'] | To effectively exploit the potential of large-scale models, various
pre-training strategies supported by massive data from different sources are
proposed, including supervised pre-training, weakly-supervised pre-training,
and self-supervised pre-training. It has been proved that combining multiple
pre-training strategi... | 2022-11-17T18:59:49Z | null | null | null | null | null | null | null | null | null | null |
2,211.09808 | Uni-Perceiver v2: A Generalist Model for Large-Scale Vision and
Vision-Language Tasks | ['Hao Li', 'Jinguo Zhu', 'Xiaohu Jiang', 'Xizhou Zhu', 'Hongsheng Li', 'Chun Yuan', 'Xiaohua Wang', 'Yu Qiao', 'Xiaogang Wang', 'Wenhai Wang', 'Jifeng Dai'] | ['cs.CV'] | Despite the remarkable success of foundation models, their task-specific
fine-tuning paradigm makes them inconsistent with the goal of general
perception modeling. The key to eliminating this inconsistency is to use
generalist models for general task modeling. However, existing attempts at
generalist models are inadequ... | 2022-11-17T18:59:52Z | Code shall be released at
https://github.com/fundamentalvision/Uni-Perceiver | null | null | null | null | null | null | null | null | null |
2,211.10086 | Metadata Might Make Language Models Better | ['Kaspar Beelen', 'Daniel van Strien'] | ['cs.CL', 'cs.DL'] | This paper discusses the benefits of including metadata when training
language models on historical collections. Using 19th-century newspapers as a
case study, we extend the time-masking approach proposed by Rosin et al., 2022
and compare different strategies for inserting temporal, political and
geographical informati... | 2022-11-18T08:29:00Z | null | null | null | null | null | null | null | null | null | null |
2,211.1033 | GENIUS: Sketch-based Language Model Pre-training via Extreme and
Selective Masking for Text Generation and Augmentation | ['Biyang Guo', 'Yeyun Gong', 'Yelong Shen', 'Songqiao Han', 'Hailiang Huang', 'Nan Duan', 'Weizhu Chen'] | ['cs.CL'] | We introduce GENIUS: a conditional text generation model using sketches as
input, which can fill in the missing contexts for a given sketch (key
information consisting of textual spans, phrases, or words, concatenated by
mask tokens). GENIUS is pre-trained on a large-scale textual corpus with a
novel reconstruction fro... | 2022-11-18T16:39:45Z | 21 pages | null | null | null | null | null | null | null | null | null |
2,211.10438 | SmoothQuant: Accurate and Efficient Post-Training Quantization for Large
Language Models | ['Guangxuan Xiao', 'Ji Lin', 'Mickael Seznec', 'Hao Wu', 'Julien Demouth', 'Song Han'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Large language models (LLMs) show excellent performance but are compute- and
memory-intensive. Quantization can reduce memory and accelerate inference.
However, existing methods cannot maintain accuracy and hardware efficiency at
the same time. We propose SmoothQuant, a training-free, accuracy-preserving,
and general-p... | 2022-11-18T18:59:33Z | ICML 2023. First two authors contributed equally to this work | null | null | null | null | null | null | null | null | null |
2,211.10439 | BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View
Recognition via Perspective Supervision | ['Chenyu Yang', 'Yuntao Chen', 'Hao Tian', 'Chenxin Tao', 'Xizhou Zhu', 'Zhaoxiang Zhang', 'Gao Huang', 'Hongyang Li', 'Yu Qiao', 'Lewei Lu', 'Jie Zhou', 'Jifeng Dai'] | ['cs.CV'] | We present a novel bird's-eye-view (BEV) detector with perspective
supervision, which converges faster and better suits modern image backbones.
Existing state-of-the-art BEV detectors are often tied to certain depth
pre-trained backbones like VoVNet, hindering the synergy between booming image
backbones and BEV detecto... | 2022-11-18T18:59:48Z | null | null | null | BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervision | ['Chenyu Yang', 'Yuntao Chen', 'Haofei Tian', 'Chenxin Tao', 'Xizhou Zhu', 'Zhaoxiang Zhang', 'Gao Huang', 'Hongyang Li', 'Y. Qiao', 'Lewei Lu', 'Jie Zhou', 'Jifeng Dai'] | 2,022 | Computer Vision and Pattern Recognition | 279 | 46 | ['Computer Science'] |
2,211.11187 | L3Cube-MahaSBERT and HindSBERT: Sentence BERT Models and Benchmarking
BERT Sentence Representations for Hindi and Marathi | ['Ananya Joshi', 'Aditi Kajale', 'Janhavi Gadre', 'Samruddhi Deode', 'Raviraj Joshi'] | ['cs.CL', 'cs.LG'] | Sentence representation from vanilla BERT models does not work well on
sentence similarity tasks. Sentence-BERT models specifically trained on STS or
NLI datasets are shown to provide state-of-the-art performance. However,
building these models for low-resource languages is not straightforward due to
the lack of these ... | 2022-11-21T05:15:48Z | Accepted at Computing Conference 2023 | null | null | L3Cube-MahaSBERT and HindSBERT: Sentence BERT Models and Benchmarking BERT Sentence Representations for Hindi and Marathi | ['Ananya Joshi', 'Aditi Kajale', 'Janhavi Gadre', 'Samruddhi Deode', 'Raviraj Joshi'] | 2,022 | arXiv.org | 12 | 32 | ['Computer Science'] |
2,211.11216 | Exploring the Efficacy of Pre-trained Checkpoints in Text-to-Music
Generation Task | ['Shangda Wu', 'Maosong Sun'] | ['cs.SD', 'cs.CL', 'eess.AS'] | Benefiting from large-scale datasets and pre-trained models, the field of
generative models has recently gained significant momentum. However, most
datasets for symbolic music are very small, which potentially limits the
performance of data-driven multimodal models. An intuitive solution to this
problem is to leverage ... | 2022-11-21T07:19:17Z | Accepted by the Creative AI Across Modalities workshop at AAAI 2023 | null | null | Exploring the Efficacy of Pre-trained Checkpoints in Text-to-Music Generation Task | ['Shangda Wu', 'Maosong Sun'] | 2,022 | arXiv.org | 20 | 24 | ['Computer Science', 'Engineering'] |
2,211.11304 | TCBERT: A Technical Report for Chinese Topic Classification BERT | ['Ting Han', 'Kunhao Pan', 'Xinyu Chen', 'Dingjie Song', 'Yuchen Fan', 'Xinyu Gao', 'Ruyi Gan', 'Jiaxing Zhang'] | ['cs.CL'] | Bidirectional Encoder Representations from Transformers or
BERT~\cite{devlin-etal-2019-bert} has been one of the base models for various
NLP tasks due to its remarkable performance. Variants customized for different
languages and tasks are proposed to further improve the performance. In this
work, we investigate superv... | 2022-11-21T09:45:15Z | null | null | null | null | null | null | null | null | null | null |
2,211.11418 | L3Cube-HindBERT and DevBERT: Pre-Trained BERT Transformer models for
Devanagari based Hindi and Marathi Languages | ['Raviraj Joshi'] | ['cs.CL', 'cs.LG'] | The monolingual Hindi BERT models currently available on the model hub do not
perform better than the multi-lingual models on downstream tasks. We present
L3Cube-HindBERT, a Hindi BERT model pre-trained on Hindi monolingual corpus.
Further, since Indic languages, Hindi and Marathi share the Devanagari script,
we train ... | 2022-11-21T13:02:52Z | Accepted at ICICC 2023 | null | null | null | null | null | null | null | null | null |
2,211.12194 | SadTalker: Learning Realistic 3D Motion Coefficients for Stylized
Audio-Driven Single Image Talking Face Animation | ['Wenxuan Zhang', 'Xiaodong Cun', 'Xuan Wang', 'Yong Zhang', 'Xi Shen', 'Yu Guo', 'Ying Shan', 'Fei Wang'] | ['cs.CV'] | Generating talking head videos through a face image and a piece of speech
audio still contains many challenges. ie, unnatural head movement, distorted
expression, and identity modification. We argue that these issues are mainly
because of learning from the coupled 2D motion fields. On the other hand,
explicitly using 3... | 2022-11-22T11:35:07Z | Accepted by CVPR 2023, Project page: https://sadtalker.github.io,
Code: https://github.com/Winfredy/SadTalker | null | null | SadTalker: Learning Realistic 3D Motion Coefficients for Stylized Audio-Driven Single Image Talking Face Animation | ['Wenxuan Zhang', 'Xiaodong Cun', 'Xuan Wang', 'Yong Zhang', 'Xiaodong Shen', 'Yu Guo', 'Ying Shan', 'Fei Wang'] | 2,022 | Computer Vision and Pattern Recognition | 256 | 55 | ['Computer Science'] |
2,211.12509 | SimVPv2: Towards Simple yet Powerful Spatiotemporal Predictive Learning | ['Cheng Tan', 'Zhangyang Gao', 'Siyuan Li', 'Stan Z. Li'] | ['cs.LG'] | Recent years have witnessed remarkable advances in spatiotemporal predictive
learning, with methods incorporating auxiliary inputs, complex neural
architectures, and sophisticated training strategies. While SimVP has
introduced a simpler, CNN-based baseline for this task, it still relies on
heavy Unet-like architecture... | 2022-11-22T08:01:33Z | Accepted by TMM | null | null | SimVPv2: Towards Simple yet Powerful Spatiotemporal Predictive Learning | ['Cheng Tan', 'Zhangyang Gao', 'Siyuan Li', 'Stan Z. Li'] | 2,022 | IEEE transactions on multimedia | 3 | 107 | ['Computer Science'] |
2,211.12588 | Program of Thoughts Prompting: Disentangling Computation from Reasoning
for Numerical Reasoning Tasks | ['Wenhu Chen', 'Xueguang Ma', 'Xinyi Wang', 'William W. Cohen'] | ['cs.CL', 'cs.AI'] | Recently, there has been significant progress in teaching language models to
perform step-by-step reasoning to solve complex numerical reasoning tasks.
