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2,210.07228 | Language Model Decoding as Likelihood-Utility Alignment | ['Martin Josifoski', 'Maxime Peyrard', 'Frano Rajic', 'Jiheng Wei', 'Debjit Paul', 'Valentin Hartmann', 'Barun Patra', 'Vishrav Chaudhary', 'Emre Kıcıman', 'Boi Faltings', 'Robert West'] | ['cs.CL', 'cs.LG'] | A critical component of a successful language generation pipeline is the
decoding algorithm. However, the general principles that should guide the
choice of a decoding algorithm remain unclear. Previous works only compare
decoding algorithms in narrow scenarios, and their findings do not generalize
across tasks. We arg... | 2022-10-13T17:55:51Z | Accepted at EACL (Findings) 2023 | null | null | Language Model Decoding as Likelihood–Utility Alignment | ['Martin Josifoski', 'Maxime Peyrard', 'Frano Rajic', 'Jiheng Wei', 'Debjit Paul', 'Valentin Hartmann', 'Barun Patra', 'Vishrav Chaudhary', 'Emre Kıcıman', 'B. Faltings', 'Robert West'] | 2,022 | Findings | 5 | 47 | ['Computer Science'] |
2,210.07316 | MTEB: Massive Text Embedding Benchmark | ['Niklas Muennighoff', 'Nouamane Tazi', 'Loïc Magne', 'Nils Reimers'] | ['cs.CL', 'cs.IR', 'cs.LG'] | Text embeddings are commonly evaluated on a small set of datasets from a
single task not covering their possible applications to other tasks. It is
unclear whether state-of-the-art embeddings on semantic textual similarity
(STS) can be equally well applied to other tasks like clustering or reranking.
This makes progres... | 2022-10-13T19:42:08Z | 24 pages, 14 tables, 6 figures | null | null | null | null | null | null | null | null | null |
2,210.07468 | Transparency Helps Reveal When Language Models Learn Meaning | ['Zhaofeng Wu', 'William Merrill', 'Hao Peng', 'Iz Beltagy', 'Noah A. Smith'] | ['cs.CL'] | Many current NLP systems are built from language models trained to optimize
unsupervised objectives on large amounts of raw text. Under what conditions
might such a procedure acquire meaning? Our systematic experiments with
synthetic data reveal that, with languages where all expressions have
context-independent denota... | 2022-10-14T02:35:19Z | Accepted for publication in Transactions of the Association for
Computational Linguistics (TACL), 2023. Author's final version (pre-MIT Press
publication) | null | null | null | null | null | null | null | null | null |
2,210.07489 | The Surprisingly Straightforward Scene Text Removal Method With Gated
Attention and Region of Interest Generation: A Comprehensive Prominent Model
Analysis | ['Hyeonsu Lee', 'Chankyu Choi'] | ['cs.CV'] | Scene text removal (STR), a task of erasing text from natural scene images,
has recently attracted attention as an important component of editing text or
concealing private information such as ID, telephone, and license plate
numbers. While there are a variety of different methods for STR actively being
researched, it ... | 2022-10-14T03:34:21Z | Accepted by ECCV 2022 | null | null | null | null | null | null | null | null | null |
2,210.08402 | LAION-5B: An open large-scale dataset for training next generation
image-text models | ['Christoph Schuhmann', 'Romain Beaumont', 'Richard Vencu', 'Cade Gordon', 'Ross Wightman', 'Mehdi Cherti', 'Theo Coombes', 'Aarush Katta', 'Clayton Mullis', 'Mitchell Wortsman', 'Patrick Schramowski', 'Srivatsa Kundurthy', 'Katherine Crowson', 'Ludwig Schmidt', 'Robert Kaczmarczyk', 'Jenia Jitsev'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Groundbreaking language-vision architectures like CLIP and DALL-E proved the
utility of training on large amounts of noisy image-text data, without relying
on expensive accurate labels used in standard vision unimodal supervised
learning. The resulting models showed capabilities of strong text-guided image
generation a... | 2022-10-16T00:08:18Z | 36th Conference on Neural Information Processing Systems (NeurIPS
2022), Track on Datasets and Benchmarks. OpenReview:
https://openreview.net/forum?id=M3Y74vmsMcY | null | null | LAION-5B: An open large-scale dataset for training next generation image-text models | ['Christoph Schuhmann', 'R. Beaumont', 'R. Vencu', 'Cade Gordon', 'Ross Wightman', 'Mehdi Cherti', 'Theo Coombes', 'Aarush Katta', 'Clayton Mullis', 'Mitchell Wortsman', 'P. Schramowski', 'Srivatsa Kundurthy', 'Katherine Crowson', 'Ludwig Schmidt', 'R. Kaczmarczyk', 'J. Jitsev'] | 2,022 | Neural Information Processing Systems | 3,522 | 109 | ['Computer Science'] |
2,210.08431 | Modeling Context With Linear Attention for Scalable Document-Level
Translation | ['Zhaofeng Wu', 'Hao Peng', 'Nikolaos Pappas', 'Noah A. Smith'] | ['cs.CL'] | Document-level machine translation leverages inter-sentence dependencies to
produce more coherent and consistent translations. However, these models,
predominantly based on transformers, are difficult to scale to long documents
as their attention layers have quadratic complexity in the sequence length.
Recent efforts o... | 2022-10-16T03:41:50Z | Findings of EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.085 | This Patient Looks Like That Patient: Prototypical Networks for
Interpretable Diagnosis Prediction from Clinical Text | ['Betty van Aken', 'Jens-Michalis Papaioannou', 'Marcel G. Naik', 'Georgios Eleftheriadis', 'Wolfgang Nejdl', 'Felix A. Gers', 'Alexander Löser'] | ['cs.CL'] | The use of deep neural models for diagnosis prediction from clinical text has
shown promising results. However, in clinical practice such models must not
only be accurate, but provide doctors with interpretable and helpful results.
We introduce ProtoPatient, a novel method based on prototypical networks and
label-wise ... | 2022-10-16T10:12:07Z | AACL-IJCNLP 2022 Main Conference (Long Paper) | null | null | null | null | null | null | null | null | null |
2,210.08511 | CDConv: A Benchmark for Contradiction Detection in Chinese Conversations | ['Chujie Zheng', 'Jinfeng Zhou', 'Yinhe Zheng', 'Libiao Peng', 'Zhen Guo', 'Wenquan Wu', 'Zhengyu Niu', 'Hua Wu', 'Minlie Huang'] | ['cs.CL'] | Dialogue contradiction is a critical issue in open-domain dialogue systems.
