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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,206.08046 | An Open-Domain QA System for e-Governance | ['Radu Ion', 'Andrei-Marius Avram', 'Vasile Păiş', 'Maria Mitrofan', 'Verginica Barbu Mititelu', 'Elena Irimia', 'Valentin Badea'] | ['cs.CL'] | The paper presents an open-domain Question Answering system for Romanian,
answering COVID-19 related questions. The QA system pipeline involves automatic
question processing, automatic query generation, web searching for the top 10
most relevant documents and answer extraction using a fine-tuned BERT model for
Extracti... | 2022-06-16T10:02:31Z | 8 pages, accepted to CLIB2022 in the main conference | null | null | null | null | null | null | null | null | null |
2,206.08063 | Towards Robust Ranker for Text Retrieval | ['Yucheng Zhou', 'Tao Shen', 'Xiubo Geng', 'Chongyang Tao', 'Can Xu', 'Guodong Long', 'Binxing Jiao', 'Daxin Jiang'] | ['cs.IR', 'cs.CL'] | A ranker plays an indispensable role in the de facto 'retrieval & rerank'
pipeline, but its training still lags behind -- learning from moderate
negatives or/and serving as an auxiliary module for a retriever. In this work,
we first identify two major barriers to a robust ranker, i.e., inherent label
noises caused by a... | 2022-06-16T10:27:46Z | 11 pages of main content, 4 tables, 3 figures | null | null | null | null | null | null | null | null | null |
2,206.08236 | Simple and Efficient Architectures for Semantic Segmentation | ['Dushyant Mehta', 'Andrii Skliar', 'Haitam Ben Yahia', 'Shubhankar Borse', 'Fatih Porikli', 'Amirhossein Habibian', 'Tijmen Blankevoort'] | ['cs.CV', 'cs.LG', 'eess.IV'] | Though the state-of-the architectures for semantic segmentation, such as
HRNet, demonstrate impressive accuracy, the complexity arising from their
salient design choices hinders a range of model acceleration tools, and further
they make use of operations that are inefficient on current hardware. This
paper demonstrates... | 2022-06-16T15:08:34Z | To be presented at Efficient Deep Learning for Computer Vision
Workshop at CVPR 2022 | null | null | null | null | null | null | null | null | null |
2,206.08317 | Paraformer: Fast and Accurate Parallel Transformer for
Non-autoregressive End-to-End Speech Recognition | ['Zhifu Gao', 'Shiliang Zhang', 'Ian McLoughlin', 'Zhijie Yan'] | ['cs.SD', 'cs.CL', 'eess.AS'] | Transformers have recently dominated the ASR field. Although able to yield
good performance, they involve an autoregressive (AR) decoder to generate
tokens one by one, which is computationally inefficient. To speed up inference,
non-autoregressive (NAR) methods, e.g. single-step NAR, were designed, to
enable parallel g... | 2022-06-16T17:24:14Z | 5 pages, 3 figures, accepted by INTERSPEECH 2022 | null | null | null | null | null | null | null | null | null |
2,206.08343 | Realistic One-shot Mesh-based Head Avatars | ['Taras Khakhulin', 'Vanessa Sklyarova', 'Victor Lempitsky', 'Egor Zakharov'] | ['cs.CV', 'cs.GR'] | We present a system for realistic one-shot mesh-based human head avatars
creation, ROME for short. Using a single photograph, our model estimates a
person-specific head mesh and the associated neural texture, which encodes both
local photometric and geometric details. The resulting avatars are rigged and
can be rendere... | 2022-06-16T17:45:23Z | null | null | null | null | null | null | null | null | null | null |
2,206.08441 | GAAMA 2.0: An Integrated System that Answers Boolean and Extractive
Questions | ['Scott McCarley', 'Mihaela Bornea', 'Sara Rosenthal', 'Anthony Ferritto', 'Md Arafat Sultan', 'Avirup Sil', 'Radu Florian'] | ['cs.CL'] | Recent machine reading comprehension datasets include extractive and boolean
questions but current approaches do not offer integrated support for answering
both question types. We present a multilingual machine reading comprehension
system and front-end demo that handles boolean questions by providing both a
YES/NO ans... | 2022-06-16T20:46:04Z | null | null | null | null | null | null | null | null | null | null |
2,206.08657 | BridgeTower: Building Bridges Between Encoders in Vision-Language
Representation Learning | ['Xiao Xu', 'Chenfei Wu', 'Shachar Rosenman', 'Vasudev Lal', 'Wanxiang Che', 'Nan Duan'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Vision-Language (VL) models with the Two-Tower architecture have dominated
visual-language representation learning in recent years. Current VL models
either use lightweight uni-modal encoders and learn to extract, align and fuse
both modalities simultaneously in a deep cross-modal encoder, or feed the
last-layer uni-mo... | 2022-06-17T09:42:35Z | Accepted by AAAI 2023, Oral | null | null | Bridge-Tower: Building Bridges Between Encoders in Vision-Language Representation Learning | ['Xiao Xu', 'Chenfei Wu', 'Shachar Rosenman', 'Vasudev Lal', 'Nan Duan'] | 2,022 | AAAI Conference on Artificial Intelligence | 69 | 116 | ['Computer Science'] |
2,206.08853 | MineDojo: Building Open-Ended Embodied Agents with Internet-Scale
Knowledge | ['Linxi Fan', 'Guanzhi Wang', 'Yunfan Jiang', 'Ajay Mandlekar', 'Yuncong Yang', 'Haoyi Zhu', 'Andrew Tang', 'De-An Huang', 'Yuke Zhu', 'Anima Anandkumar'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CV'] | Autonomous agents have made great strides in specialist domains like Atari
games and Go. However, they typically learn tabula rasa in isolated
environments with limited and manually conceived objectives, thus failing to
generalize across a wide spectrum of tasks and capabilities. Inspired by how
humans continually lear... | 2022-06-17T15:53:05Z | Outstanding Paper Award at NeurIPS 2022. Project website:
https://minedojo.org | null | null | null | null | null | null | null | null | null |
2,206.09479 | StudioGAN: A Taxonomy and Benchmark of GANs for Image Synthesis | ['Minguk Kang', 'Joonghyuk Shin', 'Jaesik Park'] | ['cs.CV', 'cs.LG', 'eess.IV'] | Generative Adversarial Network (GAN) is one of the state-of-the-art
generative models for realistic image synthesis. While training and evaluating
GAN becomes increasingly important, the current GAN research ecosystem does not
provide reliable benchmarks for which the evaluation is conducted consistently
and fairly. Fu... | 2022-06-19T20:12:41Z | 32 pages, IEEE Transactions on Pattern Analysis and Machine
Intelligence (TPAMI, 2023) | null | null | null | null | null | null | null | null | null |
2,206.09507 | Resource-Efficient Separation Transformer | ['Luca Della Libera', 'Cem Subakan', 'Mirco Ravanelli', 'Samuele Cornell', 'Frédéric Lepoutre', 'François Grondin'] | ['eess.AS', 'cs.LG', 'cs.SD', 'eess.SP'] | Transformers have recently achieved state-of-the-art performance in speech
separation. These models, however, are computationally demanding and require a
lot of learnable parameters. This paper explores Transformer-based speech
separation with a reduced computational cost. Our main contribution is the
development of th... | 2022-06-19T23:37:24Z | Accepted to ICASSP 2024 | null | null | null | null | null | null | null | null | null |
2,206.09553 | Capturing and Inferring Dense Full-Body Human-Scene Contact | ['Chun-Hao P. Huang', 'Hongwei Yi', 'Markus Höschle', 'Matvey Safroshkin', 'Tsvetelina Alexiadis', 'Senya Polikovsky', 'Daniel Scharstein', 'Michael J. Black'] | ['cs.CV'] | Inferring human-scene contact (HSC) is the first step toward understanding
how humans interact with their surroundings. While detecting 2D human-object
interaction (HOI) and reconstructing 3D human pose and shape (HPS) have enjoyed
significant progress, reasoning about 3D human-scene contact from a single
image is stil... | 2022-06-20T03:31:00Z | CVPR 2022 | null | null | Capturing and Inferring Dense Full-Body Human-Scene Contact | ['C. Huang', 'Hongwei Yi', 'Markus Hoschle', 'Matvey Safroshkin', 'Tsvetelina Alexiadis', 'Senya Polikovsky', 'D. Scharstein', 'Michael J. Black'] | 2,022 | Computer Vision and Pattern Recognition | 127 | 104 | ['Computer Science'] |
2,206.09959 | Global Context Vision Transformers | ['Ali Hatamizadeh', 'Hongxu Yin', 'Greg Heinrich', 'Jan Kautz', 'Pavlo Molchanov'] | ['cs.CV', 'cs.AI', 'cs.LG'] | We propose global context vision transformer (GC ViT), a novel architecture
that enhances parameter and compute utilization for computer vision. Our method
leverages global context self-attention modules, joint with standard local
self-attention, to effectively and efficiently model both long and short-range
spatial in... | 2022-06-20T18:42:44Z | Accepted to ICML 2023 | null | null | null | null | null | null | null | null | null |
2,206.10128 | Bridging the Gap Between Indexing and Retrieval for Differentiable
Search Index with Query Generation | ['Shengyao Zhuang', 'Houxing Ren', 'Linjun Shou', 'Jian Pei', 'Ming Gong', 'Guido Zuccon', 'Daxin Jiang'] | ['cs.IR', 'cs.CL'] | The Differentiable Search Index (DSI) is an emerging paradigm for information
retrieval. Unlike traditional retrieval architectures where index and retrieval
are two different and separate components, DSI uses a single transformer model
to perform both indexing and retrieval.