Chain-of-thoughts prompting (CoT) is by far the state-of-art method for these
tasks. CoT uses language models to perform both reasoning and computation in
the multi-ste... | 2022-11-22T21:06:00Z | Published at TMLR 2023 | null | null | Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks | ['Wenhu Chen', 'Xueguang Ma', 'Xinyi Wang', 'William W. Cohen'] | 2,022 | Trans. Mach. Learn. Res. | 829 | 49 | ['Computer Science'] |
2,211.12905 | GhostNetV2: Enhance Cheap Operation with Long-Range Attention | ['Yehui Tang', 'Kai Han', 'Jianyuan Guo', 'Chang Xu', 'Chao Xu', 'Yunhe Wang'] | ['cs.CV'] | Light-weight convolutional neural networks (CNNs) are specially designed for
applications on mobile devices with faster inference speed. The convolutional
operation can only capture local information in a window region, which prevents
performance from being further improved. Introducing self-attention into
convolution ... | 2022-11-23T12:16:59Z | This paper is accepted by NeurIPS 2022 (Spotlight) | null | null | null | null | null | null | null | null | null |
2,211.12979 | FLAIR #1: semantic segmentation and domain adaptation dataset | ['Anatol Garioud', 'Stéphane Peillet', 'Eva Bookjans', 'Sébastien Giordano', 'Boris Wattrelos'] | ['cs.CV', 'eess.IV'] | The French National Institute of Geographical and Forest Information (IGN)
has the mission to document and measure land-cover on French territory and
provides referential geographical datasets, including high-resolution aerial
images and topographic maps. The monitoring of land-cover plays a crucial role
in land manage... | 2022-11-23T14:38:59Z | Data access update | null | 10.13140/RG.2.2.30183.73128/1 | null | null | null | null | null | null | null |
2,211.13221 | Latent Video Diffusion Models for High-Fidelity Long Video Generation | ['Yingqing He', 'Tianyu Yang', 'Yong Zhang', 'Ying Shan', 'Qifeng Chen'] | ['cs.CV', 'cs.AI'] | AI-generated content has attracted lots of attention recently, but
photo-realistic video synthesis is still challenging. Although many attempts
using GANs and autoregressive models have been made in this area, the visual
quality and length of generated videos are far from satisfactory. Diffusion
models have shown remar... | 2022-11-23T18:58:39Z | Project Page: https://yingqinghe.github.io/LVDM/ Github:
https://github.com/YingqingHe/LVDM | null | null | Latent Video Diffusion Models for High-Fidelity Long Video Generation | ['Yin-Yin He', 'Tianyu Yang', 'Yong Zhang', 'Ying Shan', 'Qifeng Chen'] | 2,022 | null | 243 | 47 | ['Computer Science'] |
2,211.13227 | Paint by Example: Exemplar-based Image Editing with Diffusion Models | ['Binxin Yang', 'Shuyang Gu', 'Bo Zhang', 'Ting Zhang', 'Xuejin Chen', 'Xiaoyan Sun', 'Dong Chen', 'Fang Wen'] | ['cs.CV'] | Language-guided image editing has achieved great success recently. In this
paper, for the first time, we investigate exemplar-guided image editing for
more precise control. We achieve this goal by leveraging self-supervised
training to disentangle and re-organize the source image and the exemplar.
However, the naive ap... | 2022-11-23T18:59:52Z | Code: https://github.com/Fantasy-Studio/Paint-by-Example | null | null | null | null | null | null | null | null | null |
2,211.14275 | Solving math word problems with process- and outcome-based feedback | ['Jonathan Uesato', 'Nate Kushman', 'Ramana Kumar', 'Francis Song', 'Noah Siegel', 'Lisa Wang', 'Antonia Creswell', 'Geoffrey Irving', 'Irina Higgins'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Recent work has shown that asking language models to generate reasoning steps
improves performance on many reasoning tasks. When moving beyond prompting,
this raises the question of how we should supervise such models: outcome-based
approaches which supervise the final result, or process-based approaches which
supervis... | 2022-11-25T18:19:44Z | null | null | null | null | null | null | null | null | null | null |
2,211.14304 | BeLFusion: Latent Diffusion for Behavior-Driven Human Motion Prediction | ['German Barquero', 'Sergio Escalera', 'Cristina Palmero'] | ['cs.CV'] | Stochastic human motion prediction (HMP) has generally been tackled with
generative adversarial networks and variational autoencoders. Most prior works
aim at predicting highly diverse movements in terms of the skeleton joints'
dispersion. This has led to methods predicting fast and motion-divergent
movements, which ar... | 2022-11-25T18:59:03Z | ICCV 2023 Camera-ready version. Project page:
https://barquerogerman.github.io/BeLFusion/ | Proceedings of the IEEE/CVF International Conference on Computer
Vision. 2023 | null | null | null | null | null | null | null | null |
2,211.1473 | A Time Series is Worth 64 Words: Long-term Forecasting with Transformers | ['Yuqi Nie', 'Nam H. Nguyen', 'Phanwadee Sinthong', 'Jayant Kalagnanam'] | ['cs.LG', 'cs.AI'] | We propose an efficient design of Transformer-based models for multivariate
time series forecasting and self-supervised representation learning. It is
based on two key components: (i) segmentation of time series into
subseries-level patches which are served as input tokens to Transformer; (ii)
channel-independence wher... | 2022-11-27T05:15:42Z | Accepted by ICLR 2023 | null | null | A Time Series is Worth 64 Words: Long-term Forecasting with Transformers | ['Yuqi Nie', 'Nam H. Nguyen', 'Phanwadee Sinthong', 'J. Kalagnanam'] | 2,022 | International Conference on Learning Representations | 1,449 | 45 | ['Computer Science'] |
2,211.14758 | VideoReTalking: Audio-based Lip Synchronization for Talking Head Video
Editing In the Wild | ['Kun Cheng', 'Xiaodong Cun', 'Yong Zhang', 'Menghan Xia', 'Fei Yin', 'Mingrui Zhu', 'Xuan Wang', 'Jue Wang', 'Nannan Wang'] | ['cs.CV'] | We present VideoReTalking, a new system to edit the faces of a real-world
talking head video according to input audio, producing a high-quality and
lip-syncing output video even with a different emotion. Our system disentangles
this objective into three sequential tasks: (1) face video generation with a
canonical expre... | 2022-11-27T08:14:23Z | Accepted by SIGGRAPH Asia 2022 Conference Proceedings. Project page:
https://vinthony.github.io/video-retalking/ | null | null | VideoReTalking: Audio-based Lip Synchronization for Talking Head Video Editing In the Wild | ['K. Cheng', 'Xiaodong Cun', 'Yong Zhang', 'Menghan Xia', 'Fei Yin', 'Mingrui Zhu', 'Xuanxia Wang', 'Jue Wang', 'Nan Wang'] | 2,022 | ACM SIGGRAPH Conference and Exhibition on Computer Graphics and Interactive Techniques in Asia | 106 | 62 | ['Computer Science'] |
2,211.15199 | Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive
Analysis of Hebrew BERT Models and a New One to Outperform Them All | ['Eylon Gueta', 'Avi Shmidman', 'Shaltiel Shmidman', 'Cheyn Shmuel Shmidman', 'Joshua Guedalia', 'Moshe Koppel', 'Dan Bareket', 'Amit Seker', 'Reut Tsarfaty'] | ['cs.CL'] | We present a new pre-trained language model (PLM) for modern Hebrew, termed
AlephBERTGimmel, which employs a much larger vocabulary (128K items) than
standard Hebrew PLMs before. We perform a contrastive analysis of this model
against all previous Hebrew PLMs (mBERT, heBERT, AlephBERT) and assess the
