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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,201.12507 | AutoDistil: Few-shot Task-agnostic Neural Architecture Search for
Distilling Large Language Models | ['Dongkuan Xu', 'Subhabrata Mukherjee', 'Xiaodong Liu', 'Debadeepta Dey', 'Wenhui Wang', 'Xiang Zhang', 'Ahmed Hassan Awadallah', 'Jianfeng Gao'] | ['cs.CL'] | Knowledge distillation (KD) methods compress large models into smaller
students with manually-designed student architectures given pre-specified
computational cost. This requires several trials to find a viable student, and
further repeating the process for each student or computational budget change.
We use Neural Arc... | 2022-01-29T06:13:04Z | 15 pages, 4 figures, 10 tables | null | null | AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models | ['Dongkuan Xu', 'Subhabrata Mukherjee', 'Xiaodong Liu', 'Debadeepta Dey', 'Wenhui Wang', 'Xiang Zhang', 'A. Awadallah', 'Jianfeng Gao'] | 2,022 | arXiv.org | 4 | 49 | ['Computer Science'] |
2,201.13125 | Corpus for Automatic Structuring of Legal Documents | ['Prathamesh Kalamkar', 'Aman Tiwari', 'Astha Agarwal', 'Saurabh Karn', 'Smita Gupta', 'Vivek Raghavan', 'Ashutosh Modi'] | ['cs.CL', 'cs.AI', 'cs.LG'] | In populous countries, pending legal cases have been growing exponentially.
There is a need for developing techniques for processing and organizing legal
documents. In this paper, we introduce a new corpus for structuring legal
documents. In particular, we introduce a corpus of legal judgment documents in
English that ... | 2022-01-31T11:12:44Z | Accepted at LREC 2022, 10 Pages (8 page main paper + 2 page
references) | null | null | null | null | null | null | null | null | null |
2,201.13271 | StRegA: Unsupervised Anomaly Detection in Brain MRIs using a Compact
Context-encoding Variational Autoencoder | ['Soumick Chatterjee', 'Alessandro Sciarra', 'Max Dünnwald', 'Pavan Tummala', 'Shubham Kumar Agrawal', 'Aishwarya Jauhari', 'Aman Kalra', 'Steffen Oeltze-Jafra', 'Oliver Speck', 'Andreas Nürnberger'] | ['eess.IV', 'cs.CV', 'cs.LG', 'physics.med-ph'] | Expert interpretation of anatomical images of the human brain is the central
part of neuro-radiology. Several machine learning-based techniques have been
proposed to assist in the analysis process. However, the ML models typically
need to be trained to perform a specific task, e.g., brain tumour segmentation
or classif... | 2022-01-31T14:27:35Z | null | Computers in Biology and Medicine, 106093 (2022) | 10.1016/j.compbiomed.2022.106093 | StRegA: Unsupervised Anomaly Detection in Brain MRIs using a Compact Context-encoding Variational Autoencoder | ['S. Chatterjee', 'A. Sciarra', 'M. Dünnwald', 'Pavan Tummala', 'Shubham Kumar Agrawal', 'Aishwarya Jauhari', 'Aman Kalra', 'S. Oeltze-Jafra', 'O. Speck', 'A. Nürnberger'] | 2,022 | Comput. Biol. Medicine | 16 | 48 | ['Engineering', 'Computer Science', 'Physics', 'Medicine'] |
2,202.00273 | StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets | ['Axel Sauer', 'Katja Schwarz', 'Andreas Geiger'] | ['cs.LG', 'cs.CV'] | Computer graphics has experienced a recent surge of data-centric approaches
for photorealistic and controllable content creation. StyleGAN in particular
sets new standards for generative modeling regarding image quality and
controllability. However, StyleGAN's performance severely degrades on large
unstructured dataset... | 2022-02-01T08:22:34Z | To appear in SIGGRAPH 2022. Project Page:
https://sites.google.com/view/stylegan-xl/ | null | null | StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasets | ['Axel Sauer', 'Katja Schwarz', 'Andreas Geiger'] | 2,022 | International Conference on Computer Graphics and Interactive Techniques | 514 | 76 | ['Computer Science'] |
2,202.00396 | Negativity Spreads Faster: A Large-Scale Multilingual Twitter Analysis
on the Role of Sentiment in Political Communication | ['Dimosthenis Antypas', 'Alun Preece', 'Jose Camacho-Collados'] | ['cs.CL', 'cs.LG', 'I.2.7'] | Social media has become extremely influential when it comes to policy making
in modern societies, especially in the western world, where platforms such as
Twitter allow users to follow politicians, thus making citizens more involved
in political discussion. In the same vein, politicians use Twitter to express
their opi... | 2022-02-01T13:25:19Z | Accepted at "Online Social Networks and Media, Volume 33"; for code
and data used see https://github.com/cardiffnlp/politics-and-virality-twitter | Online Social Networks and Media, 2023, Volume 33 Online Social
Networks and Media | 10.1016/j.osnem.2023.100242 | null | null | null | null | null | null | null |
2,202.00436 | ROCK: Causal Inference Principles for Reasoning about Commonsense
Causality | ['Jiayao Zhang', 'Hongming Zhang', 'Weijie J. Su', 'Dan Roth'] | ['cs.CL', 'cs.AI', 'cs.LG', 'stat.AP'] | Commonsense causality reasoning (CCR) aims at identifying plausible causes
and effects in natural language descriptions that are deemed reasonable by an
average person. Although being of great academic and practical interest, this
problem is still shadowed by the lack of a well-posed theoretical framework;
existing wor... | 2022-01-31T06:12:39Z | To appear, ICML 2022 | null | null | null | null | null | null | null | null | null |
2,202.00512 | Progressive Distillation for Fast Sampling of Diffusion Models | ['Tim Salimans', 'Jonathan Ho'] | ['cs.LG', 'cs.AI', 'stat.ML'] | Diffusion models have recently shown great promise for generative modeling,
outperforming GANs on perceptual quality and autoregressive models at density
estimation. A remaining downside is their slow sampling time: generating high
quality samples takes many hundreds or thousands of model evaluations. Here we
make two ... | 2022-02-01T16:07:25Z | Published as a conference paper at ICLR 2022 | null | null | null | null | null | null | null | null | null |
2,202.00874 | HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound
Classification and Detection | ['Ke Chen', 'Xingjian Du', 'Bilei Zhu', 'Zejun Ma', 'Taylor Berg-Kirkpatrick', 'Shlomo Dubnov'] | ['cs.SD', 'cs.AI', 'cs.IR', 'cs.LG', 'eess.AS'] | Audio classification is an important task of mapping audio samples into their
corresponding labels. Recently, the transformer model with self-attention
mechanisms has been adopted in this field. However, existing audio transformers
require large GPU memories and long training time, meanwhile relying on
pretrained visio... | 2022-02-02T04:49:14Z | Preprint version for ICASSP 2022, Singapore | null | null | null | null | null | null | null | null | null |
2,202.01159 | L3Cube-MahaCorpus and MahaBERT: Marathi Monolingual Corpus, Marathi BERT
Language Models, and Resources | ['Raviraj Joshi'] | ['cs.CL', 'cs.LG'] | We present L3Cube-MahaCorpus a Marathi monolingual data set scraped from
different internet sources. We expand the existing Marathi monolingual corpus
with 24.8M sentences and 289M tokens. We further present, MahaBERT, MahaAlBERT,
and MahaRoBerta all BERT-based masked language models, and MahaFT, the fast
text word emb... | 2022-02-02T17:35:52Z | null | null | null | L3Cube-MahaCorpus and MahaBERT: Marathi Monolingual Corpus, Marathi BERT Language Models, and Resources | ['Raviraj Joshi'] | 2,022 | WILDRE | 54 | 34 | ['Computer Science'] |
2,202.01252 | Speaker Normalization for Self-supervised Speech Emotion Recognition | ['Itai Gat', 'Hagai Aronowitz', 'Weizhong Zhu', 'Edmilson Morais', 'Ron Hoory'] | ['cs.LG'] | Large speech emotion recognition datasets are hard to obtain, and small
datasets may contain biases. Deep-net-based classifiers, in turn, are prone to
exploit those biases and find shortcuts such as speaker characteristics. These
shortcuts usually harm a model's ability to generalize. To address this
challenge, we prop... | 2022-02-02T19:30:47Z | ICASSP 22 | null | null | null | null | null | null | null | null | null |
2,202.01764 | JaQuAD: Japanese Question Answering Dataset for Machine Reading
Comprehension | ['ByungHoon So', 'Kyuhong Byun', 'Kyungwon Kang', 'Seongjin Cho'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Question Answering (QA) is a task in which a machine understands a given
document and a question to find an answer. Despite impressive progress in the
NLP area, QA is still a challenging problem, especially for non-English
languages due to the lack of annotated datasets. In this paper, we present the
Japanese Question ... | 2022-02-03T18:40:25Z | 11 pages, 3 figures, 6 tables | null | null | null | null | null | null | null | null | null |
2,202.03052 | OFA: Unifying Architectures, Tasks, and Modalities Through a Simple
Sequence-to-Sequence Learning Framework | ['Peng Wang', 'An Yang', 'Rui Men', 'Junyang Lin', 'Shuai Bai', 'Zhikang Li', 'Jianxin Ma', 'Chang Zhou', 'Jingren Zhou', 'Hongxia Yang'] | ['cs.CV', 'cs.CL'] | In this work, we pursue a unified paradigm for multimodal pretraining to
break the scaffolds of complex task/modality-specific customization. We propose
OFA, a Task-Agnostic and Modality-Agnostic framework that supports Task
Comprehensiveness. OFA unifies a diverse set of cross-modal and unimodal tasks,
including image... | 2022-02-07T10:38:21Z | Accepted at ICML2022 | null | null | OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework | ['Peng Wang', 'An Yang', 'Rui Men', 'Junyang Lin', 'Shuai Bai', 'Zhikang Li', 'Jianxin Ma', 'Chang Zhou', 'Jingren Zhou', 'Hongxia Yang'] | 2,022 | International Conference on Machine Learning | 884 | 123 | ['Computer Science'] |
2,202.03286 | Red Teaming Language Models with Language Models | ['Ethan Perez', 'Saffron Huang', 'Francis Song', 'Trevor Cai', 'Roman Ring', 'John Aslanides', 'Amelia Glaese', 'Nat McAleese', 'Geoffrey Irving'] | ['cs.CL', 'cs.AI', 'cs.CR', 'cs.LG'] | Language Models (LMs) often cannot be deployed because of their potential to
harm users in hard-to-predict ways. Prior work identifies harmful behaviors
before deployment by using human annotators to hand-write test cases. However,
human annotation is expensive, limiting the number and diversity of test cases.
