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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,205.01782 | Learning Multi-dimensional Edge Feature-based AU Relation Graph for
Facial Action Unit Recognition | ['Cheng Luo', 'Siyang Song', 'Weicheng Xie', 'Linlin Shen', 'Hatice Gunes'] | ['cs.CV', 'cs.AI'] | The activations of Facial Action Units (AUs) mutually influence one another.
While the relationship between a pair of AUs can be complex and unique,
existing approaches fail to specifically and explicitly represent such cues for
each pair of AUs in each facial display. This paper proposes an AU relationship
modelling a... | 2022-05-02T03:38:00Z | IJCAI 2022 conference (accepted) | null | 10.24963/ijcai.2022/173 | null | null | null | null | null | null | null |
2,205.01917 | CoCa: Contrastive Captioners are Image-Text Foundation Models | ['Jiahui Yu', 'Zirui Wang', 'Vijay Vasudevan', 'Legg Yeung', 'Mojtaba Seyedhosseini', 'Yonghui Wu'] | ['cs.CV', 'cs.LG', 'cs.MM'] | Exploring large-scale pretrained foundation models is of significant interest
in computer vision because these models can be quickly transferred to many
downstream tasks. This paper presents Contrastive Captioner (CoCa), a
minimalist design to pretrain an image-text encoder-decoder foundation model
jointly with contras... | 2022-05-04T07:01:14Z | Preprint | null | null | null | null | null | null | null | null | null |
2,205.01972 | Sequencer: Deep LSTM for Image Classification | ['Yuki Tatsunami', 'Masato Taki'] | ['cs.CV', 'cs.AI', 'cs.LG'] | In recent computer vision research, the advent of the Vision Transformer
(ViT) has rapidly revolutionized various architectural design efforts: ViT
achieved state-of-the-art image classification performance using self-attention
found in natural language processing, and MLP-Mixer achieved competitive
performance using s... | 2022-05-04T09:47:46Z | Accepted in NeurIPS 2022; camera ready edition | null | null | Sequencer: Deep LSTM for Image Classification | ['Yuki Tatsunami', 'M. Taki'] | 2,022 | Neural Information Processing Systems | 82 | 91 | ['Computer Science'] |
2,205.02289 | A Dataset for N-ary Relation Extraction of Drug Combinations | ['Aryeh Tiktinsky', 'Vijay Viswanathan', 'Danna Niezni', 'Dana Meron Azagury', 'Yosi Shamay', 'Hillel Taub-Tabib', 'Tom Hope', 'Yoav Goldberg'] | ['cs.CL', 'cs.IR'] | Combination therapies have become the standard of care for diseases such as
cancer, tuberculosis, malaria and HIV. However, the combinatorial set of
available multi-drug treatments creates a challenge in identifying effective
combination therapies available in a situation. To assist medical professionals
in identifying... | 2022-05-04T19:01:16Z | To appear in NAACL 2022 | null | null | null | null | null | null | null | null | null |
2,205.0234 | Knowledge Distillation of Russian Language Models with Reduction of
Vocabulary | ['Alina Kolesnikova', 'Yuri Kuratov', 'Vasily Konovalov', 'Mikhail Burtsev'] | ['cs.CL', 'cs.LG'] | Today, transformer language models serve as a core component for majority of
natural language processing tasks. Industrial application of such models
requires minimization of computation time and memory footprint. Knowledge
distillation is one of approaches to address this goal. Existing methods in
this field are mainl... | 2022-05-04T21:56:57Z | null | null | null | null | null | null | null | null | null | null |
2,205.02455 | COGMEN: COntextualized GNN based Multimodal Emotion recognitioN | ['Abhinav Joshi', 'Ashwani Bhat', 'Ayush Jain', 'Atin Vikram Singh', 'Ashutosh Modi'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Emotions are an inherent part of human interactions, and consequently, it is
imperative to develop AI systems that understand and recognize human emotions.
During a conversation involving various people, a person's emotions are
influenced by the other speaker's utterances and their own emotional state over
the utteranc... | 2022-05-05T05:54:24Z | 17 pages (9 main + 8 appendix). Accepted at NAACL 2022 | null | null | COGMEN: COntextualized GNN based Multimodal Emotion recognitioN | ['Abhinav Joshi', 'A. Bhat', 'Ayush Jain', 'Atinesh Singh', 'Ashutosh Modi'] | 2,022 | North American Chapter of the Association for Computational Linguistics | 80 | 62 | ['Computer Science'] |
2,205.02545 | Introducing the Welsh Text Summarisation Dataset and Baseline Systems | ['Ignatius Ezeani', 'Mahmoud El-Haj', 'Jonathan Morris', 'Dawn Knight'] | ['cs.CL', 'cs.IR'] | Welsh is an official language in Wales and is spoken by an estimated 884,300
people (29.2% of the population of Wales). Despite this status and estimated
increase in speaker numbers since the last (2011) census, Welsh remains a
minority language undergoing revitalization and promotion by Welsh Government
and relevant s... | 2022-05-05T10:12:45Z | null | null | null | null | null | null | null | null | null | null |
2,205.02728 | CATs are Fuzzy PETs: A Corpus and Analysis of Potentially Euphemistic
Terms | ['Martha Gavidia', 'Patrick Lee', 'Anna Feldman', 'Jing Peng'] | ['cs.CL'] | Euphemisms have not received much attention in natural language processing,
despite being an important element of polite and figurative language.
Euphemisms prove to be a difficult topic, not only because they are subject to
language change, but also because humans may not agree on what is a euphemism
and what is not. ... | 2022-05-05T16:01:39Z | Proceedings of LREC 2022 | null | null | CATs are Fuzzy PETs: A Corpus and Analysis of Potentially Euphemistic Terms | ['M. Gavidia', 'Patrick Lee', 'Anna Feldman', 'Jing Peng'] | 2,022 | International Conference on Language Resources and Evaluation | 24 | 41 | ['Computer Science'] |
2,205.03026 | Hearing voices at the National Library -- a speech corpus and acoustic
model for the Swedish language | ['Martin Malmsten', 'Chris Haffenden', 'Love Börjeson'] | ['cs.CL'] | This paper explains our work in developing new acoustic models for automated
speech recognition (ASR) at KBLab, the infrastructure for data-driven research
at the National Library of Sweden (KB). We evaluate different approaches for a
viable speech-to-text pipeline for audiovisual resources in Swedish, using the
wav2ve... | 2022-05-06T06:06:00Z | null | null | null | Hearing voices at the National Library - a speech corpus and acoustic model for the Swedish language | ['Martin Malmsten', 'Chris Haffenden', 'Love Borjeson'] | 2,022 | arXiv.org | 10 | 20 | ['Computer Science'] |
2,205.04733 | From Distillation to Hard Negative Sampling: Making Sparse Neural IR
Models More Effective | ['Thibault Formal', 'Carlos Lassance', 'Benjamin Piwowarski', 'Stéphane Clinchant'] | ['cs.IR', 'cs.CL'] | Neural retrievers based on dense representations combined with Approximate
Nearest Neighbors search have recently received a lot of attention, owing their
success to distillation and/or better sampling of examples for training --
while still relying on the same backbone architecture. In the meantime, sparse
representat... | 2022-05-10T08:08:43Z | Accepted at SIGIR22 as a short paper (this work is the extension of
SPLADE v2) | null | null | null | null | null | null | null | null | null |
2,205.05131 | UL2: Unifying Language Learning Paradigms | ['Yi Tay', 'Mostafa Dehghani', 'Vinh Q. Tran', 'Xavier Garcia', 'Jason Wei', 'Xuezhi Wang', 'Hyung Won Chung', 'Siamak Shakeri', 'Dara Bahri', 'Tal Schuster', 'Huaixiu Steven Zheng', 'Denny Zhou', 'Neil Houlsby', 'Donald Metzler'] | ['cs.CL'] | Existing pre-trained models are generally geared towards a particular class
of problems. To date, there seems to be still no consensus on what the right
architecture and pre-training setup should be. This paper presents a unified
framework for pre-training models that are universally effective across
datasets and setup... | 2022-05-10T19:32:20Z | Updated Q1 2023 with Flan-UL2 20B release! :) | null | null | UL2: Unifying Language Learning Paradigms | ['Yi Tay', 'Mostafa Dehghani', 'Vinh Q. Tran', 'Xavier García', 'Jason Wei', 'Xuezhi Wang', 'Hyung Won Chung', 'Dara Bahri', 'Tal Schuster', 'H. Zheng', 'Denny Zhou', 'N. Houlsby', 'Donald Metzler'] | 2,022 | International Conference on Learning Representations | 313 | 144 | ['Computer Science'] |
2,205.05789 | RITA: a Study on Scaling Up Generative Protein Sequence Models | ['Daniel Hesslow', 'Niccoló Zanichelli', 'Pascal Notin', 'Iacopo Poli', 'Debora Marks'] | ['q-bio.QM', 'cs.LG'] | In this work we introduce RITA: a suite of autoregressive generative models
for protein sequences, with up to 1.2 billion parameters, trained on over 280
million protein sequences belonging to the UniRef-100 database. Such generative
models hold the promise of greatly accelerating protein design. We conduct the
first s... | 2022-05-11T22:06:03Z | null | null | null | RITA: a Study on Scaling Up Generative Protein Sequence Models | ['Daniel Hesslow', 'Niccoló Zanichelli', 'Pascal Notin', 'Iacopo Poli', 'D. Marks'] | 2,022 | arXiv.org | 99 | 45 | ['Computer Science', 'Biology'] |
2,205.05862 | AdaVAE: Exploring Adaptive GPT-2s in Variational Auto-Encoders for
Language Modeling | ['Haoqin Tu', 'Zhongliang Yang', 'Jinshuai Yang', 'Yongfeng Huang'] | ['cs.CL'] | Variational Auto-Encoder (VAE) has become the de-facto learning paradigm in
achieving representation learning and generation for natural language at the
same time. Nevertheless, existing VAE-based language models either employ
elementary RNNs, which is not powerful to handle complex works in the
multi-task situation, o... | 2022-05-12T03:22:07Z | null | null | null | AdaVAE: Exploring Adaptive GPT-2s in Variational Auto-Encoders for Language Modeling | ['Haoqin Tu', 'Zhongliang Yang', 'Jinshuai Yang', 'Siyu Zhang', 'Yong Huang'] | 2,022 | arXiv.org | 12 | 44 | ['Computer Science'] |
2,205.06207 | CiteSum: Citation Text-guided Scientific Extreme Summarization and