effects of larger ... | 2022-11-28T10:17:35Z | null | null | null | Large Pre-Trained Models with Extra-Large Vocabularies: A Contrastive Analysis of Hebrew BERT Models and a New One to Outperform Them All | ['Eylon Guetta', 'Avi Shmidman', 'Shaltiel Shmidman', 'C. Shmidman', 'Joshua Guedalia', 'Moshe Koppel', 'Dan Bareket', 'Amit Seker', 'Reut Tsarfaty'] | 2,022 | arXiv.org | 15 | 14 | ['Computer Science'] |
2,211.15444 | DAMO-YOLO : A Report on Real-Time Object Detection Design | ['Xianzhe Xu', 'Yiqi Jiang', 'Weihua Chen', 'Yilun Huang', 'Yuan Zhang', 'Xiuyu Sun'] | ['cs.CV'] | In this report, we present a fast and accurate object detection method dubbed
DAMO-YOLO, which achieves higher performance than the state-of-the-art YOLO
series. DAMO-YOLO is extended from YOLO with some new technologies, including
Neural Architecture Search (NAS), efficient Reparameterized Generalized-FPN
(RepGFPN), a... | 2022-11-23T17:59:12Z | Project Website: https://github.com/tinyvision/damo-yolo | null | null | null | null | null | null | null | null | null |
2,211.15518 | ReCo: Region-Controlled Text-to-Image Generation | ['Zhengyuan Yang', 'Jianfeng Wang', 'Zhe Gan', 'Linjie Li', 'Kevin Lin', 'Chenfei Wu', 'Nan Duan', 'Zicheng Liu', 'Ce Liu', 'Michael Zeng', 'Lijuan Wang'] | ['cs.CV'] | Recently, large-scale text-to-image (T2I) models have shown impressive
performance in generating high-fidelity images, but with limited
controllability, e.g., precisely specifying the content in a specific region
with a free-form text description. In this paper, we propose an effective
technique for such regional contr... | 2022-11-23T18:56:31Z | null | null | null | ReCo: Region-Controlled Text-to-Image Generation | ['Zhengyuan Yang', 'Jianfeng Wang', 'Zhe Gan', 'Linjie Li', 'Kevin Lin', 'Chenfei Wu', 'Nan Duan', 'Zicheng Liu', 'Ce Liu', 'Michael Zeng', 'Lijuan Wang'] | 2,022 | Computer Vision and Pattern Recognition | 150 | 53 | ['Computer Science'] |
2,211.15533 | The Stack: 3 TB of permissively licensed source code | ['Denis Kocetkov', 'Raymond Li', 'Loubna Ben Allal', 'Jia Li', 'Chenghao Mou', 'Carlos Muñoz Ferrandis', 'Yacine Jernite', 'Margaret Mitchell', 'Sean Hughes', 'Thomas Wolf', 'Dzmitry Bahdanau', 'Leandro von Werra', 'Harm de Vries'] | ['cs.CL', 'cs.AI'] | Large Language Models (LLMs) play an ever-increasing role in the field of
Artificial Intelligence (AI)--not only for natural language processing but also
for code understanding and generation. To stimulate open and responsible
research on LLMs for code, we introduce The Stack, a 3.1 TB dataset consisting
of permissivel... | 2022-11-20T18:15:30Z | null | null | null | The Stack: 3 TB of permissively licensed source code | ['Denis Kocetkov', 'Raymond Li', 'Loubna Ben Allal', 'Jia Li', 'Chenghao Mou', 'Carlos Muñoz Ferrandis', 'Yacine Jernite', 'Margaret Mitchell', 'Sean Hughes', 'Thomas Wolf', 'Dzmitry Bahdanau', 'L. V. Werra', 'H. D. Vries'] | 2,022 | Trans. Mach. Learn. Res. | 339 | 50 | ['Computer Science'] |
2,211.15613 | Frustratingly Easy Label Projection for Cross-lingual Transfer | ['Yang Chen', 'Chao Jiang', 'Alan Ritter', 'Wei Xu'] | ['cs.CL', 'cs.AI'] | Translating training data into many languages has emerged as a practical
solution for improving cross-lingual transfer. For tasks that involve
span-level annotations, such as information extraction or question answering,
an additional label projection step is required to map annotated spans onto the
translated texts. R... | 2022-11-28T18:11:48Z | This paper has been accepted at Findings of ACL 2023 | null | null | null | null | null | null | null | null | null |
2,211.1566 | SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image
Understanding | ['Favyen Bastani', 'Piper Wolters', 'Ritwik Gupta', 'Joe Ferdinando', 'Aniruddha Kembhavi'] | ['cs.CV'] | Remote sensing images are useful for a wide variety of planet monitoring
applications, from tracking deforestation to tackling illegal fishing. The
Earth is extremely diverse -- the amount of potential tasks in remote sensing
images is massive, and the sizes of features range from several kilometers to
just tens of cen... | 2022-11-28T18:59:26Z | ICCV 2023 | null | null | null | null | null | null | null | null | null |
2,211.15841 | MegaBlocks: Efficient Sparse Training with Mixture-of-Experts | ['Trevor Gale', 'Deepak Narayanan', 'Cliff Young', 'Matei Zaharia'] | ['cs.LG', 'cs.AI', 'cs.DC'] | We present MegaBlocks, a system for efficient Mixture-of-Experts (MoE)
training on GPUs. Our system is motivated by the limitations of current
frameworks, which restrict the dynamic routing in MoE layers to satisfy the
constraints of existing software and hardware. These formulations force a
tradeoff between model qual... | 2022-11-29T00:27:08Z | null | null | null | MegaBlocks: Efficient Sparse Training with Mixture-of-Experts | ['Trevor Gale', 'D. Narayanan', 'C. Young', 'M. Zaharia'] | 2,022 | Conference on Machine Learning and Systems | 109 | 51 | ['Computer Science'] |
2,211.16028 | JaCappella Corpus: A Japanese a Cappella Vocal Ensemble Corpus | ['Tomohiko Nakamura', 'Shinnosuke Takamichi', 'Naoko Tanji', 'Satoru Fukayama', 'Hiroshi Saruwatari'] | ['eess.AS', 'cs.LG', 'cs.SD'] | We construct a corpus of Japanese a cappella vocal ensembles (jaCappella
corpus) for vocal ensemble separation and synthesis. It consists of 35
copyright-cleared vocal ensemble songs and their audio recordings of individual
voice parts. These songs were arranged from out-of-copyright Japanese
children's songs and have ... | 2022-11-29T08:52:29Z | Accepted for ICASSP2023 | IEEE International Conference on Acoustics, Speech, and Signal
Processing (ICASSP), Jun. 2023, 5 pages | 10.1109/ICASSP49357.2023.10095569 | null | null | null | null | null | null | null |
2,211.16349 | BARTSmiles: Generative Masked Language Models for Molecular
Representations | ['Gayane Chilingaryan', 'Hovhannes Tamoyan', 'Ani Tevosyan', 'Nelly Babayan', 'Lusine Khondkaryan', 'Karen Hambardzumyan', 'Zaven Navoyan', 'Hrant Khachatrian', 'Armen Aghajanyan'] | ['cs.LG', 'q-bio.BM'] | We discover a robust self-supervised strategy tailored towards molecular
representations for generative masked language models through a series of
tailored, in-depth ablations. Using this pre-training strategy, we train
BARTSmiles, a BART-like model with an order of magnitude more compute than
previous self-supervised ... | 2022-11-29T16:30:53Z | 27 pages (including appendix) | null | null | BARTSmiles: Generative Masked Language Models for Molecular Representations | ['Gayane Chilingaryan', 'Hovhannes Tamoyan', 'A. Tevosyan', 'N. Babayan', 'Lusine Khondkaryan', 'Karen Hambardzumyan', 'Z. Navoyan', 'Hrant Khachatrian', 'Armen Aghajanyan'] | 2,022 | Journal of Chemical Information and Modeling | 28 | 74 | ['Medicine', 'Computer Science', 'Biology'] |
2,211.16492 | Abstract Visual Reasoning with Tangram Shapes | ['Anya Ji', 'Noriyuki Kojima', 'Noah Rush', 'Alane Suhr', 'Wai Keen Vong', 'Robert D. Hawkins', 'Yoav Artzi'] | ['cs.CL', 'cs.AI', 'cs.CV', 'cs.LG'] | We introduce KiloGram, a resource for studying abstract visual reasoning in
humans and machines. Drawing on the history of tangram puzzles as stimuli in
cognitive science, we build a richly annotated dataset that, with >1k distinct
stimuli, is orders of magnitude larger and more diverse than prior resources.