The contextualization nature of conversations makes dialogue contradiction
detection rather challenging. In this work, we propose a benchmark for
Contradiction Detection in Chinese Conversations, namely CDConv. It contains
12K multi-turn conver... | 2022-10-16T11:37:09Z | EMNLP 2022 | null | null | CDConv: A Benchmark for Contradiction Detection in Chinese Conversations | ['Chujie Zheng', 'Jinfeng Zhou', 'Yinhe Zheng', 'Libiao Peng', 'Zhen Guo', 'Wenquan Wu', 'Zhengyu Niu', 'Hua Wu', 'Minlie Huang'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 14 | 53 | ['Computer Science'] |
2,210.0859 | Zero-Shot Learners for Natural Language Understanding via a Unified
Multiple Choice Perspective | ['Ping Yang', 'Junjie Wang', 'Ruyi Gan', 'Xinyu Zhu', 'Lin Zhang', 'Ziwei Wu', 'Xinyu Gao', 'Jiaxing Zhang', 'Tetsuya Sakai'] | ['cs.CL'] | We propose a new paradigm for zero-shot learners that is format agnostic,
i.e., it is compatible with any format and applicable to a list of language
tasks, such as text classification, commonsense reasoning, coreference
resolution, and sentiment analysis. Zero-shot learning aims to train a model on
a given task such t... | 2022-10-16T17:24:06Z | EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.08859 | Social Biases in Automatic Evaluation Metrics for NLG | ['Mingqi Gao', 'Xiaojun Wan'] | ['cs.CL', 'cs.AI'] | Many studies have revealed that word embeddings, language models, and models
for specific downstream tasks in NLP are prone to social biases, especially
gender bias. Recently these techniques have been gradually applied to automatic
evaluation metrics for text generation. In the paper, we propose an evaluation
method b... | 2022-10-17T08:55:26Z | null | null | null | Social Biases in Automatic Evaluation Metrics for NLG | ['Mingqi Gao', 'Xiaojun Wan'] | 2,022 | arXiv.org | 3 | 63 | ['Computer Science'] |
2,210.08873 | Semi-Supervised Knowledge-Grounded Pre-training for Task-Oriented Dialog
Systems | ['Weihao Zeng', 'Keqing He', 'Zechen Wang', 'Dayuan Fu', 'Guanting Dong', 'Ruotong Geng', 'Pei Wang', 'Jingang Wang', 'Chaobo Sun', 'Wei Wu', 'Weiran Xu'] | ['cs.CL'] | Recent advances in neural approaches greatly improve task-oriented dialogue
(TOD) systems which assist users to accomplish their goals. However, such
systems rely on costly manually labeled dialogs which are not available in
practical scenarios. In this paper, we present our models for Track 2 of the
SereTOD 2022 chall... | 2022-10-17T09:10:03Z | Accepted at the SereTOD 2022 Workshop, EMNLP 2022 | null | null | Semi-Supervised Knowledge-Grounded Pre-training for Task-Oriented Dialog Systems | ['Weihao Zeng', 'Keqing He', 'Zechen Wang', 'Dayuan Fu', 'Guanting Dong', 'Ruotong Geng', 'Pei Wang', 'Jingang Wang', 'Chaobo Sun', 'Wei Wu', 'Weiran Xu'] | 2,022 | SERETOD | 16 | 23 | ['Computer Science'] |
2,210.09184 | Packed-Ensembles for Efficient Uncertainty Estimation | ['Olivier Laurent', 'Adrien Lafage', 'Enzo Tartaglione', 'Geoffrey Daniel', 'Jean-Marc Martinez', 'Andrei Bursuc', 'Gianni Franchi'] | ['cs.LG', 'stat.ML'] | Deep Ensembles (DE) are a prominent approach for achieving excellent
performance on key metrics such as accuracy, calibration, uncertainty
estimation, and out-of-distribution detection. However, hardware limitations of
real-world systems constrain to smaller ensembles and lower-capacity networks,
significantly deterior... | 2022-10-17T15:37:04Z | Published as a conference paper at ICLR 2023 (notable 25%) | null | null | null | null | null | null | null | null | null |
2,210.09261 | Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them | ['Mirac Suzgun', 'Nathan Scales', 'Nathanael Schärli', 'Sebastian Gehrmann', 'Yi Tay', 'Hyung Won Chung', 'Aakanksha Chowdhery', 'Quoc V. Le', 'Ed H. Chi', 'Denny Zhou', 'Jason Wei'] | ['cs.CL', 'cs.AI'] | BIG-Bench (Srivastava et al., 2022) is a diverse evaluation suite that
focuses on tasks believed to be beyond the capabilities of current language
models. Language models have already made good progress on this benchmark, with
the best model in the BIG-Bench paper outperforming average reported
human-rater results on 6... | 2022-10-17T17:08:26Z | GitHub repository: https://github.com/suzgunmirac/BIG-Bench-Hard | null | null | null | null | null | null | null | null | null |
2,210.09298 | What Makes Convolutional Models Great on Long Sequence Modeling? | ['Yuhong Li', 'Tianle Cai', 'Yi Zhang', 'Deming Chen', 'Debadeepta Dey'] | ['cs.LG', 'cs.AI', 'cs.CV', 'stat.ML'] | Convolutional models have been widely used in multiple domains. However, most
existing models only use local convolution, making the model unable to handle
long-range dependency efficiently. Attention overcomes this problem by
aggregating global information but also makes the computational complexity
quadratic to the s... | 2022-10-17T17:53:29Z | The code is available at https://github.com/ctlllll/SGConv | null | null | What Makes Convolutional Models Great on Long Sequence Modeling? | ['Yuhong Li', 'Tianle Cai', 'Yi Zhang', 'De-huai Chen', 'Debadeepta Dey'] | 2,022 | International Conference on Learning Representations | 99 | 53 | ['Computer Science', 'Mathematics'] |
2,210.09338 | Deep Bidirectional Language-Knowledge Graph Pretraining | ['Michihiro Yasunaga', 'Antoine Bosselut', 'Hongyu Ren', 'Xikun Zhang', 'Christopher D Manning', 'Percy Liang', 'Jure Leskovec'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Pretraining a language model (LM) on text has been shown to help various
downstream NLP tasks. Recent works show that a knowledge graph (KG) can
complement text data, offering structured background knowledge that provides a
useful scaffold for reasoning. However, these works are not pretrained to learn
a deep fusion of... | 2022-10-17T18:02:52Z | Published at NeurIPS 2022. Code, data, and trained models are
available at https://github.com/michiyasunaga/dragon | null | null | Deep Bidirectional Language-Knowledge Graph Pretraining | ['Michihiro Yasunaga', 'Antoine Bosselut', 'Hongyu Ren', 'Xikun Zhang', 'Christopher D. Manning', 'Percy Liang', 'J. Leskovec'] | 2,022 | Neural Information Processing Systems | 205 | 88 | ['Computer Science'] |
2,210.09984 | Making a MIRACL: Multilingual Information Retrieval Across a Continuum
of Languages | ['Xinyu Zhang', 'Nandan Thakur', 'Odunayo Ogundepo', 'Ehsan Kamalloo', 'David Alfonso-Hermelo', 'Xiaoguang Li', 'Qun Liu', 'Mehdi Rezagholizadeh', 'Jimmy Lin'] | ['cs.IR', 'cs.CL'] | MIRACL (Multilingual Information Retrieval Across a Continuum of Languages)
is a multilingual dataset we have built for the WSDM 2023 Cup challenge that
focuses on ad hoc retrieval across 18 different languages, which collectively
encompass over three billion native speakers around the world. These languages
have diver... | 2022-10-18T16:47:18Z | null | null | null | Making a MIRACL: Multilingual Information Retrieval Across a Continuum of Languages | ['Xinyu Crystina Zhang', 'Nandan Thakur', 'Odunayo Ogundepo', 'Ehsan Kamalloo', 'David Alfonso-Hermelo', 'Xiaoguang Li', 'Qun Liu', 'Mehdi Rezagholizadeh', 'Jimmy J. Lin'] | 2,022 | arXiv.org | 55 | 29 | ['Computer Science'] |
2,210.09996 | Perceptual Grouping in Contrastive Vision-Language Models | ['Kanchana Ranasinghe', 'Brandon McKinzie', 'Sachin Ravi', 'Yinfei Yang', 'Alexander Toshev', 'Jonathon Shlens'] | ['cs.CV', 'cs.LG'] | Recent advances in zero-shot image recognition suggest that vision-language
models learn generic visual representations with a high degree of semantic
information that may be arbitrarily probed with natural language phrases.