Domain Adaptation with Limited Supervision | ['Yuning Mao', 'Ming Zhong', 'Jiawei Han'] | ['cs.CL'] | Scientific extreme summarization (TLDR) aims to form ultra-short summaries of
scientific papers. Previous efforts on curating scientific TLDR datasets failed
to scale up due to the heavy human annotation and domain expertise required. In
this paper, we propose a simple yet effective approach to automatically
extracting... | 2022-05-12T16:44:19Z | EMNLP 2022. TLDR: By pretraining on (automatically extracted)
citation sentences in scientific papers, we achieve SOTA on SciTLDR, XSum,
and Gigaword in zero-shot and (or) few-shot settings | null | null | CiteSum: Citation Text-guided Scientific Extreme Summarization and Domain Adaptation with Limited Supervision | ['Yuning Mao', 'Ming Zhong', 'Jiawei Han'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 15 | 49 | ['Computer Science'] |
2,205.0623 | Simple Open-Vocabulary Object Detection with Vision Transformers | ['Matthias Minderer', 'Alexey Gritsenko', 'Austin Stone', 'Maxim Neumann', 'Dirk Weissenborn', 'Alexey Dosovitskiy', 'Aravindh Mahendran', 'Anurag Arnab', 'Mostafa Dehghani', 'Zhuoran Shen', 'Xiao Wang', 'Xiaohua Zhai', 'Thomas Kipf', 'Neil Houlsby'] | ['cs.CV'] | Combining simple architectures with large-scale pre-training has led to
massive improvements in image classification. For object detection,
pre-training and scaling approaches are less well established, especially in
the long-tailed and open-vocabulary setting, where training data is relatively
scarce. In this paper, w... | 2022-05-12T17:20:36Z | ECCV 2022 camera-ready version | null | null | Simple Open-Vocabulary Object Detection with Vision Transformers | ['Matthias Minderer', 'A. Gritsenko', 'Austin Stone', 'Maxim Neumann', 'Dirk Weissenborn', 'Alexey Dosovitskiy', 'Aravindh Mahendran', 'Anurag Arnab', 'Mostafa Dehghani', 'Zhuoran Shen', 'Xiao Wang', 'Xiaohua Zhai', 'Thomas Kipf', 'N. Houlsby'] | 2,022 | arXiv.org | 314 | 49 | ['Computer Science'] |
2,205.06421 | Talking Face Generation with Multilingual TTS | ['Hyoung-Kyu Song', 'Sang Hoon Woo', 'Junhyeok Lee', 'Seungmin Yang', 'Hyunjae Cho', 'Youseong Lee', 'Dongho Choi', 'Kang-wook Kim'] | ['cs.CV', 'cs.AI'] | In this work, we propose a joint system combining a talking face generation
system with a text-to-speech system that can generate multilingual talking face
videos from only the text input. Our system can synthesize natural multilingual
speeches while maintaining the vocal identity of the speaker, as well as lip
movemen... | 2022-05-13T02:08:35Z | Accepted to CVPR Demo Track (2022) | null | null | null | null | null | null | null | null | null |
2,205.06457 | ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language
Generation | ['Long Phan', 'Hieu Tran', 'Hieu Nguyen', 'Trieu H. Trinh'] | ['cs.CL', 'cs.AI'] | We present ViT5, a pretrained Transformer-based encoder-decoder model for the
Vietnamese language. With T5-style self-supervised pretraining, ViT5 is trained
on a large corpus of high-quality and diverse Vietnamese texts. We benchmark
ViT5 on two downstream text generation tasks, Abstractive Text Summarization
and Name... | 2022-05-13T06:08:35Z | NAACL SRW 2022. arXiv admin note: text overlap with arXiv:2110.04257 | null | null | ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation | ['Long Phan', 'H. Tran', 'H. Nguyen', 'Trieu H. Trinh'] | 2,022 | North American Chapter of the Association for Computational Linguistics | 72 | 27 | ['Computer Science'] |
2,205.06885 | PathologyBERT -- Pre-trained Vs. A New Transformer Language Model for
Pathology Domain | ['Thiago Santos', 'Amara Tariq', 'Susmita Das', 'Kavyasree Vayalpati', 'Geoffrey H. Smith', 'Hari Trivedi', 'Imon Banerjee'] | ['cs.CL'] | Pathology text mining is a challenging task given the reporting variability
and constant new findings in cancer sub-type definitions. However, successful
text mining of a large pathology database can play a critical role to advance
'big data' cancer research like similarity-based treatment selection, case
identificatio... | 2022-05-13T20:42:07Z | submitted to "American Medical Informatics Association (AMIA)" 2022
Annual Symposium | null | null | PathologyBERT - Pre-trained Vs. A New Transformer Language Model for Pathology Domain | ['Thiago Santos', 'Amara Tariq', 'Susmita Das', 'Kavyasree Vayalpati', 'Geoffrey H. Smith', 'H. Trivedi', 'I. Banerjee'] | 2,022 | American Medical Informatics Association Annual Symposium | 18 | 21 | ['Computer Science', 'Medicine'] |
2,205.0739 | Learning Representations for New Sound Classes With Continual
Self-Supervised Learning | ['Zhepei Wang', 'Cem Subakan', 'Xilin Jiang', 'Junkai Wu', 'Efthymios Tzinis', 'Mirco Ravanelli', 'Paris Smaragdis'] | ['eess.AS', 'cs.LG', 'cs.SD', 'eess.SP'] | In this paper, we work on a sound recognition system that continually
incorporates new sound classes. Our main goal is to develop a framework where
the model can be updated without relying on labeled data. For this purpose, we
propose adopting representation learning, where an encoder is trained using
unlabeled data. T... | 2022-05-15T22:15:21Z | Accepted to IEEE Signal Processing Letters | null | 10.1109/LSP.2022.3229643 | null | null | null | null | null | null | null |
2,205.08794 | LogiGAN: Learning Logical Reasoning via Adversarial Pre-training | ['Xinyu Pi', 'Wanjun Zhong', 'Yan Gao', 'Nan Duan', 'Jian-Guang Lou'] | ['cs.CL'] | We present LogiGAN, an unsupervised adversarial pre-training framework for
improving logical reasoning abilities of language models. Upon automatic
identifying logical reasoning phenomena in massive text corpus via detection
heuristics, we train language models to predict the masked-out logical
statements. Inspired by ... | 2022-05-18T08:46:49Z | Accepted by NeurIPS 2022 | null | null | null | null | null | null | null | null | null |
2,205.08808 | Evaluation of Transfer Learning for Polish with a Text-to-Text Model | ['Aleksandra Chrabrowa', 'Łukasz Dragan', 'Karol Grzegorczyk', 'Dariusz Kajtoch', 'Mikołaj Koszowski', 'Robert Mroczkowski', 'Piotr Rybak'] | ['cs.CL', 'cs.LG'] | We introduce a new benchmark for assessing the quality of text-to-text models
for Polish. The benchmark consists of diverse tasks and datasets: KLEJ
benchmark adapted for text-to-text, en-pl translation, summarization, and
question answering. In particular, since summarization and question answering
lack benchmark data... | 2022-05-18T09:17:14Z | Accepted at LREC 2022 | null | null | null | null | null | null | null | null | null |
2,205.09651 | Wojood: Nested Arabic Named Entity Corpus and Recognition using BERT | ['Mustafa Jarrar', 'Mohammed Khalilia', 'Sana Ghanem'] | ['cs.CL', 'cs.AI', 'cs.IR', 'cs.LG'] | This paper presents Wojood, a corpus for Arabic nested Named Entity
Recognition (NER). Nested entities occur when one entity mention is embedded
inside another entity mention. Wojood consists of about 550K Modern Standard
Arabic (MSA) and dialect tokens that are manually annotated with 21 entity
types including person,... | 2022-05-19T16:06:49Z | null | In Proceedings of the International Conference on Language
Resources and Evaluation (LREC 2022), Marseille, France. 2022 | null | null | null | null | null | null | null | null |
2,205.09685 | ArabGlossBERT: Fine-Tuning BERT on Context-Gloss Pairs for WSD | ['Moustafa Al-Hajj', 'Mustafa Jarrar'] | ['cs.CL', 'cs.AI', 'cs.IR', 'cs.LG'] | Using pre-trained transformer models such as BERT has proven to be effective
in many NLP tasks. This paper presents our work to fine-tune BERT models for
Arabic Word Sense Disambiguation (WSD). We treated the WSD task as a
sentence-pair binary classification task. First, we constructed a dataset of
labeled Arabic conte... | 2022-05-19T16:47:18Z | null | In Proceedings of the International Conference on Recent Advances
in Natural Language Processing (RANLP 2021), PP 40--48. (2021) | 10.26615/978-954-452-072-4_005 | null | null | null | null | null | null | null |
2,205.09707 | PLAID: An Efficient Engine for Late Interaction Retrieval | ['Keshav Santhanam', 'Omar Khattab', 'Christopher Potts', 'Matei Zaharia'] | ['cs.IR', 'cs.CL'] | Pre-trained language models are increasingly important components across
multiple information retrieval (IR) paradigms. Late interaction, introduced
with the ColBERT model and recently refined in ColBERTv2, is a popular paradigm
that holds state-of-the-art status across many benchmarks. To dramatically
speed up the sea... | 2022-05-19T17:19:31Z | Preprint. Omar and Keshav contributed equally to this work | null | null | PLAID: An Efficient Engine for Late Interaction Retrieval | ['Keshav Santhanam', 'O. Khattab', 'Christopher Potts', 'M. Zaharia'] | 2,022 | International Conference on Information and Knowledge Management | 76 | 56 | ['Computer Science'] |
2,205.09853 | MCVD: Masked Conditional Video Diffusion for Prediction, Generation, and
Interpolation | ['Vikram Voleti', 'Alexia Jolicoeur-Martineau', 'Christopher Pal'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Video prediction is a challenging task. The quality of video frames from
current state-of-the-art (SOTA) generative models tends to be poor and
generalization beyond the training data is difficult. Furthermore, existing
prediction frameworks are typically not capable of simultaneously handling
other video-related tasks... | 2022-05-19T20:58:05Z | NeurIPS 2022 ; 10 pages, 4 figures, 7 tables | null | null | null | null | null | null | null | null | null |
2,205.09911 | Can Foundation Models Wrangle Your Data? | ['Avanika Narayan', 'Ines Chami', 'Laurel Orr', 'Simran Arora', 'Christopher Ré'] | ['cs.LG', 'cs.AI', 'cs.DB'] | Foundation Models (FMs) are models trained on large corpora of data that, at
very large scale, can generalize to new tasks without any task-specific
finetuning. As these models continue to grow in size, innovations continue to
push the boundaries of what these models can do on language and image tasks.