It is both... | 2022-11-29T18:57:06Z | EMNLP 2022 long paper | null | null | null | null | null | null | null | null | null |
2,211.17046 | Rationale-Guided Few-Shot Classification to Detect Abusive Language | ['Punyajoy Saha', 'Divyanshu Sheth', 'Kushal Kedia', 'Binny Mathew', 'Animesh Mukherjee'] | ['cs.CL', 'cs.CY'] | Abusive language is a concerning problem in online social media. Past
research on detecting abusive language covers different platforms, languages,
demographies, etc. However, models trained using these datasets do not perform
well in cross-domain evaluation settings. To overcome this, a common strategy
is to use a few... | 2022-11-30T14:47:14Z | 11 pages, 14 tables, 3 figures, The code repository is
https://github.com/punyajoy/RGFS_ECAI | null | null | Rationale-Guided Few-Shot Classification to Detect Abusive Language | ['Punyajoy Saha', 'Divyanshu Sheth', 'K. Kedia', 'Binny Mathew', 'Animesh Mukherjee'] | 2,022 | European Conference on Artificial Intelligence | 3 | 49 | ['Computer Science'] |
2,211.17135 | BudgetLongformer: Can we Cheaply Pretrain a SotA Legal Language Model
From Scratch? | ['Joel Niklaus', 'Daniele Giofré'] | ['cs.CL', 'cs.AI', 'cs.LG', '68T50', 'I.2; I.7'] | Pretrained transformer models have achieved state-of-the-art results in many
tasks and benchmarks recently. Many state-of-the-art Language Models (LMs),
however, do not scale well above the threshold of 512 input tokens. In
specialized domains though (such as legal, scientific or biomedical), models
often need to proce... | 2022-11-30T16:09:20Z | Accepted at ENLSP @ NeurIPS 2022 | null | null | null | null | null | null | null | null | null |
2,211.17192 | Fast Inference from Transformers via Speculative Decoding | ['Yaniv Leviathan', 'Matan Kalman', 'Yossi Matias'] | ['cs.LG', 'cs.CL'] | Inference from large autoregressive models like Transformers is slow -
decoding K tokens takes K serial runs of the model. In this work we introduce
speculative decoding - an algorithm to sample from autoregressive models faster
without any changes to the outputs, by computing several tokens in parallel. At
the heart o... | 2022-11-30T17:33:28Z | ICML 2023 Oral | null | null | Fast Inference from Transformers via Speculative Decoding | ['Yaniv Leviathan', 'Matan Kalman', 'Yossi Matias'] | 2,022 | International Conference on Machine Learning | 738 | 31 | ['Computer Science'] |
2,212.00794 | Scaling Language-Image Pre-training via Masking | ['Yanghao Li', 'Haoqi Fan', 'Ronghang Hu', 'Christoph Feichtenhofer', 'Kaiming He'] | ['cs.CV'] | We present Fast Language-Image Pre-training (FLIP), a simple and more
efficient method for training CLIP. Our method randomly masks out and removes a
large portion of image patches during training. Masking allows us to learn from
more image-text pairs given the same wall-clock time and contrast more samples
per iterati... | 2022-12-01T18:59:57Z | Tech report; arXiv v2: update scaling results and add code repo | null | null | Scaling Language-Image Pre-Training via Masking | ['Yanghao Li', 'Haoqi Fan', 'Ronghang Hu', 'Christoph Feichtenhofer', 'Kaiming He'] | 2,022 | Computer Vision and Pattern Recognition | 330 | 75 | ['Computer Science'] |
2,212.01349 | Nonparametric Masked Language Modeling | ['Sewon Min', 'Weijia Shi', 'Mike Lewis', 'Xilun Chen', 'Wen-tau Yih', 'Hannaneh Hajishirzi', 'Luke Zettlemoyer'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Existing language models (LMs) predict tokens with a softmax over a finite
vocabulary, which can make it difficult to predict rare tokens or phrases. We
introduce NPM, the first nonparametric masked language model that replaces this
softmax with a nonparametric distribution over every phrase in a reference
corpus. NPM ... | 2022-12-02T18:10:42Z | 20 pages; 9 figures. Published at ACL 2023 Findings. Code available
at https://github.com/facebookresearch/NPM | null | null | Nonparametric Masked Language Modeling | ['Sewon Min', 'Weijia Shi', 'M. Lewis', 'Xilun Chen', 'Wen-tau Yih', 'Hannaneh Hajishirzi', 'Luke Zettlemoyer'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 51 | 95 | ['Computer Science'] |
2,212.01378 | ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning | ['Shachar Don-Yehiya', 'Elad Venezian', 'Colin Raffel', 'Noam Slonim', 'Yoav Katz', 'Leshem Choshen'] | ['cs.LG', 'cs.CL', 'cs.DC'] | We propose a new paradigm to continually evolve pretrained models, denoted
ColD Fusion. It provides the benefits of multitask learning but leverages
distributed computation with limited communication and eliminates the need for
shared data. Consequentially, ColD Fusion can give rise to a synergistic loop,
where finetun... | 2022-12-02T18:59:04Z | ACL 23 | null | null | ColD Fusion: Collaborative Descent for Distributed Multitask Finetuning | ['Shachar Don-Yehiya', 'Elad Venezian', 'Colin Raffel', 'N. Slonim', 'Yoav Katz', 'Leshem Choshen'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 55 | 91 | ['Computer Science'] |
2,212.02027 | Retrieval as Attention: End-to-end Learning of Retrieval and Reading
within a Single Transformer | ['Zhengbao Jiang', 'Luyu Gao', 'Jun Araki', 'Haibo Ding', 'Zhiruo Wang', 'Jamie Callan', 'Graham Neubig'] | ['cs.CL', 'cs.LG'] | Systems for knowledge-intensive tasks such as open-domain question answering
(QA) usually consist of two stages: efficient retrieval of relevant documents
from a large corpus and detailed reading of the selected documents to generate
answers. Retrievers and readers are usually modeled separately, which
necessitates a c... | 2022-12-05T04:51:21Z | EMNLP 2022 | null | null | Retrieval as Attention: End-to-end Learning of Retrieval and Reading within a Single Transformer | ['Zhengbao Jiang', 'Luyu Gao', 'J. Araki', 'Haibo Ding', 'Zhiruo Wang', 'Jamie Callan', 'Graham Neubig'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 43 | 52 | ['Computer Science'] |
2,212.02499 | Images Speak in Images: A Generalist Painter for In-Context Visual
Learning | ['Xinlong Wang', 'Wen Wang', 'Yue Cao', 'Chunhua Shen', 'Tiejun Huang'] | ['cs.CV'] | In-context learning, as a new paradigm in NLP, allows the model to rapidly
adapt to various tasks with only a handful of prompts and examples. But in
computer vision, the difficulties for in-context learning lie in that tasks
vary significantly in the output representations, thus it is unclear how to
define the general... | 2022-12-05T18:59:50Z | Accepted to CVPR 2023. Code and model is available at:
https://github.com/baaivision/Painter | null | null | Images Speak in Images: A Generalist Painter for In-Context Visual Learning | ['Xinlong Wang', 'Wen Wang', 'Yue Cao', 'Chunhua Shen', 'Tiejun Huang'] | 2,022 | Computer Vision and Pattern Recognition | 262 | 58 | ['Computer Science'] |
2,212.02508 | MAP-Music2Vec: A Simple and Effective Baseline for Self-Supervised Music
Audio Representation Learning | ['Yizhi Li', 'Ruibin Yuan', 'Ge Zhang', 'Yinghao Ma', 'Chenghua Lin', 'Xingran Chen', 'Anton Ragni', 'Hanzhi Yin', 'Zhijie Hu', 'Haoyu He', 'Emmanouil Benetos', 'Norbert Gyenge', 'Ruibo Liu', 'Jie Fu'] | ['cs.SD', 'cs.AI', 'cs.LG', 'cs.MM', 'eess.AS'] | The deep learning community has witnessed an exponentially growing interest
in self-supervised learning (SSL). However, it still remains unexplored how to
build a framework for learning useful representations of raw music waveforms in
a self-supervised manner. In this work, we design Music2Vec, a framework
exploring di... | 2022-12-05T16:04:26Z | null | null | null | null | null | null | null | null | null | null |
2,212.02623 | Unifying Vision, Text, and Layout for Universal Document Processing | ['Zineng Tang', 'Ziyi Yang', 'Guoxin Wang', 'Yuwei Fang', 'Yang Liu', 'Chenguang Zhu', 'Michael Zeng', 'Cha Zhang', 'Mohit Bansal'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG'] | We propose Universal Document Processing (UDOP), a foundation Document AI
model which unifies text, image, and layout modalities together with varied
task formats, including document understanding and generation. UDOP leverages
the spatial correlation between textual content and document image to model
image, text, and... | 2022-12-05T22:14:49Z | CVPR 2023 | null | null | null | null | null | null | null | null | null |
2,212.02974 | CySecBERT: A Domain-Adapted Language Model for the Cybersecurity Domain | ['Markus Bayer', 'Philipp Kuehn', 'Ramin Shanehsaz', 'Christian Reuter'] | ['cs.CR', 'cs.CL'] | The field of cybersecurity is evolving fast. Experts need to be informed
about past, current and - in the best case - upcoming threats, because attacks
are becoming more advanced, targets bigger and systems more complex. As this
cannot be addressed manually, cybersecurity experts need to rely on machine