In this ... | 2022-02-07T15:22:17Z | null | null | null | Red Teaming Language Models with Language Models | ['Ethan Perez', 'Saffron Huang', 'Francis Song', 'Trevor Cai', 'Roman Ring', 'John Aslanides', 'Amelia Glaese', 'Nat McAleese', 'G. Irving'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 672 | 109 | ['Computer Science'] |
2,202.03371 | Cedille: A large autoregressive French language model | ['Martin Müller', 'Florian Laurent'] | ['cs.CL', '68T50', 'I.2.7'] | Scaling up the size and training of autoregressive language models has
enabled novel ways of solving Natural Language Processing tasks using zero-shot
and few-shot learning. While extreme-scale language models such as GPT-3 offer
multilingual capabilities, zero-shot learning for languages other than English
remain larg... | 2022-02-07T17:40:43Z | 8 pages, 1 figure, 7 tables | null | null | null | null | null | null | null | null | null |
2,202.03555 | data2vec: A General Framework for Self-supervised Learning in Speech,
Vision and Language | ['Alexei Baevski', 'Wei-Ning Hsu', 'Qiantong Xu', 'Arun Babu', 'Jiatao Gu', 'Michael Auli'] | ['cs.LG'] | While the general idea of self-supervised learning is identical across
modalities, the actual algorithms and objectives differ widely because they
were developed with a single modality in mind. To get us closer to general
self-supervised learning, we present data2vec, a framework that uses the same
learning method for ... | 2022-02-07T22:52:11Z | null | null | null | null | null | null | null | null | null | null |
2,202.03799 | What are the best systems? New perspectives on NLP Benchmarking | ['Pierre Colombo', 'Nathan Noiry', 'Ekhine Irurozki', 'Stephan Clemencon'] | ['cs.CL', 'cs.AI'] | In Machine Learning, a benchmark refers to an ensemble of datasets associated
with one or multiple metrics together with a way to aggregate different systems
performances. They are instrumental in (i) assessing the progress of new
methods along different axes and (ii) selecting the best systems for practical
use. This ... | 2022-02-08T11:44:20Z | null | null | null | What are the best systems? New perspectives on NLP Benchmarking | ['Pierre Colombo', 'Nathan Noiry', 'Ekhine Irurozki', 'S. Clémençon'] | 2,022 | Neural Information Processing Systems | 42 | 120 | ['Computer Science'] |
2,202.03829 | TimeLMs: Diachronic Language Models from Twitter | ['Daniel Loureiro', 'Francesco Barbieri', 'Leonardo Neves', 'Luis Espinosa Anke', 'Jose Camacho-Collados'] | ['cs.CL', 'cs.AI'] | Despite its importance, the time variable has been largely neglected in the
NLP and language model literature. In this paper, we present TimeLMs, a set of
language models specialized on diachronic Twitter data. We show that a
continual learning strategy contributes to enhancing Twitter-based language
models' capacity t... | 2022-02-08T12:47:38Z | Accepted to ACL 2022 (Demo Track) -
https://github.com/cardiffnlp/timelms | null | null | null | null | null | null | null | null | null |
2,202.04053 | DALL-Eval: Probing the Reasoning Skills and Social Biases of
Text-to-Image Generation Models | ['Jaemin Cho', 'Abhay Zala', 'Mohit Bansal'] | ['cs.CV', 'cs.AI', 'cs.CL'] | Recently, DALL-E, a multimodal transformer language model, and its variants,
including diffusion models, have shown high-quality text-to-image generation
capabilities. However, despite the realistic image generation results, there
has not been a detailed analysis of how to evaluate such models. In this work,
we investi... | 2022-02-08T18:36:52Z | ICCV 2023 (34 pages; see appendix for version changelog) | null | null | null | null | null | null | null | null | null |
2,202.042 | MaskGIT: Masked Generative Image Transformer | ['Huiwen Chang', 'Han Zhang', 'Lu Jiang', 'Ce Liu', 'William T. Freeman'] | ['cs.CV'] | Generative transformers have experienced rapid popularity growth in the
computer vision community in synthesizing high-fidelity and high-resolution
images. The best generative transformer models so far, however, still treat an
image naively as a sequence of tokens, and decode an image sequentially
following the raster ... | 2022-02-08T23:54:06Z | null | null | null | null | null | null | null | null | null | null |
2,202.04901 | FILM: Frame Interpolation for Large Motion | ['Fitsum Reda', 'Janne Kontkanen', 'Eric Tabellion', 'Deqing Sun', 'Caroline Pantofaru', 'Brian Curless'] | ['cs.CV'] | We present a frame interpolation algorithm that synthesizes multiple
intermediate frames from two input images with large in-between motion. Recent
methods use multiple networks to estimate optical flow or depth and a separate
network dedicated to frame synthesis. This is often complex and requires scarce
optical flow ... | 2022-02-10T08:48:18Z | Accepted to ECCV 2022. Project website: https://film-net.github.io.
Code: https://github.com/google-research/frame-interpolation. YouTube:
https://www.youtube.com/watch?v=OAD-BieIjH4 | null | null | null | null | null | null | null | null | null |
2,202.05599 | ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization | ['Jiaan Wang', 'Fandong Meng', 'Ziyao Lu', 'Duo Zheng', 'Zhixu Li', 'Jianfeng Qu', 'Jie Zhou'] | ['cs.CL', 'cs.AI'] | We present ClidSum, a benchmark dataset for building cross-lingual
summarization systems on dialogue documents. It consists of 67k+ dialogue
documents from two subsets (i.e., SAMSum and MediaSum) and 112k+ annotated
summaries in different target languages. Based on the proposed ClidSum, we
introduce two benchmark setti... | 2022-02-11T13:32:14Z | Accepted to EMNLP 2022 (main conference) | null | null | ClidSum: A Benchmark Dataset for Cross-Lingual Dialogue Summarization | ['Jiaan Wang', 'Fandong Meng', 'Ziyao Lu', 'Duo Zheng', 'Zhixu Li', 'Jianfeng Qu', 'Jie Zhou'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 35 | 70 | ['Computer Science'] |
2,202.0569 | HaT5: Hate Language Identification using Text-to-Text Transfer
Transformer | ['Sana Sabah Sabry', 'Tosin Adewumi', 'Nosheen Abid', 'György Kovacs', 'Foteini Liwicki', 'Marcus Liwicki'] | ['cs.CL', '68'] | We investigate the performance of a state-of-the art (SoTA) architecture T5
(available on the SuperGLUE) and compare with it 3 other previous SoTA
architectures across 5 different tasks from 2 relatively diverse datasets. The
datasets are diverse in terms of the number and types of tasks they have. To
improve performan... | 2022-02-11T15:21:27Z | 7 pages, 3 figures , conference | null | null | null | null | null | null | null | null | null |
2,202.06219 | PQuAD: A Persian Question Answering Dataset | ['Kasra Darvishi', 'Newsha Shahbodagh', 'Zahra Abbasiantaeb', 'Saeedeh Momtazi'] | ['cs.CL', 'cs.IR', 'cs.LG'] | We present Persian Question Answering Dataset (PQuAD), a crowdsourced reading
comprehension dataset on Persian Wikipedia articles. It includes 80,000
questions along with their answers, with 25% of the questions being
adversarially unanswerable. We examine various properties of the dataset to
show the diversity and the... | 2022-02-13T05:42:55Z | null | Computer Speech & Language, Volume 80, 2023, 101486 | 10.1016/j.csl.2023.101486 | PQuAD: A Persian Question Answering Dataset | ['Kasra Darvishi', 'Newsha Shahbodagh', 'Zahra Abbasiantaeb', 'S. Momtazi'] | 2,022 | Computer Speech and Language | 19 | 30 | ['Computer Science'] |
2,202.06417 | A Contrastive Framework for Neural Text Generation | ['Yixuan Su', 'Tian Lan', 'Yan Wang', 'Dani Yogatama', 'Lingpeng Kong', 'Nigel Collier'] | ['cs.CL'] | Text generation is of great importance to many natural language processing
applications. However, maximization-based decoding methods (e.g. beam search)
of neural language models often lead to degenerate solutions -- the generated
text is unnatural and contains undesirable repetitions. Existing approaches
introduce sto... | 2022-02-13T21:46:14Z | NeurIPS 2022 | null | null | null | null | null | null | null | null | null |
2,202.06671 | Neighborhood Contrastive Learning for Scientific Document
Representations with Citation Embeddings | ['Malte Ostendorff', 'Nils Rethmeier', 'Isabelle Augenstein', 'Bela Gipp', 'Georg Rehm'] | ['cs.CL'] | Learning scientific document representations can be substantially improved
through contrastive learning objectives, where the challenge lies in creating
positive and negative training samples that encode the desired similarity
semantics. Prior work relies on discrete citation relations to generate
contrast samples. How... | 2022-02-14T12:57:37Z | Accepted to EMNLP 2022 | null | null | Neighborhood Contrastive Learning for Scientific Document Representations with Citation Embeddings | ['Malte Ostendorff', 'Nils Rethmeier', 'Isabelle Augenstein', 'Bela Gipp', 'Georg Rehm'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 77 | 78 | ['Computer Science'] |
2,202.06934 | Slicing Aided Hyper Inference and Fine-tuning for Small Object Detection | ['Fatih Cagatay Akyon', 'Sinan Onur Altinuc', 'Alptekin Temizel'] | ['cs.CV', 'cs.LG'] | Detection of small objects and objects far away in the scene is a major
challenge in surveillance applications. Such objects are represented by small
number of pixels in the image and lack sufficient details, making them
difficult to detect using conventional detectors. In this work, an open-source
framework called Sli... | 2022-02-14T18:49:12Z | Presented at ICIP 2022, 5 pages, 4 figures, 2 tables | null | 10.1109/ICIP46576.2022.9897990 | Slicing Aided Hyper Inference and Fine-Tuning for Small Object Detection | ['F. C. Akyon', 'S. Altinuc', 'A. Temi̇zel'] | 2,022 | International Conference on Information Photonics | 237 | 27 | ['Computer Science'] |
2,202.06935 | Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation
Practices for Generated Text | ['Sebastian Gehrmann', 'Elizabeth Clark', 'Thibault Sellam'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Evaluation practices in natural language generation (NLG) have many known
flaws, but improved evaluation approaches are rarely widely adopted. This issue
has become more urgent, since neural NLG models have improved to the point
where they can often no longer be distinguished based on the surface-level
features that ol... | 2022-02-14T18:51:07Z | null | null | null | Repairing the Cracked Foundation: A Survey of Obstacles in Evaluation Practices for Generated Text | ['Sebastian Gehrmann', 'Elizabeth Clark', 'Thibault Sellam'] | 2,022 | Journal of Artificial Intelligence Research | 193 | 304 | ['Computer Science'] |
2,202.07654 | Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question
Answering Evaluation | ['Jannis Bulian', 'Christian Buck', 'Wojciech Gajewski', 'Benjamin Boerschinger', 'Tal Schuster'] | ['cs.CL', 'cs.LG'] | The predictions of question answering (QA)systems are typically evaluated
against manually annotated finite sets of one or more answers. This leads to a
coverage limitation that results in underestimating the true performance of
systems, and is typically addressed by extending over exact match (EM) with
pre-defined rul... | 2022-02-15T18:53:58Z | null | null | null | Tomayto, Tomahto. Beyond Token-level Answer Equivalence for Question Answering Evaluation | ['Jannis Bulian', 'C. Buck', 'Wojciech Gajewski', 'Benjamin Boerschinger', 'Tal Schuster'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 47 | 54 | ['Computer Science'] |
2,202.07765 | General-purpose, long-context autoregressive modeling with Perceiver AR | ['Curtis Hawthorne', 'Andrew Jaegle', 'Cătălina Cangea', 'Sebastian Borgeaud', 'Charlie Nash', 'Mateusz Malinowski', 'Sander Dieleman', 'Oriol Vinyals', 'Matthew Botvinick', 'Ian Simon', 'Hannah Sheahan', 'Neil Zeghidour', 'Jean-Baptiste Alayrac', 'João Carreira', 'Jesse Engel'] | ['cs.LG', 'cs.AI', 'cs.CV', 'cs.SD', 'eess.AS'] | Real-world data is high-dimensional: a book, image, or musical performance
can easily contain hundreds of thousands of elements even after compression.