This paper aims ... | 2022-05-20T00:53:43Z | 12 pages, 5 figures; additional experiments, typo corrections,
modifications to Section 5 (Research Agenda) | null | null | Can Foundation Models Wrangle Your Data? | ['A. Narayan', 'Ines Chami', 'Laurel J. Orr', "Christopher R'e"] | 2,022 | Proceedings of the VLDB Endowment | 231 | 100 | ['Computer Science'] |
2,205.09921 | KERPLE: Kernelized Relative Positional Embedding for Length
Extrapolation | ['Ta-Chung Chi', 'Ting-Han Fan', 'Peter J. Ramadge', 'Alexander I. Rudnicky'] | ['cs.CL', 'cs.LG'] | Relative positional embeddings (RPE) have received considerable attention
since RPEs effectively model the relative distance among tokens and enable
length extrapolation. We propose KERPLE, a framework that generalizes relative
position embedding for extrapolation by kernelizing positional differences. We
achieve this ... | 2022-05-20T01:25:57Z | Accepted at the 36th Conference on Neural Information Processing
Systems (NeurIPS 2022). The first two authors contributed equally to this
work | null | null | null | null | null | null | null | null | null |
2,205.1045 | Temporally Precise Action Spotting in Soccer Videos Using Dense
Detection Anchors | ['João V. B. Soares', 'Avijit Shah', 'Topojoy Biswas'] | ['cs.CV'] | We present a model for temporally precise action spotting in videos, which
uses a dense set of detection anchors, predicting a detection confidence and
corresponding fine-grained temporal displacement for each anchor. We experiment
with two trunk architectures, both of which are able to incorporate large
temporal conte... | 2022-05-20T22:14:02Z | Accepted in International Conference on Image Processing (ICIP), 2022 | null | null | Temporally Precise Action Spotting in Soccer Videos Using Dense Detection Anchors | ['Joao V. B. Soares', 'Avijit Shah', 'Topojoy Biswas'] | 2,022 | International Conference on Information Photonics | 32 | 22 | ['Computer Science'] |
2,205.10687 | Revisiting Pre-trained Language Models and their Evaluation for Arabic
Natural Language Understanding | ['Abbas Ghaddar', 'Yimeng Wu', 'Sunyam Bagga', 'Ahmad Rashid', 'Khalil Bibi', 'Mehdi Rezagholizadeh', 'Chao Xing', 'Yasheng Wang', 'Duan Xinyu', 'Zhefeng Wang', 'Baoxing Huai', 'Xin Jiang', 'Qun Liu', 'Philippe Langlais'] | ['cs.CL'] | There is a growing body of work in recent years to develop pre-trained
language models (PLMs) for the Arabic language. This work concerns addressing
two major problems in existing Arabic PLMs which constraint progress of the
Arabic NLU and NLG fields.First, existing Arabic PLMs are not well-explored and
their pre-train... | 2022-05-21T22:38:19Z | null | null | null | null | null | null | null | null | null | null |
2,205.10726 | TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection
Tasks | ['Ruofan Hu', 'Dongyu Zhang', 'Dandan Tao', 'Thomas Hartvigsen', 'Hao Feng', 'Elke Rundensteiner'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Foodborne illness is a serious but preventable public health problem -- with
delays in detecting the associated outbreaks resulting in productivity loss,
expensive recalls, public safety hazards, and even loss of life. While social
media is a promising source for identifying unreported foodborne illnesses,
there is a d... | 2022-05-22T03:47:18Z | LREC 2022 | null | null | TWEET-FID: An Annotated Dataset for Multiple Foodborne Illness Detection Tasks | ['Ruofan Hu', 'Dongyu Zhang', 'Dandan Tao', 'Thomas Hartvigsen', 'Hao Feng', 'Elke A. Rundensteiner'] | 2,022 | International Conference on Language Resources and Evaluation | 7 | 21 | ['Computer Science'] |
2,205.11081 | BanglaNLG and BanglaT5: Benchmarks and Resources for Evaluating
Low-Resource Natural Language Generation in Bangla | ['Abhik Bhattacharjee', 'Tahmid Hasan', 'Wasi Uddin Ahmad', 'Rifat Shahriyar'] | ['cs.CL'] | This work presents BanglaNLG, a comprehensive benchmark for evaluating
natural language generation (NLG) models in Bangla, a widely spoken yet
low-resource language. We aggregate six challenging conditional text generation
tasks under the BanglaNLG benchmark, introducing a new dataset on dialogue
generation in the proc... | 2022-05-23T06:54:56Z | Findings of EACL 2023 (camera-ready) | null | null | null | null | null | null | null | null | null |
2,205.11111 | DistilCamemBERT: a distillation of the French model CamemBERT | ['Cyrile Delestre', 'Abibatou Amar'] | ['cs.CL', 'cs.LG'] | Modern Natural Language Processing (NLP) models based on Transformer
structures represent the state of the art in terms of performance on very
diverse tasks. However, these models are complex and represent several hundred
million parameters for the smallest of them. This may hinder their adoption at
the industrial leve... | 2022-05-23T08:04:58Z | in French language. CAp (Conf{\'e}rence sur l'Apprentissage
automatique), Jul 2022, Vannes, France | null | null | null | null | null | null | null | null | null |
2,205.11342 | The Diminishing Returns of Masked Language Models to Science | ['Zhi Hong', 'Aswathy Ajith', 'Gregory Pauloski', 'Eamon Duede', 'Kyle Chard', 'Ian Foster'] | ['cs.CL', 'cs.LG', 'I.2.7'] | Transformer-based masked language models such as BERT, trained on general
corpora, have shown impressive performance on downstream tasks. It has also
been demonstrated that the downstream task performance of such models can be
improved by pretraining larger models for longer on more data. In this work, we
empirically e... | 2022-05-23T14:35:08Z | 12 pages. 3 figures. 5 tables. Accepted to the Findings of ACL 2023 | null | null | null | null | null | null | null | null | null |
2,205.11487 | Photorealistic Text-to-Image Diffusion Models with Deep Language
Understanding | ['Chitwan Saharia', 'William Chan', 'Saurabh Saxena', 'Lala Li', 'Jay Whang', 'Emily Denton', 'Seyed Kamyar Seyed Ghasemipour', 'Burcu Karagol Ayan', 'S. Sara Mahdavi', 'Rapha Gontijo Lopes', 'Tim Salimans', 'Jonathan Ho', 'David J Fleet', 'Mohammad Norouzi'] | ['cs.CV', 'cs.LG'] | We present Imagen, a text-to-image diffusion model with an unprecedented
degree of photorealism and a deep level of language understanding. Imagen
builds on the power of large transformer language models in understanding text
and hinges on the strength of diffusion models in high-fidelity image
generation. Our key disc... | 2022-05-23T17:42:53Z | null | null | null | null | null | null | null | null | null | null |
2,205.11656 | FlexiBERT: Are Current Transformer Architectures too Homogeneous and
Rigid? | ['Shikhar Tuli', 'Bhishma Dedhia', 'Shreshth Tuli', 'Niraj K. Jha'] | ['cs.LG', 'cs.CL'] | The existence of a plethora of language models makes the problem of selecting
the best one for a custom task challenging. Most state-of-the-art methods
leverage transformer-based models (e.g., BERT) or their variants. Training such
models and exploring their hyperparameter space, however, is computationally
expensive. ... | 2022-05-23T22:44:34Z | Preprint. In review | null | null | null | null | null | null | null | null | null |
2,205.11916 | Large Language Models are Zero-Shot Reasoners | ['Takeshi Kojima', 'Shixiang Shane Gu', 'Machel Reid', 'Yutaka Matsuo', 'Yusuke Iwasawa'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Pretrained large language models (LLMs) are widely used in many sub-fields of
natural language processing (NLP) and generally known as excellent few-shot
learners with task-specific exemplars. Notably, chain of thought (CoT)
prompting, a recent technique for eliciting complex multi-step reasoning
through step-by-step a... | 2022-05-24T09:22:26Z | Accepted to NeurIPS2022. Our code is available at
https://github.com/kojima-takeshi188/zero_shot_cot | null | null | null | null | null | null | null | null | null |
2,205.11966 | Benchmark Data and Evaluation Framework for Intent Discovery Around
COVID-19 Vaccine Hesitancy | ['Shai Gretz', 'Assaf Toledo', 'Roni Friedman', 'Dan Lahav', 'Rose Weeks', 'Naor Bar-Zeev', 'João Sedoc', 'Pooja Sangha', 'Yoav Katz', 'Noam Slonim'] | ['cs.CL'] | The COVID-19 pandemic has made a huge global impact and cost millions of
lives. As COVID-19 vaccines were rolled out, they were quickly met with
widespread hesitancy. To address the concerns of hesitant people, we launched
VIRA, a public dialogue system aimed at addressing questions and concerns
surrounding the COVID-1... | 2022-05-24T10:58:11Z | null | null | null | Benchmark Data and Evaluation Framework for Intent Discovery Around COVID-19 Vaccine Hesitancy | ['Shai Gretz', 'Assaf Toledo', 'Roni Friedman', 'Dan Lahav', 'Rose Weeks', 'N. Bar-Zeev', 'João Sedoc', 'P. Sangha', 'Yoav Katz', 'N. Slonim'] | 2,022 | Findings | 8 | 27 | ['Computer Science'] |
2,205.12005 | mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal
Skip-connections | ['Chenliang Li', 'Haiyang Xu', 'Junfeng Tian', 'Wei Wang', 'Ming Yan', 'Bin Bi', 'Jiabo Ye', 'Hehong Chen', 'Guohai Xu', 'Zheng Cao', 'Ji Zhang', 'Songfang Huang', 'Fei Huang', 'Jingren Zhou', 'Luo Si'] | ['cs.CL', 'cs.CV'] | Large-scale pretrained foundation models have been an emerging paradigm for