learning techni... | 2022-12-06T13:49:12Z | 13 Pages, 7 tables, 1 figure | null | null | CySecBERT: A Domain-Adapted Language Model for the Cybersecurity Domain | ['Markus Bayer', 'Philip D. . Kuehn', 'Ramin Shanehsaz', 'Christian A. Reuter'] | 2,022 | ACM Transactions on Privacy and Security | 50 | 56 | ['Computer Science'] |
2,212.03191 | InternVideo: General Video Foundation Models via Generative and
Discriminative Learning | ['Yi Wang', 'Kunchang Li', 'Yizhuo Li', 'Yinan He', 'Bingkun Huang', 'Zhiyu Zhao', 'Hongjie Zhang', 'Jilan Xu', 'Yi Liu', 'Zun Wang', 'Sen Xing', 'Guo Chen', 'Junting Pan', 'Jiashuo Yu', 'Yali Wang', 'Limin Wang', 'Yu Qiao'] | ['cs.CV'] | The foundation models have recently shown excellent performance on a variety
of downstream tasks in computer vision. However, most existing vision
foundation models simply focus on image-level pretraining and adpation, which
are limited for dynamic and complex video-level understanding tasks. To fill
the gap, we presen... | 2022-12-06T18:09:49Z | technical report | null | null | null | null | null | null | null | null | null |
2,212.03533 | Text Embeddings by Weakly-Supervised Contrastive Pre-training | ['Liang Wang', 'Nan Yang', 'Xiaolong Huang', 'Binxing Jiao', 'Linjun Yang', 'Daxin Jiang', 'Rangan Majumder', 'Furu Wei'] | ['cs.CL', 'cs.IR'] | This paper presents E5, a family of state-of-the-art text embeddings that
transfer well to a wide range of tasks. The model is trained in a contrastive
manner with weak supervision signals from our curated large-scale text pair
dataset (called CCPairs). E5 can be readily used as a general-purpose embedding
model for an... | 2022-12-07T09:25:54Z | 17 pages, v2 fixes the SummEval numbers | null | null | Text Embeddings by Weakly-Supervised Contrastive Pre-training | ['Liang Wang', 'Nan Yang', 'Xiaolong Huang', 'Binxing Jiao', 'Linjun Yang', 'Daxin Jiang', 'Rangan Majumder', 'Furu Wei'] | 2,022 | arXiv.org | 625 | 66 | ['Computer Science'] |
2,212.0386 | Diffusion Art or Digital Forgery? Investigating Data Replication in
Diffusion Models | ['Gowthami Somepalli', 'Vasu Singla', 'Micah Goldblum', 'Jonas Geiping', 'Tom Goldstein'] | ['cs.LG', 'cs.CV', 'cs.CY'] | Cutting-edge diffusion models produce images with high quality and
customizability, enabling them to be used for commercial art and graphic design
purposes. But do diffusion models create unique works of art, or are they
replicating content directly from their training sets? In this work, we study
image retrieval frame... | 2022-12-07T18:58:02Z | Updated draft with the following changes (1) Clarified the LAION
Aesthetics versions everywhere (2) Correction on which LAION Aesthetics
version SD - 1.4 is finetuned on and updated figure 12 based on this (3) A
section on possible causes of replication | null | null | null | null | null | null | null | null | null |
2,212.03984 | Elucidation of Relaxation Dynamics Beyond Equilibrium Through
AI-informed X-ray Photon Correlation Spectroscopy | ['James P. Horwath', 'Xiao-Min Lin', 'Hongrui He', 'Qingteng Zhang', 'Eric M. Dufresne', 'Miaoqi Chu', 'Subramanian K. R. S. Sankaranarayanan', 'Wei Chen', 'Suresh Narayanan', 'Mathew J. Cherukara'] | ['cond-mat.mtrl-sci', 'cond-mat.mes-hall'] | Understanding and interpreting dynamics of functional materials \textit{in
situ} is a grand challenge in physics and materials science due to the
difficulty of experimentally probing materials at varied length and time
scales. X-ray photon correlation spectroscopy (XPCS) is uniquely well-suited
for characterizing mater... | 2022-12-07T22:36:53Z | null | null | null | null | null | null | null | null | null | null |
2,212.04068 | Investigating Glyph Phonetic Information for Chinese Spell Checking:
What Works and What's Next | ['Xiaotian Zhang', 'Yanjun Zheng', 'Hang Yan', 'Xipeng Qiu'] | ['cs.CL', 'cs.AI'] | While pre-trained Chinese language models have demonstrated impressive
performance on a wide range of NLP tasks, the Chinese Spell Checking (CSC) task
remains a challenge. Previous research has explored using information such as
glyphs and phonetics to improve the ability to distinguish misspelled
characters, with good... | 2022-12-08T04:37:29Z | null | null | null | Investigating Glyph Phonetic Information for Chinese Spell Checking: What Works and What's Next | ['Xiaotian Zhang', 'Yanjun Zheng', 'Hang Yan', 'Xipeng Qiu'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 5 | 44 | ['Computer Science'] |
2,212.04089 | Editing Models with Task Arithmetic | ['Gabriel Ilharco', 'Marco Tulio Ribeiro', 'Mitchell Wortsman', 'Suchin Gururangan', 'Ludwig Schmidt', 'Hannaneh Hajishirzi', 'Ali Farhadi'] | ['cs.LG', 'cs.CL', 'cs.CV'] | Changing how pre-trained models behave -- e.g., improving their performance
on a downstream task or mitigating biases learned during pre-training -- is a
common practice when developing machine learning systems. In this work, we
propose a new paradigm for steering the behavior of neural networks, centered
around \texti... | 2022-12-08T05:50:53Z | In Proceedings of the 11th International Conference on Learning
Representations (ICLR 2023) | null | null | Editing Models with Task Arithmetic | ['Gabriel Ilharco', 'Marco Tulio Ribeiro', 'Mitchell Wortsman', 'Suchin Gururangan', 'Ludwig Schmidt', 'Hannaneh Hajishirzi', 'Ali Farhadi'] | 2,022 | International Conference on Learning Representations | 523 | 111 | ['Computer Science'] |
2,212.04129 | Deep Incubation: Training Large Models by Divide-and-Conquering | ['Zanlin Ni', 'Yulin Wang', 'Jiangwei Yu', 'Haojun Jiang', 'Yue Cao', 'Gao Huang'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Recent years have witnessed a remarkable success of large deep learning
models. However, training these models is challenging due to high computational
costs, painfully slow convergence, and overfitting issues. In this paper, we
present Deep Incubation, a novel approach that enables the efficient and
effective training... | 2022-12-08T08:04:06Z | null | null | null | null | null | null | null | null | null | null |
2,212.04246 | ViTPose++: Vision Transformer for Generic Body Pose Estimation | ['Yufei Xu', 'Jing Zhang', 'Qiming Zhang', 'Dacheng Tao'] | ['cs.CV'] | In this paper, we show the surprisingly good properties of plain vision
transformers for body pose estimation from various aspects, namely simplicity
in model structure, scalability in model size, flexibility in training
paradigm, and transferability of knowledge between models, through a simple
baseline model dubbed V... | 2022-12-07T12:33:28Z | Extension of ViTPose paper, accepted by TPAMI | null | null | null | null | null | null | null | null | null |
2,212.04356 | Robust Speech Recognition via Large-Scale Weak Supervision | ['Alec Radford', 'Jong Wook Kim', 'Tao Xu', 'Greg Brockman', 'Christine McLeavey', 'Ilya Sutskever'] | ['eess.AS', 'cs.CL', 'cs.LG', 'cs.SD'] | We study the capabilities of speech processing systems trained simply to
predict large amounts of transcripts of audio on the internet. When scaled to
680,000 hours of multilingual and multitask supervision, the resulting models
generalize well to standard benchmarks and are often competitive with prior
fully supervise... | 2022-12-06T18:46:04Z | null | null | null | Robust Speech Recognition via Large-Scale Weak Supervision | ['Alec Radford', 'Jong Wook Kim', 'Tao Xu', 'Greg Brockman', 'Christine McLeavey', 'I. Sutskever'] | 2,022 | International Conference on Machine Learning | 3,780 | 100 | ['Engineering', 'Computer Science'] |
2,212.04582 | Towards Holistic Surgical Scene Understanding | ['Natalia Valderrama', 'Paola Ruiz Puentes', 'Isabela Hernández', 'Nicolás Ayobi', 'Mathilde Verlyk', 'Jessica Santander', 'Juan Caicedo', 'Nicolás Fernández', 'Pablo Arbeláez'] | ['cs.CV', 'cs.AI'] | Most benchmarks for studying surgical interventions focus on a specific
challenge instead of leveraging the intrinsic complementarity among different
tasks. In this work, we present a new experimental framework towards holistic
surgical scene understanding. First, we introduce the Phase, Step, Instrument,
and Atomic Vi... | 2022-12-08T22:15:27Z | MICCAI 2022 Oral. Official extension published at arXiv:2401.11174 .
Data and codes available at https://github.com/BCV-Uniandes/TAPIR | Medical Image Computing and Computer Assisted Intervention 2022, | 10.1007/978-3-031-16449-1_42 | Towards Holistic Surgical Scene Understanding | ['Natalia Valderrama', 'Paola Ruiz Puentes', 'Isabela Hernández', 'Nicolás Ayobi', 'Mathilde Verlyck', 'J. Santander', 'J. Caicedo', 'N. Fernández', 'P. Arbeláez'] | 2,022 | International Conference on Medical Image Computing and Computer-Assisted Intervention | 36 | 34 | ['Computer Science'] |
2,212.0469 | Benchmarking Self-Supervised Learning on Diverse Pathology Datasets | ['Mingu Kang', 'Heon Song', 'Seonwook Park', 'Donggeun Yoo', 'Sérgio Pereira'] | ['cs.CV', 'cs.LG'] | Computational pathology can lead to saving human lives, but models are
annotation hungry and pathology images are notoriously expensive to annotate.