In this paper, we identify and tackle an ... | 2022-06-21T06:21:23Z | 11 pages | null | null | null | null | null | null | null | null | null |
2,206.10589 | EdgeNeXt: Efficiently Amalgamated CNN-Transformer Architecture for
Mobile Vision Applications | ['Muhammad Maaz', 'Abdelrahman Shaker', 'Hisham Cholakkal', 'Salman Khan', 'Syed Waqas Zamir', 'Rao Muhammad Anwer', 'Fahad Shahbaz Khan'] | ['cs.CV'] | In the pursuit of achieving ever-increasing accuracy, large and complex
neural networks are usually developed. Such models demand high computational
resources and therefore cannot be deployed on edge devices. It is of great
interest to build resource-efficient general purpose networks due to their
usefulness in several... | 2022-06-21T17:59:56Z | Accepted at ECCVW 2022 (Oral, CADL: Computational Aspects of Deep
Learning) | null | null | null | null | null | null | null | null | null |
2,206.10698 | TiCo: Transformation Invariance and Covariance Contrast for
Self-Supervised Visual Representation Learning | ['Jiachen Zhu', 'Rafael M. Moraes', 'Serkan Karakulak', 'Vlad Sobol', 'Alfredo Canziani', 'Yann LeCun'] | ['cs.CV', 'cs.AI', 'cs.LG'] | We present Transformation Invariance and Covariance Contrast (TiCo) for
self-supervised visual representation learning. Similar to other recent
self-supervised learning methods, our method is based on maximizing the
agreement among embeddings of different distorted versions of the same image,
which pushes the encoder t... | 2022-06-21T19:44:01Z | null | null | null | TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning | ['Jiachen Zhu', 'R. M. Moraes', 'Serkan Karakulak', 'Vlad Sobol', 'A. Canziani', 'Yann LeCun'] | 2,022 | arXiv.org | 22 | 38 | ['Computer Science'] |
2,206.10789 | Scaling Autoregressive Models for Content-Rich Text-to-Image Generation | ['Jiahui Yu', 'Yuanzhong Xu', 'Jing Yu Koh', 'Thang Luong', 'Gunjan Baid', 'Zirui Wang', 'Vijay Vasudevan', 'Alexander Ku', 'Yinfei Yang', 'Burcu Karagol Ayan', 'Ben Hutchinson', 'Wei Han', 'Zarana Parekh', 'Xin Li', 'Han Zhang', 'Jason Baldridge', 'Yonghui Wu'] | ['cs.CV', 'cs.LG'] | We present the Pathways Autoregressive Text-to-Image (Parti) model, which
generates high-fidelity photorealistic images and supports content-rich
synthesis involving complex compositions and world knowledge. Parti treats
text-to-image generation as a sequence-to-sequence modeling problem, akin to
machine translation, w... | 2022-06-22T01:11:29Z | Preprint | null | null | null | null | null | null | null | null | null |
2,206.10883 | Multi-LexSum: Real-World Summaries of Civil Rights Lawsuits at Multiple
Granularities | ['Zejiang Shen', 'Kyle Lo', 'Lauren Yu', 'Nathan Dahlberg', 'Margo Schlanger', 'Doug Downey'] | ['cs.CL', 'cs.CY'] | With the advent of large language models, methods for abstractive
summarization have made great strides, creating potential for use in
applications to aid knowledge workers processing unwieldy document collections.
One such setting is the Civil Rights Litigation Clearinghouse (CRLC)
(https://clearinghouse.net),which po... | 2022-06-22T07:26:55Z | 37 pages, 2 figures, 9 tables | null | null | null | null | null | null | null | null | null |
2,206.11147 | reStructured Pre-training | ['Weizhe Yuan', 'Pengfei Liu'] | ['cs.CL', 'cs.AI', 'cs.LG'] | In this work, we try to decipher the internal connection of NLP technology
development in the past decades, searching for essence, which rewards us with a
(potential) new learning paradigm for NLP tasks, dubbed as reStructured
Pre-training (RST). In such a paradigm, the role of data will be re-emphasized,
and model pre... | 2022-06-22T14:49:24Z | A gift for NLPers :) => update (v2): We released all data and models
for 13 categories of NLP applications (very easy to use:
\url{https://github.com/ExpressAI/reStructured-Pretraining}) | null | null | null | null | null | null | null | null | null |
2,206.11253 | Towards Robust Blind Face Restoration with Codebook Lookup Transformer | ['Shangchen Zhou', 'Kelvin C. K. Chan', 'Chongyi Li', 'Chen Change Loy'] | ['cs.CV'] | Blind face restoration is a highly ill-posed problem that often requires
auxiliary guidance to 1) improve the mapping from degraded inputs to desired
outputs, or 2) complement high-quality details lost in the inputs. In this
paper, we demonstrate that a learned discrete codebook prior in a small proxy
space largely red... | 2022-06-22T17:58:01Z | Accepted by NeurIPS 2022. Code: https://github.com/sczhou/CodeFormer | null | null | null | null | null | null | null | null | null |
2,206.11309 | GODEL: Large-Scale Pre-Training for Goal-Directed Dialog | ['Baolin Peng', 'Michel Galley', 'Pengcheng He', 'Chris Brockett', 'Lars Liden', 'Elnaz Nouri', 'Zhou Yu', 'Bill Dolan', 'Jianfeng Gao'] | ['cs.CL'] | We introduce GODEL (Grounded Open Dialogue Language Model), a large
pre-trained language model for dialog. In contrast with earlier models such as
DialoGPT, GODEL leverages a new phase of grounded pre-training designed to
better support adapting GODEL to a wide range of downstream dialog tasks that
require information ... | 2022-06-22T18:19:32Z | null | null | null | null | null | null | null | null | null | null |
2,206.11404 | The ArtBench Dataset: Benchmarking Generative Models with Artworks | ['Peiyuan Liao', 'Xiuyu Li', 'Xihui Liu', 'Kurt Keutzer'] | ['cs.CV', 'cs.AI', 'cs.LG'] | We introduce ArtBench-10, the first class-balanced, high-quality, cleanly
annotated, and standardized dataset for benchmarking artwork generation. It
comprises 60,000 images of artwork from 10 distinctive artistic styles, with
5,000 training images and 1,000 testing images per style. ArtBench-10 has
several advantages ... | 2022-06-22T22:10:18Z | The first two authors contributed equally to this work. The code and
data are available at https://github.com/liaopeiyuan/artbench | null | null | null | null | null | null | null | null | null |
2,206.11892 | DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors
for Change Detection | ['Wele Gedara Chaminda Bandara', 'Nithin Gopalakrishnan Nair', 'Vishal M. Patel'] | ['cs.CV', 'cs.LG'] | Remote sensing change detection is crucial for understanding the dynamics of
our planet's surface, facilitating the monitoring of environmental changes,
evaluating human impact, predicting future trends, and supporting
decision-making. In this work, we introduce a novel approach for change
detection that can leverage o... | 2022-06-23T17:58:29Z | Code available at: https://github.com/wgcban/ddpm-cd | null | null | DDPM-CD: Denoising Diffusion Probabilistic Models as Feature Extractors for Change Detection | ['W. G. C. Bandara', 'Nithin Gopalakrishnan Nair', 'Vishal M. Patel'] | 2,022 | null | 8 | 111 | ['Computer Science'] |
2,206.11893 | On the Parameterization and Initialization of Diagonal State Space
Models | ['Albert Gu', 'Ankit Gupta', 'Karan Goel', 'Christopher Ré'] | ['cs.LG'] | State space models (SSM) have recently been shown to be very effective as a
deep learning layer as a promising alternative to sequence models such as RNNs,
CNNs, or Transformers. The first version to show this potential was the S4
model, which is particularly effective on tasks involving long-range
dependencies by usin... | 2022-06-23T17:58:39Z | null | null | null | On the Parameterization and Initialization of Diagonal State Space Models | ['Albert Gu', 'Ankit Gupta', 'Karan Goel', 'Christopher Ré'] | 2,022 | Neural Information Processing Systems | 330 | 41 | ['Computer Science'] |