building artificial intelligence (AI) systems, which can be quickly adapted to
a wide range of downstream tasks. This paper presents mPLUG, a new
vision-language foundation model for both cross-modal understanding and
generation. Most existing ... | 2022-05-24T11:52:06Z | null | EMNLP2022 | null | mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connections | ['Chenliang Li', 'Haiyang Xu', 'Junfeng Tian', 'Wei Wang', 'Ming Yan', 'Bin Bi', 'Jiabo Ye', 'Hehong Chen', 'Guohai Xu', 'Zheng-da Cao', 'Ji Zhang', 'Songfang Huang', 'Feiran Huang', 'Jingren Zhou', 'Luo Si'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 224 | 85 | ['Computer Science'] |
2,205.1201 | SFace: Sigmoid-Constrained Hypersphere Loss for Robust Face Recognition | ['Yaoyao Zhong', 'Weihong Deng', 'Jiani Hu', 'Dongyue Zhao', 'Xian Li', 'Dongchao Wen'] | ['cs.CV'] | Deep face recognition has achieved great success due to large-scale training
databases and rapidly developing loss functions. The existing algorithms devote
to realizing an ideal idea: minimizing the intra-class distance and maximizing
the inter-class distance. However, they may neglect that there are also low
quality ... | 2022-05-24T11:54:15Z | 12 pages, 9 figures | IEEE Transactions on Image Processing, 2021 | 10.1109/TIP.2020.3048632 | null | null | null | null | null | null | null |
2,205.12035 | RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked
Auto-Encoder | ['Shitao Xiao', 'Zheng Liu', 'Yingxia Shao', 'Zhao Cao'] | ['cs.CL'] | Despite pre-training's progress in many important NLP tasks, it remains to
explore effective pre-training strategies for dense retrieval. In this paper,
we propose RetroMAE, a new retrieval oriented pre-training paradigm based on
Masked Auto-Encoder (MAE). RetroMAE is highlighted by three critical designs.
1) A novel M... | 2022-05-24T12:43:04Z | Accepted to EMNLP 2022 | null | null | RetroMAE: Pre-Training Retrieval-oriented Language Models Via Masked Auto-Encoder | ['Shitao Xiao', 'Zheng Liu', 'Yingxia Shao', 'Zhao Cao'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 126 | 44 | ['Computer Science'] |
2,205.12335 | K-12BERT: BERT for K-12 education | ['Vasu Goel', 'Dhruv Sahnan', 'Venktesh V', 'Gaurav Sharma', 'Deep Dwivedi', 'Mukesh Mohania'] | ['cs.CL', 'cs.LG'] | Online education platforms are powered by various NLP pipelines, which
utilize models like BERT to aid in content curation. Since the inception of the
pre-trained language models like BERT, there have also been many efforts toward
adapting these pre-trained models to specific domains. However, there has not
been a mode... | 2022-05-24T19:35:41Z | 4 pages | null | null | null | null | null | null | null | null | null |
2,205.12393 | Fine-tuned Language Models are Continual Learners | ['Thomas Scialom', 'Tuhin Chakrabarty', 'Smaranda Muresan'] | ['cs.CL'] | Recent work on large language models relies on the intuition that most
natural language processing tasks can be described via natural language
instructions. Language models trained on these instructions show strong
zero-shot performance on several standard datasets. However, these models even
though impressive still pe... | 2022-05-24T22:53:34Z | null | null | null | Fine-tuned Language Models are Continual Learners | ['Thomas Scialom', 'Tuhin Chakrabarty', 'S. Muresan'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 123 | 48 | ['Computer Science'] |
2,205.12446 | FLEURS: Few-shot Learning Evaluation of Universal Representations of
Speech | ['Alexis Conneau', 'Min Ma', 'Simran Khanuja', 'Yu Zhang', 'Vera Axelrod', 'Siddharth Dalmia', 'Jason Riesa', 'Clara Rivera', 'Ankur Bapna'] | ['cs.CL', 'cs.LG', 'cs.SD', 'eess.AS'] | We introduce FLEURS, the Few-shot Learning Evaluation of Universal
Representations of Speech benchmark. FLEURS is an n-way parallel speech dataset
in 102 languages built on top of the machine translation FLoRes-101 benchmark,
with approximately 12 hours of speech supervision per language. FLEURS can be
used for a varie... | 2022-05-25T02:29:03Z | null | null | null | null | null | null | null | null | null | null |
2,205.12496 | Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard
Contexts | ['Harsh Trivedi', 'Niranjan Balasubramanian', 'Tushar Khot', 'Ashish Sabharwal'] | ['cs.CL', 'cs.AI'] | Question-answering datasets require a broad set of reasoning skills. We show
how to use question decompositions to teach language models these broad
reasoning skills in a robust fashion. Specifically, we use widely available
QDMR representations to programmatically create hard-to-cheat synthetic
contexts for real quest... | 2022-05-25T05:13:21Z | Accepted at EMNLP'22 | null | null | null | null | null | null | null | null | null |
2,205.12522 | Crossmodal-3600: A Massively Multilingual Multimodal Evaluation Dataset | ['Ashish V. Thapliyal', 'Jordi Pont-Tuset', 'Xi Chen', 'Radu Soricut'] | ['cs.CV', 'cs.CL'] | Research in massively multilingual image captioning has been severely
hampered by a lack of high-quality evaluation datasets. In this paper we
present the Crossmodal-3600 dataset (XM3600 in short), a geographically diverse
set of 3600 images annotated with human-generated reference captions in 36
languages. The images ... | 2022-05-25T06:30:19Z | EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,205.12644 | LingMess: Linguistically Informed Multi Expert Scorers for Coreference
Resolution | ['Shon Otmazgin', 'Arie Cattan', 'Yoav Goldberg'] | ['cs.CL'] | While coreference resolution typically involves various linguistic
challenges, recent models are based on a single pairwise scorer for all types
of pairs. We present LingMess, a new coreference model that defines different
categories of coreference cases and optimize multiple pairwise scorers, where
each scorer learns ... | 2022-05-25T10:39:46Z | EACL 2023 | null | null | null | null | null | null | null | null | null |
2,205.12647 | Overcoming Catastrophic Forgetting in Zero-Shot Cross-Lingual Generation | ['Tu Vu', 'Aditya Barua', 'Brian Lester', 'Daniel Cer', 'Mohit Iyyer', 'Noah Constant'] | ['cs.CL'] | In this paper, we explore the challenging problem of performing a generative
task in a target language when labeled data is only available in English, using
summarization as a case study. We assume a strict setting with no access to
parallel data or machine translation and find that common transfer learning
approaches ... | 2022-05-25T10:41:34Z | Accepted as a main conference paper at EMNLP 2022, 22 pages, 8
figures, 11 tables | null | null | null | null | null | null | null | null | null |
2,205.12673 | InstructDial: Improving Zero and Few-shot Generalization in Dialogue
through Instruction Tuning | ['Prakhar Gupta', 'Cathy Jiao', 'Yi-Ting Yeh', 'Shikib Mehri', 'Maxine Eskenazi', 'Jeffrey P. Bigham'] | ['cs.CL'] | Instruction tuning is an emergent paradigm in NLP wherein natural language
instructions are leveraged with language models to induce zero-shot performance
on unseen tasks. Instructions have been shown to enable good performance on
unseen tasks and datasets in both large and small language models. Dialogue is
an especia... | 2022-05-25T11:37:06Z | EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,205.12854 | Understanding Factual Errors in Summarization: Errors, Summarizers,
Datasets, Error Detectors | ['Liyan Tang', 'Tanya Goyal', 'Alexander R. Fabbri', 'Philippe Laban', 'Jiacheng Xu', 'Semih Yavuz', 'Wojciech Kryściński', 'Justin F. Rousseau', 'Greg Durrett'] | ['cs.CL', 'cs.AI'] | The propensity of abstractive summarization models to make factual errors has
been studied extensively, including design of metrics to detect factual errors
and annotation of errors in current systems' outputs. However, the
ever-evolving nature of summarization systems, metrics, and annotated
benchmarks makes factualit... | 2022-05-25T15:26:48Z | Accepted to ACL 2023 | null | null | null | null | null | null | null | null | null |
2,205.12934 | Amortized Inference for Causal Structure Learning | ['Lars Lorch', 'Scott Sussex', 'Jonas Rothfuss', 'Andreas Krause', 'Bernhard Schölkopf'] | ['cs.LG', 'stat.ML'] | Inferring causal structure poses a combinatorial search problem that
typically involves evaluating structures with a score or independence test. The
resulting search is costly, and designing suitable scores or tests that capture
prior knowledge is difficult. In this work, we propose to amortize causal
structure learnin... | 2022-05-25T17:37:08Z | NeurIPS 2022, fixed formatting of Figure 5 | null | null | null | null | null | null | null | null | null |
2,205.12952 | Pretraining is All You Need for Image-to-Image Translation | ['Tengfei Wang', 'Ting Zhang', 'Bo Zhang', 'Hao Ouyang', 'Dong Chen', 'Qifeng Chen', 'Fang Wen'] | ['cs.CV'] | We propose to use pretraining to boost general image-to-image translation.