However, the most commonly used autoregressive models, Transformers, are
prohibitively expensive to scale to the number of inputs and layers needed to
capture this long... | 2022-02-15T22:31:42Z | ICML 2022 | null | null | General-purpose, long-context autoregressive modeling with Perceiver AR | ['Curtis Hawthorne', 'Andrew Jaegle', 'Cătălina Cangea', 'Sebastian Borgeaud', 'C. Nash', 'Mateusz Malinowski', 'S. Dieleman', 'O. Vinyals', 'M. Botvinick', 'Ian Simon', 'Hannah Sheahan', 'Neil Zeghidour', 'Jean-Baptiste Alayrac', 'João Carreira', 'Jesse Engel'] | 2,022 | International Conference on Machine Learning | 66 | 77 | ['Computer Science', 'Engineering'] |
2,202.08005 | Should You Mask 15% in Masked Language Modeling? | ['Alexander Wettig', 'Tianyu Gao', 'Zexuan Zhong', 'Danqi Chen'] | ['cs.CL', 'cs.LG'] | Masked language models (MLMs) conventionally mask 15% of tokens due to the
belief that more masking would leave insufficient context to learn good
representations; this masking rate has been widely used, regardless of model
sizes or masking strategies. In this work, we revisit this important choice of
MLM pre-training.... | 2022-02-16T11:42:34Z | Accepted to EACL 2023. The code and pre-trained models are available
at https://github.com/princeton-nlp/DinkyTrain | null | null | Should You Mask 15% in Masked Language Modeling? | ['Alexander Wettig', 'Tianyu Gao', 'Zexuan Zhong', 'Danqi Chen'] | 2,022 | Conference of the European Chapter of the Association for Computational Linguistics | 167 | 57 | ['Computer Science'] |
2,202.08238 | A multi-reconstruction study of breast density estimation using Deep
Learning | ['Vikash Gupta', 'Mutlu Demirer', 'Robert W. Maxwell', 'Richard D. White', 'Barbaros Selnur Erdal'] | ['eess.IV', 'cs.CV', 'cs.LG', 'I.2.1; J.3; I.4'] | Breast density estimation is one of the key tasks in recognizing individuals
predisposed to breast cancer. It is often challenging because of low contrast
and fluctuations in mammograms' fatty tissue background. Most of the time, the
breast density is estimated manually where a radiologist assigns one of the
four densi... | 2022-02-16T18:34:08Z | 4 pages | null | null | null | null | null | null | null | null | null |
2,202.0836 | Vision Models Are More Robust And Fair When Pretrained On Uncurated
Images Without Supervision | ['Priya Goyal', 'Quentin Duval', 'Isaac Seessel', 'Mathilde Caron', 'Ishan Misra', 'Levent Sagun', 'Armand Joulin', 'Piotr Bojanowski'] | ['cs.CV', 'cs.AI', 'cs.CY'] | Discriminative self-supervised learning allows training models on any random
group of internet images, and possibly recover salient information that helps
differentiate between the images. Applied to ImageNet, this leads to object
centric features that perform on par with supervised features on most
object-centric down... | 2022-02-16T22:26:47Z | null | null | null | Vision Models Are More Robust And Fair When Pretrained On Uncurated Images Without Supervision | ['Priya Goyal', 'Quentin Duval', 'Isaac Seessel', 'Mathilde Caron', 'Ishan Misra', 'Levent Sagun', 'Armand Joulin', 'Piotr Bojanowski'] | 2,022 | arXiv.org | 111 | 157 | ['Computer Science'] |
2,202.08904 | SGPT: GPT Sentence Embeddings for Semantic Search | ['Niklas Muennighoff'] | ['cs.CL', 'cs.AI', 'cs.IR'] | Decoder transformers have continued increasing in scale reaching hundreds of
billions of parameters. Due to their scale the same decoder sets
state-of-the-art results on various language tasks via prompting or
fine-tuning. Yet, these large foundation models remain unusable for the related
fields of semantic search and ... | 2022-02-17T21:35:56Z | 19 pages, 3 figures, 12 tables. v2 corrects a misreported nDCG@10
number for the SGPT-BE-5.8B model. v3 updates SGPT-BE-5.8B scores based on
retrained models with larger batch sizes v4 removes a superfluous table. v5
adds OpenAI scores on USEB and makes the paper easier to read | null | null | SGPT: GPT Sentence Embeddings for Semantic Search | ['Niklas Muennighoff'] | 2,022 | arXiv.org | 191 | 55 | ['Computer Science'] |
2,202.08906 | ST-MoE: Designing Stable and Transferable Sparse Expert Models | ['Barret Zoph', 'Irwan Bello', 'Sameer Kumar', 'Nan Du', 'Yanping Huang', 'Jeff Dean', 'Noam Shazeer', 'William Fedus'] | ['cs.CL', 'cs.LG'] | Scale has opened new frontiers in natural language processing -- but at a
high cost. In response, Mixture-of-Experts (MoE) and Switch Transformers have
been proposed as an energy efficient path to even larger and more capable
language models. But advancing the state-of-the-art across a broad set of
natural language tas... | 2022-02-17T21:39:10Z | 25 pages main text, 39 pages overall | null | null | null | null | null | null | null | null | null |
2,202.09729 | It's Raw! Audio Generation with State-Space Models | ['Karan Goel', 'Albert Gu', 'Chris Donahue', 'Christopher Ré'] | ['cs.SD', 'cs.AI', 'cs.LG', 'eess.AS'] | Developing architectures suitable for modeling raw audio is a challenging
problem due to the high sampling rates of audio waveforms. Standard sequence
modeling approaches like RNNs and CNNs have previously been tailored to fit the
demands of audio, but the resultant architectures make undesirable
computational tradeoff... | 2022-02-20T04:45:46Z | 23 pages, 7 figures, 7 tables | null | null | null | null | null | null | null | null | null |
2,202.09741 | Visual Attention Network | ['Meng-Hao Guo', 'Cheng-Ze Lu', 'Zheng-Ning Liu', 'Ming-Ming Cheng', 'Shi-Min Hu'] | ['cs.CV'] | While originally designed for natural language processing tasks, the
self-attention mechanism has recently taken various computer vision areas by
storm. However, the 2D nature of images brings three challenges for applying
self-attention in computer vision. (1) Treating images as 1D sequences neglects
their 2D structur... | 2022-02-20T06:35:18Z | Code is available at https://github.com/Visual-Attention-Network | null | null | null | null | null | null | null | null | null |
2,202.09778 | Pseudo Numerical Methods for Diffusion Models on Manifolds | ['Luping Liu', 'Yi Ren', 'Zhijie Lin', 'Zhou Zhao'] | ['cs.CV', 'cs.LG', 'cs.NA', 'math.NA', 'stat.ML'] | Denoising Diffusion Probabilistic Models (DDPMs) can generate high-quality
samples such as image and audio samples. However, DDPMs require hundreds to
thousands of iterations to produce final samples. Several prior works have
successfully accelerated DDPMs through adjusting the variance schedule (e.g.,
Improved Denoisi... | 2022-02-20T10:37:52Z | ICLR 2022 | null | null | Pseudo Numerical Methods for Diffusion Models on Manifolds | ['Luping Liu', 'Yi Ren', 'Zhijie Lin', 'Zhou Zhao'] | 2,022 | International Conference on Learning Representations | 658 | 35 | ['Computer Science', 'Mathematics'] |
2,202.10261 | A Self-Supervised Descriptor for Image Copy Detection | ['Ed Pizzi', 'Sreya Dutta Roy', 'Sugosh Nagavara Ravindra', 'Priya Goyal', 'Matthijs Douze'] | ['cs.CV', 'cs.CR', 'cs.LG'] | Image copy detection is an important task for content moderation. We
introduce SSCD, a model that builds on a recent self-supervised contrastive
training objective. We adapt this method to the copy detection task by changing
the architecture and training objective, including a pooling operator from the
instance matchin... | 2022-02-21T14:25:32Z | null | null | null | A Self-Supervised Descriptor for Image Copy Detection | ['Ed Pizzi', 'Sreya . Dutta Roy', 'Sugosh Nagavara Ravindra', 'Priya Goyal', 'Matthijs Douze'] | 2,022 | Computer Vision and Pattern Recognition | 126 | 63 | ['Computer Science'] |
2,202.11094 | GroupViT: Semantic Segmentation Emerges from Text Supervision | ['Jiarui Xu', 'Shalini De Mello', 'Sifei Liu', 'Wonmin Byeon', 'Thomas Breuel', 'Jan Kautz', 'Xiaolong Wang'] | ['cs.CV'] | Grouping and recognition are important components of visual scene
understanding, e.g., for object detection and semantic segmentation. With
end-to-end deep learning systems, grouping of image regions usually happens
implicitly via top-down supervision from pixel-level recognition labels.