Self-supervised learning has shown to be an effective method for utilizing
unlabeled data, and its application to pathology could greatly benefit its
downstream tasks. Yet... | 2022-12-09T06:38:34Z | Accepted to CVPR 2023 | null | null | null | null | null | null | null | null | null |
2,212.04755 | From Cloze to Comprehension: Retrofitting Pre-trained Masked Language
Model to Pre-trained Machine Reader | ['Weiwen Xu', 'Xin Li', 'Wenxuan Zhang', 'Meng Zhou', 'Wai Lam', 'Luo Si', 'Lidong Bing'] | ['cs.CL'] | We present Pre-trained Machine Reader (PMR), a novel method for retrofitting
pre-trained masked language models (MLMs) to pre-trained machine reading
comprehension (MRC) models without acquiring labeled data. PMR can resolve the
discrepancy between model pre-training and downstream fine-tuning of existing
MLMs. To buil... | 2022-12-09T10:21:56Z | Accepted to NeurIPS 2023 | null | null | null | null | null | null | null | null | null |
2,212.04917 | TRBLLmaker -- Transformer Reads Between Lyrics Lines maker | ['Mor Ventura', 'Michael Toker'] | ['cs.CL', 'cs.AI'] | Even for us, it can be challenging to comprehend the meaning of songs. As
part of this project, we explore the process of generating the meaning of
songs. Despite the widespread use of text-to-text models, few attempts have
been made to achieve a similar objective. Songs are primarily studied in the
context of sentimen... | 2022-12-09T15:27:36Z | null | null | null | TRBLLmaker - Transformer Reads Between Lyrics Lines maker | ['Mor Ventura', 'Michael Toker'] | 2,022 | arXiv.org | 2 | 20 | ['Computer Science'] |
2,212.05055 | Sparse Upcycling: Training Mixture-of-Experts from Dense Checkpoints | ['Aran Komatsuzaki', 'Joan Puigcerver', 'James Lee-Thorp', 'Carlos Riquelme Ruiz', 'Basil Mustafa', 'Joshua Ainslie', 'Yi Tay', 'Mostafa Dehghani', 'Neil Houlsby'] | ['cs.LG', 'cs.CL', 'cs.CV'] | Training large, deep neural networks to convergence can be prohibitively
expensive. As a result, often only a small selection of popular, dense models
are reused across different contexts and tasks. Increasingly, sparsely
activated models, which seek to decouple model size from computation costs, are
becoming an attrac... | 2022-12-09T18:57:37Z | null | null | null | null | null | null | null | null | null | null |
2,212.05702 | Implementing Deep Learning-Based Approaches for Article Summarization in
Indian Languages | ['Rahul Tangsali', 'Aabha Pingle', 'Aditya Vyawahare', 'Isha Joshi', 'Raviraj Joshi'] | ['cs.CL', 'cs.LG'] | The research on text summarization for low-resource Indian languages has been
limited due to the availability of relevant datasets. This paper presents a
summary of various deep-learning approaches used for the ILSUM 2022 Indic
language summarization datasets. The ISUM 2022 dataset consists of news
articles written in ... | 2022-12-12T04:50:43Z | Accepted at ILSUM at FIRE 2022 | null | null | null | null | null | null | null | null | null |
2,212.05935 | Hierarchical multimodal transformers for Multi-Page DocVQA | ['Rubèn Tito', 'Dimosthenis Karatzas', 'Ernest Valveny'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Document Visual Question Answering (DocVQA) refers to the task of answering
questions from document images. Existing work on DocVQA only considers
single-page documents. However, in real scenarios documents are mostly composed
of multiple pages that should be processed altogether. In this work we extend
DocVQA to the m... | 2022-12-07T10:09:49Z | null | null | null | null | null | null | null | null | null | null |
2,212.06042 | AD-BERT: Using Pre-trained contextualized embeddings to Predict the
Progression from Mild Cognitive Impairment to Alzheimer's Disease | ['Chengsheng Mao', 'Jie Xu', 'Luke Rasmussen', 'Yikuan Li', 'Prakash Adekkanattu', 'Jennifer Pacheco', 'Borna Bonakdarpour', 'Robert Vassar', 'Guoqian Jiang', 'Fei Wang', 'Jyotishman Pathak', 'Yuan Luo'] | ['cs.CL', 'cs.LG'] | Objective: We develop a deep learning framework based on the pre-trained
Bidirectional Encoder Representations from Transformers (BERT) model using
unstructured clinical notes from electronic health records (EHRs) to predict
the risk of disease progression from Mild Cognitive Impairment (MCI) to
Alzheimer's Disease (AD... | 2022-11-07T04:05:46Z | null | null | null | null | null | null | null | null | null | null |
2,212.06137 | NMS Strikes Back | ['Jeffrey Ouyang-Zhang', 'Jang Hyun Cho', 'Xingyi Zhou', 'Philipp Krähenbühl'] | ['cs.CV'] | Detection Transformer (DETR) directly transforms queries to unique objects by
using one-to-one bipartite matching during training and enables end-to-end
object detection. Recently, these models have surpassed traditional detectors
on COCO with undeniable elegance. However, they differ from traditional
detectors in mult... | 2022-12-12T18:59:58Z | Code is available at https://github.com/jozhang97/DETA | null | null | null | null | null | null | null | null | null |
2,212.06385 | TencentPretrain: A Scalable and Flexible Toolkit for Pre-training Models
of Different Modalities | ['Zhe Zhao', 'Yudong Li', 'Cheng Hou', 'Jing Zhao', 'Rong Tian', 'Weijie Liu', 'Yiren Chen', 'Ningyuan Sun', 'Haoyan Liu', 'Weiquan Mao', 'Han Guo', 'Weigang Guo', 'Taiqiang Wu', 'Tao Zhu', 'Wenhang Shi', 'Chen Chen', 'Shan Huang', 'Sihong Chen', 'Liqun Liu', 'Feifei Li', 'Xiaoshuai Chen', 'Xingwu Sun', 'Zhanhui Kang',... | ['cs.CL'] | Recently, the success of pre-training in text domain has been fully extended
to vision, audio, and cross-modal scenarios. The proposed pre-training models
of different modalities are showing a rising trend of homogeneity in their
model structures, which brings the opportunity to implement different
pre-training models ... | 2022-12-13T05:46:40Z | null | null | null | null | null | null | null | null | null | null |
2,212.06512 | DifFace: Blind Face Restoration with Diffused Error Contraction | ['Zongsheng Yue', 'Chen Change Loy'] | ['cs.CV', 'I.4.4'] | While deep learning-based methods for blind face restoration have achieved
unprecedented success, they still suffer from two major limitations. First,
most of them deteriorate when facing complex degradations out of their training
data. Second, these methods require multiple constraints, e.g., fidelity,
perceptual, and... | 2022-12-13T11:52:33Z | Accepted by TPAMI@2024. Project: https://github.com/zsyOAOA/DifFace | null | null | null | null | null | null | null | null | null |
2,212.06742 | ERNIE-Code: Beyond English-Centric Cross-lingual Pretraining for
Programming Languages | ['Yekun Chai', 'Shuohuan Wang', 'Chao Pang', 'Yu Sun', 'Hao Tian', 'Hua Wu'] | ['cs.CL', 'cs.LG', 'cs.PL', 'cs.SE'] | Software engineers working with the same programming language (PL) may speak
different natural languages (NLs) and vice versa, erecting huge barriers to
communication and working efficiency. Recent studies have demonstrated the
effectiveness of generative pre-training in computer programs, yet they are
always English-c... | 2022-12-13T17:21:44Z | Accepted at ACL 2023 (Findings) | null | null | null | null | null | null | null | null | null |
2,212.07016 | Understanding Zero-Shot Adversarial Robustness for Large-Scale Models | ['Chengzhi Mao', 'Scott Geng', 'Junfeng Yang', 'Xin Wang', 'Carl Vondrick'] | ['cs.CV'] | Pretrained large-scale vision-language models like CLIP have exhibited strong
generalization over unseen tasks. Yet imperceptible adversarial perturbations
can significantly reduce CLIP's performance on new tasks. In this work, we
identify and explore the problem of \emph{adapting large-scale models for
zero-shot adver... | 2022-12-14T04:08:56Z | null | null | null | Understanding Zero-Shot Adversarial Robustness for Large-Scale Models | ['Chengzhi Mao', 'Scott Geng', 'Junfeng Yang', 'Xin Eric Wang', 'Carl Vondrick'] | 2,022 | International Conference on Learning Representations | 71 | 76 | ['Computer Science'] |
2,212.07143 | Reproducible scaling laws for contrastive language-image learning | ['Mehdi Cherti', 'Romain Beaumont', 'Ross Wightman', 'Mitchell Wortsman', 'Gabriel Ilharco', 'Cade Gordon', 'Christoph Schuhmann', 'Ludwig Schmidt', 'Jenia Jitsev'] | ['cs.LG', 'cs.AI', 'cs.CV'] | Scaling up neural networks has led to remarkable performance across a wide
range of tasks. Moreover, performance often follows reliable scaling laws as a
function of training set size, model size, and compute, which offers valuable
guidance as large-scale experiments are becoming increasingly expensive.