Understanding an image, however, is not just about understanding what content
resides within an... | 2022-10-18T17:01:35Z | Accepted and presented at ICCV 2023 | null | null | null | null | null | null | null | null | null |
2,210.10163 | MedCLIP: Contrastive Learning from Unpaired Medical Images and Text | ['Zifeng Wang', 'Zhenbang Wu', 'Dinesh Agarwal', 'Jimeng Sun'] | ['cs.CV', 'cs.CL'] | Existing vision-text contrastive learning like CLIP aims to match the paired
image and caption embeddings while pushing others apart, which improves
representation transferability and supports zero-shot prediction. However,
medical image-text datasets are orders of magnitude below the general images
and captions from t... | 2022-10-18T21:06:29Z | EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.10258 | Continued Pretraining for Better Zero- and Few-Shot Promptability | ['Zhaofeng Wu', 'Robert L. Logan IV', 'Pete Walsh', 'Akshita Bhagia', 'Dirk Groeneveld', 'Sameer Singh', 'Iz Beltagy'] | ['cs.CL'] | Recently introduced language model prompting methods can achieve high
accuracy in zero- and few-shot settings while requiring few to no learned
task-specific parameters. Nevertheless, these methods still often trail behind
full model finetuning. In this work, we investigate if a dedicated continued
pretraining stage co... | 2022-10-19T02:41:51Z | EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.1034 | The Devil in Linear Transformer | ['Zhen Qin', 'XiaoDong Han', 'Weixuan Sun', 'Dongxu Li', 'Lingpeng Kong', 'Nick Barnes', 'Yiran Zhong'] | ['cs.CL', 'cs.LG'] | Linear transformers aim to reduce the quadratic space-time complexity of
vanilla transformers. However, they usually suffer from degraded performances
on various tasks and corpus. In this paper, we examine existing kernel-based
linear transformers and identify two key issues that lead to such performance
gaps: 1) unbou... | 2022-10-19T07:15:35Z | accepted to EMNLP2022 | null | null | The Devil in Linear Transformer | ['Zhen Qin', 'Xiaodong Han', 'Weixuan Sun', 'Dongxu Li', 'Lingpeng Kong', 'Nick Barnes', 'Yiran Zhong'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 74 | 34 | ['Computer Science'] |
2,210.10341 | BioGPT: Generative Pre-trained Transformer for Biomedical Text
Generation and Mining | ['Renqian Luo', 'Liai Sun', 'Yingce Xia', 'Tao Qin', 'Sheng Zhang', 'Hoifung Poon', 'Tie-Yan Liu'] | ['cs.CL', 'cs.AI'] | Pre-trained language models have attracted increasing attention in the
biomedical domain, inspired by their great success in the general natural
language domain. Among the two main branches of pre-trained language models in
the general language domain, i.e., BERT (and its variants) and GPT (and its
variants), the first... | 2022-10-19T07:17:39Z | Published at Briefings in Bioinformatics. Code is available at
https://github.com/microsoft/BioGPT | Briefings in Bioinformatics, 2022;, bbac409 | 10.1093/bib/bbac409 | BioGPT: Generative Pre-trained Transformer for Biomedical Text Generation and Mining | ['Renqian Luo', 'Liai Sun', 'Yingce Xia', 'Tao Qin', 'Sheng Zhang', 'Hoifung Poon', 'Tie-Yan Liu'] | 2,022 | Briefings Bioinform. | 859 | 59 | ['Computer Science', 'Medicine'] |
2,210.10473 | FaceDancer: Pose- and Occlusion-Aware High Fidelity Face Swapping | ['Felix Rosberg', 'Eren Erdal Aksoy', 'Fernando Alonso-Fernandez', 'Cristofer Englund'] | ['cs.CV'] | In this work, we present a new single-stage method for subject agnostic face
swapping and identity transfer, named FaceDancer. We have two major
contributions: Adaptive Feature Fusion Attention (AFFA) and Interpreted Feature
Similarity Regularization (IFSR). The AFFA module is embedded in the decoder
and adaptively lea... | 2022-10-19T11:31:38Z | Fixed the supplementary material layout in the end (past references).