Instead, in this paper, we prop... | 2022-02-22T18:56:04Z | CVPR 2022. Project page and code: https://jerryxu.net/GroupViT | null | null | null | null | null | null | null | null | null |
2,202.11176 | A New Generation of Perspective API: Efficient Multilingual
Character-level Transformers | ['Alyssa Lees', 'Vinh Q. Tran', 'Yi Tay', 'Jeffrey Sorensen', 'Jai Gupta', 'Donald Metzler', 'Lucy Vasserman'] | ['cs.CL', 'cs.AI', 'cs.CY', 'cs.LG'] | On the world wide web, toxic content detectors are a crucial line of defense
against potentially hateful and offensive messages. As such, building highly
effective classifiers that enable a safer internet is an important research
area. Moreover, the web is a highly multilingual, cross-cultural community that
develops i... | 2022-02-22T20:55:31Z | null | null | null | null | null | null | null | null | null | null |
2,202.11214 | FourCastNet: A Global Data-driven High-resolution Weather Model using
Adaptive Fourier Neural Operators | ['Jaideep Pathak', 'Shashank Subramanian', 'Peter Harrington', 'Sanjeev Raja', 'Ashesh Chattopadhyay', 'Morteza Mardani', 'Thorsten Kurth', 'David Hall', 'Zongyi Li', 'Kamyar Azizzadenesheli', 'Pedram Hassanzadeh', 'Karthik Kashinath', 'Animashree Anandkumar'] | ['physics.ao-ph', 'cs.LG'] | FourCastNet, short for Fourier Forecasting Neural Network, is a global
data-driven weather forecasting model that provides accurate short to
medium-range global predictions at $0.25^{\circ}$ resolution. FourCastNet
accurately forecasts high-resolution, fast-timescale variables such as the
surface wind speed, precipitat... | 2022-02-22T22:19:35Z | null | null | null | null | null | null | null | null | null | null |
2,202.12064 | Interfering Paths in Decision Trees: A Note on Deodata Predictors | ['Cristian Alb'] | ['cs.LG'] | A technique for improving the prediction accuracy of decision trees is
proposed. It consists in evaluating the tree's branches in parallel over
multiple paths. The technique enables predictions that are more aligned with
the ones generated by the nearest neighborhood variant of the deodata
algorithms. The technique als... | 2022-02-24T12:41:20Z | null | null | 10.13140/RG.2.2.12510.10565 | null | null | null | null | null | null | null |
2,202.12163 | Attentive Temporal Pooling for Conformer-based Streaming Language
Identification in Long-form Speech | ['Quan Wang', 'Yang Yu', 'Jason Pelecanos', 'Yiling Huang', 'Ignacio Lopez Moreno'] | ['eess.AS', 'cs.CL', 'cs.LG', 'stat.ML'] | In this paper, we introduce a novel language identification system based on
conformer layers. We propose an attentive temporal pooling mechanism to allow
the model to carry information in long-form audio via a recurrent form, such
that the inference can be performed in a streaming fashion. Additionally, we
investigate ... | 2022-02-24T16:01:07Z | null | null | null | Attentive Temporal Pooling for Conformer-based Streaming Language Identification in Long-form Speech | ['Quan Wang', 'Yang Yu', 'Jason W. Pelecanos', 'Yiling Huang', 'I. López-Moreno'] | 2,022 | The Speaker and Language Recognition Workshop | 15 | 63 | ['Computer Science', 'Engineering', 'Mathematics'] |
2,202.12211 | Self-Distilled StyleGAN: Towards Generation from Internet Photos | ['Ron Mokady', 'Michal Yarom', 'Omer Tov', 'Oran Lang', 'Daniel Cohen-Or', 'Tali Dekel', 'Michal Irani', 'Inbar Mosseri'] | ['cs.CV'] | StyleGAN is known to produce high-fidelity images, while also offering
unprecedented semantic editing. However, these fascinating abilities have been
demonstrated only on a limited set of datasets, which are usually structurally
aligned and well curated. In this paper, we show how StyleGAN can be adapted to
work on raw... | 2022-02-24T17:16:47Z | null | null | null | null | null | null | null | null | null | null |
2,202.12233 | Automatic speaker verification spoofing and deepfake detection using
wav2vec 2.0 and data augmentation | ['Hemlata Tak', 'Massimiliano Todisco', 'Xin Wang', 'Jee-weon Jung', 'Junichi Yamagishi', 'Nicholas Evans'] | ['eess.AS', 'cs.SD'] | The performance of spoofing countermeasure systems depends fundamentally upon
the use of sufficiently representative training data. With this usually being
limited, current solutions typically lack generalisation to attacks encountered
in the wild. Strategies to improve reliability in the face of uncontrolled,
unpredic... | 2022-02-24T17:55:00Z | Submitted to Speaker Odyssey Workshop 2022 | null | null | null | null | null | null | null | null | null |
2,202.12837 | Rethinking the Role of Demonstrations: What Makes In-Context Learning
Work? | ['Sewon Min', 'Xinxi Lyu', 'Ari Holtzman', 'Mikel Artetxe', 'Mike Lewis', 'Hannaneh Hajishirzi', 'Luke Zettlemoyer'] | ['cs.CL', 'cs.AI'] | Large language models (LMs) are able to in-context learn -- perform a new
task via inference alone by conditioning on a few input-label pairs
(demonstrations) and making predictions for new inputs. However, there has been
little understanding of how the model learns and which aspects of the
demonstrations contribute to... | 2022-02-25T17:25:19Z | 17 pages; 12 figures. Published as a conference paper at EMNLP 2022
(long). Code available at
https://github.com/Alrope123/rethinking-demonstrations | null | null | Rethinking the Role of Demonstrations: What Makes In-Context Learning Work? | ['Sewon Min', 'Xinxi Lyu', 'Ari Holtzman', 'Mikel Artetxe', 'M. Lewis', 'Hannaneh Hajishirzi', 'Luke Zettlemoyer'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 1,507 | 73 | ['Computer Science'] |
2,202.13047 | AugESC: Dialogue Augmentation with Large Language Models for Emotional
Support Conversation | ['Chujie Zheng', 'Sahand Sabour', 'Jiaxin Wen', 'Zheng Zhang', 'Minlie Huang'] | ['cs.CL'] | Crowdsourced dialogue corpora are usually limited in scale and topic coverage
due to the expensive cost of data curation. This would hinder the
generalization of downstream dialogue models to open-domain topics. In this
work, we leverage large language models for dialogue augmentation in the task
of emotional support c... | 2022-02-26T03:17:08Z | Findings of ACL 2023 | null | null | AugESC: Dialogue Augmentation with Large Language Models for Emotional Support Conversation | ['Chujie Zheng', 'Sahand Sabour', 'Jiaxin Wen', 'Zheng Zhang', 'Minlie Huang'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 66 | 54 | ['Computer Science'] |
2,202.13169 | A Systematic Evaluation of Large Language Models of Code | ['Frank F. Xu', 'Uri Alon', 'Graham Neubig', 'Vincent J. Hellendoorn'] | ['cs.PL', 'cs.CL'] | Large language models (LMs) of code have recently shown tremendous promise in
completing code and synthesizing code from natural language descriptions.