Prior image-to-image translation methods usually need dedicated architectural
design and train individual translation models from scratch, struggling for
high-quality generation of complex scenes, especially when paired training data
are not abu... | 2022-05-25T17:58:26Z | Project Page: https://tengfei-wang.github.io/PITI/index.html | null | null | null | null | null | null | null | null | null |
2,205.12956 | Inception Transformer | ['Chenyang Si', 'Weihao Yu', 'Pan Zhou', 'Yichen Zhou', 'Xinchao Wang', 'Shuicheng Yan'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Recent studies show that Transformer has strong capability of building
long-range dependencies, yet is incompetent in capturing high frequencies that
predominantly convey local information. To tackle this issue, we present a
novel and general-purpose Inception Transformer, or iFormer for short, that
effectively learns ... | 2022-05-25T17:59:54Z | Code and models will be released at
https://github.com/sail-sg/iFormer | null | null | null | null | null | null | null | null | null |
2,205.13115 | Fine-grained Image Captioning with CLIP Reward | ['Jaemin Cho', 'Seunghyun Yoon', 'Ajinkya Kale', 'Franck Dernoncourt', 'Trung Bui', 'Mohit Bansal'] | ['cs.CL', 'cs.AI', 'cs.CV'] | Modern image captioning models are usually trained with text similarity
objectives. However, since reference captions in public datasets often describe
the most salient common objects, models trained with text similarity objectives
tend to ignore specific and detailed aspects of an image that distinguish it
from others... | 2022-05-26T02:46:09Z | NAACL Findings 2022 | null | null | Fine-grained Image Captioning with CLIP Reward | ['Jaemin Cho', 'Seunghyun Yoon', 'Ajinkya Kale', 'Franck Dernoncourt', 'Trung Bui', 'Mohit Bansal'] | 2,022 | NAACL-HLT | 79 | 41 | ['Computer Science'] |
2,205.13147 | Matryoshka Representation Learning | ['Aditya Kusupati', 'Gantavya Bhatt', 'Aniket Rege', 'Matthew Wallingford', 'Aditya Sinha', 'Vivek Ramanujan', 'William Howard-Snyder', 'Kaifeng Chen', 'Sham Kakade', 'Prateek Jain', 'Ali Farhadi'] | ['cs.LG', 'cs.CV'] | Learned representations are a central component in modern ML systems, serving
a multitude of downstream tasks. When training such representations, it is
often the case that computational and statistical constraints for each
downstream task are unknown. In this context rigid, fixed capacity
representations can be either... | 2022-05-26T04:33:56Z | Edited related work to include intrinsic dimensionality works | null | null | null | null | null | null | null | null | null |
2,205.13636 | Quark: Controllable Text Generation with Reinforced Unlearning | ['Ximing Lu', 'Sean Welleck', 'Jack Hessel', 'Liwei Jiang', 'Lianhui Qin', 'Peter West', 'Prithviraj Ammanabrolu', 'Yejin Choi'] | ['cs.CL', 'cs.LG'] | Large-scale language models often learn behaviors that are misaligned with
user expectations. Generated text may contain offensive or toxic language,
contain significant repetition, or be of a different sentiment than desired by
the user. We consider the task of unlearning these misalignments by fine-tuning
the languag... | 2022-05-26T21:11:51Z | null | NeurIPS 2022 (Oral Selection) | null | null | null | null | null | null | null | null |
2,205.1376 | Tranception: protein fitness prediction with autoregressive transformers
and inference-time retrieval | ['Pascal Notin', 'Mafalda Dias', 'Jonathan Frazer', 'Javier Marchena-Hurtado', 'Aidan Gomez', 'Debora S. Marks', 'Yarin Gal'] | ['cs.LG'] | The ability to accurately model the fitness landscape of protein sequences is
critical to a wide range of applications, from quantifying the effects of human
variants on disease likelihood, to predicting immune-escape mutations in
viruses and designing novel biotherapeutic proteins. Deep generative models of
protein se... | 2022-05-27T04:51:15Z | ICML 2022 | null | null | null | null | null | null | null | null | null |
2,205.141 | GIT: A Generative Image-to-text Transformer for Vision and Language | ['Jianfeng Wang', 'Zhengyuan Yang', 'Xiaowei Hu', 'Linjie Li', 'Kevin Lin', 'Zhe Gan', 'Zicheng Liu', 'Ce Liu', 'Lijuan Wang'] | ['cs.CV'] | In this paper, we design and train a Generative Image-to-text Transformer,
GIT, to unify vision-language tasks such as image/video captioning and question
answering. While generative models provide a consistent network architecture
between pre-training and fine-tuning, existing work typically contains complex
structure... | 2022-05-27T17:03:38Z | null | null | null | GIT: A Generative Image-to-text Transformer for Vision and Language | ['Jianfeng Wang', 'Zhengyuan Yang', 'Xiaowei Hu', 'Linjie Li', 'Kevin Lin', 'Zhe Gan', 'Zicheng Liu', 'Ce Liu', 'Lijuan Wang'] | 2,022 | Trans. Mach. Learn. Res. | 564 | 149 | ['Computer Science'] |
2,205.14135 | FlashAttention: Fast and Memory-Efficient Exact Attention with
IO-Awareness | ['Tri Dao', 'Daniel Y. Fu', 'Stefano Ermon', 'Atri Rudra', 'Christopher Ré'] | ['cs.LG'] | Transformers are slow and memory-hungry on long sequences, since the time and
memory complexity of self-attention are quadratic in sequence length.
Approximate attention methods have attempted to address this problem by trading
off model quality to reduce the compute complexity, but often do not achieve
wall-clock spee... | 2022-05-27T17:53:09Z | null | null | null | FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness | ['Tri Dao', 'Daniel Y. Fu', 'Stefano Ermon', 'A. Rudra', "Christopher R'e"] | 2,022 | Neural Information Processing Systems | 2,299 | 111 | ['Computer Science'] |
2,205.14304 | Multimodal Fake News Detection via CLIP-Guided Learning | ['Yangming Zhou', 'Qichao Ying', 'Zhenxing Qian', 'Sheng Li', 'Xinpeng Zhang'] | ['cs.CV'] | Multimodal fake news detection has attracted many research interests in
social forensics. Many existing approaches introduce tailored attention
mechanisms to guide the fusion of unimodal features. However, how the
similarity of these features is calculated and how it will affect the
decision-making process in FND are s... | 2022-05-28T02:43:18Z | Submitted to CIKM 2022 | null | null | null | null | null | null | null | null | null |
2,205.14375 | WaveMix: A Resource-efficient Neural Network for Image Analysis | ['Pranav Jeevan', 'Kavitha Viswanathan', 'Anandu A S', 'Amit Sethi'] | ['cs.CV', 'cs.AI', 'cs.LG', 'I.2.10; I.4.0; I.4.1; I.4.2; I.4.6; I.4.7; I.4.8; I.4.9; I.4.10;\n I.2.10; I.5.1; I.5.2; I.5.4; J.2'] | We propose a novel neural architecture for computer vision -- WaveMix -- that
is resource-efficient and yet generalizable and scalable. While using fewer
trainable parameters, GPU RAM, and computations, WaveMix networks achieve
comparable or better accuracy than the state-of-the-art convolutional neural
networks, visio... | 2022-05-28T09:08:50Z | 20 pages, 5 figures | null | null | WaveMix: A Resource-efficient Neural Network for Image Analysis | ['Pranav Jeevan', 'Kavitha Viswanathan', 'S. AnanduA', 'A. Sethi'] | 2,022 | null | 21 | 102 | ['Computer Science'] |
2,205.14728 | L3Cube-MahaNLP: Marathi Natural Language Processing Datasets, Models,
and Library | ['Raviraj Joshi'] | ['cs.CL', 'cs.LG'] | Despite being the third most popular language in India, the Marathi language
lacks useful NLP resources. Moreover, popular NLP libraries do not have support
for the Marathi language. With L3Cube-MahaNLP, we aim to build resources and a
library for Marathi natural language processing. We present datasets and
transformer... | 2022-05-29T17:51:00Z | null | null | null | null | null | null | null | null | null | null |
2,205.14756 | EfficientViT: Multi-Scale Linear Attention for High-Resolution Dense
Prediction | ['Han Cai', 'Junyan Li', 'Muyan Hu', 'Chuang Gan', 'Song Han'] | ['cs.CV'] | High-resolution dense prediction enables many appealing real-world
applications, such as computational photography, autonomous driving, etc.