2,206.12055 | SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generation | ['Xin-Yang Zheng', 'Yang Liu', 'Peng-Shuai Wang', 'Xin Tong'] | ['cs.CV'] | We present a StyleGAN2-based deep learning approach for 3D shape generation,
called SDF-StyleGAN, with the aim of reducing visual and geometric
dissimilarity between generated shapes and a shape collection. We extend
StyleGAN2 to 3D generation and utilize the implicit signed distance function
(SDF) as the 3D shape repr... | 2022-06-24T03:11:28Z | Accepted to Computer Graphics Forum (SGP), 2022 | null | null | null | null | null | null | null | null | null |
2,206.12094 | Unified BERT for Few-shot Natural Language Understanding | ['Junyu Lu', 'Ping Yang', 'Ruyi Gan', 'Jing Yang', 'Jiaxing Zhang'] | ['cs.CL', 'cs.AI'] | Even as pre-trained language models share a semantic encoder, natural
language understanding suffers from a diversity of output schemas. In this
paper, we propose UBERT, a unified bidirectional language understanding model
based on BERT framework, which can universally model the training objects of
different NLU tasks ... | 2022-06-24T06:10:53Z | null | null | null | Unified BERT for Few-shot Natural Language Understanding | ['Junyu Lu', 'Ping Yang', 'Jiaxing Zhang', 'Ruyi Gan', 'Jing Yang'] | 2,022 | arXiv.org | 2 | 16 | ['Computer Science'] |
2,206.12131 | MVP: Multi-task Supervised Pre-training for Natural Language Generation | ['Tianyi Tang', 'Junyi Li', 'Wayne Xin Zhao', 'Ji-Rong Wen'] | ['cs.CL'] | Pre-trained language models (PLMs) have achieved remarkable success in
natural language generation (NLG) tasks. Up to now, most NLG-oriented PLMs are
pre-trained in an unsupervised manner using the large-scale general corpus. In
the meanwhile, an increasing number of models pre-trained with labeled data
(i.e. "supervis... | 2022-06-24T07:49:47Z | Accepted by ACL 2023 | null | null | null | null | null | null | null | null | null |
2,206.12693 | TEVR: Improving Speech Recognition by Token Entropy Variance Reduction | ['Hajo Nils Krabbenhöft', 'Erhardt Barth'] | ['cs.CL', 'cs.SD', 'eess.AS', 'F.2.1; I.2.6; I.2.7'] | This paper presents TEVR, a speech recognition model designed to minimize the
variation in token entropy w.r.t. to the language model. This takes advantage
of the fact that if the language model will reliably and accurately predict a
token anyway, then the acoustic model doesn't need to be accurate in
recognizing it. W... | 2022-06-25T16:42:05Z | 10 pages including 2 pages appendix, 1 figure, 6 tables | null | null | null | null | null | null | null | null | null |
2,206.13236 | Pruned RNN-T for fast, memory-efficient ASR training | ['Fangjun Kuang', 'Liyong Guo', 'Wei Kang', 'Long Lin', 'Mingshuang Luo', 'Zengwei Yao', 'Daniel Povey'] | ['eess.AS', 'cs.AI', 'cs.LG'] | The RNN-Transducer (RNN-T) framework for speech recognition has been growing
in popularity, particularly for deployed real-time ASR systems, because it
combines high accuracy with naturally streaming recognition. One of the
drawbacks of RNN-T is that its loss function is relatively slow to compute, and
can use a lot of... | 2022-06-23T12:18:03Z | null | null | null | Pruned RNN-T for fast, memory-efficient ASR training | ['Fangjun Kuang', 'Liyong Guo', 'Wei Kang', 'Long Lin', 'Mingshuang Luo', 'Zengwei Yao', 'Daniel Povey'] | 2,022 | Interspeech | 69 | 17 | ['Engineering', 'Computer Science'] |
2,206.13517 | ProGen2: Exploring the Boundaries of Protein Language Models | ['Erik Nijkamp', 'Jeffrey Ruffolo', 'Eli N. Weinstein', 'Nikhil Naik', 'Ali Madani'] | ['cs.LG', 'q-bio.QM'] | Attention-based models trained on protein sequences have demonstrated
incredible success at classification and generation tasks relevant for
artificial intelligence-driven protein design. However, we lack a sufficient
understanding of how very large-scale models and data play a role in effective
protein model developme... | 2022-06-27T17:55:02Z | null | null | null | null | null | null | null | null | null | null |
2,206.13947 | Long Range Language Modeling via Gated State Spaces | ['Harsh Mehta', 'Ankit Gupta', 'Ashok Cutkosky', 'Behnam Neyshabur'] | ['cs.LG', 'cs.CL'] | State space models have shown to be effective at modeling long range
dependencies, specially on sequence classification tasks. In this work we focus
on autoregressive sequence modeling over English books, Github source code and
ArXiv mathematics articles. Based on recent developments around the
effectiveness of gated a... | 2022-06-27T01:50:18Z | null | null | null | Long Range Language Modeling via Gated State Spaces | ['Harsh Mehta', 'Ankit Gupta', 'Ashok Cutkosky', 'Behnam Neyshabur'] | 2,022 | International Conference on Learning Representations | 243 | 53 | ['Computer Science'] |
2,206.14244 | Masked World Models for Visual Control | ['Younggyo Seo', 'Danijar Hafner', 'Hao Liu', 'Fangchen Liu', 'Stephen James', 'Kimin Lee', 'Pieter Abbeel'] | ['cs.RO', 'cs.AI', 'cs.CV', 'cs.LG'] | Visual model-based reinforcement learning (RL) has the potential to enable
sample-efficient robot learning from visual observations. Yet the current
approaches typically train a single model end-to-end for learning both visual
representations and dynamics, making it difficult to accurately model the
interaction between... | 2022-06-28T18:42:27Z | Project website: https://sites.google.com/view/mwm-rl. Accepted to
CoRL 2022 | null | null | null | null | null | null | null | null | null |
2,207.0022 | Pile of Law: Learning Responsible Data Filtering from the Law and a
256GB Open-Source Legal Dataset | ['Peter Henderson', 'Mark S. Krass', 'Lucia Zheng', 'Neel Guha', 'Christopher D. Manning', 'Dan Jurafsky', 'Daniel E. Ho'] | ['cs.CL', 'cs.CY'] | One concern with the rise of large language models lies with their potential
for significant harm, particularly from pretraining on biased, obscene,
copyrighted, and private information. Emerging ethical approaches have
attempted to filter pretraining material, but such approaches have been ad hoc
and failed to take co... | 2022-07-01T06:25:15Z | Presented at NeurIPS Datasets & Benchmarks (2022) | null | null | Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset | ['Peter Henderson', 'M. Krass', 'Lucia Zheng', 'Neel Guha', 'Christopher D. Manning', 'Dan Jurafsky', 'Daniel E. Ho'] | 2,022 | Neural Information Processing Systems | 103 | 135 | ['Computer Science'] |
2,207.0067 | DRESS: Dynamic REal-time Sparse Subnets | ['Zhongnan Qu', 'Syed Shakib Sarwar', 'Xin Dong', 'Yuecheng Li', 'Ekin Sumbul', 'Barbara De Salvo'] | ['cs.CV', 'cs.LG'] | The limited and dynamically varied resources on edge devices motivate us to
deploy an optimized deep neural network that can adapt its sub-networks to fit
in different resource constraints. However, existing works often build
sub-networks through searching different network architectures in a
hand-crafted sampling spac... | 2022-07-01T22:05:07Z | Published in Efficient Deep Learning for Computer Vision (ECV) CVPR
Workshop 2022 | null | null | null | null | null | null | null | null | null |
2,207.00712 | Turning to a Teacher for Timestamp Supervised Temporal Action
Segmentation | ['Yang Zhao', 'Yan Song'] | ['cs.CV'] | Temporal action segmentation in videos has drawn much attention recently.