Added link to video results, which is mentioned in Results but was missing in
the supplementary material | null | null | FaceDancer: Pose- and Occlusion-Aware High Fidelity Face Swapping | ['Felix Rosberg', 'E. Aksoy', 'F. Alonso-Fernandez', 'Cristofer Englund'] | 2,022 | IEEE Workshop/Winter Conference on Applications of Computer Vision | 33 | 46 | ['Computer Science'] |
2,210.10634 | RankT5: Fine-Tuning T5 for Text Ranking with Ranking Losses | ['Honglei Zhuang', 'Zhen Qin', 'Rolf Jagerman', 'Kai Hui', 'Ji Ma', 'Jing Lu', 'Jianmo Ni', 'Xuanhui Wang', 'Michael Bendersky'] | ['cs.IR', 'cs.CL'] | Recently, substantial progress has been made in text ranking based on
pretrained language models such as BERT. However, there are limited studies on
how to leverage more powerful sequence-to-sequence models such as T5. Existing
attempts usually formulate text ranking as classification and rely on
postprocessing to obta... | 2022-10-12T20:51:49Z | 13 pages | null | null | null | null | null | null | null | null | null |
2,210.10996 | Improving Chinese Spelling Check by Character Pronunciation Prediction:
The Effects of Adaptivity and Granularity | ['Jiahao Li', 'Quan Wang', 'Zhendong Mao', 'Junbo Guo', 'Yanyan Yang', 'Yongdong Zhang'] | ['cs.CL'] | Chinese spelling check (CSC) is a fundamental NLP task that detects and
corrects spelling errors in Chinese texts. As most of these spelling errors are
caused by phonetic similarity, effectively modeling the pronunciation of
Chinese characters is a key factor for CSC. In this paper, we consider
introducing an auxiliary... | 2022-10-20T03:42:35Z | To appear at the main conference of EMNLP 2022 | null | null | Improving Chinese Spelling Check by Character Pronunciation Prediction: The Effects of Adaptivity and Granularity | ['Jiahao Li', 'Quang Wang', 'Zhendong Mao', 'Junbo Guo', 'Yanyan Yang', 'Yongdong Zhang'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 27 | 29 | ['Computer Science'] |
2,210.11399 | Transcending Scaling Laws with 0.1% Extra Compute | ['Yi Tay', 'Jason Wei', 'Hyung Won Chung', 'Vinh Q. Tran', 'David R. So', 'Siamak Shakeri', 'Xavier Garcia', 'Huaixiu Steven Zheng', 'Jinfeng Rao', 'Aakanksha Chowdhery', 'Denny Zhou', 'Donald Metzler', 'Slav Petrov', 'Neil Houlsby', 'Quoc V. Le', 'Mostafa Dehghani'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Scaling language models improves performance but comes with significant
computational costs. This paper proposes UL2R, a method that substantially
improves existing language models and their scaling curves with a relatively
tiny amount of extra compute. The key idea is to continue training a
state-of-the-art large lang... | 2022-10-20T16:46:41Z | V2 has updated references/related work | null | null | null | null | null | null | null | null | null |
2,210.11416 | Scaling Instruction-Finetuned Language Models | ['Hyung Won Chung', 'Le Hou', 'Shayne Longpre', 'Barret Zoph', 'Yi Tay', 'William Fedus', 'Yunxuan Li', 'Xuezhi Wang', 'Mostafa Dehghani', 'Siddhartha Brahma', 'Albert Webson', 'Shixiang Shane Gu', 'Zhuyun Dai', 'Mirac Suzgun', 'Xinyun Chen', 'Aakanksha Chowdhery', 'Alex Castro-Ros', 'Marie Pellat', 'Kevin Robinson', '... | ['cs.LG', 'cs.CL'] | Finetuning language models on a collection of datasets phrased as
instructions has been shown to improve model performance and generalization to
unseen tasks. In this paper we explore instruction finetuning with a particular
focus on (1) scaling the number of tasks, (2) scaling the model size, and (3)
finetuning on cha... | 2022-10-20T16:58:32Z | Public checkpoints:
https://huggingface.co/docs/transformers/model_doc/flan-t5 | null | null | Scaling Instruction-Finetuned Language Models | ['Hyung Won Chung', 'Le Hou', 'S. Longpre', 'Barret Zoph', 'Yi Tay', 'W. Fedus', 'Eric Li', 'Xuezhi Wang', 'Mostafa Dehghani', 'Siddhartha Brahma', 'Albert Webson', 'S. Gu', 'Zhuyun Dai', 'Mirac Suzgun', 'Xinyun Chen', 'Aakanksha Chowdhery', 'Dasha Valter', 'Sharan Narang', 'Gaurav Mishra', 'Adams Wei Yu', 'Vincent Zha... | 2,022 | Journal of machine learning research | 3,180 | 106 | ['Computer Science'] |
2,210.11621 | SMaLL-100: Introducing Shallow Multilingual Machine Translation Model
for Low-Resource Languages | ['Alireza Mohammadshahi', 'Vassilina Nikoulina', 'Alexandre Berard', 'Caroline Brun', 'James Henderson', 'Laurent Besacier'] | ['cs.CL', 'cs.AI', 'cs.LG'] | In recent years, multilingual machine translation models have achieved
promising performance on low-resource language pairs by sharing information
between similar languages, thus enabling zero-shot translation. To overcome the
"curse of multilinguality", these models often opt for scaling up the number of
parameters, w... | 2022-10-20T22:32:29Z | Accepted to EMNLP 2022 | https://aclanthology.org/2022.emnlp-main.571 | null | null | null | null | null | null | null | null |
2,210.11744 | AfroLID: A Neural Language Identification Tool for African Languages | ['Ife Adebara', 'AbdelRahim Elmadany', 'Muhammad Abdul-Mageed', 'Alcides Alcoba Inciarte'] | ['cs.CL', 'cs.LG'] | Language identification (LID) is a crucial precursor for NLP, especially for
mining web data. Problematically, most of the world's 7000+ languages today are
not covered by LID technologies. We address this pressing issue for Africa by
introducing AfroLID, a neural LID toolkit for $517$ African languages and
varieties. ... | 2022-10-21T05:45:50Z | To appear at EMNLP 2022 Main conference | null | null | AfroLID: A Neural Language Identification Tool for African Languages | ['Ife Adebara', 'AbdelRahim Elmadany', 'M. Abdul-Mageed', 'Alcides Alcoba Inciarte'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 33 | 79 | ['Computer Science'] |
2,210.11771 | InforMask: Unsupervised Informative Masking for Language Model
Pretraining | ['Nafis Sadeq', 'Canwen Xu', 'Julian McAuley'] | ['cs.CL'] | Masked language modeling is widely used for pretraining large language models
for natural language understanding (NLU). However, random masking is
suboptimal, allocating an equal masking rate for all tokens. In this paper, we
propose InforMask, a new unsupervised masking strategy for training masked
language models. In... | 2022-10-21T07:10:56Z | null | null | null | InforMask: Unsupervised Informative Masking for Language Model Pretraining | ['Nafis Sadeq', 'Canwen Xu', 'Julian McAuley'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 13 | 39 | ['Computer Science'] |
2,210.11892 | BioLORD: Learning Ontological Representations from Definitions (for
Biomedical Concepts and their Textual Descriptions) | ['François Remy', 'Kris Demuynck', 'Thomas Demeester'] | ['cs.CL', 'cs.IR'] | This work introduces BioLORD, a new pre-training strategy for producing
meaningful representations for clinical sentences and biomedical concepts.