However, the current state-of-the-art code LMs (e.g., Codex (Chen et al.,
2021)) are not publicly available, leaving many questions about their model and
data design de... | 2022-02-26T15:53:55Z | DL4C@ICLR 2022, and MAPS@PLDI 2022 | null | null | null | null | null | null | null | null | null |
2,202.13469 | UCTopic: Unsupervised Contrastive Learning for Phrase Representations
and Topic Mining | ['Jiacheng Li', 'Jingbo Shang', 'Julian McAuley'] | ['cs.CL', 'cs.AI'] | High-quality phrase representations are essential to finding topics and
related terms in documents (a.k.a. topic mining). Existing phrase
representation learning methods either simply combine unigram representations
in a context-free manner or rely on extensive annotations to learn
context-aware knowledge. In this pape... | 2022-02-27T22:43:06Z | Accepted as ACL 2022 main conference paper | null | null | UCTopic: Unsupervised Contrastive Learning for Phrase Representations and Topic Mining | ['Jiacheng Li', 'Jingbo Shang', 'Julian McAuley'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 46 | 46 | ['Computer Science'] |
2,202.13514 | StrongSORT: Make DeepSORT Great Again | ['Yunhao Du', 'Zhicheng Zhao', 'Yang Song', 'Yanyun Zhao', 'Fei Su', 'Tao Gong', 'Hongying Meng'] | ['cs.CV'] | Recently, Multi-Object Tracking (MOT) has attracted rising attention, and
accordingly, remarkable progresses have been achieved. However, the existing
methods tend to use various basic models (e.g, detector and embedding model),
and different training or inference tricks, etc. As a result, the construction
of a good ba... | 2022-02-28T02:37:19Z | Accepted by IEEE Transactions on Multimedia 2023 | null | null | null | null | null | null | null | null | null |
2,202.13669 | LiLT: A Simple yet Effective Language-Independent Layout Transformer for
Structured Document Understanding | ['Jiapeng Wang', 'Lianwen Jin', 'Kai Ding'] | ['cs.CL'] | Structured document understanding has attracted considerable attention and
made significant progress recently, owing to its crucial role in intelligent
document processing. However, most existing related models can only deal with
the document data of specific language(s) (typically English) included in the
pre-training... | 2022-02-28T10:33:01Z | ACL 2022 Main conference | null | null | null | null | null | null | null | null | null |
2,202.13756 | Data-to-text Generation with Variational Sequential Planning | ['Ratish Puduppully', 'Yao Fu', 'Mirella Lapata'] | ['cs.CL'] | We consider the task of data-to-text generation, which aims to create textual
output from non-linguistic input. We focus on generating long-form text, i.e.,
documents with multiple paragraphs, and propose a neural model enhanced with a
planning component responsible for organizing high-level information in a
coherent a... | 2022-02-28T13:17:59Z | To appear in Transactions of the Association for Computational
Linguistics (TACL); 18 pages | null | null | Data-to-text Generation with Variational Sequential Planning | ['Ratish Puduppully', 'Yao Fu', 'Mirella Lapata'] | 2,022 | Transactions of the Association for Computational Linguistics | 21 | 80 | ['Computer Science'] |
2,203.00148 | Improved iterative methods for solving risk parity portfolio | ['Jaehyuk Choi', 'Rong Chen'] | ['q-fin.PM'] | Risk parity, also known as equal risk contribution, has recently gained
increasing attention as a portfolio allocation method. However, solving
portfolio weights must resort to numerical methods as the analytic solution is
not available. This study improves two existing iterative methods: the cyclical
coordinate descen... | 2022-02-28T23:59:37Z | null | Journal of Derivatives and Quantitative Studies, 30(2):114-124,
2022 | 10.1108/JDQS-12-2021-0031 | null | null | null | null | null | null | null |
2,203.00249 | Exploring and Adapting Chinese GPT to Pinyin Input Method | ['Minghuan Tan', 'Yong Dai', 'Duyu Tang', 'Zhangyin Feng', 'Guoping Huang', 'Jing Jiang', 'Jiwei Li', 'Shuming Shi'] | ['cs.CL', 'cs.AI'] | While GPT has become the de-facto method for text generation tasks, its
application to pinyin input method remains unexplored. In this work, we make
the first exploration to leverage Chinese GPT for pinyin input method. We find
that a frozen GPT achieves state-of-the-art performance on perfect pinyin.
However, the perf... | 2022-03-01T06:05:07Z | To appear in ACL 2022 | null | null | null | null | null | null | null | null | null |
2,203.00555 | DeepNet: Scaling Transformers to 1,000 Layers | ['Hongyu Wang', 'Shuming Ma', 'Li Dong', 'Shaohan Huang', 'Dongdong Zhang', 'Furu Wei'] | ['cs.CL', 'cs.LG'] | In this paper, we propose a simple yet effective method to stabilize
extremely deep Transformers. Specifically, we introduce a new normalization
function (DeepNorm) to modify the residual connection in Transformer,
accompanying with theoretically derived initialization. In-depth theoretical
analysis shows that model up... | 2022-03-01T15:36:38Z | Work in progress | null | null | DeepNet: Scaling Transformers to 1,000 Layers | ['Hongyu Wang', 'Shuming Ma', 'Li Dong', 'Shaohan Huang', 'Dongdong Zhang', 'Furu Wei'] | 2,022 | IEEE Transactions on Pattern Analysis and Machine Intelligence | 162 | 74 | ['Computer Science'] |
2,203.00585 | Self-Supervised Vision Transformers Learn Visual Concepts in
Histopathology | ['Richard J. Chen', 'Rahul G. Krishnan'] | ['cs.CV', 'q-bio.TO'] | Tissue phenotyping is a fundamental task in learning objective
characterizations of histopathologic biomarkers within the tumor-immune
microenvironment in cancer pathology. However, whole-slide imaging (WSI) is a
complex computer vision in which: 1) WSIs have enormous image resolutions with
precludes large-scale pixel-... | 2022-03-01T16:14:41Z | Learning Meaningful Representations of Life (NeurIPS 2021) | null | null | Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology | ['Richard J. Chen', 'R. G. Krishnan'] | 2,022 | arXiv.org | 88 | 46 | ['Computer Science', 'Biology'] |
2,203.00991 | The Past Mistake is the Future Wisdom: Error-driven Contrastive
Probability Optimization for Chinese Spell Checking | ['Yinghui Li', 'Qingyu Zhou', 'Yangning Li', 'Zhongli Li', 'Ruiyang Liu', 'Rongyi Sun', 'Zizhen Wang', 'Chao Li', 'Yunbo Cao', 'Hai-Tao Zheng'] | ['cs.CL'] | Chinese Spell Checking (CSC) aims to detect and correct Chinese spelling
errors, which are mainly caused by the phonological or visual similarity.
Recently, pre-trained language models (PLMs) promote the progress of CSC task.
However, there exists a gap between the learned knowledge of PLMs and the goal
of CSC task. PL... | 2022-03-02T09:58:56Z | Long paper, accepted at the Findings of ACL 2022 | null | null | The Past Mistake is the Future Wisdom: Error-driven Contrastive Probability Optimization for Chinese Spell Checking | ['Yinghui Li', 'Qingyu Zhou', 'Y. Li', 'Zhongli Li', 'Ruiyang Liu', 'Rongyi Sun', 'Zizhen Wang', 'Chao Li', 'Yunbo Cao', 'Haitao Zheng'] | 2,022 | Findings | 70 | 43 | ['Computer Science'] |
2,203.01023 | Nuclear Structure with Discrete Non-Orthogonal Shell-Model : new
frontiers | ['D. D. Dao', 'Frédéric Nowacki'] | ['nucl-th', 'nucl-ex'] | We present developments and applications for the diagonalization of
shell-model hamiltonians in a discrete non-orthogonal basis (DNO-SM). The
method, and its actual numerical implementation CARINA, based on mean-field and
beyond-mean field techniques has already been applied in previous studies and
is focused on basis ... | 2022-03-02T10:54:55Z | null | null | 10.1103/PhysRevC.105.054314 | null | null | null | null | null | null | null |
2,203.01215 | Mukayese: Turkish NLP Strikes Back | ['Ali Safaya', 'Emirhan Kurtuluş', 'Arda Göktoğan', 'Deniz Yuret'] | ['cs.CL'] | Having sufficient resources for language X lifts it from the under-resourced
languages class, but not necessarily from the under-researched class. In this
paper, we address the problem of the absence of organized benchmarks in the
Turkish language. We demonstrate that languages such as Turkish are left behind
the state... | 2022-03-02T16:18:44Z | Accepted at Findings of ACL 2022 (Camera Ready) | null | null | null | null | null | null | null | null | null |
2,203.01437 | MUAD: Multiple Uncertainties for Autonomous Driving, a benchmark for
multiple uncertainty types and tasks | ['Gianni Franchi', 'Xuanlong Yu', 'Andrei Bursuc', 'Angel Tena', 'Rémi Kazmierczak', 'Séverine Dubuisson', 'Emanuel Aldea', 'David Filliat'] | ['cs.CV'] | Predictive uncertainty estimation is essential for safe deployment of Deep
Neural Networks in real-world autonomous systems. However, disentangling the