Timestamp supervision is a cost-effective way for this task. To obtain more
information to optimize the model, the existing method generated pseudo
frame-wise labels iteratively based on the output of a segmentation model and
the timestamp annota... | 2022-07-02T02:00:55Z | 6 pages, ICME 2022 oral | null | 10.1109/ICME52920.2022.9859626 | null | null | null | null | null | null | null |
2,207.00794 | Boundary-Guided Camouflaged Object Detection | ['Yujia Sun', 'Shuo Wang', 'Chenglizhao Chen', 'Tian-Zhu Xiang'] | ['cs.CV'] | Camouflaged object detection (COD), segmenting objects that are elegantly
blended into their surroundings, is a valuable yet challenging task. Existing
deep-learning methods often fall into the difficulty of accurately identifying
the camouflaged object with complete and fine object structure. To this end, in
this pape... | 2022-07-02T10:48:35Z | Accepted by IJCAI2022 | IJCAI2022 | null | null | null | null | null | null | null | null |
2,207.01084 | Enhancing Automated Software Traceability by Transfer Learning from
Open-World Data | ['Jinfeng Lin', 'Amrit Poudel', 'Wenhao Yu', 'Qingkai Zeng', 'Meng Jiang', 'Jane Cleland-Huang'] | ['cs.SE'] | Software requirements traceability is a critical component of the software
engineering process, enabling activities such as requirements validation,
compliance verification, and safety assurance. However, the cost and effort of
manually creating a complete set of trace links across natural language
artifacts such as re... | 2022-07-03T17:37:28Z | null | null | null | Enhancing Automated Software Traceability by Transfer Learning from Open-World Data | ['Jinfeng Lin', 'Amrit Poudel', 'Wenhao Yu', 'Qingkai Zeng', 'Meng Jiang', 'J. Cleland-Huang'] | 2,022 | arXiv.org | 9 | 82 | ['Computer Science'] |
2,207.0178 | CodeRL: Mastering Code Generation through Pretrained Models and Deep
Reinforcement Learning | ['Hung Le', 'Yue Wang', 'Akhilesh Deepak Gotmare', 'Silvio Savarese', 'Steven C. H. Hoi'] | ['cs.LG', 'cs.CL', 'cs.PL'] | Program synthesis or code generation aims to generate a program that
satisfies a problem specification. Recent approaches using large-scale
pretrained language models (LMs) have shown promising results, yet they have
some critical limitations. In particular, they often follow a standard
supervised fine-tuning procedure... | 2022-07-05T02:42:15Z | An earlier version of the work was accepted to NeurIPS 2022 | null | null | null | null | null | null | null | null | null |
2,207.01848 | TabPFN: A Transformer That Solves Small Tabular Classification Problems
in a Second | ['Noah Hollmann', 'Samuel Müller', 'Katharina Eggensperger', 'Frank Hutter'] | ['cs.LG', 'stat.ML'] | We present TabPFN, a trained Transformer that can do supervised
classification for small tabular datasets in less than a second, needs no
hyperparameter tuning and is competitive with state-of-the-art classification
methods. TabPFN performs in-context learning (ICL), it learns to make
predictions using sequences of lab... | 2022-07-05T07:17:43Z | null | null | null | null | null | null | null | null | null | null |
2,207.02522 | The Role of Complex NLP in Transformers for Text Ranking? | ['David Rau', 'Jaap Kamps'] | ['cs.CL', 'cs.AI'] | Even though term-based methods such as BM25 provide strong baselines in
ranking, under certain conditions they are dominated by large pre-trained
masked language models (MLMs) such as BERT. To date, the source of their
effectiveness remains unclear. Is it their ability to truly understand the
meaning through modeling s... | 2022-07-06T08:54:18Z | Proceedings of the 2022 ACM SIGIR International Conference on the
Theory of Information Retrieval (ICTIR '22) | null | 10.1145/3539813.3545144 | null | null | null | null | null | null | null |
2,207.02578 | SimLM: Pre-training with Representation Bottleneck for Dense Passage
Retrieval | ['Liang Wang', 'Nan Yang', 'Xiaolong Huang', 'Binxing Jiao', 'Linjun Yang', 'Daxin Jiang', 'Rangan Majumder', 'Furu Wei'] | ['cs.IR'] | In this paper, we propose SimLM (Similarity matching with Language Model
pre-training), a simple yet effective pre-training method for dense passage
retrieval. It employs a simple bottleneck architecture that learns to compress
the passage information into a dense vector through self-supervised
pre-training. We use a r... | 2022-07-06T10:51:33Z | Accepted to ACL 2023 | null | null | null | null | null | null | null | null | null |
2,207.02696 | YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for
real-time object detectors | ['Chien-Yao Wang', 'Alexey Bochkovskiy', 'Hong-Yuan Mark Liao'] | ['cs.CV'] | YOLOv7 surpasses all known object detectors in both speed and accuracy in the
range from 5 FPS to 160 FPS and has the highest accuracy 56.8% AP among all
known real-time object detectors with 30 FPS or higher on GPU V100. YOLOv7-E6
object detector (56 FPS V100, 55.9% AP) outperforms both transformer-based
detector SWIN... | 2022-07-06T14:01:58Z | null | null | null | YOLOv7: Trainable Bag-of-Freebies Sets New State-of-the-Art for Real-Time Object Detectors | ['Chien-Yao Wang', 'Alexey Bochkovskiy', 'H. Liao'] | 2,022 | Computer Vision and Pattern Recognition | 6,678 | 99 | ['Computer Science'] |
2,207.03051 | A Large Scale Search Dataset for Unbiased Learning to Rank | ['Lixin Zou', 'Haitao Mao', 'Xiaokai Chu', 'Jiliang Tang', 'Wenwen Ye', 'Shuaiqiang Wang', 'Dawei Yin'] | ['cs.AI'] | The unbiased learning to rank (ULTR) problem has been greatly advanced by
recent deep learning techniques and well-designed debias algorithms. However,
promising results on the existing benchmark datasets may not be extended to the
practical scenario due to the following disadvantages observed from those
popular benchm... | 2022-07-07T02:37:25Z | 15 pages, 9 figures | null | null | A Large Scale Search Dataset for Unbiased Learning to Rank | ['Lixin Zou', 'Haitao Mao', 'Xiaokai Chu', 'Jiliang Tang', 'Wenwen Ye', 'Shuaiqiang Wang', 'Dawei Yin'] | 2,022 | Neural Information Processing Systems | 23 | 46 | ['Computer Science'] |
2,207.03637 | OmniTab: Pretraining with Natural and Synthetic Data for Few-shot
Table-based Question Answering | ['Zhengbao Jiang', 'Yi Mao', 'Pengcheng He', 'Graham Neubig', 'Weizhu Chen'] | ['cs.CL'] | The information in tables can be an important complement to text, making
table-based question answering (QA) systems of great value. The intrinsic
complexity of handling tables often adds an extra burden to both model design
and data annotation. In this paper, we aim to develop a simple table-based QA
model with minima... | 2022-07-08T01:23:45Z | NAACL 2022 | null | null | null | null | null | null | null | null | null |
2,207.03691 | Neural Implicit Dictionary via Mixture-of-Expert Training | ['Peihao Wang', 'Zhiwen Fan', 'Tianlong Chen', 'Zhangyang Wang'] | ['cs.CV'] | Representing visual signals by coordinate-based deep fully-connected networks
has been shown advantageous in fitting complex details and solving inverse
problems than discrete grid-based representation. However, acquiring such a
continuous Implicit Neural Representation (INR) requires tedious per-scene
training on tons... | 2022-07-08T05:07:19Z | International Conference on Machine Learning (ICML), 2022 | null | null | null | null | null | null | null | null | null |
2,207.04043 | The Harvard USPTO Patent Dataset: A Large-Scale, Well-Structured, and
Multi-Purpose Corpus of Patent Applications | ['Mirac Suzgun', 'Luke Melas-Kyriazi', 'Suproteem K. Sarkar', 'Scott Duke Kominers', 'Stuart M. Shieber'] | ['cs.CL', 'cs.CY', 'cs.LG'] | Innovation is a major driver of economic and social development, and
information about many kinds of innovation is embedded in semi-structured data
from patents and patent applications. Although the impact and novelty of
innovations expressed in patent data are difficult to measure through
traditional means, ML offers ... | 2022-07-08T17:57:15Z | Website: https://patentdataset.org/, GitHub Repository:
https://github.com/suzgunmirac/hupd, Hugging Face Datasets:
https://huggingface.co/datasets/HUPD/hupd | null | null | null | null | null | null | null | null | null |
2,207.04108 | ReFinED: An Efficient Zero-shot-capable Approach to End-to-End Entity
Linking | ['Tom Ayoola', 'Shubhi Tyagi', 'Joseph Fisher', 'Christos Christodoulopoulos', 'Andrea Pierleoni'] | ['cs.CL'] | We introduce ReFinED, an efficient end-to-end entity linking model which uses
fine-grained entity types and entity descriptions to perform linking. The model
performs mention detection, fine-grained entity typing, and entity
disambiguation for all mentions within a document in a single forward pass,
making it more than... | 2022-07-08T19:20:42Z | Accepted at NAACL Industry Track 2022 | null | null | null | null | null | null | null | null | null |
2,207.04154 | TalkToModel: Explaining Machine Learning Models with Interactive Natural
Language Conversations | ['Dylan Slack', 'Satyapriya Krishna', 'Himabindu Lakkaraju', 'Sameer Singh'] | ['cs.LG', 'cs.AI', 'cs.CL'] | Machine Learning (ML) models are increasingly used to make critical decisions
in real-world applications, yet they have become more complex, making them
harder to understand. To this end, researchers have proposed several techniques
to explain model predictions. However, practitioners struggle to use these
explainabili... | 2022-07-08T23:42:56Z | Pre-print; comments welcome! Reach out to dslack@uci.edu v3 update
title and abstract | null | null | null | null | null | null | null | null | null |
2,207.04632 | SkexGen: Autoregressive Generation of CAD Construction Sequences with
Disentangled Codebooks | ['Xiang Xu', 'Karl D. D. Willis', 'Joseph G. Lambourne', 'Chin-Yi Cheng', 'Pradeep Kumar Jayaraman', 'Yasutaka Furukawa'] | ['cs.CV', 'cs.LG'] | We present SkexGen, a novel autoregressive generative model for
computer-aided design (CAD) construction sequences containing
sketch-and-extrude modeling operations. Our model utilizes distinct Transformer
architectures to encode topological, geometric, and extrusion variations of
construction sequences into disentangl... | 2022-07-11T05:10:51Z | Accepted to ICML 2022 | null | null | null | null | null | null | null | null | null |
2,207.04672 | No Language Left Behind: Scaling Human-Centered Machine Translation | ['NLLB Team', 'Marta R. Costa-jussà', 'James Cross', 'Onur Çelebi', 'Maha Elbayad', 'Kenneth Heafield', 'Kevin Heffernan', 'Elahe Kalbassi', 'Janice Lam', 'Daniel Licht', 'Jean Maillard', 'Anna Sun', 'Skyler Wang', 'Guillaume Wenzek', 'Al Youngblood', 'Bapi Akula', 'Loic Barrault', 'Gabriel Mejia Gonzalez', 'Prangthip ... | ['cs.CL', 'cs.AI', '68T50', 'I.2.7'] | Driven by the goal of eradicating language barriers on a global scale,
machine translation has solidified itself as a key focus of artificial
intelligence research today. However, such efforts have coalesced around a
small subset of languages, leaving behind the vast majority of mostly
low-resource languages. What does... | 2022-07-11T07:33:36Z | 190 pages | null | null | null | null | null | null | null | null | null |
2,207.04684 | Deep Squared Euclidean Approximation to the Levenshtein Distance for DNA
Storage | ['Alan J. X. Guo', 'Cong Liang', 'Qing-Hu Hou'] | ['cs.LG', 'cs.ET'] | Storing information in DNA molecules is of great interest because of its
advantages in longevity, high storage density, and low maintenance cost. A key
step in the DNA storage pipeline is to efficiently cluster the retrieved DNA
sequences according to their similarities. Levenshtein distance is the most
suitable metric... | 2022-07-11T07:59:36Z | null | null | null | Deep Squared Euclidean Approximation to the Levenshtein Distance for DNA Storage | ['Alan J. X. Guo', 'Cong Liang', 'Q. Hou'] | 2,022 | International Conference on Machine Learning | 4 | 42 | ['Computer Science'] |
2,207.05188 | Knowledge Graph Induction enabling Recommending and Trend Analysis: A
Corporate Research Community Use Case | ['Nandana Mihindukulasooriya', 'Mike Sava', 'Gaetano Rossiello', 'Md Faisal Mahbub Chowdhury', 'Irene Yachbes', 'Aditya Gidh', 'Jillian Duckwitz', 'Kovit Nisar', 'Michael Santos', 'Alfio Gliozzo'] | ['cs.AI', 'cs.CL', 'cs.IR', '68T01, 68T30', 'I.2.7; I.2.4; H.5'] | A research division plays an important role of driving innovation in an
organization. Drawing insights, following trends, keeping abreast of new
research, and formulating strategies are increasingly becoming more challenging
for both researchers and executives as the amount of information grows in both
velocity and vol... | 2022-07-11T20:51:28Z | Accepted at ISWC 2022 | null | null | null | null | null | null | null | null | null |
2,207.05501 | Next-ViT: Next Generation Vision Transformer for Efficient Deployment in
Realistic Industrial Scenarios | ['Jiashi Li', 'Xin Xia', 'Wei Li', 'Huixia Li', 'Xing Wang', 'Xuefeng Xiao', 'Rui Wang', 'Min Zheng', 'Xin Pan'] | ['cs.CV'] | Due to the complex attention mechanisms and model design, most existing
vision Transformers (ViTs) can not perform as efficiently as convolutional
neural networks (CNNs) in realistic industrial deployment scenarios, e.g.