However, the vast computational cost makes deploying state-of-the-art
high-resolution dense prediction models on hardware devices difficult. This
work presents EfficientViT, a new... | 2022-05-29T20:07:23Z | ICCV 2023; Update EfficientViT-SAM results | null | null | null | null | null | null | null | null | null |
2,205.14879 | Easter2.0: Improving convolutional models for handwritten text
recognition | ['Kartik Chaudhary', 'Raghav Bali'] | ['cs.CV', 'cs.AI'] | Convolutional Neural Networks (CNN) have shown promising results for the task
of Handwritten Text Recognition (HTR) but they still fall behind Recurrent
Neural Networks (RNNs)/Transformer based models in terms of performance. In
this paper, we propose a CNN based architecture that bridges this gap. Our
work, Easter2.0,... | 2022-05-30T06:33:15Z | 12 pages, 8 figures | null | null | Easter2.0: Improving convolutional models for handwritten text recognition | ['Kartik Chaudhary', 'Raghav Bali'] | 2,022 | arXiv.org | 10 | 30 | ['Computer Science'] |
2,205.14986 | GMML is All you Need | ['Sara Atito', 'Muhammad Awais', 'Josef Kittler'] | ['cs.CV'] | Vision transformers have generated significant interest in the computer
vision community because of their flexibility in exploiting contextual
information, whether it is sharply confined local, or long range global.
However, they are known to be data hungry. This has motivated the research in
self-supervised transforme... | 2022-05-30T10:36:55Z | null | null | null | null | null | null | null | null | null | null |
2,205.15575 | hmBERT: Historical Multilingual Language Models for Named Entity
Recognition | ['Stefan Schweter', 'Luisa März', 'Katharina Schmid', 'Erion Çano'] | ['cs.CL'] | Compared to standard Named Entity Recognition (NER), identifying persons,
locations, and organizations in historical texts constitutes a big challenge.
To obtain machine-readable corpora, the historical text is usually scanned and
Optical Character Recognition (OCR) needs to be performed. As a result, the
historical co... | 2022-05-31T07:30:33Z | Camera-ready HIPE-2022 Working Note Paper for CLEF 2022 (Conference
and Labs of the Evaluation Forum (CLEF 2022)) | null | null | hmBERT: Historical Multilingual Language Models for Named Entity Recognition | ['Stefan Schweter', 'Luisa März', 'Katharina Schmid', 'Erion cCano'] | 2,022 | Conference and Labs of the Evaluation Forum | 18 | 31 | ['Computer Science'] |
2,205.15868 | CogVideo: Large-scale Pretraining for Text-to-Video Generation via
Transformers | ['Wenyi Hong', 'Ming Ding', 'Wendi Zheng', 'Xinghan Liu', 'Jie Tang'] | ['cs.CV', 'cs.CL', 'cs.LG'] | Large-scale pretrained transformers have created milestones in text (GPT-3)
and text-to-image (DALL-E and CogView) generation. Its application to video
generation is still facing many challenges: The potential huge computation cost
makes the training from scratch unaffordable; The scarcity and weak relevance
of text-vi... | 2022-05-29T19:02:15Z | null | null | null | CogVideo: Large-scale Pretraining for Text-to-Video Generation via Transformers | ['Wenyi Hong', 'Ming Ding', 'Wendi Zheng', 'Xinghan Liu', 'Jie Tang'] | 2,022 | International Conference on Learning Representations | 633 | 45 | ['Computer Science'] |
2,205.15997 | TransFuser: Imitation with Transformer-Based Sensor Fusion for
Autonomous Driving | ['Kashyap Chitta', 'Aditya Prakash', 'Bernhard Jaeger', 'Zehao Yu', 'Katrin Renz', 'Andreas Geiger'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | How should we integrate representations from complementary sensors for
autonomous driving? Geometry-based fusion has shown promise for perception
(e.g. object detection, motion forecasting). However, in the context of
end-to-end driving, we find that imitation learning based on existing sensor
fusion methods underperfo... | 2022-05-31T17:57:19Z | arXiv admin note: text overlap with arXiv:2104.09224 | null | null | TransFuser: Imitation With Transformer-Based Sensor Fusion for Autonomous Driving | ['Kashyap Chitta', 'Aditya Prakash', 'Bernhard Jaeger', 'Zehao Yu', 'Katrin Renz', 'Andreas Geiger'] | 2,022 | IEEE Transactions on Pattern Analysis and Machine Intelligence | 335 | 134 | ['Computer Science', 'Medicine'] |
2,205.16007 | Improved Vector Quantized Diffusion Models | ['Zhicong Tang', 'Shuyang Gu', 'Jianmin Bao', 'Dong Chen', 'Fang Wen'] | ['cs.CV'] | Vector quantized diffusion (VQ-Diffusion) is a powerful generative model for
text-to-image synthesis, but sometimes can still generate low-quality samples
or weakly correlated images with text input. We find these issues are mainly
due to the flawed sampling strategy. In this paper, we propose two important
techniques ... | 2022-05-31T17:59:53Z | update reference | null | null | null | null | null | null | null | null | null |
2,206.00364 | Elucidating the Design Space of Diffusion-Based Generative Models | ['Tero Karras', 'Miika Aittala', 'Timo Aila', 'Samuli Laine'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.NE', 'stat.ML'] | We argue that the theory and practice of diffusion-based generative models
are currently unnecessarily convoluted and seek to remedy the situation by
presenting a design space that clearly separates the concrete design choices.
This lets us identify several changes to both the sampling and training
processes, as well a... | 2022-06-01T10:03:24Z | NeurIPS 2022 | null | null | null | null | null | null | null | null | null |
2,206.00888 | Squeezeformer: An Efficient Transformer for Automatic Speech Recognition | ['Sehoon Kim', 'Amir Gholami', 'Albert Shaw', 'Nicholas Lee', 'Karttikeya Mangalam', 'Jitendra Malik', 'Michael W. Mahoney', 'Kurt Keutzer'] | ['eess.AS', 'cs.CL', 'cs.SD'] | The recently proposed Conformer model has become the de facto backbone model
for various downstream speech tasks based on its hybrid attention-convolution
architecture that captures both local and global features. However, through a
series of systematic studies, we find that the Conformer architecture's design
choices ... | 2022-06-02T06:06:29Z | NeurIPS 2022 | null | null | null | null | null | null | null | null | null |
2,206.00927 | DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling
in Around 10 Steps | ['Cheng Lu', 'Yuhao Zhou', 'Fan Bao', 'Jianfei Chen', 'Chongxuan Li', 'Jun Zhu'] | ['cs.LG', 'stat.ML'] | Diffusion probabilistic models (DPMs) are emerging powerful generative
models. Despite their high-quality generation performance, DPMs still suffer
from their slow sampling as they generally need hundreds or thousands of
sequential function evaluations (steps) of large neural networks to draw a
sample. Sampling from DP... | 2022-06-02T08:43:16Z | Accepted in Neurips 2022 | null | null | null | null | null | null | null | null | null |
2,206.00929 | The ParlaSent-BCS dataset of sentiment-annotated parliamentary debates
from Bosnia-Herzegovina, Croatia, and Serbia | ['Michal Mochtak', 'Peter Rupnik', 'Nikola Ljubešič'] | ['cs.CL'] | Expression of sentiment in parliamentary debates is deemed to be
significantly different from that on social media or in product reviews. This
paper adds to an emerging body of research on parliamentary debates with a
dataset of sentences annotated for detection sentiment polarity in political
discourse. We sample the ... | 2022-06-02T08:45:14Z | 8 pages, submitted to JT-DH 2022 (Language Technologies and Digital
Humanities 2022) conference, number 4293 | null | null | null | null | null | null | null | null | null |
2,206.01062 | DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis | ['Birgit Pfitzmann', 'Christoph Auer', 'Michele Dolfi', 'Ahmed S Nassar', 'Peter W J Staar'] | ['cs.CV', 'cs.LG'] | Accurate document layout analysis is a key requirement for high-quality PDF
document conversion. With the recent availability of public, large ground-truth
datasets such as PubLayNet and DocBank, deep-learning models have proven to be
very effective at layout detection and segmentation. While these datasets are
of adeq... | 2022-06-02T14:25:12Z | 9 pages, 6 figures, 5 tables. Accepted paper at SIGKDD 2022