different types and sources of uncertainty is non trivial for most datasets,
especially since there is no ground truth for uncertainty. In addition, while
adverse weath... | 2022-03-02T22:14:12Z | Accepted at BMVC 2022 | null | null | null | null | null | null | null | null | null |
2,203.01552 | Dialogue Summaries as Dialogue States (DS2), Template-Guided
Summarization for Few-shot Dialogue State Tracking | ['Jamin Shin', 'Hangyeol Yu', 'Hyeongdon Moon', 'Andrea Madotto', 'Juneyoung Park'] | ['cs.CL', 'cs.AI'] | Annotating task-oriented dialogues is notorious for the expensive and
difficult data collection process. Few-shot dialogue state tracking (DST) is a
realistic solution to this problem. In this paper, we hypothesize that dialogue
summaries are essentially unstructured dialogue states; hence, we propose to
reformulate di... | 2022-03-03T07:54:09Z | ACL 2022 (Long, Findings) | null | null | Dialogue Summaries as Dialogue States (DS2), Template-Guided Summarization for Few-shot Dialogue State Tracking | ['Jamin Shin', 'Hangyeol Yu', 'Hyeongdon Moon', 'Andrea Madotto', 'Juneyoung Park'] | 2,022 | Findings | 29 | 73 | ['Computer Science'] |
2,203.02155 | Training language models to follow instructions with human feedback | ['Long Ouyang', 'Jeff Wu', 'Xu Jiang', 'Diogo Almeida', 'Carroll L. Wainwright', 'Pamela Mishkin', 'Chong Zhang', 'Sandhini Agarwal', 'Katarina Slama', 'Alex Ray', 'John Schulman', 'Jacob Hilton', 'Fraser Kelton', 'Luke Miller', 'Maddie Simens', 'Amanda Askell', 'Peter Welinder', 'Paul Christiano', 'Jan Leike', 'Ryan L... | ['cs.CL', 'cs.AI', 'cs.LG'] | Making language models bigger does not inherently make them better at
following a user's intent. For example, large language models can generate
outputs that are untruthful, toxic, or simply not helpful to the user. In other
words, these models are not aligned with their users. In this paper, we show an
avenue for alig... | 2022-03-04T07:04:42Z | null | null | null | null | null | null | null | null | null | null |
2,203.02284 | Nuclei instance segmentation and classification in histopathology images
with StarDist | ['Martin Weigert', 'Uwe Schmidt'] | ['cs.CV'] | Instance segmentation and classification of nuclei is an important task in
computational pathology. We show that StarDist, a deep learning nuclei
segmentation method originally developed for fluorescence microscopy, can be
extended and successfully applied to histopathology images. This is
substantiated by conducting e... | 2022-03-03T01:00:26Z | null | null | 10.1109/ISBIC56247.2022.9854534 | null | null | null | null | null | null | null |
2,203.02378 | DiT: Self-supervised Pre-training for Document Image Transformer | ['Junlong Li', 'Yiheng Xu', 'Tengchao Lv', 'Lei Cui', 'Cha Zhang', 'Furu Wei'] | ['cs.CV'] | Image Transformer has recently achieved significant progress for natural
image understanding, either using supervised (ViT, DeiT, etc.) or
self-supervised (BEiT, MAE, etc.) pre-training techniques. In this paper, we
propose \textbf{DiT}, a self-supervised pre-trained \textbf{D}ocument
\textbf{I}mage \textbf{T}ransforme... | 2022-03-04T15:34:46Z | ACM Multimedia 2022 | null | null | null | null | null | null | null | null | null |
2,203.02395 | iSTFTNet: Fast and Lightweight Mel-Spectrogram Vocoder Incorporating
Inverse Short-Time Fourier Transform | ['Takuhiro Kaneko', 'Kou Tanaka', 'Hirokazu Kameoka', 'Shogo Seki'] | ['cs.SD', 'cs.LG', 'eess.AS', 'stat.ML'] | In recent text-to-speech synthesis and voice conversion systems, a
mel-spectrogram is commonly applied as an intermediate representation, and the
necessity for a mel-spectrogram vocoder is increasing. A mel-spectrogram
vocoder must solve three inverse problems: recovery of the original-scale
magnitude spectrogram, phas... | 2022-03-04T16:05:48Z | Accepted to ICASSP 2022. Project page:
https://www.kecl.ntt.co.jp/people/kaneko.takuhiro/projects/istftnet/ | null | null | ISTFTNET: Fast and Lightweight Mel-Spectrogram Vocoder Incorporating Inverse Short-Time Fourier Transform | ['Takuhiro Kaneko', 'Kou Tanaka', 'H. Kameoka', 'Shogo Seki'] | 2,022 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 62 | 40 | ['Computer Science', 'Engineering', 'Mathematics'] |
2,203.0243 | Characterizing Renal Structures with 3D Block Aggregate Transformers | ['Xin Yu', 'Yucheng Tang', 'Yinchi Zhou', 'Riqiang Gao', 'Qi Yang', 'Ho Hin Lee', 'Thomas Li', 'Shunxing Bao', 'Yuankai Huo', 'Zhoubing Xu', 'Thomas A. Lasko', 'Richard G. Abramson', 'Bennett A. Landman'] | ['eess.IV', 'cs.CV'] | Efficiently quantifying renal structures can provide distinct spatial context
and facilitate biomarker discovery for kidney morphology. However, the
development and evaluation of the transformer model to segment the renal
cortex, medulla, and collecting system remains challenging due to data
inefficiency. Inspired by t... | 2022-03-04T17:00:14Z | null | null | null | null | null | null | null | null | null | null |
2,203.03041 | Highly Accurate Dichotomous Image Segmentation | ['Xuebin Qin', 'Hang Dai', 'Xiaobin Hu', 'Deng-Ping Fan', 'Ling Shao', 'Luc Van Gool'] | ['cs.CV'] | We present a systematic study on a new task called dichotomous image
segmentation (DIS) , which aims to segment highly accurate objects from natural
images. To this end, we collected the first large-scale DIS dataset, called
DIS5K, which contains 5,470 high-resolution (e.g., 2K, 4K or larger) images
covering camouflage... | 2022-03-06T20:09:19Z | 29 pages, 18 figures, ECCV 2022 | null | null | null | null | null | null | null | null | null |
2,203.03466 | Tensor Programs V: Tuning Large Neural Networks via Zero-Shot
Hyperparameter Transfer | ['Greg Yang', 'Edward J. Hu', 'Igor Babuschkin', 'Szymon Sidor', 'Xiaodong Liu', 'David Farhi', 'Nick Ryder', 'Jakub Pachocki', 'Weizhu Chen', 'Jianfeng Gao'] | ['cs.LG', 'cond-mat.dis-nn', 'cs.NE'] | Hyperparameter (HP) tuning in deep learning is an expensive process,
prohibitively so for neural networks (NNs) with billions of parameters. We show
that, in the recently discovered Maximal Update Parametrization (muP), many
optimal HPs remain stable even as model size changes. This leads to a new HP
tuning paradigm we... | 2022-03-07T15:37:35Z | NeurIPS 2021 | null | null | null | null | null | null | null | null | null |
2,203.03605 | DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object
Detection | ['Hao Zhang', 'Feng Li', 'Shilong Liu', 'Lei Zhang', 'Hang Su', 'Jun Zhu', 'Lionel M. Ni', 'Heung-Yeung Shum'] | ['cs.CV'] | We present DINO (\textbf{D}ETR with \textbf{I}mproved de\textbf{N}oising
anch\textbf{O}r boxes), a state-of-the-art end-to-end object detector. % in
this paper. DINO improves over previous DETR-like models in performance and
efficiency by using a contrastive way for denoising training, a mixed query
selection method fo... | 2022-03-07T18:55:26Z | null | null | null | null | null | null | null | null | null | null |
2,203.03689 | WaveMix: Resource-efficient Token Mixing for Images | ['Pranav Jeevan', 'Amit Sethi'] | ['cs.CV', 'cs.AI', 'cs.LG', 'I.4.0; I.4.1; I.4.7; I.4.8; I.4.9; I.4.10; I.2.10; I.5.1; I.5.2;\n I.5.4'] | Although certain vision transformer (ViT) and CNN architectures generalize
well on vision tasks, it is often impractical to use them on green, edge, or
desktop computing due to their computational requirements for training and even
testing. We present WaveMix as an alternative neural architecture that uses a
multi-scal... | 2022-03-07T20:15:17Z | 12 pages, 2 figures | null | null | null | null | null | null | null | null | null |
2,203.03759 | IT5: Text-to-text Pretraining for Italian Language Understanding and
Generation | ['Gabriele Sarti', 'Malvina Nissim'] | ['cs.CL'] | We introduce IT5, the first family of encoder-decoder transformer models
pretrained specifically on Italian. We document and perform a thorough cleaning
procedure for a large Italian corpus and use it to pretrain four IT5 model
sizes. We then introduce the ItaGen benchmark, which includes a broad range of
natural langu... | 2022-03-07T22:39:01Z | LREC-COLING 2024. Code and checkpoints: https://github.com/gsarti/it5 | Proceedings of LREC-COLING (2024) 9422-9433 | null | null | null | null | null | null | null | null |
2,203.03802 | Understanding Iterative Revision from Human-Written Text | ['Wanyu Du', 'Vipul Raheja', 'Dhruv Kumar', 'Zae Myung Kim', 'Melissa Lopez', 'Dongyeop Kang'] | ['cs.CL', 'cs.HC'] | Writing is, by nature, a strategic, adaptive, and more importantly, an
iterative process. A crucial part of writing is editing and revising the text.