TensorRT and CoreML. This poses a distinct challenge: Can a visual neural
network be designed to in... | 2022-07-12T12:50:34Z | null | null | null | null | null | null | null | null | null | null |
2,207.0613 | Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent
Variable Inference for Text Generation | ['Jinyi Hu', 'Xiaoyuan Yi', 'Wenhao Li', 'Maosong Sun', 'Xing Xie'] | ['cs.CL'] | The past several years have witnessed Variational Auto-Encoder's superiority
in various text generation tasks. However, due to the sequential nature of the
text, auto-regressive decoders tend to ignore latent variables and then reduce
to simple language models, known as the KL vanishing problem, which would
further det... | 2022-07-13T11:27:46Z | NAACL 2022 | null | null | null | null | null | null | null | null | null |
2,207.06389 | ProDiff: Progressive Fast Diffusion Model For High-Quality
Text-to-Speech | ['Rongjie Huang', 'Zhou Zhao', 'Huadai Liu', 'Jinglin Liu', 'Chenye Cui', 'Yi Ren'] | ['eess.AS', 'cs.LG', 'cs.SD'] | Denoising diffusion probabilistic models (DDPMs) have recently achieved
leading performances in many generative tasks. However, the inherited iterative
sampling process costs hinder their applications to text-to-speech deployment.
Through the preliminary study on diffusion model parameterization, we find that
previous ... | 2022-07-13T17:45:43Z | Accepted by ACM Multimedia 2022 | null | null | null | null | null | null | null | null | null |
2,207.06405 | Masked Autoencoders that Listen | ['Po-Yao Huang', 'Hu Xu', 'Juncheng Li', 'Alexei Baevski', 'Michael Auli', 'Wojciech Galuba', 'Florian Metze', 'Christoph Feichtenhofer'] | ['cs.SD', 'cs.AI', 'cs.LG', 'eess.AS'] | This paper studies a simple extension of image-based Masked Autoencoders
(MAE) to self-supervised representation learning from audio spectrograms.
Following the Transformer encoder-decoder design in MAE, our Audio-MAE first
encodes audio spectrogram patches with a high masking ratio, feeding only the
non-masked tokens ... | 2022-07-13T17:59:55Z | Accepted at NeurIPS 2022 | null | null | Masked Autoencoders that Listen | ['Po-Yao (Bernie) Huang', 'Hu Xu', 'Juncheng Billy Li', 'Alexei Baevski', 'Michael Auli', 'Wojciech Galuba', 'Florian Metze', 'Christoph Feichtenhofer'] | 2,022 | Neural Information Processing Systems | 290 | 84 | ['Computer Science', 'Engineering'] |
2,207.06814 | BERTIN: Efficient Pre-Training of a Spanish Language Model using
Perplexity Sampling | ['Javier de la Rosa', 'Eduardo G. Ponferrada', 'Paulo Villegas', 'Pablo Gonzalez de Prado Salas', 'Manu Romero', 'Marıa Grandury'] | ['cs.CL', 'cs.AI'] | The pre-training of large language models usually requires massive amounts of
resources, both in terms of computation and data. Frequently used web sources
such as Common Crawl might contain enough noise to make this pre-training
sub-optimal. In this work, we experiment with different sampling methods from
the Spanish ... | 2022-07-14T10:48:42Z | Published at Procesamiento del Lenguaje Natural | Procesamiento del Lenguaje Natural, 68 (2022): 13-23 | null | BERTIN: Efficient Pre-Training of a Spanish Language Model using Perplexity Sampling | ['Javier de la Rosa', 'E. G. Ponferrada', 'Paulo Villegas', 'Pablo González de Prado Salas', 'Manu Romero', 'María Grandury'] | 2,022 | Proces. del Leng. Natural | 96 | 56 | ['Computer Science'] |
2,207.06881 | Recurrent Memory Transformer | ['Aydar Bulatov', 'Yuri Kuratov', 'Mikhail S. Burtsev'] | ['cs.CL', 'cs.LG'] | Transformer-based models show their effectiveness across multiple domains and
tasks. The self-attention allows to combine information from all sequence
elements into context-aware representations. However, global and local
information has to be stored mostly in the same element-wise representations.
Moreover, the lengt... | 2022-07-14T13:00:22Z | 36th Conference on Neural Information Processing Systems (NeurIPS
2022) | null | null | Recurrent Memory Transformer | ['Aydar Bulatov', 'Yuri Kuratov', 'M. Burtsev'] | 2,022 | Neural Information Processing Systems | 113 | 56 | ['Computer Science'] |
2,207.06991 | Language Modelling with Pixels | ['Phillip Rust', 'Jonas F. Lotz', 'Emanuele Bugliarello', 'Elizabeth Salesky', 'Miryam de Lhoneux', 'Desmond Elliott'] | ['cs.CL', 'cs.AI', 'cs.CV', 'cs.LG'] | Language models are defined over a finite set of inputs, which creates a
vocabulary bottleneck when we attempt to scale the number of supported
languages. Tackling this bottleneck results in a trade-off between what can be
represented in the embedding matrix and computational issues in the output
layer. This paper intr... | 2022-07-14T15:20:36Z | ICLR 2023 | null | null | null | null | null | null | null | null | null |
2,207.08143 | Can large language models reason about medical questions? | ['Valentin Liévin', 'Christoffer Egeberg Hother', 'Andreas Geert Motzfeldt', 'Ole Winther'] | ['cs.CL', 'cs.AI', 'cs.LG', 'I.2.1; I.2.7'] | Although large language models (LLMs) often produce impressive outputs, it
remains unclear how they perform in real-world scenarios requiring strong
reasoning skills and expert domain knowledge. We set out to investigate whether
close- and open-source models (GPT-3.5, LLama-2, etc.) can be applied to answer
and reason ... | 2022-07-17T11:24:44Z | 37 pages, 23 figures. v1: results using InstructGPT, v2.0: added the
Codex experiments, v2.1: added the missing test MedMCQA results for Codex
5-shot CoT and using k=100 samples, v3.0: added results for open source
models -- ready for publication (final version) | null | null | null | null | null | null | null | null | null |
2,207.08292 | A Spoken Drug Prescription Dataset in French for Spoken Language
Understanding | ['Ali Can Kocabiyikoglu', 'François Portet', 'Prudence Gibert', 'Hervé Blanchon', 'Jean-Marc Babouchkine', 'Gaëtan Gavazzi'] | ['cs.CL'] | Spoken medical dialogue systems are increasingly attracting interest to
enhance access to healthcare services and improve quality and traceability of
patient care. In this paper, we focus on medical drug prescriptions acquired on
smartphones through spoken dialogue. Such systems would facilitate the
traceability of car... | 2022-07-17T21:18:03Z | Ali Can Kocabiyikoglu,Fran\c{c}ois Portet, Prudence Gibert, Herv\'e
Blanchon, Jean-Marc Babouchkine, Ga\"etan Gavazzi. A Spoken Drug Prescription
Dataset in French for Spoken Language Understanding. LREC2022, Marseille,
France, 21-22-23 June 2022 | null | null | null | null | null | null | null | null | null |
2,207.0915 | On the Usability of Transformers-based models for a French
Question-Answering task | ['Oralie Cattan', 'Christophe Servan', 'Sophie Rosset'] | ['cs.CL', 'cs.AI', '68T50', 'I.2.7'] | For many tasks, state-of-the-art results have been achieved with
Transformer-based architectures, resulting in a paradigmatic shift in practices
from the use of task-specific architectures to the fine-tuning of pre-trained
language models. The ongoing trend consists in training models with an
ever-increasing amount of ... | 2022-07-19T09:46:15Z | French compact model paper: FrALBERT, Accepted to RANLP 2021 | null | null | null | null | null | null | null | null | null |
2,207.09238 | Formal Algorithms for Transformers | ['Mary Phuong', 'Marcus Hutter'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.NE'] | This document aims to be a self-contained, mathematically precise overview of
transformer architectures and algorithms (*not* results). It covers what
transformers are, how they are trained, what they are used for, their key
architectural components, and a preview of the most prominent models. The
reader is assumed to ... | 2022-07-19T12:49:02Z | 16 pages, 15 algorithms | Latest 2022 version at http://www.hutter1.net/publ/transalg.pdf | null | null | null | null | null | null | null | null |
2,207.10284 | Multi Resolution Analysis (MRA) for Approximate Self-Attention | ['Zhanpeng Zeng', 'Sourav Pal', 'Jeffery Kline', 'Glenn M Fung', 'Vikas Singh'] | ['cs.LG', 'cs.CL', 'eess.SP'] | Transformers have emerged as a preferred model for many tasks in natural
langugage processing and vision. Recent efforts on training and deploying
Transformers more efficiently have identified many strategies to approximate
the self-attention matrix, a key module in a Transformer architecture.