However, previo... | 2022-12-14T10:24:50Z | CVPR 2023. Version with minor extension. Original:
https://openaccess.thecvf.com/content/CVPR2023/html/Cherti_Reproducible_Scaling_Laws_for_Contrastive_Language-Image_Learning_CVPR_2023_paper | Proceedings of the IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR), 2023, pp. 2818-2829 | 10.1109/CVPR52729.2023.00276 | null | null | null | null | null | null | null |
2,212.07249 | APOLLO: An Optimized Training Approach for Long-form Numerical Reasoning | ['Jiashuo Sun', 'Hang Zhang', 'Chen Lin', 'Xiangdong Su', 'Yeyun Gong', 'Jian Guo'] | ['cs.CL', 'cs.LG'] | Long-form numerical reasoning in financial analysis aims to generate a
reasoning program to calculate the correct answer for a given question.
Previous work followed a retriever-generator framework, where the retriever
selects key facts from a long-form document, and the generator generates a
reasoning program based on... | 2022-12-14T14:34:15Z | Accepted by COLING 2024 | null | null | null | null | null | null | null | null | null |
2,212.07652 | Body-Part Joint Detection and Association via Extended Object
Representation | ['Huayi Zhou', 'Fei Jiang', 'Hongtao Lu'] | ['cs.CV'] | The detection of human body and its related parts (e.g., face, head or hands)
have been intensively studied and greatly improved since the breakthrough of
deep CNNs. However, most of these detectors are trained independently, making
it a challenging task to associate detected body parts with people. This paper
focuses ... | 2022-12-15T08:19:02Z | accepted by ICME2023 | null | null | Body-Part Joint Detection and Association via Extended Object Representation | ['Huayi Zhou', 'Fei Jiang', 'Hongtao Lu'] | 2,022 | IEEE International Conference on Multimedia and Expo | 9 | 35 | ['Computer Science'] |
2,212.07841 | MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders are
Better Dense Retrievers | ['Kun Zhou', 'Xiao Liu', 'Yeyun Gong', 'Wayne Xin Zhao', 'Daxin Jiang', 'Nan Duan', 'Ji-Rong Wen'] | ['cs.CL', 'cs.IR'] | Pre-trained Transformers (\eg BERT) have been commonly used in existing dense
retrieval methods for parameter initialization, and recent studies are
exploring more effective pre-training tasks for further improving the quality
of dense vectors. Although various novel and effective tasks have been
proposed, their differ... | 2022-12-15T13:57:07Z | Accepted by ECML-PKDD 2023, 16 pages | null | null | null | null | null | null | null | null | null |
2,212.07919 | ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning | ['Olga Golovneva', 'Moya Chen', 'Spencer Poff', 'Martin Corredor', 'Luke Zettlemoyer', 'Maryam Fazel-Zarandi', 'Asli Celikyilmaz'] | ['cs.CL', 'cs.LG'] | Large language models show improved downstream task performance when prompted
to generate step-by-step reasoning to justify their final answers. These
reasoning steps greatly improve model interpretability and verification, but
objectively studying their correctness (independent of the final answer) is
difficult withou... | 2022-12-15T15:52:39Z | null | null | null | ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning | ['O. Yu. Golovneva', 'Moya Chen', 'Spencer Poff', 'Martin Corredor', 'Luke Zettlemoyer', 'Maryam Fazel-Zarandi', 'Asli Celikyilmaz'] | 2,022 | arXiv.org | 152 | 54 | ['Computer Science'] |
2,212.08013 | FlexiViT: One Model for All Patch Sizes | ['Lucas Beyer', 'Pavel Izmailov', 'Alexander Kolesnikov', 'Mathilde Caron', 'Simon Kornblith', 'Xiaohua Zhai', 'Matthias Minderer', 'Michael Tschannen', 'Ibrahim Alabdulmohsin', 'Filip Pavetic'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Vision Transformers convert images to sequences by slicing them into patches.
The size of these patches controls a speed/accuracy tradeoff, with smaller
patches leading to higher accuracy at greater computational cost, but changing
the patch size typically requires retraining the model. In this paper, we
demonstrate th... | 2022-12-15T18:18:38Z | Code and pre-trained models available at
https://github.com/google-research/big_vision. All authors made significant
technical contributions. CVPR 2023 | null | null | FlexiViT: One Model for All Patch Sizes | ['Lucas Beyer', 'Pavel Izmailov', 'Alexander Kolesnikov', 'Mathilde Caron', 'Simon Kornblith', 'Xiaohua Zhai', 'Matthias Minderer', 'Michael Tschannen', 'Ibrahim M. Alabdulmohsin', 'Filip Pavetic'] | 2,022 | Computer Vision and Pattern Recognition | 94 | 83 | ['Computer Science'] |
2,212.08059 | Rethinking Vision Transformers for MobileNet Size and Speed | ['Yanyu Li', 'Ju Hu', 'Yang Wen', 'Georgios Evangelidis', 'Kamyar Salahi', 'Yanzhi Wang', 'Sergey Tulyakov', 'Jian Ren'] | ['cs.CV', 'cs.AI', 'cs.LG'] | With the success of Vision Transformers (ViTs) in computer vision tasks,
recent arts try to optimize the performance and complexity of ViTs to enable
efficient deployment on mobile devices. Multiple approaches are proposed to
accelerate attention mechanism, improve inefficient designs, or incorporate
mobile-friendly li... | 2022-12-15T18:59:12Z | Code is available at:
https://github.com/snap-research/EfficientFormer | null | null | null | null | null | null | null | null | null |
2,212.08073 | Constitutional AI: Harmlessness from AI Feedback | ['Yuntao Bai', 'Saurav Kadavath', 'Sandipan Kundu', 'Amanda Askell', 'Jackson Kernion', 'Andy Jones', 'Anna Chen', 'Anna Goldie', 'Azalia Mirhoseini', 'Cameron McKinnon', 'Carol Chen', 'Catherine Olsson', 'Christopher Olah', 'Danny Hernandez', 'Dawn Drain', 'Deep Ganguli', 'Dustin Li', 'Eli Tran-Johnson', 'Ethan Perez'... | ['cs.CL', 'cs.AI'] | As AI systems become more capable, we would like to enlist their help to
supervise other AIs. We experiment with methods for training a harmless AI
assistant through self-improvement, without any human labels identifying
harmful outputs. The only human oversight is provided through a list of rules
or principles, and so... | 2022-12-15T06:19:23Z | null | null | null | Constitutional AI: Harmlessness from AI Feedback | ['Yuntao Bai', 'Saurav Kadavath', 'Sandipan Kundu', 'Amanda Askell', 'John Kernion', 'Andy Jones', 'A. Chen', 'Anna Goldie', 'Azalia Mirhoseini', 'C. McKinnon', 'Carol Chen', 'Catherine Olsson', 'Chris Olah', 'Danny Hernandez', 'Dawn Drain', 'Deep Ganguli', 'Dustin Li', 'Eli Tran-Johnson', 'E. Perez', 'Jamie Kerr', 'J.... | 2,022 | arXiv.org | 1,651 | 82 | ['Computer Science'] |
2,212.08751 | Point-E: A System for Generating 3D Point Clouds from Complex Prompts | ['Alex Nichol', 'Heewoo Jun', 'Prafulla Dhariwal', 'Pamela Mishkin', 'Mark Chen'] | ['cs.CV', 'cs.LG'] | While recent work on text-conditional 3D object generation has shown
promising results, the state-of-the-art methods typically require multiple
GPU-hours to produce a single sample. This is in stark contrast to
state-of-the-art generative image models, which produce samples in a number of
seconds or minutes. In this pa... | 2022-12-16T23:22:59Z | 8 pages, 11 figures | null | null | null | null | null | null | null | null | null |
2,212.09019 | Fast FullSubNet: Accelerate Full-band and Sub-band Fusion Model for
Single-channel Speech Enhancement | ['Xiang Hao', 'Xiaofei Li'] | ['eess.AS', 'eess.SP'] | FullSubNet is our recently proposed real-time single-channel speech
enhancement network that achieves outstanding performance on the Deep Noise
Suppression (DNS) Challenge dataset. A number of variants of FullSubNet have
been proposed, but they all focus on the structure design towards better
performance and are rarely... | 2022-12-18T05:41:33Z | null | null | null | null | null | null | null | null | null | null |
2,212.09058 | BEATs: Audio Pre-Training with Acoustic Tokenizers | ['Sanyuan Chen', 'Yu Wu', 'Chengyi Wang', 'Shujie Liu', 'Daniel Tompkins', 'Zhuo Chen', 'Furu Wei'] | ['eess.AS', 'cs.AI', 'cs.CL', 'cs.LG', 'cs.SD'] | The massive growth of self-supervised learning (SSL) has been witnessed in
language, vision, speech, and audio domains over the past few years. While
discrete label prediction is widely adopted for other modalities, the
state-of-the-art audio SSL models still employ reconstruction loss for
pre-training. Compared with r... | 2022-12-18T10:41:55Z | null | null | null | null | null | null | null | null | null | null |
2,212.09255 | Multi hash embeddings in spaCy | ['Lester James Miranda', 'Ákos Kádár', 'Adriane Boyd', 'Sofie Van Landeghem', 'Anders Søgaard', 'Matthew Honnibal'] | ['cs.CL', 'I.2.7'] | The distributed representation of symbols is one of the key technologies in
machine learning systems today, playing a pivotal role in modern natural
language processing. Traditional word embeddings associate a separate vector
with each word. While this approach is simple and leads to good performance, it