conference | null | 10.1145/3534678.3539043 | null | null | null | null | null | null | null |
2,206.01191 | EfficientFormer: Vision Transformers at MobileNet Speed | ['Yanyu Li', 'Geng Yuan', 'Yang Wen', 'Ju Hu', 'Georgios Evangelidis', 'Sergey Tulyakov', 'Yanzhi Wang', 'Jian Ren'] | ['cs.CV'] | Vision Transformers (ViT) have shown rapid progress in computer vision tasks,
achieving promising results on various benchmarks. However, due to the massive
number of parameters and model design, \textit{e.g.}, attention mechanism,
ViT-based models are generally times slower than lightweight convolutional
networks. The... | 2022-06-02T17:51:03Z | null | null | null | null | null | null | null | null | null | null |
2,206.01718 | A-OKVQA: A Benchmark for Visual Question Answering using World Knowledge | ['Dustin Schwenk', 'Apoorv Khandelwal', 'Christopher Clark', 'Kenneth Marino', 'Roozbeh Mottaghi'] | ['cs.CV', 'cs.CL'] | The Visual Question Answering (VQA) task aspires to provide a meaningful
testbed for the development of AI models that can jointly reason over visual
and natural language inputs. Despite a proliferation of VQA datasets, this goal
is hindered by a set of common limitations. These include a reliance on
relatively simplis... | 2022-06-03T17:52:27Z | null | null | null | null | null | null | null | null | null | null |
2,206.02066 | PIDNet: A Real-time Semantic Segmentation Network Inspired by PID
Controllers | ['Jiacong Xu', 'Zixiang Xiong', 'Shankar P. Bhattacharyya'] | ['cs.CV', 'cs.AI'] | Two-branch network architecture has shown its efficiency and effectiveness in
real-time semantic segmentation tasks. However, direct fusion of
high-resolution details and low-frequency context has the drawback of detailed
features being easily overwhelmed by surrounding contextual information. This
overshoot phenomenon... | 2022-06-04T23:16:52Z | 11 pages, 9 figures; This paper will be published by CVPR2023 soon,
please refer to the official version then | null | null | null | null | null | null | null | null | null |
2,206.02262 | Diffusion-GAN: Training GANs with Diffusion | ['Zhendong Wang', 'Huangjie Zheng', 'Pengcheng He', 'Weizhu Chen', 'Mingyuan Zhou'] | ['cs.LG', 'stat.ML'] | Generative adversarial networks (GANs) are challenging to train stably, and a
promising remedy of injecting instance noise into the discriminator input has
not been very effective in practice. In this paper, we propose Diffusion-GAN, a
novel GAN framework that leverages a forward diffusion chain to generate
Gaussian-mi... | 2022-06-05T20:45:01Z | Project homepage: https://github.com/Zhendong-Wang/Diffusion-GAN;
ICLR 2023 camera ready version | null | null | null | null | null | null | null | null | null |
2,206.02369 | Learning to Break the Loop: Analyzing and Mitigating Repetitions for
Neural Text Generation | ['Jin Xu', 'Xiaojiang Liu', 'Jianhao Yan', 'Deng Cai', 'Huayang Li', 'Jian Li'] | ['cs.CL'] | While large-scale neural language models, such as GPT2 and BART, have
achieved impressive results on various text generation tasks, they tend to get
stuck in undesirable sentence-level loops with maximization-based decoding
algorithms (\textit{e.g.}, greedy search). This phenomenon is counter-intuitive
since there are ... | 2022-06-06T05:51:12Z | Accepted by NeurIPS 2022. Code is released at
https://github.com/Jxu-Thu/DITTO | null | null | null | null | null | null | null | null | null |
2,206.0268 | Separable Self-attention for Mobile Vision Transformers | ['Sachin Mehta', 'Mohammad Rastegari'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Mobile vision transformers (MobileViT) can achieve state-of-the-art
performance across several mobile vision tasks, including classification and
detection. Though these models have fewer parameters, they have high latency as
compared to convolutional neural network-based models. The main efficiency
bottleneck in Mobile... | 2022-06-06T15:31:35Z | Technical report | null | null | null | null | null | null | null | null | null |
2,206.02873 | No Parameter Left Behind: How Distillation and Model Size Affect
Zero-Shot Retrieval | ['Guilherme Moraes Rosa', 'Luiz Bonifacio', 'Vitor Jeronymo', 'Hugo Abonizio', 'Marzieh Fadaee', 'Roberto Lotufo', 'Rodrigo Nogueira'] | ['cs.IR', 'cs.CL', 'cs.PF'] | Recent work has shown that small distilled language models are strong
competitors to models that are orders of magnitude larger and slower in a wide
range of information retrieval tasks. This has made distilled and dense models,
due to latency constraints, the go-to choice for deployment in real-world
retrieval applica... | 2022-06-06T19:56:14Z | null | null | null | null | null | null | null | null | null | null |
2,206.03001 | PP-OCRv3: More Attempts for the Improvement of Ultra Lightweight OCR
System | ['Chenxia Li', 'Weiwei Liu', 'Ruoyu Guo', 'Xiaoting Yin', 'Kaitao Jiang', 'Yongkun Du', 'Yuning Du', 'Lingfeng Zhu', 'Baohua Lai', 'Xiaoguang Hu', 'Dianhai Yu', 'Yanjun Ma'] | ['cs.CV'] | Optical character recognition (OCR) technology has been widely used in
various scenes, as shown in Figure 1. Designing a practical OCR system is still
a meaningful but challenging task. In previous work, considering the efficiency
and accuracy, we proposed a practical ultra lightweight OCR system (PP-OCR),
and an optim... | 2022-06-07T04:33:50Z | arXiv admin note: text overlap with arXiv:2109.03144 | null | null | null | null | null | null | null | null | null |
2,206.03065 | Universal Speech Enhancement with Score-based Diffusion | ['Joan Serrà', 'Santiago Pascual', 'Jordi Pons', 'R. Oguz Araz', 'Davide Scaini'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Removing background noise from speech audio has been the subject of
considerable effort, especially in recent years due to the rise of virtual
communication and amateur recordings. Yet background noise is not the only
unpleasant disturbance that can prevent intelligibility: reverb, clipping,
codec artifacts, problemati... | 2022-06-07T07:32:32Z | 24 pages, 6 figures; includes appendix; examples in
https://serrjoa.github.io/projects/universe/ | null | null | null | null | null | null | null | null | null |
2,206.03382 | Tutel: Adaptive Mixture-of-Experts at Scale | ['Changho Hwang', 'Wei Cui', 'Yifan Xiong', 'Ziyue Yang', 'Ze Liu', 'Han Hu', 'Zilong Wang', 'Rafael Salas', 'Jithin Jose', 'Prabhat Ram', 'Joe Chau', 'Peng Cheng', 'Fan Yang', 'Mao Yang', 'Yongqiang Xiong'] | ['cs.DC', 'cs.CL', 'cs.CV'] | Sparsely-gated mixture-of-experts (MoE) has been widely adopted to scale deep
learning models to trillion-plus parameters with fixed computational cost. The
algorithmic performance of MoE relies on its token routing mechanism that
forwards each input token to the right sub-models or experts. While token
routing dynamic... | 2022-06-07T15:20:20Z | null | null | null | null | null | null | null | null | null | null |
2,206.03933 | TURJUMAN: A Public Toolkit for Neural Arabic Machine Translation | ['El Moatez Billah Nagoudi', 'AbdelRahim Elmadany', 'Muhammad Abdul-Mageed'] | ['cs.CL', 'cs.AI', 'cs.LG'] | We present TURJUMAN, a neural toolkit for translating from 20 languages into
Modern Standard Arabic (MSA). TURJUMAN exploits the recently-introduced
text-to-text Transformer AraT5 model, endowing it with a powerful ability to
decode into Arabic. The toolkit offers the possibility of employing a number of
diverse decodi... | 2022-05-27T18:05:50Z | All authors contributed equally | Proceedings of the 5th Workshop on Open-Source Arabic Corpora and
Processing Tools (OSACT5), 2022 | null | null | null | null | null | null | null | null |
2,206.0404 | MobileOne: An Improved One millisecond Mobile Backbone | ['Pavan Kumar Anasosalu Vasu', 'James Gabriel', 'Jeff Zhu', 'Oncel Tuzel', 'Anurag Ranjan'] | ['cs.CV'] | Efficient neural network backbones for mobile devices are often optimized for
metrics such as FLOPs or parameter count. However, these metrics may not
correlate well with latency of the network when deployed on a mobile device.