Effective ideas include v... | 2022-07-21T03:36:30Z | ICML2022 | null | null | Multi Resolution Analysis (MRA) for Approximate Self-Attention | ['Zhanpeng Zeng', 'Sourav Pal', 'Jeffery Kline', 'G. Fung', 'Vikas Singh'] | 2,022 | International Conference on Machine Learning | 8 | 44 | ['Medicine', 'Computer Science', 'Engineering'] |
2,207.10442 | Estimation of Non-Crossing Quantile Regression Process with Deep ReQU
Neural Networks | ['Guohao Shen', 'Yuling Jiao', 'Yuanyuan Lin', 'Joel L. Horowitz', 'Jian Huang'] | ['stat.ML', 'cs.LG', '62G05, 62G08, 68T07'] | We propose a penalized nonparametric approach to estimating the quantile
regression process (QRP) in a nonseparable model using rectifier quadratic unit
(ReQU) activated deep neural networks and introduce a novel penalty function to
enforce non-crossing of quantile regression curves. We establish the
non-asymptotic exc... | 2022-07-21T12:26:45Z | 44 pages, 10 figures, 6 tables | null | null | Estimation of Non-Crossing Quantile Regression Process with Deep ReQU Neural Networks | ['Guohao Shen', 'Yuling Jiao', 'Yuanyuan Lin', 'J. Horowitz', 'Jian Huang'] | 2,022 | arXiv.org | 4 | 53 | ['Computer Science', 'Mathematics'] |
2,207.1066 | Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild | ['Garrick Brazil', 'Abhinav Kumar', 'Julian Straub', 'Nikhila Ravi', 'Justin Johnson', 'Georgia Gkioxari'] | ['cs.CV'] | Recognizing scenes and objects in 3D from a single image is a longstanding
goal of computer vision with applications in robotics and AR/VR. For 2D
recognition, large datasets and scalable solutions have led to unprecedented
advances. In 3D, existing benchmarks are small in size and approaches
specialize in few object c... | 2022-07-21T17:56:22Z | CVPR 2023, Project website: https://omni3d.garrickbrazil.com/ | null | null | Omni3D: A Large Benchmark and Model for 3D Object Detection in the Wild | ['Garrick Brazil', 'Abhinav Kumar', 'Julian Straub', 'Nikhila Ravi', 'Justin Johnson', 'Georgia Gkioxari'] | 2,022 | Computer Vision and Pattern Recognition | 105 | 96 | ['Computer Science'] |
2,207.10666 | TinyViT: Fast Pretraining Distillation for Small Vision Transformers | ['Kan Wu', 'Jinnian Zhang', 'Houwen Peng', 'Mengchen Liu', 'Bin Xiao', 'Jianlong Fu', 'Lu Yuan'] | ['cs.CV'] | Vision transformer (ViT) recently has drawn great attention in computer
vision due to its remarkable model capability. However, most prevailing ViT
models suffer from huge number of parameters, restricting their applicability
on devices with limited resources. To alleviate this issue, we propose TinyViT,
a new family o... | 2022-07-21T17:59:56Z | Accepted by ECCV 2022 | null | null | null | null | null | null | null | null | null |
2,207.11094 | Visual Speech-Aware Perceptual 3D Facial Expression Reconstruction from
Videos | ['Panagiotis P. Filntisis', 'George Retsinas', 'Foivos Paraperas-Papantoniou', 'Athanasios Katsamanis', 'Anastasios Roussos', 'Petros Maragos'] | ['cs.CV'] | The recent state of the art on monocular 3D face reconstruction from image
data has made some impressive advancements, thanks to the advent of Deep
Learning. However, it has mostly focused on input coming from a single RGB
image, overlooking the following important factors: a) Nowadays, the vast
majority of facial imag... | 2022-07-22T14:07:46Z | null | null | null | null | null | null | null | null | null | null |
2,207.12345 | The Mira-Titan Universe IV. High Precision Power Spectrum Emulation | ['Kelly R. Moran', 'Katrin Heitmann', 'Earl Lawrence', 'Salman Habib', 'Derek Bingham', 'Amol Upadhye', 'Juliana Kwan', 'David Higdon', 'Richard Payne'] | ['astro-ph.CO', 'stat.AP'] | Modern cosmological surveys are delivering datasets characterized by
unprecedented quality and statistical completeness; this trend is expected to
continue into the future as new ground- and space-based surveys come online. In
order to maximally extract cosmological information from these observations,
matching theoret... | 2022-07-25T17:01:04Z | null | null | 10.1093/mnras/stac3452 | null | null | null | null | null | null | null |
2,207.12396 | Exploring CLIP for Assessing the Look and Feel of Images | ['Jianyi Wang', 'Kelvin C. K. Chan', 'Chen Change Loy'] | ['cs.CV'] | Measuring the perception of visual content is a long-standing problem in
computer vision. Many mathematical models have been developed to evaluate the
look or quality of an image. Despite the effectiveness of such tools in
quantifying degradations such as noise and blurriness levels, such
quantification is loosely coup... | 2022-07-25T17:58:16Z | Accepted by AAAI2023. Code: https://github.com/IceClear/CLIP-IQA | null | null | null | null | null | null | null | null | null |
2,207.12598 | Classifier-Free Diffusion Guidance | ['Jonathan Ho', 'Tim Salimans'] | ['cs.LG', 'cs.AI'] | Classifier guidance is a recently introduced method to trade off mode
coverage and sample fidelity in conditional diffusion models post training, in
the same spirit as low temperature sampling or truncation in other types of
generative models. Classifier guidance combines the score estimate of a
diffusion model with th... | 2022-07-26T01:42:07Z | A short version of this paper appeared in the NeurIPS 2021 Workshop
on Deep Generative Models and Downstream Applications:
https://openreview.net/pdf?id=qw8AKxfYbI | null | null | null | null | null | null | null | null | null |
2,207.12691 | CENet: Toward Concise and Efficient LiDAR Semantic Segmentation for
Autonomous Driving | ['Hui-Xian Cheng', 'Xian-Feng Han', 'Guo-Qiang Xiao'] | ['cs.CV'] | Accurate and fast scene understanding is one of the challenging task for
autonomous driving, which requires to take full advantage of LiDAR point clouds
for semantic segmentation. In this paper, we present a \textbf{concise} and
\textbf{efficient} image-based semantic segmentation network, named
\textbf{CENet}. In orde... | 2022-07-26T07:22:19Z | Accepted by ICME 2022 | null | null | null | null | null | null | null | null | null |
2,207.13703 | SoundChoice: Grapheme-to-Phoneme Models with Semantic Disambiguation | ['Artem Ploujnikov', 'Mirco Ravanelli'] | ['cs.SD', 'cs.LG', 'eess.AS'] | End-to-end speech synthesis models directly convert the input characters into
an audio representation (e.g., spectrograms). Despite their impressive
performance, such models have difficulty disambiguating the pronunciations of
identically spelled words. To mitigate this issue, a separate
Grapheme-to-Phoneme (G2P) model... | 2022-07-27T01:14:59Z | 5 pages, submitted to INTERSPEECH 2022 | null | null | null | null | null | null | null | null | null |
2,207.13988 | Sequence to sequence pretraining for a less-resourced Slovenian language | ['Matej Ulčar', 'Marko Robnik-Šikonja'] | ['cs.CL'] | Large pretrained language models have recently conquered the area of natural
language processing. As an alternative to predominant masked language modelling
introduced in BERT, the T5 model has introduced a more general training
objective, namely sequence to sequence transformation, which includes masked
language model... | 2022-07-28T10:08:50Z | 19 pages | null | null | null | null | null | null | null | null | null |
2,207.14251 | Measuring Causal Effects of Data Statistics on Language Model's
`Factual' Predictions | ['Yanai Elazar', 'Nora Kassner', 'Shauli Ravfogel', 'Amir Feder', 'Abhilasha Ravichander', 'Marius Mosbach', 'Yonatan Belinkov', 'Hinrich Schütze', 'Yoav Goldberg'] | ['cs.CL'] | Large amounts of training data are one of the major reasons for the high
performance of state-of-the-art NLP models. But what exactly in the training
data causes a model to make a certain prediction? We seek to answer this
question by providing a language for describing how training data influences
predictions, through... | 2022-07-28T17:36:24Z | We received a criticism regarding the validity of the causal
formulation in this paper. We will address them in an upcoming version | null | null | null | null | null | null | null | null | null |