State-of-the-art methodologies operate by maximizing the similarity in
representation of names referring to the same concept, and preventing collapse
through contrastive lea... | 2022-10-21T11:43:59Z | Accepted in Findings of EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.11899 | A Semi-supervised Approach for a Better Translation of Sentiment in
Dialectical Arabic UGT | ['Hadeel Saadany', 'Constantin Orasan', 'Emad Mohamed', 'Ashraf Tantawy'] | ['cs.CL'] | In the online world, Machine Translation (MT) systems are extensively used to
translate User-Generated Text (UGT) such as reviews, tweets, and social media
posts, where the main message is often the author's positive or negative
attitude towards the topic of the text. However, MT systems still lack accuracy
in some low... | 2022-10-21T11:55:55Z | WANLP2022 at EMNLP 2022 | Association for Computational Linguistics 2022 | null | null | null | null | null | null | null | null |
2,210.12374 | ReasTAP: Injecting Table Reasoning Skills During Pre-training via
Synthetic Reasoning Examples | ['Yilun Zhao', 'Linyong Nan', 'Zhenting Qi', 'Rui Zhang', 'Dragomir Radev'] | ['cs.CL'] | Reasoning over tabular data requires both table structure understanding and a
broad set of table reasoning skills. Current models with table-specific
architectures and pre-training methods perform well on understanding table
structures, but they still struggle with tasks that require various table
reasoning skills. In ... | 2022-10-22T07:04:02Z | accepted by EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.124 | Varifocal Question Generation for Fact-checking | ['Nedjma Ousidhoum', 'Zhangdie Yuan', 'Andreas Vlachos'] | ['cs.CL'] | Fact-checking requires retrieving evidence related to a claim under
investigation. The task can be formulated as question generation based on a
claim, followed by question answering. However, recent question generation
approaches assume that the answer is known and typically contained in a passage
given as input, where... | 2022-10-22T09:41:47Z | Accepted at EMNLP 2022, 13 pages | null | null | Varifocal Question Generation for Fact-checking | ['N. Ousidhoum', 'Moy Yuan', 'Andreas Vlachos'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 25 | 59 | ['Computer Science'] |
2,210.12478 | DiscoSense: Commonsense Reasoning with Discourse Connectives | ['Prajjwal Bhargava', 'Vincent Ng'] | ['cs.CL'] | We present DiscoSense, a benchmark for commonsense reasoning via
understanding a wide variety of discourse connectives. We generate compelling
distractors in DiscoSense using Conditional Adversarial Filtering, an extension
of Adversarial Filtering that employs conditional generation. We show that
state-of-the-art pre-t... | 2022-10-22T15:33:38Z | EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.12579 | Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix
Factorization | ['Nishant Yadav', 'Nicholas Monath', 'Rico Angell', 'Manzil Zaheer', 'Andrew McCallum'] | ['cs.CL', 'cs.IR', 'cs.LG'] | Efficient k-nearest neighbor search is a fundamental task, foundational for
many problems in NLP. When the similarity is measured by dot-product between
dual-encoder vectors or $\ell_2$-distance, there already exist many scalable
and efficient search methods. But not so when similarity is measured by more
accurate and ... | 2022-10-23T00:32:04Z | EMNLP 2022. Code for all experiments and model checkpoints are
available at https://github.com/iesl/anncur | null | null | Efficient Nearest Neighbor Search for Cross-Encoder Models using Matrix Factorization | ['Nishant Yadav', 'Nicholas Monath', 'Rico Angell', 'M. Zaheer', 'A. McCallum'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 13 | 52 | ['Computer Science'] |
2,210.13001 | Modeling Information Change in Science Communication with Semantically
Matched Paraphrases | ['Dustin Wright', 'Jiaxin Pei', 'David Jurgens', 'Isabelle Augenstein'] | ['cs.CL', 'cs.CY', 'cs.LG'] | Whether the media faithfully communicate scientific information has long been
a core issue to the science community. Automatically identifying paraphrased
scientific findings could enable large-scale tracking and analysis of
information changes in the science communication process, but this requires
systems to understa... | 2022-10-24T07:44:38Z | In EMNLP 2022; 25 pages; 11 figures; 6 tables | null | null | null | null | null | null | null | null | null |
2,210.13248 | Brouhaha: multi-task training for voice activity detection,
speech-to-noise ratio, and C50 room acoustics estimation | ['Marvin Lavechin', 'Marianne Métais', 'Hadrien Titeux', 'Alodie Boissonnet', 'Jade Copet', 'Morgane Rivière', 'Elika Bergelson', 'Alejandrina Cristia', 'Emmanuel Dupoux', 'Hervé Bredin'] | ['eess.AS', 'cs.SD'] | Most automatic speech processing systems register degraded performance when
applied to noisy or reverberant speech. But how can one tell whether speech is
noisy or reverberant? We propose Brouhaha, a neural network jointly trained to
extract speech/non-speech segments, speech-to-noise ratios, and C50room
acoustics from... | 2022-10-24T13:47:36Z | null | null | null | null | null | null | null | null | null | null |
2,210.13304 | ELMER: A Non-Autoregressive Pre-trained Language Model for Efficient and
Effective Text Generation | ['Junyi Li', 'Tianyi Tang', 'Wayne Xin Zhao', 'Jian-Yun Nie', 'Ji-Rong Wen'] | ['cs.CL'] | We study the text generation task under the approach of pre-trained language
models (PLMs). Typically, an auto-regressive (AR) method is adopted for
generating texts in a token-by-token manner. Despite many advantages of AR
generation, it usually suffers from inefficient inference. Therefore,
non-autoregressive (NAR) m... | 2022-10-24T14:46:47Z | Accepted to EMNLP 2022 main conference (long paper) | null | null | null | null | null | null | null | null | null |
2,210.13352 | ESB: A Benchmark For Multi-Domain End-to-End Speech Recognition | ['Sanchit Gandhi', 'Patrick von Platen', 'Alexander M. Rush'] | ['cs.CL', 'cs.SD', 'eess.AS'] | Speech recognition applications cover a range of different audio and text
distributions, with different speaking styles, background noise, transcription
punctuation and character casing. However, many speech recognition systems
require dataset-specific tuning (audio filtering, punctuation removal and
normalisation of c... | 2022-10-24T15:58:48Z | 25 pages, 1 figure, submitted to ICLR 2023 | null | null | null | null | null | null | null | null | null |
2,210.13438 | High Fidelity Neural Audio Compression | ['Alexandre Défossez', 'Jade Copet', 'Gabriel Synnaeve', 'Yossi Adi'] | ['eess.AS', 'cs.AI', 'cs.SD', 'stat.ML'] | We introduce a state-of-the-art real-time, high-fidelity, audio codec
leveraging neural networks. It consists in a streaming encoder-decoder
architecture with quantized latent space trained in an end-to-end fashion. We
simplify and speed-up the training by using a single multiscale spectrogram
adversary that efficientl... | 2022-10-24T17:52:02Z | Preprint | null | null | null | null | null | null | null | null | null |