requires a lot... | 2022-12-19T06:03:04Z | null | null | null | null | null | null | null | null | null | null |
2,212.09462 | Latent Diffusion for Language Generation | ['Justin Lovelace', 'Varsha Kishore', 'Chao Wan', 'Eliot Shekhtman', 'Kilian Q. Weinberger'] | ['cs.CL', 'cs.LG'] | Diffusion models have achieved great success in modeling continuous data
modalities such as images, audio, and video, but have seen limited use in
discrete domains such as language. Recent attempts to adapt diffusion to
language have presented diffusion as an alternative to existing pretrained
language models. We view ... | 2022-12-19T13:57:06Z | NeurIPS 2023 | null | null | Latent Diffusion for Language Generation | ['Justin Lovelace', 'Varsha Kishore', 'Chao-gang Wan', 'Eliot Shekhtman', 'Kilian Q. Weinberger'] | 2,022 | Neural Information Processing Systems | 82 | 81 | ['Computer Science'] |
2,212.09535 | BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting | ['Zheng-Xin Yong', 'Hailey Schoelkopf', 'Niklas Muennighoff', 'Alham Fikri Aji', 'David Ifeoluwa Adelani', 'Khalid Almubarak', 'M Saiful Bari', 'Lintang Sutawika', 'Jungo Kasai', 'Ahmed Baruwa', 'Genta Indra Winata', 'Stella Biderman', 'Edward Raff', 'Dragomir Radev', 'Vassilina Nikoulina'] | ['cs.CL', 'cs.AI', 'cs.LG'] | The BLOOM model is a large publicly available multilingual language model,
but its pretraining was limited to 46 languages. To extend the benefits of
BLOOM to other languages without incurring prohibitively large costs, it is
desirable to adapt BLOOM to new languages not seen during pretraining. In this
work, we apply ... | 2022-12-19T15:24:45Z | ACL 2023 | null | null | BLOOM+1: Adding Language Support to BLOOM for Zero-Shot Prompting | ['Zheng-Xin Yong', 'Hailey Schoelkopf', 'Niklas Muennighoff', 'Alham Fikri Aji', 'David Ifeoluwa Adelani', 'Khalid Almubarak', 'M Saiful Bari', 'Lintang Sutawika', 'Jungo Kasai', 'Ahmed Baruwa', 'Genta Indra Winata', 'Stella Biderman', 'Dragomir R. Radev', 'Vassilina Nikoulina'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 89 | 78 | ['Computer Science'] |
2,212.09662 | MatCha: Enhancing Visual Language Pretraining with Math Reasoning and
Chart Derendering | ['Fangyu Liu', 'Francesco Piccinno', 'Syrine Krichene', 'Chenxi Pang', 'Kenton Lee', 'Mandar Joshi', 'Yasemin Altun', 'Nigel Collier', 'Julian Martin Eisenschlos'] | ['cs.CL', 'cs.AI', 'cs.CV'] | Visual language data such as plots, charts, and infographics are ubiquitous
in the human world. However, state-of-the-art vision-language models do not
perform well on these data. We propose MatCha (Math reasoning and Chart
derendering pretraining) to enhance visual language models' capabilities in
jointly modeling cha... | 2022-12-19T17:44:54Z | ACL 2023 | null | null | null | null | null | null | null | null | null |
2,212.09682 | Multilingual Sequence-to-Sequence Models for Hebrew NLP | ['Matan Eyal', 'Hila Noga', 'Roee Aharoni', 'Idan Szpektor', 'Reut Tsarfaty'] | ['cs.CL'] | Recent work attributes progress in NLP to large language models (LMs) with
increased model size and large quantities of pretraining data. Despite this,
current state-of-the-art LMs for Hebrew are both under-parameterized and
under-trained compared to LMs in other languages. Additionally, previous work
on pretrained Heb... | 2022-12-19T18:10:23Z | null | null | null | null | null | null | null | null | null | null |
2,212.09689 | Unnatural Instructions: Tuning Language Models with (Almost) No Human
Labor | ['Or Honovich', 'Thomas Scialom', 'Omer Levy', 'Timo Schick'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Instruction tuning enables pretrained language models to perform new tasks
from inference-time natural language descriptions. These approaches rely on
vast amounts of human supervision in the form of crowdsourced datasets or user
interactions. In this work, we introduce Unnatural Instructions: a large
dataset of creati... | 2022-12-19T18:21:00Z | 18 pages, 7 figures | null | null | Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor | ['Or Honovich', 'Thomas Scialom', 'Omer Levy', 'Timo Schick'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 374 | 43 | ['Computer Science'] |
2,212.0972 | The case for 4-bit precision: k-bit Inference Scaling Laws | ['Tim Dettmers', 'Luke Zettlemoyer'] | ['cs.LG', 'cs.NE'] | Quantization methods reduce the number of bits required to represent each
parameter in a model, trading accuracy for smaller memory footprints and
inference latencies. However, the final model size depends on both the number
of parameters of the original model and the rate of compression. For example, a
30B 8-bit model... | 2022-12-19T18:48:33Z | null | null | null | null | null | null | null | null | null | null |
2,212.0973 | Speaking Style Conversion in the Waveform Domain Using Discrete
Self-Supervised Units | ['Gallil Maimon', 'Yossi Adi'] | ['cs.SD', 'cs.CL', 'cs.LG', 'eess.AS'] | We introduce DISSC, a novel, lightweight method that converts the rhythm,
pitch contour and timbre of a recording to a target speaker in a textless
manner. Unlike DISSC, most voice conversion (VC) methods focus primarily on
timbre, and ignore people's unique speaking style (prosody). The proposed
approach uses a pretra... | 2022-12-19T18:53:04Z | Accepted at EMNLP 2023 | null | null | null | null | null | null | null | null | null |
2,212.09739 | LENS: A Learnable Evaluation Metric for Text Simplification | ['Mounica Maddela', 'Yao Dou', 'David Heineman', 'Wei Xu'] | ['cs.CL'] | Training learnable metrics using modern language models has recently emerged
as a promising method for the automatic evaluation of machine translation.
However, existing human evaluation datasets for text simplification have
limited annotations that are based on unitary or outdated models, making them
unsuitable for th... | 2022-12-19T18:56:52Z | Accepted at ACL 2023 | null | null | null | null | null | null | null | null | null |
2,212.09741 | One Embedder, Any Task: Instruction-Finetuned Text Embeddings | ['Hongjin Su', 'Weijia Shi', 'Jungo Kasai', 'Yizhong Wang', 'Yushi Hu', 'Mari Ostendorf', 'Wen-tau Yih', 'Noah A. Smith', 'Luke Zettlemoyer', 'Tao Yu'] | ['cs.CL'] | We introduce INSTRUCTOR, a new method for computing text embeddings given
task instructions: every text input is embedded together with instructions
explaining the use case (e.g., task and domain descriptions). Unlike encoders
from prior work that are more specialized, INSTRUCTOR is a single embedder that
can generate ... | 2022-12-19T18:57:05Z | Accepted in ACL2023 Findings | null | null | null | null | null | null | null | null | null |
2,212.09748 | Scalable Diffusion Models with Transformers | ['William Peebles', 'Saining Xie'] | ['cs.CV', 'cs.LG'] | We explore a new class of diffusion models based on the transformer
architecture. We train latent diffusion models of images, replacing the
commonly-used U-Net backbone with a transformer that operates on latent
patches. We analyze the scalability of our Diffusion Transformers (DiTs)
through the lens of forward pass co... | 2022-12-19T18:59:58Z | Code, project page and videos available at
https://www.wpeebles.com/DiT | null | null | null | null | null | null | null | null | null |
2,212.10057 | WeCheck: Strong Factual Consistency Checker via Weakly Supervised
Learning | ['Wenhao Wu', 'Wei Li', 'Xinyan Xiao', 'Jiachen Liu', 'Sujian Li', 'Yajuan Lv'] | ['cs.CL'] | A crucial issue of current text generation models is that they often
uncontrollably generate factually inconsistent text with respective of their
inputs. Limited by the lack of annotated data, existing works in evaluating
factual consistency directly transfer the reasoning ability of models trained
on other data-rich u... | 2022-12-20T08:04:36Z | ACL 2023 Main Conference | null | null | null | null | null | null | null | null | null |
2,212.10168 | Naamapadam: A Large-Scale Named Entity Annotated Data for Indic
Languages | ['Arnav Mhaske', 'Harshit Kedia', 'Sumanth Doddapaneni', 'Mitesh M. Khapra', 'Pratyush Kumar', 'Rudra Murthy V', 'Anoop Kunchukuttan'] | ['cs.CL'] | We present, Naamapadam, the largest publicly available Named Entity
Recognition (NER) dataset for the 11 major Indian languages from two language
families. The dataset contains more than 400k sentences annotated with a total
of at least 100k entities from three standard entity categories (Person,
Location, and, Organiz... | 2022-12-20T11:15:24Z | ACL 2023 | null | null | Naamapadam: A Large-Scale Named Entity Annotated Data for Indic Languages | ['A. Mhaske', 'Harsh Kedia', 'Sumanth Doddapaneni', 'Mitesh M. Khapra', 'Pratyush Kumar', 'V. Rudramurthy', 'Anoop Kunchukuttan'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 31 | 51 | ['Computer Science'] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.