2,207.14255 | Efficient Training of Language Models to Fill in the Middle | ['Mohammad Bavarian', 'Heewoo Jun', 'Nikolas Tezak', 'John Schulman', 'Christine McLeavey', 'Jerry Tworek', 'Mark Chen'] | ['cs.CL'] | We show that autoregressive language models can learn to infill text after we
apply a straightforward transformation to the dataset, which simply moves a
span of text from the middle of a document to its end. While this data
augmentation has garnered much interest in recent years, we provide extensive
evidence that tra... | 2022-07-28T17:40:47Z | null | null | null | Efficient Training of Language Models to Fill in the Middle | ['Mo Bavarian', 'Heewoo Jun', 'N. Tezak', 'John Schulman', 'Christine McLeavey', 'Jerry Tworek', 'Mark Chen'] | 2,022 | arXiv.org | 197 | 56 | ['Computer Science'] |
2,207.14606 | WISE: Whitebox Image Stylization by Example-based Learning | ['Winfried Lötzsch', 'Max Reimann', 'Martin Büssemeyer', 'Amir Semmo', 'Jürgen Döllner', 'Matthias Trapp'] | ['cs.CV', 'cs.GR'] | Image-based artistic rendering can synthesize a variety of expressive styles
using algorithmic image filtering. In contrast to deep learning-based methods,
these heuristics-based filtering techniques can operate on high-resolution
images, are interpretable, and can be parameterized according to various design
aspects. ... | 2022-07-29T10:59:54Z | Accepted to ECCV | null | null | null | null | null | null | null | null | null |
2,208.00511 | Aggretriever: A Simple Approach to Aggregate Textual Representations for
Robust Dense Passage Retrieval | ['Sheng-Chieh Lin', 'Minghan Li', 'Jimmy Lin'] | ['cs.IR'] | Pre-trained language models have been successful in many knowledge-intensive
NLP tasks. However, recent work has shown that models such as BERT are not
``structurally ready'' to aggregate textual information into a [CLS] vector for
dense passage retrieval (DPR). This ``lack of readiness'' results from the gap
between l... | 2022-07-31T20:27:35Z | Published in Transactions of the Association for Computational
Linguistics | null | null | null | null | null | null | null | null | null |
2,208.00748 | Efficient Long-Text Understanding with Short-Text Models | ['Maor Ivgi', 'Uri Shaham', 'Jonathan Berant'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Transformer-based pretrained language models (LMs) are ubiquitous across
natural language understanding, but cannot be applied to long sequences such as
stories, scientific articles and long documents, due to their quadratic
complexity. While a myriad of efficient transformer variants have been
proposed, they are typic... | 2022-08-01T11:14:39Z | Accepted for publication in Transactions of the Association for
Computational Linguistics (TACL), 2023. Authors' final version (pre-MIT) | null | null | null | null | null | null | null | null | null |
2,208.01006 | Multi-Document Summarization with Centroid-Based Pretraining | ['Ratish Puduppully', 'Parag Jain', 'Nancy F. Chen', 'Mark Steedman'] | ['cs.CL'] | In Multi-Document Summarization (MDS), the input can be modeled as a set of
documents, and the output is its summary. In this paper, we focus on
pretraining objectives for MDS. Specifically, we introduce a novel pretraining
objective, which involves selecting the ROUGE-based centroid of each document
cluster as a proxy... | 2022-08-01T17:28:02Z | ACL 2023 camera-ready | null | null | null | null | null | null | null | null | null |
2,208.01626 | Prompt-to-Prompt Image Editing with Cross Attention Control | ['Amir Hertz', 'Ron Mokady', 'Jay Tenenbaum', 'Kfir Aberman', 'Yael Pritch', 'Daniel Cohen-Or'] | ['cs.CV', 'cs.CL', 'cs.GR', 'cs.LG'] | Recent large-scale text-driven synthesis models have attracted much attention
thanks to their remarkable capabilities of generating highly diverse images
that follow given text prompts. Such text-based synthesis methods are
particularly appealing to humans who are used to verbally describe their
intent. Therefore, it i... | 2022-08-02T17:55:41Z | null | null | null | null | null | null | null | null | null | null |
2,208.01875 | Introducing BEREL: BERT Embeddings for Rabbinic-Encoded Language | ['Avi Shmidman', 'Joshua Guedalia', 'Shaltiel Shmidman', 'Cheyn Shmuel Shmidman', 'Eli Handel', 'Moshe Koppel'] | ['cs.CL'] | We present a new pre-trained language model (PLM) for Rabbinic Hebrew, termed
Berel (BERT Embeddings for Rabbinic-Encoded Language). Whilst other PLMs exist
for processing Hebrew texts (e.g., HeBERT, AlephBert), they are all trained on
modern Hebrew texts, which diverges substantially from Rabbinic Hebrew in terms
of i... | 2022-08-03T06:59:04Z | null | null | null | Introducing BEREL: BERT Embeddings for Rabbinic-Encoded Language | ['Avi Shmidman', 'Joshua Guedalia', 'Shaltiel Shmidman', 'C. Shmidman', 'Eli Handel', 'Moshe Koppel'] | 2,022 | arXiv.org | 6 | 8 | ['Computer Science'] |
2,208.02816 | Expanding Language-Image Pretrained Models for General Video Recognition | ['Bolin Ni', 'Houwen Peng', 'Minghao Chen', 'Songyang Zhang', 'Gaofeng Meng', 'Jianlong Fu', 'Shiming Xiang', 'Haibin Ling'] | ['cs.CV'] | Contrastive language-image pretraining has shown great success in learning
visual-textual joint representation from web-scale data, demonstrating
remarkable "zero-shot" generalization ability for various image tasks. However,
how to effectively expand such new language-image pretraining methods to video
domains is stil... | 2022-08-04T17:59:54Z | Accepted by ECCV2022, Oral | null | null | null | null | null | null | null | null | null |
2,208.03274 | A Holistic Approach to Undesired Content Detection in the Real World | ['Todor Markov', 'Chong Zhang', 'Sandhini Agarwal', 'Tyna Eloundou', 'Teddy Lee', 'Steven Adler', 'Angela Jiang', 'Lilian Weng'] | ['cs.CL', 'cs.LG'] | We present a holistic approach to building a robust and useful natural
language classification system for real-world content moderation. The success
of such a system relies on a chain of carefully designed and executed steps,
including the design of content taxonomies and labeling instructions, data
quality control, an... | 2022-08-05T16:47:23Z | Oral presentation at AAAI-23 | null | null | A Holistic Approach to Undesired Content Detection in the Real World | ['Todor Markov', 'Chong Zhang', 'Sandhini Agarwal', 'Tyna Eloundou', 'Teddy Lee', 'Steven Adler', 'Angela Jiang', 'L. Weng'] | 2,022 | AAAI Conference on Artificial Intelligence | 237 | 107 | ['Computer Science'] |
2,208.03987 | Advancing Plain Vision Transformer Towards Remote Sensing Foundation
Model | ['Di Wang', 'Qiming Zhang', 'Yufei Xu', 'Jing Zhang', 'Bo Du', 'Dacheng Tao', 'Liangpei Zhang'] | ['cs.CV'] | Large-scale vision foundation models have made significant progress in visual
tasks on natural images, with vision transformers being the primary choice due
to their good scalability and representation ability. However, large-scale
models in remote sensing (RS) have not yet been sufficiently explored. In this
paper, we... | 2022-08-08T09:08:40Z | Accepted by IEEE TGRS. The codes and models are released at
https://github.com/ViTAE-Transformer/Remote-Sensing-RVSA | null | null | null | null | null | null | null | null | null |
2,208.04347 | Investigating Efficiently Extending Transformers for Long Input
Summarization | ['Jason Phang', 'Yao Zhao', 'Peter J. Liu'] | ['cs.CL'] | While large pretrained Transformer models have proven highly capable at
tackling natural language tasks, handling long sequence inputs continues to be
a significant challenge. One such task is long input summarization, where
inputs are longer than the maximum input context of most pretrained models.
Through an extensiv... | 2022-08-08T18:10:58Z | null | null | null | null | null | null | null | null | null | null |
2,208.04799 | Thai Wav2Vec2.0 with CommonVoice V8 | ['Wannaphong Phatthiyaphaibun', 'Chompakorn Chaksangchaichot', 'Peerat Limkonchotiwat', 'Ekapol Chuangsuwanich', 'Sarana Nutanong'] | ['cs.CL', 'cs.SD', 'eess.AS'] | Recently, Automatic Speech Recognition (ASR), a system that converts audio
into text, has caught a lot of attention in the machine learning community.