2,210.13449 | Controlled Text Reduction | ['Aviv Slobodkin', 'Paul Roit', 'Eran Hirsch', 'Ori Ernst', 'Ido Dagan'] | ['cs.CL'] | Producing a reduced version of a source text, as in generic or focused
summarization, inherently involves two distinct subtasks: deciding on targeted
content and generating a coherent text conveying it. While some popular
approaches address summarization as a single end-to-end task, prominent works
support decomposed m... | 2022-10-24T17:59:03Z | Accepted to EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.13452 | MetaFormer Baselines for Vision | ['Weihao Yu', 'Chenyang Si', 'Pan Zhou', 'Mi Luo', 'Yichen Zhou', 'Jiashi Feng', 'Shuicheng Yan', 'Xinchao Wang'] | ['cs.CV', 'cs.AI', 'cs.LG'] | MetaFormer, the abstracted architecture of Transformer, has been found to
play a significant role in achieving competitive performance. In this paper, we
further explore the capacity of MetaFormer, again, without focusing on token
mixer design: we introduce several baseline models under MetaFormer using the
most basic ... | 2022-10-24T17:59:57Z | Accepted to TPAMI. Code: https://github.com/sail-sg/metaformer | null | 10.1109/TPAMI.2023.3329173 | MetaFormer Baselines for Vision | ['Weihao Yu', 'Chenyang Si', 'Pan Zhou', 'Mi Luo', 'Yichen Zhou', 'Jiashi Feng', 'Shuicheng Yan', 'Xinchao Wang'] | 2,022 | IEEE Transactions on Pattern Analysis and Machine Intelligence | 171 | 115 | ['Computer Science', 'Medicine'] |
2,210.13569 | Characterizing Verbatim Short-Term Memory in Neural Language Models | ['Kristijan Armeni', 'Christopher Honey', 'Tal Linzen'] | ['cs.CL'] | When a language model is trained to predict natural language sequences, its
prediction at each moment depends on a representation of prior context. What
kind of information about the prior context can language models retrieve? We
tested whether language models could retrieve the exact words that occurred
previously in ... | 2022-10-24T19:47:56Z | V2 corrects an issue with tokenization for one of the models
(Wikitext-103 transformer). The relevant figures and the accompanying text
were updated. This update does not affect conclusions which remain the same
as in previous version | null | null | null | null | null | null | null | null | null |
2,210.13617 | Adapters for Enhanced Modeling of Multilingual Knowledge and Text | ['Yifan Hou', 'Wenxiang Jiao', 'Meizhen Liu', 'Carl Allen', 'Zhaopeng Tu', 'Mrinmaya Sachan'] | ['cs.CL', 'cs.AI'] | Large language models appear to learn facts from the large text corpora they
are trained on. Such facts are encoded implicitly within their many parameters,
making it difficult to verify or manipulate what knowledge has been learned.
Language models have recently been extended to multilingual language models
(MLLMs), e... | 2022-10-24T21:33:42Z | Our code, models, and data (e.g., integration corpus and extended
datasets) are available: https://github.com/yifan-h/Multilingual_Space | null | null | null | null | null | null | null | null | null |
2,210.13669 | Help me write a poem: Instruction Tuning as a Vehicle for Collaborative
Poetry Writing | ['Tuhin Chakrabarty', 'Vishakh Padmakumar', 'He He'] | ['cs.CL'] | Recent work in training large language models (LLMs) to follow natural
language instructions has opened up exciting opportunities for natural language
interface design. Building on the prior success of LLMs in the realm of
computer-assisted creativity, we aim to study if LLMs can improve the quality
of user-generated c... | 2022-10-25T00:07:10Z | To appear at EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.13952 | KnowGL: Knowledge Generation and Linking from Text | ['Gaetano Rossiello', 'Md Faisal Mahbub Chowdhury', 'Nandana Mihindukulasooriya', 'Owen Cornec', 'Alfio Massimiliano Gliozzo'] | ['cs.CL', 'cs.AI', 'cs.IR'] | We propose KnowGL, a tool that allows converting text into structured
relational data represented as a set of ABox assertions compliant with the TBox
of a given Knowledge Graph (KG), such as Wikidata. We address this problem as a
sequence generation task by leveraging pre-trained sequence-to-sequence
language models, e... | 2022-10-25T12:12:36Z | AAAI-23 Demo Track | null | null | null | null | null | null | null | null | null |
2,210.1414 | Contrastive Search Is What You Need For Neural Text Generation | ['Yixuan Su', 'Nigel Collier'] | ['cs.CL'] | Generating text with autoregressive language models (LMs) is of great
importance to many natural language processing (NLP) applications. Previous
solutions for this task often produce text that contains degenerative
expressions or lacks semantic consistency. Recently, Su et al. introduced a new
decoding method, contras... | 2022-10-25T16:40:48Z | TMLR'23 | null | null | null | null | null | null | null | null | null |
2,210.14698 | Autoregressive Structured Prediction with Language Models | ['Tianyu Liu', 'Yuchen Jiang', 'Nicholas Monath', 'Ryan Cotterell', 'Mrinmaya Sachan'] | ['cs.CL'] | Recent years have seen a paradigm shift in NLP towards using pretrained
language models ({PLM}) for a wide range of tasks.
However, there are many difficult design decisions to represent structures
(e.g. tagged text, coreference chains) in a way such that they can be captured
by PLMs.
Prior work on structured predi... | 2022-10-26T13:27:26Z | EMNLP 2022 (findings) | null | null | null | null | null | null | null | null | null |
2,210.14975 | MABEL: Attenuating Gender Bias using Textual Entailment Data | ['Jacqueline He', 'Mengzhou Xia', 'Christiane Fellbaum', 'Danqi Chen'] | ['cs.CL', 'cs.LG'] | Pre-trained language models encode undesirable social biases, which are
further exacerbated in downstream use. To this end, we propose MABEL (a Method
for Attenuating Gender Bias using Entailment Labels), an intermediate
pre-training approach for mitigating gender bias in contextualized
representations. Key to our appr... | 2022-10-26T18:36:58Z | Accepted to EMNLP 2022. Code and models are publicly available at
https://github.com/princeton-nlp/mabel | null | null | MABEL: Attenuating Gender Bias using Textual Entailment Data | ['Jacqueline He', 'Mengzhou Xia', 'C. Fellbaum', 'Danqi Chen'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 32 | 78 | ['Computer Science'] |
2,210.15067 | arXivEdits: Understanding the Human Revision Process in Scientific
Writing | ['Chao Jiang', 'Wei Xu', 'Samuel Stevens'] | ['cs.CL'] | Scientific publications are the primary means to communicate research
discoveries, where the writing quality is of crucial importance. However, prior
work studying the human editing process in this domain mainly focused on the
abstract or introduction sections, resulting in an incomplete picture. In this
work, we provi... | 2022-10-26T22:50:24Z | This paper has been accepted to EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.15191 | Truncation Sampling as Language Model Desmoothing | ['John Hewitt', 'Christopher D. Manning', 'Percy Liang'] | ['cs.CL'] | Long samples of text from neural language models can be of poor quality.