Therefore, we perform extensive analysis of different metrics by deploying
several mobile-fr... | 2022-06-08T17:55:11Z | Accepted at CVPR 2023 | null | null | null | null | null | null | null | null | null |
2,206.04514 | SAR Despeckling using a Denoising Diffusion Probabilistic Model | ['Malsha V. Perera', 'Nithin Gopalakrishnan Nair', 'Wele Gedara Chaminda Bandara', 'Vishal M. Patel'] | ['eess.IV', 'cs.CV'] | Speckle is a multiplicative noise which affects all coherent imaging
modalities including Synthetic Aperture Radar (SAR) images. The presence of
speckle degrades the image quality and adversely affects the performance of SAR
image understanding applications such as automatic target recognition and
change detection. Thu... | 2022-06-09T14:00:26Z | Our code is available at https://github.com/malshaV/SAR_DDPM | null | 10.1109/LGRS.2023.3270799 | null | null | null | null | null | null | null |
2,206.04615 | Beyond the Imitation Game: Quantifying and extrapolating the
capabilities of language models | ['Aarohi Srivastava', 'Abhinav Rastogi', 'Abhishek Rao', 'Abu Awal Md Shoeb', 'Abubakar Abid', 'Adam Fisch', 'Adam R. Brown', 'Adam Santoro', 'Aditya Gupta', 'Adrià Garriga-Alonso', 'Agnieszka Kluska', 'Aitor Lewkowycz', 'Akshat Agarwal', 'Alethea Power', 'Alex Ray', 'Alex Warstadt', 'Alexander W. Kocurek', 'Ali Safaya... | ['cs.CL', 'cs.AI', 'cs.CY', 'cs.LG', 'stat.ML'] | Language models demonstrate both quantitative improvement and new qualitative
capabilities with increasing scale. Despite their potentially transformative
impact, these new capabilities are as yet poorly characterized. In order to
inform future research, prepare for disruptive new model capabilities, and
ameliorate soc... | 2022-06-09T17:05:34Z | 27 pages, 17 figures + references and appendices, repo:
https://github.com/google/BIG-bench | Transactions on Machine Learning Research, May/2022,
https://openreview.net/forum?id=uyTL5Bvosj | null | null | null | null | null | null | null | null |
2,206.04658 | BigVGAN: A Universal Neural Vocoder with Large-Scale Training | ['Sang-gil Lee', 'Wei Ping', 'Boris Ginsburg', 'Bryan Catanzaro', 'Sungroh Yoon'] | ['cs.SD', 'cs.CL', 'cs.LG', 'eess.AS'] | Despite recent progress in generative adversarial network (GAN)-based
vocoders, where the model generates raw waveform conditioned on acoustic
features, it is challenging to synthesize high-fidelity audio for numerous
speakers across various recording environments. In this work, we present
BigVGAN, a universal vocoder ... | 2022-06-09T17:56:10Z | To appear at ICLR 2023. Listen to audio samples from BigVGAN at:
https://bigvgan-demo.github.io/ | null | null | null | null | null | null | null | null | null |
2,206.04664 | On Data Scaling in Masked Image Modeling | ['Zhenda Xie', 'Zheng Zhang', 'Yue Cao', 'Yutong Lin', 'Yixuan Wei', 'Qi Dai', 'Han Hu'] | ['cs.CV'] | An important goal of self-supervised learning is to enable model pre-training
to benefit from almost unlimited data. However, one method that has recently
become popular, namely masked image modeling (MIM), is suspected to be unable
to benefit from larger data. In this work, we break this misconception through
extensiv... | 2022-06-09T17:58:24Z | null | null | null | null | null | null | null | null | null | null |
2,206.04674 | Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional
MoEs | ['Jinguo Zhu', 'Xizhou Zhu', 'Wenhai Wang', 'Xiaohua Wang', 'Hongsheng Li', 'Xiaogang Wang', 'Jifeng Dai'] | ['cs.CV'] | To build an artificial neural network like the biological intelligence
system, recent works have unified numerous tasks into a generalist model, which
can process various tasks with shared parameters and do not have any
task-specific modules. While generalist models achieve promising results on
various benchmarks, they... | 2022-06-09T17:59:59Z | Code shall be released at
https://github.com/fundamentalvision/Uni-Perceiver | null | null | Uni-Perceiver-MoE: Learning Sparse Generalist Models with Conditional MoEs | ['Jinguo Zhu', 'Xizhou Zhu', 'Wenhai Wang', 'Xiaohua Wang', 'Hongsheng Li', 'Xiaogang Wang', 'Jifeng Dai'] | 2,022 | Neural Information Processing Systems | 70 | 102 | ['Computer Science'] |
2,206.05408 | Multi-instrument Music Synthesis with Spectrogram Diffusion | ['Curtis Hawthorne', 'Ian Simon', 'Adam Roberts', 'Neil Zeghidour', 'Josh Gardner', 'Ethan Manilow', 'Jesse Engel'] | ['cs.SD', 'cs.LG', 'eess.AS'] | An ideal music synthesizer should be both interactive and expressive,
generating high-fidelity audio in realtime for arbitrary combinations of
instruments and notes. Recent neural synthesizers have exhibited a tradeoff
between domain-specific models that offer detailed control of only specific
instruments, or raw wavef... | 2022-06-11T03:26:15Z | null | null | null | null | null | null | null | null | null | null |
2,206.06588 | Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving
Product Search | ['Chandan K. Reddy', 'Lluís Màrquez', 'Fran Valero', 'Nikhil Rao', 'Hugo Zaragoza', 'Sambaran Bandyopadhyay', 'Arnab Biswas', 'Anlu Xing', 'Karthik Subbian'] | ['cs.IR', 'cs.LG'] | Improving the quality of search results can significantly enhance users
experience and engagement with search engines. In spite of several recent
advancements in the fields of machine learning and data mining, correctly
classifying items for a particular user search query has been a long-standing
challenge, which still... | 2022-06-14T04:25:26Z | null | null | null | null | null | null | null | null | null | null |
2,206.07038 | AnimeSR: Learning Real-World Super-Resolution Models for Animation
Videos | ['Yanze Wu', 'Xintao Wang', 'Gen Li', 'Ying Shan'] | ['cs.CV', 'cs.AI'] | This paper studies the problem of real-world video super-resolution (VSR) for
animation videos, and reveals three key improvements for practical animation
VSR. First, recent real-world super-resolution approaches typically rely on
degradation simulation using basic operators without any learning capability,
such as blu... | 2022-06-14T17:57:11Z | NeurIPS 2022. Codes and models are available at
https://github.com/TencentARC/AnimeSR | null | null | AnimeSR: Learning Real-World Super-Resolution Models for Animation Videos | ['Yanze Wu', 'Xintao Wang', 'Gengyan Li', 'Ying Shan'] | 2,022 | Neural Information Processing Systems | 23 | 57 | ['Computer Science'] |
2,206.07293 | FRCRN: Boosting Feature Representation using Frequency Recurrence for
Monaural Speech Enhancement | ['Shengkui Zhao', 'Bin Ma', 'Karn N. Watcharasupat', 'Woon-Seng Gan'] | ['cs.SD', 'eess.AS'] | Convolutional recurrent networks (CRN) integrating a convolutional
encoder-decoder (CED) structure and a recurrent structure have achieved
promising performance for monaural speech enhancement. However, feature
representation across frequency context is highly constrained due to limited
receptive fields in the convolut... | 2022-06-15T04:29:10Z | The paper has been accepted by ICASSP 2022. 5 pages, 2 figures, 5
tables | null | null | FRCRN: Boosting Feature Representation Using Frequency Recurrence for Monaural Speech Enhancement | ['Shengkui Zhao', 'Bin Ma', 'Karn N. Watcharasupat', 'W. Gan'] | 2,022 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 88 | 29 | ['Computer Science', 'Engineering'] |
2,206.07557 | How to Reduce Change Detection to Semantic Segmentation | ['Guo-Hua Wang', 'Bin-Bin Gao', 'Chengjie Wang'] | ['cs.CV', 'cs.AI'] | Change detection (CD) aims to identify changes that occur in an image pair
taken different times. Prior methods devise specific networks from scratch to
predict change masks in pixel-level, and struggle with general segmentation
problems. In this paper, we propose a new paradigm that reduces CD to semantic
segmentation... | 2022-06-15T14:16:30Z | Accepted by Pattern Recognition. Code is at
https://github.com/DoctorKey/C-3PO | null | null | How to Reduce Change Detection to Semantic Segmentation | ['G. Wang', 'Bin-Bin Gao', 'Chengjie Wang'] | 2,022 | Pattern Recognition | 26 | 40 | ['Computer Science'] |
2,206.07627 | Exploring Capabilities of Monolingual Audio Transformers using Large
Datasets in Automatic Speech Recognition of Czech | ['Jan Lehečka', 'Jan Švec', 'Aleš Pražák', 'Josef V. Psutka'] | ['cs.CL', 'cs.SD', 'eess.AS'] | In this paper, we present our progress in pretraining Czech monolingual audio
transformers from a large dataset containing more than 80 thousand hours of
unlabeled speech, and subsequently fine-tuning the model on automatic speech
recognition tasks using a combination of in-domain data and almost 6 thousand
hours of ou... | 2022-06-15T16:14:37Z | to be published in Proceedings of INTERSPEECH 2022 | Interspeech 2022, 1831-1835 | 10.21437/Interspeech.2022-10439 | null | null | null | null | null | null | null |
2,206.07666 | Transformer-based Automatic Speech Recognition of Formal and Colloquial
Czech in MALACH Project | ['Jan Lehečka', 'Josef V. Psutka', 'Josef Psutka'] | ['cs.CL'] | Czech is a very specific language due to its large differences between the
formal and the colloquial form of speech. While the formal (written) form is
used mainly in official documents, literature, and public speeches, the
colloquial (spoken) form is used widely among people in casual speeches. This
gap introduces ser... | 2022-06-15T17:01:20Z | to be published in Proceedings of TSD 2022 | TSD 2022. Lecture Notes in Computer Science, vol 13502. Springer,
Cham | 10.1007/978-3-031-16270-1_25 | null | null | null | null | null | null | null |
2,206.07697 | MACE: Higher Order Equivariant Message Passing Neural Networks for Fast
and Accurate Force Fields | ['Ilyes Batatia', 'Dávid Péter Kovács', 'Gregor N. C. Simm', 'Christoph Ortner', 'Gábor Csányi'] | ['stat.ML', 'cond-mat.mtrl-sci', 'cs.LG', 'physics.chem-ph'] | Creating fast and accurate force fields is a long-standing challenge in
computational chemistry and materials science. Recently, several equivariant
message passing neural networks (MPNNs) have been shown to outperform models
built using other approaches in terms of accuracy. However, most MPNNs suffer
from high comput... | 2022-06-15T17:46:05Z | Advances in Neural Information Processing Systems, 2022 | null | null | null | null | null | null | null | null | null |
2,206.07846 | Action Spotting using Dense Detection Anchors Revisited: Submission to
the SoccerNet Challenge 2022 | ['João V. B. Soares', 'Avijit Shah'] | ['cs.CV'] | This brief technical report describes our submission to the Action Spotting
SoccerNet Challenge 2022. The challenge was part of the CVPR 2022 ActivityNet
Workshop. Our submission was based on a recently proposed method which focuses
on increasing temporal precision via a densely sampled set of detection
anchors. Due to... | 2022-06-15T23:22:36Z | v2: a few more experiments, more detailed method description | null | null | null | null | null | null | null | null | null |
2,206.07959 | Simple-BEV: What Really Matters for Multi-Sensor BEV Perception? | ['Adam W. Harley', 'Zhaoyuan Fang', 'Jie Li', 'Rares Ambrus', 'Katerina Fragkiadaki'] | ['cs.CV'] | Building 3D perception systems for autonomous vehicles that do not rely on
high-density LiDAR is a critical research problem because of the expense of
LiDAR systems compared to cameras and other sensors. Recent research has
developed a variety of camera-only methods, where features are differentiably
"lifted" from the ... | 2022-06-16T06:57:32Z | null | null | null | Simple-BEV: What Really Matters for Multi-Sensor BEV Perception? | ['Adam W. Harley', 'Zhaoyuan Fang', 'Jie Li', 'Rares Ambrus', 'Katerina Fragkiadaki'] | 2,022 | IEEE International Conference on Robotics and Automation | 131 | 47 | ['Computer Science'] |
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