Thus, a lot of publicly available models were released in HuggingFace. However,
most of these ASR models are available in English; only a minority of the
models are avai... | 2022-08-09T14:21:48Z | null | null | null | null | null | null | null | null | null | null |
2,208.04933 | Simplified State Space Layers for Sequence Modeling | ['Jimmy T. H. Smith', 'Andrew Warrington', 'Scott W. Linderman'] | ['cs.LG'] | Models using structured state space sequence (S4) layers have achieved
state-of-the-art performance on long-range sequence modeling tasks. An S4 layer
combines linear state space models (SSMs), the HiPPO framework, and deep
learning to achieve high performance. We build on the design of the S4 layer
and introduce a new... | 2022-08-09T17:57:43Z | null | null | null | null | null | null | null | null | null | null |
2,208.05868 | TotalSegmentator: robust segmentation of 104 anatomical structures in CT
images | ['Jakob Wasserthal', 'Hanns-Christian Breit', 'Manfred T. Meyer', 'Maurice Pradella', 'Daniel Hinck', 'Alexander W. Sauter', 'Tobias Heye', 'Daniel Boll', 'Joshy Cyriac', 'Shan Yang', 'Michael Bach', 'Martin Segeroth'] | ['eess.IV', 'cs.CV'] | We present a deep learning segmentation model that can automatically and
robustly segment all major anatomical structures in body CT images. In this
retrospective study, 1204 CT examinations (from the years 2012, 2016, and 2020)
were used to segment 104 anatomical structures (27 organs, 59 bones, 10
muscles, 8 vessels)... | 2022-08-11T15:16:40Z | Accepted at Radiology: Artificial Intelligence | Radiol Artif Intell 2023;5(5):e230024 | 10.1148/ryai.230024 | null | null | null | null | null | null | null |
2,208.06366 | BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers | ['Zhiliang Peng', 'Li Dong', 'Hangbo Bao', 'Qixiang Ye', 'Furu Wei'] | ['cs.CV'] | Masked image modeling (MIM) has demonstrated impressive results in
self-supervised representation learning by recovering corrupted image patches.
However, most existing studies operate on low-level image pixels, which hinders
the exploitation of high-level semantics for representation models. In this
work, we propose t... | 2022-08-12T16:48:10Z | null | null | null | null | null | null | null | null | null | null |
2,208.06525 | Automated Utterance Labeling of Conversations Using Natural Language
Processing | ['Maria Laricheva', 'Chiyu Zhang', 'Yan Liu', 'Guanyu Chen', 'Terence Tracey', 'Richard Young', 'Giuseppe Carenini'] | ['cs.CL'] | Conversational data is essential in psychology because it can help
researchers understand individuals cognitive processes, emotions, and
behaviors. Utterance labelling is a common strategy for analyzing this type of
data. The development of NLP algorithms allows researchers to automate this
task. However, psychological... | 2022-08-12T23:03:45Z | Accepted in SBP-BRiMS 2022 (Camera-ready version) | null | null | Automated Utterance Labeling of Conversations Using Natural Language Processing | ['M. Laricheva', 'Chiyu Zhang', 'Y. Liu', 'Guan-Jhih Chen', 'Terence Tracey', 'Richard Young', 'G. Carenini'] | 2,022 | International Conference on Social, Cultural, and Behavioral Modeling | 0 | 17 | ['Computer Science'] |
2,208.06768 | Flow-Guided Transformer for Video Inpainting | ['Kaidong Zhang', 'Jingjing Fu', 'Dong Liu'] | ['cs.CV'] | We propose a flow-guided transformer, which innovatively leverage the motion
discrepancy exposed by optical flows to instruct the attention retrieval in
transformer for high fidelity video inpainting. More specially, we design a
novel flow completion network to complete the corrupted flows by exploiting the
relevant fl... | 2022-08-14T03:10:01Z | ECCV 2022 | null | null | Flow-Guided Transformer for Video Inpainting | ['Kaiwen Zhang', 'Jingjing Fu', 'Dong Liu'] | 2,022 | European Conference on Computer Vision | 72 | 59 | ['Computer Science'] |
2,208.0712 | Compressing Pre-trained Models of Code into 3 MB | ['Jieke Shi', 'Zhou Yang', 'Bowen Xu', 'Hong Jin Kang', 'David Lo'] | ['cs.SE'] | Although large pre-trained models of code have delivered significant
advancements in various code processing tasks, there is an impediment to the
wide and fluent adoption of these powerful models in software developers' daily
workflow: these large models consume hundreds of megabytes of memory and run
slowly on persona... | 2022-08-15T11:22:04Z | Accepted by the Research Papers Track of 37th IEEE/ACM International
Conference on Automated Software Engineering (ASE '22) | null | null | Compressing Pre-trained Models of Code into 3 MB | ['Jieke Shi', 'Zhou Yang', 'Bowen Xu', 'Hong Jin Kang', 'David Lo'] | 2,022 | International Conference on Automated Software Engineering | 37 | 57 | ['Computer Science'] |
2,208.07339 | LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale | ['Tim Dettmers', 'Mike Lewis', 'Younes Belkada', 'Luke Zettlemoyer'] | ['cs.LG', 'cs.AI'] | Large language models have been widely adopted but require significant GPU
memory for inference. We develop a procedure for Int8 matrix multiplication for
feed-forward and attention projection layers in transformers, which cut the
memory needed for inference by half while retaining full precision performance.
With our ... | 2022-08-15T17:08:50Z | Published at NeurIPS 2022. Camera-ready version | null | null | null | null | null | null | null | null | null |
2,208.0767 | ConTextual Masked Auto-Encoder for Dense Passage Retrieval | ['Xing Wu', 'Guangyuan Ma', 'Meng Lin', 'Zijia Lin', 'Zhongyuan Wang', 'Songlin Hu'] | ['cs.CL', 'cs.AI'] | Dense passage retrieval aims to retrieve the relevant passages of a query
from a large corpus based on dense representations (i.e., vectors) of the query
and the passages. Recent studies have explored improving pre-trained language
models to boost dense retrieval performance. This paper proposes CoT-MAE
(ConTextual Mas... | 2022-08-16T11:17:22Z | This paper has been accepted by AAAI2023 | null | null | null | null | null | null | null | null | null |
2,208.08124 | Boosting Distributed Training Performance of the Unpadded BERT Model | ['Jinle Zeng', 'Min Li', 'Zhihua Wu', 'Jiaqi Liu', 'Yuang Liu', 'Dianhai Yu', 'Yanjun Ma'] | ['cs.DC'] | Pre-training models are an important tool in Natural Language Processing
(NLP), while the BERT model is a classic pre-training model whose structure has
been widely adopted by followers. It was even chosen as the reference model for
the MLPerf training benchmark. The distributed training performance
optimization of BER... | 2022-08-17T07:40:20Z | null | null | null | null | null | null | null | null | null | null |
2,208.08706 | Musika! Fast Infinite Waveform Music Generation | ['Marco Pasini', 'Jan Schlüter'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Fast and user-controllable music generation could enable novel ways of
composing or performing music. However, state-of-the-art music generation
systems require large amounts of data and computational resources for training,
and are slow at inference. This makes them impractical for real-time
interactive use. In this w... | 2022-08-18T08:31:15Z | Accepted at ISMIR 2022 | null | null | null | null | null | null | null | null | null |
2,208.09225 | FP8 Quantization: The Power of the Exponent | ['Andrey Kuzmin', 'Mart Van Baalen', 'Yuwei Ren', 'Markus Nagel', 'Jorn Peters', 'Tijmen Blankevoort'] | ['cs.LG'] | When quantizing neural networks for efficient inference, low-bit integers are
the go-to format for efficiency. However, low-bit floating point numbers have
an extra degree of freedom, assigning some bits to work on an exponential scale
instead. This paper in-depth investigates this benefit of the floating point
format ... | 2022-08-19T09:03:00Z | null | null | null | null | null | null | null | null | null | null |
2,208.10264 | Using Large Language Models to Simulate Multiple Humans and Replicate
Human Subject Studies | ['Gati Aher', 'Rosa I. Arriaga', 'Adam Tauman Kalai'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We introduce a new type of test, called a Turing Experiment (TE), for
evaluating to what extent a given language model, such as GPT models, can
simulate different aspects of human behavior. A TE can also reveal consistent
distortions in a language model's simulation of a specific human behavior.
Unlike the Turing Test,... | 2022-08-18T17:54:49Z | Accepted for oral presentation at International Conference on Machine
Learning (ICML) 2023 | null | null | null | null | null | null | null | null | null |
2,208.10442 | Image as a Foreign Language: BEiT Pretraining for All Vision and
Vision-Language Tasks | ['Wenhui Wang', 'Hangbo Bao', 'Li Dong', 'Johan Bjorck', 'Zhiliang Peng', 'Qiang Liu', 'Kriti Aggarwal', 'Owais Khan Mohammed', 'Saksham Singhal', 'Subhojit Som', 'Furu Wei'] | ['cs.CV', 'cs.CL'] | A big convergence of language, vision, and multimodal pretraining is
emerging. In this work, we introduce a general-purpose multimodal foundation
model BEiT-3, which achieves state-of-the-art transfer performance on both
vision and vision-language tasks. Specifically, we advance the big convergence
from three aspects: ... | 2022-08-22T16:55:04Z | 18 pages | null | null | null | null | null | null | null | null | null |
2,208.1158 | Optimal Brain Compression: A Framework for Accurate Post-Training
Quantization and Pruning | ['Elias Frantar', 'Sidak Pal Singh', 'Dan Alistarh'] | ['cs.LG'] | We consider the problem of model compression for deep neural networks (DNNs)
in the challenging one-shot/post-training setting, in which we are given an
accurate trained model, and must compress it without any retraining, based only
on a small amount of calibration input data. This problem has become popular in
view of... | 2022-08-24T14:33:35Z | Published at NeurIPS 2022 | null | null | Optimal Brain Compression: A Framework for Accurate Post-Training Quantization and Pruning | ['Elias Frantar', 'Dan Alistarh'] | 2,022 | Neural Information Processing Systems | 245 | 48 | ['Computer Science'] |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.