Truncation sampling algorithms--like top-$p$ or top-$k$ -- address this by
setting some words' probabilities to zero at each step. This work provides
framing for the aim of truncation, and an improved algorithm for that aim. We
propose thinking of... | 2022-10-27T05:52:35Z | Findings of EMNLP, + small fixes | null | null | null | null | null | null | null | null | null |
2,210.15212 | COCO-DR: Combating Distribution Shifts in Zero-Shot Dense Retrieval with
Contrastive and Distributionally Robust Learning | ['Yue Yu', 'Chenyan Xiong', 'Si Sun', 'Chao Zhang', 'Arnold Overwijk'] | ['cs.CL', 'cs.IR', 'cs.LG'] | We present a new zero-shot dense retrieval (ZeroDR) method, COCO-DR, to
improve the generalization ability of dense retrieval by combating the
distribution shifts between source training tasks and target scenarios. To
mitigate the impact of document differences, COCO-DR continues pretraining the
language model on the t... | 2022-10-27T06:51:39Z | EMNLP 2022 (Main Conference). The code and Model can be found at
https://github.com/OpenMatch/COCO-DR | EMNLP 2022 | null | null | null | null | null | null | null | null |
2,210.15226 | Iterative pseudo-forced alignment by acoustic CTC loss for
self-supervised ASR domain adaptation | ['Fernando López', 'Jordi Luque'] | ['cs.CL', 'cs.SD', 'eess.AS'] | High-quality data labeling from specific domains is costly and human
time-consuming. In this work, we propose a self-supervised domain adaptation
method, based upon an iterative pseudo-forced alignment algorithm. The produced
alignments are employed to customize an end-to-end Automatic Speech Recognition
(ASR) and iter... | 2022-10-27T07:23:08Z | 5 pages, 4 figures, IberSPEECH2022 | null | null | Iterative pseudo-forced alignment by acoustic CTC loss for self-supervised ASR domain adaptation | ["F. L'opez", 'J. Luque'] | 2,022 | IberSPEECH Conference | 6 | 26 | ['Computer Science', 'Engineering'] |
2,210.15418 | FreeVC: Towards High-Quality Text-Free One-Shot Voice Conversion | ['Jingyi li', 'Weiping tu', 'Li xiao'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Voice conversion (VC) can be achieved by first extracting source content
information and target speaker information, and then reconstructing waveform
with these information. However, current approaches normally either extract
dirty content information with speaker information leaked in, or demand a large
amount of anno... | 2022-10-27T13:32:38Z | null | null | null | Freevc: Towards High-Quality Text-Free One-Shot Voice Conversion | ['Jingyi Li', 'Weiping Tu', 'Li Xiao'] | 2,022 | IEEE International Conference on Acoustics, Speech, and Signal Processing | 113 | 31 | ['Computer Science', 'Engineering'] |
2,210.15497 | LSG Attention: Extrapolation of pretrained Transformers to long
sequences | ['Charles Condevaux', 'Sébastien Harispe'] | ['cs.CL'] | Transformer models achieve state-of-the-art performance on a wide range of
NLP tasks. They however suffer from a prohibitive limitation due to the
self-attention mechanism, inducing $O(n^2)$ complexity with regard to sequence
length. To answer this limitation we introduce the LSG architecture which
relies on Local, Spa... | 2022-10-13T13:10:41Z | null | null | null | LSG Attention: Extrapolation of pretrained Transformers to long sequences | ['Charles Condevaux', 'S. Harispe'] | 2,022 | Pacific-Asia Conference on Knowledge Discovery and Data Mining | 24 | 42 | ['Computer Science'] |
2,210.15586 | Joint Multi-Person Body Detection and Orientation Estimation via One
Unified Embedding | ['Huayi Zhou', 'Fei Jiang', 'Jiaxin Si', 'Hongtao Lu'] | ['cs.CV'] | Human body orientation estimation (HBOE) is widely applied into various
applications, including robotics, surveillance, pedestrian analysis and
autonomous driving. Although many approaches have been addressing the HBOE
problem from specific under-controlled scenes to challenging in-the-wild
environments, they assume hu... | 2022-10-27T16:22:50Z | null | null | null | Joint Multi-Person Body Detection and Orientation Estimation via One Unified Embedding | ['Huayi Zhou', 'Fei Jiang', 'Jiaxin Si', 'Hongtao Lu'] | 2,022 | Chinese Conference on Pattern Recognition and Computer Vision | 6 | 25 | ['Computer Science'] |
2,210.16407 | Just-DREAM-about-it: Figurative Language Understanding with DREAM-FLUTE | ['Yuling Gu', 'Yao Fu', 'Valentina Pyatkin', 'Ian Magnusson', 'Bhavana Dalvi Mishra', 'Peter Clark'] | ['cs.CL'] | Figurative language (e.g., "he flew like the wind") is challenging to
understand, as it is hard to tell what implicit information is being conveyed
from the surface form alone. We hypothesize that to perform this task well, the
reader needs to mentally elaborate the scene being described to identify a
sensible meaning ... | 2022-10-28T21:14:23Z | Accepted at The Third Workshop on Figurative Language Processing @
EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,210.17016 | Wespeaker: A Research and Production oriented Speaker Embedding Learning
Toolkit | ['Hongji Wang', 'Chengdong Liang', 'Shuai Wang', 'Zhengyang Chen', 'Binbin Zhang', 'Xu Xiang', 'Yanlei Deng', 'Yanmin Qian'] | ['cs.SD', 'eess.AS'] | Speaker modeling is essential for many related tasks, such as speaker
recognition and speaker diarization. The dominant modeling approach is
fixed-dimensional vector representation, i.e., speaker embedding. This paper
introduces a research and production oriented speaker embedding learning
toolkit, Wespeaker. Wespeaker... | 2022-10-31T02:11:58Z | null | null | null | null | null | null | null | null | null | null |
2,210.17114 | QuaLA-MiniLM: a Quantized Length Adaptive MiniLM | ['Shira Guskin', 'Moshe Wasserblat', 'Chang Wang', 'Haihao Shen'] | ['cs.CL'] | Limited computational budgets often prevent transformers from being used in
production and from having their high accuracy utilized. A knowledge
distillation approach addresses the computational efficiency by self-distilling
BERT into a smaller transformer representation having fewer layers and smaller
internal embeddi... | 2022-10-31T07:42:52Z | In this version we updated the reference to the source code in the
abstract. arXiv admin note: text overlap with arXiv:2111.09645 | null | null | QuaLA-MiniLM: a Quantized Length Adaptive MiniLM | ['Shira Guskin', 'Moshe Wasserblat', 'Chang Wang', 'Haihao Shen'] | 2,022 | arXiv.org | 2 | 22 | ['Computer Science'] |
2,210.17167 | Reduce Catastrophic Forgetting of Dense Retrieval Training with
Teleportation Negatives | ['Si Sun', 'Chenyan Xiong', 'Yue Yu', 'Arnold Overwijk', 'Zhiyuan Liu', 'Jie Bao'] | ['cs.CL'] | In this paper, we investigate the instability in the standard dense retrieval