Previous works on text revision have focused on defining edit intention
taxonomies within a single domain or developing computational models with a
single level of edit g... | 2022-03-08T01:47:42Z | To appear in ACL2022 | null | 10.18653/v1/2022.acl-long.250 | Understanding Iterative Revision from Human-Written Text | ['Wanyu Du', 'Vipul Raheja', 'Dhruv Kumar', 'Zae Myung Kim', 'Melissa Lopez', 'Dongyeop Kang'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 60 | 53 | ['Computer Science'] |
2,203.0385 | UniXcoder: Unified Cross-Modal Pre-training for Code Representation | ['Daya Guo', 'Shuai Lu', 'Nan Duan', 'Yanlin Wang', 'Ming Zhou', 'Jian Yin'] | ['cs.CL', 'cs.PL', 'cs.SE'] | Pre-trained models for programming languages have recently demonstrated great
success on code intelligence. To support both code-related understanding and
generation tasks, recent works attempt to pre-train unified encoder-decoder
models. However, such encoder-decoder framework is sub-optimal for
auto-regressive tasks,... | 2022-03-08T04:48:07Z | Published in ACL 2022 | null | null | null | null | null | null | null | null | null |
2,203.03903 | InstructionNER: A Multi-Task Instruction-Based Generative Framework for
Few-shot NER | ['Liwen Wang', 'Rumei Li', 'Yang Yan', 'Yuanmeng Yan', 'Sirui Wang', 'Wei Wu', 'Weiran Xu'] | ['cs.CL'] | Recently, prompt-based methods have achieved significant performance in
few-shot learning scenarios by bridging the gap between language model
pre-training and fine-tuning for downstream tasks. However, existing prompt
templates are mostly designed for sentence-level tasks and are inappropriate
for sequence labeling ob... | 2022-03-08T07:56:36Z | Work in progress | null | null | null | null | null | null | null | null | null |
2,203.05437 | IndicNLG Benchmark: Multilingual Datasets for Diverse NLG Tasks in Indic
Languages | ['Aman Kumar', 'Himani Shrotriya', 'Prachi Sahu', 'Raj Dabre', 'Ratish Puduppully', 'Anoop Kunchukuttan', 'Amogh Mishra', 'Mitesh M. Khapra', 'Pratyush Kumar'] | ['cs.CL', 'cs.AI'] | Natural Language Generation (NLG) for non-English languages is hampered by
the scarcity of datasets in these languages. In this paper, we present the
IndicNLG Benchmark, a collection of datasets for benchmarking NLG for 11 Indic
languages. We focus on five diverse tasks, namely, biography generation using
Wikipedia inf... | 2022-03-10T15:53:58Z | Accepted at EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,203.05482 | Model soups: averaging weights of multiple fine-tuned models improves
accuracy without increasing inference time | ['Mitchell Wortsman', 'Gabriel Ilharco', 'Samir Yitzhak Gadre', 'Rebecca Roelofs', 'Raphael Gontijo-Lopes', 'Ari S. Morcos', 'Hongseok Namkoong', 'Ali Farhadi', 'Yair Carmon', 'Simon Kornblith', 'Ludwig Schmidt'] | ['cs.LG', 'cs.CL', 'cs.CV'] | The conventional recipe for maximizing model accuracy is to (1) train
multiple models with various hyperparameters and (2) pick the individual model
which performs best on a held-out validation set, discarding the remainder. In
this paper, we revisit the second step of this procedure in the context of
fine-tuning large... | 2022-03-10T17:03:49Z | ICML 2022. The last three authors contributed equally | null | null | null | null | null | null | null | null | null |
2,203.05557 | Conditional Prompt Learning for Vision-Language Models | ['Kaiyang Zhou', 'Jingkang Yang', 'Chen Change Loy', 'Ziwei Liu'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG'] | With the rise of powerful pre-trained vision-language models like CLIP, it
becomes essential to investigate ways to adapt these models to downstream
datasets. A recently proposed method named Context Optimization (CoOp)
introduces the concept of prompt learning -- a recent trend in NLP -- to the
vision domain for adapt... | 2022-03-10T18:59:41Z | CVPR 2022. Update: Adds results on the DOSCO (DOmain Shift in
COntext) benchmark | null | null | Conditional Prompt Learning for Vision-Language Models | ['Kaiyang Zhou', 'Jingkang Yang', 'Chen Change Loy', 'Ziwei Liu'] | 2,022 | Computer Vision and Pattern Recognition | 1,367 | 67 | ['Computer Science'] |
2,203.05659 | NELA-GT-2022: A Large Multi-Labelled News Dataset for The Study of
Misinformation in News Articles | ['Maurício Gruppi', 'Benjamin D. Horne', 'Sibel Adalı'] | ['cs.CL', 'cs.CY', 'cs.LG', 'cs.SI'] | In this paper, we present the fifth installment of the NELA-GT datasets,
NELA-GT-2022. The dataset contains 1,778,361 articles from 361 outlets between
January 1st, 2022 and December 31st, 2022. Just as in past releases of the
dataset, NELA-GT-2022 includes outlet-level veracity labels from Media
Bias/Fact Check and tw... | 2022-03-10T21:58:33Z | Technical report documenting the NELA-GT recent update
(NELA-GT-2022). arXiv admin note: substantial text overlap with
arXiv:2102.04567 | null | null | null | null | null | null | null | null | null |
2,203.06169 | LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text
Retrieval | ['Canwen Xu', 'Daya Guo', 'Nan Duan', 'Julian McAuley'] | ['cs.CL', 'cs.AI', 'cs.IR', 'cs.LG'] | In this paper, we propose LaPraDoR, a pretrained dual-tower dense retriever
that does not require any supervised data for training. Specifically, we first
present Iterative Contrastive Learning (ICoL) that iteratively trains the query
and document encoders with a cache mechanism. ICoL not only enlarges the number
of ne... | 2022-03-11T18:53:12Z | ACL 2022 (Findings) | null | null | LaPraDoR: Unsupervised Pretrained Dense Retriever for Zero-Shot Text Retrieval | ['Canwen Xu', 'Daya Guo', 'Nan Duan', 'Julian McAuley'] | 2,022 | Findings | 49 | 72 | ['Computer Science'] |
2,203.06482 | FiNER: Financial Numeric Entity Recognition for XBRL Tagging | ['Lefteris Loukas', 'Manos Fergadiotis', 'Ilias Chalkidis', 'Eirini Spyropoulou', 'Prodromos Malakasiotis', 'Ion Androutsopoulos', 'Georgios Paliouras'] | ['cs.CL'] | Publicly traded companies are required to submit periodic reports with
eXtensive Business Reporting Language (XBRL) word-level tags. Manually tagging
the reports is tedious and costly. We, therefore, introduce XBRL tagging as a
new entity extraction task for the financial domain and release FiNER-139, a
dataset of 1.1M... | 2022-03-12T16:43:57Z | 13 pages, long paper at ACL 2022 | null | 10.18653/v1/2022.acl-long.303 | null | null | null | null | null | null | null |
2,203.06875 | Improved Universal Sentence Embeddings with Prompt-based Contrastive
Learning and Energy-based Learning | ['Yuxin Jiang', 'Linhan Zhang', 'Wei Wang'] | ['cs.CL'] | Contrastive learning has been demonstrated to be effective in enhancing
pre-trained language models (PLMs) to derive superior universal sentence
embeddings. However, existing contrastive methods still have two limitations.
Firstly, previous works may acquire poor performance under domain shift
settings, thus hindering ... | 2022-03-14T06:07:44Z | 15 pages, 3 figures, Findings of EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,203.07259 | The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for
Large Language Models | ['Eldar Kurtic', 'Daniel Campos', 'Tuan Nguyen', 'Elias Frantar', 'Mark Kurtz', 'Benjamin Fineran', 'Michael Goin', 'Dan Alistarh'] | ['cs.CL', 'cs.LG'] | Transformer-based language models have become a key building block for
natural language processing. While these models are extremely accurate, they
can be too large and computationally intensive to run on standard deployments.
A variety of compression methods, including distillation, quantization,
structured and unstru... | 2022-03-14T16:40:31Z | Accepted to EMNLP 2022 | null | null | The Optimal BERT Surgeon: Scalable and Accurate Second-Order Pruning for Large Language Models | ['Eldar Kurtic', 'Daniel Fernando Campos', 'Tuan Nguyen', 'Elias Frantar', 'Mark Kurtz', 'Ben Fineran', 'M. Goin', 'Dan Alistarh'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 127 | 54 | ['Computer Science'] |
2,203.07362 | CoNTACT: A Dutch COVID-19 Adapted BERT for Vaccine Hesitancy and
Argumentation Detection | ['Jens Lemmens', 'Jens Van Nooten', 'Tim Kreutz', 'Walter Daelemans'] | ['cs.CL'] | We present CoNTACT: a Dutch language model adapted to the domain of COVID-19
tweets. The model was developed by continuing the pre-training phase of RobBERT
(Delobelle, 2020) by using 2.8M Dutch COVID-19 related tweets posted in 2021.
In order to test the performance of the model and compare it to RobBERT, the
two mode... | 2022-03-14T17:55:32Z | null | null | null | null | null | null | null | null | null | null |
2,203.07378 | Dawn of the transformer era in speech emotion recognition: closing the
valence gap | ['Johannes Wagner', 'Andreas Triantafyllopoulos', 'Hagen Wierstorf', 'Maximilian Schmitt', 'Felix Burkhardt', 'Florian Eyben', 'Björn W. Schuller'] | ['eess.AS', 'cs.LG', 'cs.SD'] | Recent advances in transformer-based architectures which are pre-trained in
self-supervised manner have shown great promise in several machine learning
tasks. In the audio domain, such architectures have also been successfully
utilised in the field of speech emotion recognition (SER). However, existing
works have not e... | 2022-03-14T13:21:47Z | null | in IEEE Transactions on Pattern Analysis and Machine Intelligence,
vol. 45, no. 9, pp. 10745-10759, 1 Sept. 2023 | 10.1109/TPAMI.2023.3263585 | null | null | null | null | null | null | null |
2,203.07436 | SuperAnimal pretrained pose estimation models for behavioral analysis | ['Shaokai Ye', 'Anastasiia Filippova', 'Jessy Lauer', 'Steffen Schneider', 'Maxime Vidal', 'Tian Qiu', 'Alexander Mathis', 'Mackenzie Weygandt Mathis'] | ['cs.CV', 'cs.AI', 'q-bio.QM'] | Quantification of behavior is critical in applications ranging from
neuroscience, veterinary medicine and animal conservation efforts. A common key
step for behavioral analysis is first extracting relevant keypoints on animals,
known as pose estimation. However, reliable inference of poses currently
requires domain kno... | 2022-03-14T18:46:57Z | Models and demos available at http://modelzoo.deeplabcut.org | Nature Communications 2024 | 10.1038/s41467-024-48792-2 | null | null | null | null | null | null | null |
2,203.07648 | Contrastive Learning of Sociopragmatic Meaning in Social Media | ['Chiyu Zhang', 'Muhammad Abdul-Mageed', 'Ganesh Jawahar'] | ['cs.CL', 'cs.AI'] | Recent progress in representation and contrastive learning in NLP has not
widely considered the class of \textit{sociopragmatic meaning} (i.e., meaning
in interaction within different language communities). To bridge this gap, we
propose a novel framework for learning task-agnostic representations
transferable to a wid... | 2022-03-15T05:07:04Z | Final camera-ready version for ACL2023 | null | null | null | null | null | null | null | null | null |
2,203.07687 | Compressing Sentence Representation for Semantic Retrieval via
Homomorphic Projective Distillation | ['Xuandong Zhao', 'Zhiguo Yu', 'Ming Wu', 'Lei Li'] | ['cs.CL', 'cs.IR'] | How to learn highly compact yet effective sentence representation?
Pre-trained language models have been effective in many NLP tasks. However,
these models are often huge and produce large sentence embeddings. Moreover,
there is a big performance gap between large and small models. In this paper,
we propose Homomorphic... | 2022-03-15T07:05:43Z | Findings of ACL 2022 | null | null | Compressing Sentence Representation for Semantic Retrieval via Homomorphic Projective Distillation | ['Xuandong Zhao', 'Zhiguo Yu', 'Ming-li Wu', 'Lei Li'] | 2,022 | Findings | 5 | 42 | ['Computer Science'] |
2,203.07722 | ReACC: A Retrieval-Augmented Code Completion Framework | ['Shuai Lu', 'Nan Duan', 'Hojae Han', 'Daya Guo', 'Seung-won Hwang', 'Alexey Svyatkovskiy'] | ['cs.SE', 'cs.AI', 'cs.CL'] | Code completion, which aims to predict the following code token(s) according
to the code context, can improve the productivity of software development.
Recent work has proved that statistical language modeling with transformers can
greatly improve the performance in the code completion task via learning from
large-scal... | 2022-03-15T08:25:08Z | Published in ACL 2022 | null | null | null | null | null | null | null | null | null |
2,203.07836 | Graph Pre-training for AMR Parsing and Generation | ['Xuefeng Bai', 'Yulong Chen', 'Yue Zhang'] | ['cs.CL'] | Abstract meaning representation (AMR) highlights the core semantic
information of text in a graph structure. Recently, pre-trained language models
(PLMs) have advanced tasks of AMR parsing and AMR-to-text generation,
respectively. However, PLMs are typically pre-trained on textual data, thus are
sub-optimal for modelin... | 2022-03-15T12:47:00Z | ACL2022 camera-ready final version | null | null | null | null | null | null | null | null | null |
2,203.08063 | MotionCLIP: Exposing Human Motion Generation to CLIP Space | ['Guy Tevet', 'Brian Gordon', 'Amir Hertz', 'Amit H. Bermano', 'Daniel Cohen-Or'] | ['cs.CV', 'cs.GR'] | We introduce MotionCLIP, a 3D human motion auto-encoder featuring a latent
embedding that is disentangled, well behaved, and supports highly semantic
textual descriptions. MotionCLIP gains its unique power by aligning its latent
space with that of the Contrastive Language-Image Pre-training (CLIP) model.
Aligning the h... | 2022-03-15T16:56:22Z | null | null | null | MotionCLIP: Exposing Human Motion Generation to CLIP Space | ['Guy Tevet', 'Brian Gordon', 'Amir Hertz', 'Amit H. Bermano', 'D. Cohen-Or'] | 2,022 | European Conference on Computer Vision | 348 | 50 | ['Computer Science'] |
2,203.08111 | Does Corpus Quality Really Matter for Low-Resource Languages? | ['Mikel Artetxe', 'Itziar Aldabe', 'Rodrigo Agerri', 'Olatz Perez-de-Viñaspre', 'Aitor Soroa'] | ['cs.CL', 'cs.AI', 'cs.LG'] | The vast majority of non-English corpora are derived from automatically
filtered versions of CommonCrawl. While prior work has identified major issues
on the quality of these datasets (Kreutzer et al., 2021), it is not clear how
this impacts downstream performance. Taking representation learning in Basque
as a case stu... | 2022-03-15T17:40:27Z | EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,203.09095 | Automating Code Review Activities by Large-Scale Pre-training | ['Zhiyu Li', 'Shuai Lu', 'Daya Guo', 'Nan Duan', 'Shailesh Jannu', 'Grant Jenks', 'Deep Majumder', 'Jared Green', 'Alexey Svyatkovskiy', 'Shengyu Fu', 'Neel Sundaresan'] | ['cs.SE', 'cs.AI'] | Code review is an essential part to software development lifecycle since it
aims at guaranteeing the quality of codes. Modern code review activities
necessitate developers viewing, understanding and even running the programs to
assess logic, functionality, latency, style and other factors. It turns out
that developers ... | 2022-03-17T05:40:13Z | ESEC/FSE 2022, camera-ready version | null | null | null | null | null | null | null | null | null |
2,203.09178 | Multilingual Detection of Personal Employment Status on Twitter | ['Manuel Tonneau', 'Dhaval Adjodah', 'João Palotti', 'Nir Grinberg', 'Samuel Fraiberger'] | ['cs.CL'] | Detecting disclosures of individuals' employment status on social media can
provide valuable information to match job seekers with suitable vacancies,
offer social protection, or measure labor market flows. However, identifying
such personal disclosures is a challenging task due to their rarity in a sea of
social media... | 2022-03-17T08:55:18Z | ACL 2022 main conference. Data and models available at
https://github.com/manueltonneau/twitter-unemployment | null | 10.18653/v1/2022.acl-long.453 | null | null | null | null | null | null | null |
2,203.09313 | EVA2.0: Investigating Open-Domain Chinese Dialogue Systems with
Large-Scale Pre-Training | ['Yuxian Gu', 'Jiaxin Wen', 'Hao Sun', 'Yi Song', 'Pei Ke', 'Chujie Zheng', 'Zheng Zhang', 'Jianzhu Yao', 'Lei Liu', 'Xiaoyan Zhu', 'Minlie Huang'] | ['cs.CL', 'cs.AI'] | Large-scale pre-training has shown remarkable performance in building
open-domain dialogue systems. However, previous works mainly focus on showing
and evaluating the conversational performance of the released dialogue model,
ignoring the discussion of some key factors towards a powerful human-like
chatbot, especially ... | 2022-03-17T13:33:17Z | Machine Intelligence Research.
https://link.springer.com/article/10.1007/s11633-022-1387-3 . 12 pages, 5
figures. The code and pre-trained models are publicly available at
https://github.com/thu-coai/EVA | null | 10.1007/s11633-022-1387-3 | EVA2.0: Investigating Open-domain Chinese Dialogue Systems with Large-scale Pre-training | ['Yuxian Gu', 'Jiaxin Wen', 'Hao Sun', 'Yi Song', 'Pei Ke', 'Chujie Zheng', 'Zheng Zhang', 'Jianzhu Yao', 'Lei Liu', 'Xiaoyan Zhu', 'Jie Tang', 'Minlie Huang'] | 2,022 | Machine Intelligence Research | 55 | 70 | ['Computer Science'] |
2,203.09509 | ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and
Implicit Hate Speech Detection | ['Thomas Hartvigsen', 'Saadia Gabriel', 'Hamid Palangi', 'Maarten Sap', 'Dipankar Ray', 'Ece Kamar'] | ['cs.CL'] | Toxic language detection systems often falsely flag text that contains
minority group mentions as toxic, as those groups are often the targets of
online hate. Such over-reliance on spurious correlations also causes systems to
struggle with detecting implicitly toxic language. To help mitigate these
issues, we create To... | 2022-03-17T17:57:56Z | Published as a long paper at ACL 2022. Code:
https://github.com/microsoft/TOXIGEN | null | null | ToxiGen: A Large-Scale Machine-Generated Dataset for Adversarial and Implicit Hate Speech Detection | ['Thomas Hartvigsen', 'Saadia Gabriel', 'Hamid Palangi', 'Maarten Sap', 'Dipankar Ray', 'Ece Kamar'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 393 | 69 | ['Computer Science'] |
2,203.09893 | A Lightweight Instrument-Agnostic Model for Polyphonic Note
Transcription and Multipitch Estimation | ['Rachel M. Bittner', 'Juan José Bosch', 'David Rubinstein', 'Gabriel Meseguer-Brocal', 'Sebastian Ewert'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Automatic Music Transcription (AMT) has been recognized as a key enabling
technology with a wide range of applications. Given the task's complexity, best
results have typically been reported for systems focusing on specific settings,
e.g. instrument-specific systems tend to yield improved results over
instrument-agnost... | 2022-03-18T12:07:36Z | null | null | null | A Lightweight Instrument-Agnostic Model for Polyphonic Note Transcription and Multipitch Estimation | ['Rachel M. Bittner', 'Juan J. Bosch', 'David Rubinstein', 'Gabriel Meseguer-Brocal', 'Sebastian Ewert'] | 2,022 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 43 | 34 | ['Computer Science', 'Engineering'] |
2,203.10244 | ChartQA: A Benchmark for Question Answering about Charts with Visual and
Logical Reasoning | ['Ahmed Masry', 'Do Xuan Long', 'Jia Qing Tan', 'Shafiq Joty', 'Enamul Hoque'] | ['cs.CL'] | Charts are very popular for analyzing data. When exploring charts, people
often ask a variety of complex reasoning questions that involve several logical
and arithmetic operations. They also commonly refer to visual features of a
chart in their questions. However, most existing datasets do not focus on such
complex rea... | 2022-03-19T05:00:30Z | Accepted by ACL 2022 Findings | null | null | null | null | null | null | null | null | null |
2,203.1094 | Quality Controlled Paraphrase Generation | ['Elron Bandel', 'Ranit Aharonov', 'Michal Shmueli-Scheuer', 'Ilya Shnayderman', 'Noam Slonim', 'Liat Ein-Dor'] | ['cs.CL'] | Paraphrase generation has been widely used in various downstream tasks. Most
tasks benefit mainly from high quality paraphrases, namely those that are
semantically similar to, yet linguistically diverse from, the original
sentence. Generating high-quality paraphrases is challenging as it becomes
increasingly hard to pr... | 2022-03-21T13:09:59Z | Accepted as a long paper at ACL 2022 | null | null | Quality Controlled Paraphrase Generation | ['Elron Bandel', 'R. Aharonov', 'Michal Shmueli-Scheuer', 'Ilya Shnayderman', 'N. Slonim', 'L. Ein-Dor'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 38 | 43 | ['Computer Science'] |
2,203.11593 | Unified Negative Pair Generation toward Well-discriminative Feature
Space for Face Recognition | ['Junuk Jung', 'Seonhoon Lee', 'Heung-Seon Oh', 'Yongjun Park', 'Joochan Park', 'Sungbin Son'] | ['cs.CV'] | The goal of face recognition (FR) can be viewed as a pair similarity
optimization problem, maximizing a similarity set $\mathcal{S}^p$ over positive
pairs, while minimizing similarity set $\mathcal{S}^n$ over negative pairs.
Ideally, it is expected that FR models form a well-discriminative feature space
(WDFS) that sat... | 2022-03-22T10:21:11Z | 9 pages, 6 figures, Published at BMVC22 | null | null | null | null | null | null | null | null | null |
2,203.11635 | Feature Distribution Matching for Federated Domain Generalization | ['Yuwei Sun', 'Ng Chong', 'Hideya Ochiai'] | ['cs.LG'] | Multi-source domain adaptation has been intensively studied. The distribution
shift in features inherent to specific domains causes the negative transfer
problem, degrading a model's generality to unseen tasks. In Federated Learning
(FL), learned model parameters are shared to train a global model that
leverages the un... | 2022-03-22T11:42:25Z | Accepted for Asian Conference on Machine Learning (ACML 2022) | null | null | null | null | null | null | null | null | null |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.