training, which iterates between model training and hard negative selection
using the being-trained model. We show the catastrophic forgetting phenomena
behind the training instability, where models learn and forget different
negative groups ... | 2022-10-31T09:25:42Z | Accepted to EMNLP 2022 main conference | null | null | Reduce Catastrophic Forgetting of Dense Retrieval Training with Teleportation Negatives | ['Si Sun', 'Chenyan Xiong', 'Yue Yu', 'Arnold Overwijk', 'Zhiyuan Liu', 'Jie Bao'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 6 | 48 | ['Computer Science'] |
2,210.17323 | GPTQ: Accurate Post-Training Quantization for Generative Pre-trained
Transformers | ['Elias Frantar', 'Saleh Ashkboos', 'Torsten Hoefler', 'Dan Alistarh'] | ['cs.LG'] | Generative Pre-trained Transformer models, known as GPT or OPT, set
themselves apart through breakthrough performance across complex language
modelling tasks, but also by their extremely high computational and storage
costs. Specifically, due to their massive size, even inference for large,
highly-accurate GPT models m... | 2022-10-31T13:42:40Z | ICLR 2023 | null | null | null | null | null | null | null | null | null |
2,210.17517 | Lila: A Unified Benchmark for Mathematical Reasoning | ['Swaroop Mishra', 'Matthew Finlayson', 'Pan Lu', 'Leonard Tang', 'Sean Welleck', 'Chitta Baral', 'Tanmay Rajpurohit', 'Oyvind Tafjord', 'Ashish Sabharwal', 'Peter Clark', 'Ashwin Kalyan'] | ['cs.CL', 'cs.AI', '68T50', 'I.2.7'] | Mathematical reasoning skills are essential for general-purpose intelligent
systems to perform tasks from grocery shopping to climate modeling. Towards
evaluating and improving AI systems in this domain, we propose LILA, a unified
mathematical reasoning benchmark consisting of 23 diverse tasks along four
dimensions: (i... | 2022-10-31T17:41:26Z | EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,211.00508 | Predicting Multi-Codebook Vector Quantization Indexes for Knowledge
Distillation | ['Liyong Guo', 'Xiaoyu Yang', 'Quandong Wang', 'Yuxiang Kong', 'Zengwei Yao', 'Fan Cui', 'Fangjun Kuang', 'Wei Kang', 'Long Lin', 'Mingshuang Luo', 'Piotr Zelasko', 'Daniel Povey'] | ['eess.AS', 'cs.CL', 'cs.SD'] | Knowledge distillation(KD) is a common approach to improve model performance
in automatic speech recognition (ASR), where a student model is trained to
imitate the output behaviour of a teacher model. However, traditional KD
methods suffer from teacher label storage issue, especially when the training
corpora are large... | 2022-10-31T07:03:17Z | Submitted to ICASSP 2022 | null | null | null | null | null | null | null | null | null |
2,211.00575 | Text-Only Training for Image Captioning using Noise-Injected CLIP | ['David Nukrai', 'Ron Mokady', 'Amir Globerson'] | ['cs.CV', 'cs.AI', 'cs.LG'] | We consider the task of image-captioning using only the CLIP model and
additional text data at training time, and no additional captioned images. Our
approach relies on the fact that CLIP is trained to make visual and textual
embeddings similar. Therefore, we only need to learn how to translate CLIP
textual embeddings ... | 2022-11-01T16:36:01Z | Will be presented at EMNLP 2022. GitHub:
https://github.com/DavidHuji/CapDec | EMNLP 2022 | 10.48448/n7sq-p557 | Text-Only Training for Image Captioning using Noise-Injected CLIP | ['David Nukrai', 'Ron Mokady', 'A. Globerson'] | 2,022 | Conference on Empirical Methods in Natural Language Processing | 98 | 62 | ['Computer Science'] |
2,211.00585 | Adapter-Based Extension of Multi-Speaker Text-to-Speech Model for New
Speakers | ['Cheng-Ping Hsieh', 'Subhankar Ghosh', 'Boris Ginsburg'] | ['eess.AS', 'cs.LG', 'cs.SD'] | Fine-tuning is a popular method for adapting text-to-speech (TTS) models to
new speakers. However this approach has some challenges. Usually fine-tuning
requires several hours of high quality speech per speaker. There is also that
fine-tuning will negatively affect the quality of speech synthesis for
previously learnt ... | 2022-11-01T16:59:54Z | Submitted to ICASSP 2023 | null | null | null | null | null | null | null | null | null |
2,211.00895 | Pop2Piano : Pop Audio-based Piano Cover Generation | ['Jongho Choi', 'Kyogu Lee'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Piano covers of pop music are enjoyed by many people. However, the task of
automatically generating piano covers of pop music is still understudied. This
is partly due to the lack of synchronized {Pop, Piano Cover} data pairs, which
made it challenging to apply the latest data-intensive deep learning-based
methods. To ... | 2022-11-02T05:42:22Z | null | null | null | null | null | null | null | null | null | null |
2,211.01095 | DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic
Models | ['Cheng Lu', 'Yuhao Zhou', 'Fan Bao', 'Jianfei Chen', 'Chongxuan Li', 'Jun Zhu'] | ['cs.LG', 'cs.CV'] | Diffusion probabilistic models (DPMs) have achieved impressive success in
high-resolution image synthesis, especially in recent large-scale text-to-image
generation applications. An essential technique for improving the sample
quality of DPMs is guided sampling, which usually needs a large guidance scale
to obtain the ... | 2022-11-02T13:14:30Z | Machine Intelligence Research | null | 10.1007/s11633-025-1562-4 | null | null | null | null | null | null | null |
2,211.01226 | DEArt: Dataset of European Art | ['Artem Reshetnikov', 'Maria-Cristina Marinescu', 'Joaquim More Lopez'] | ['cs.CV'] | Large datasets that were made publicly available to the research community
over the last 20 years have been a key enabling factor for the advances in deep
learning algorithms for NLP or computer vision. These datasets are generally
pairs of aligned image / manually annotated metadata, where images are
photographs of ev... | 2022-11-02T16:05:35Z | VISART VI. Workshop at the European Conference of Computer Vision
(ECCV) | null | null | null | null | null | null | null | null | null |
2,211.01324 | eDiff-I: Text-to-Image Diffusion Models with an Ensemble of Expert
Denoisers | ['Yogesh Balaji', 'Seungjun Nah', 'Xun Huang', 'Arash Vahdat', 'Jiaming Song', 'Qinsheng Zhang', 'Karsten Kreis', 'Miika Aittala', 'Timo Aila', 'Samuli Laine', 'Bryan Catanzaro', 'Tero Karras', 'Ming-Yu Liu'] | ['cs.CV', 'cs.LG'] | Large-scale diffusion-based generative models have led to breakthroughs in
text-conditioned high-resolution image synthesis. Starting from random noise,
such text-to-image diffusion models gradually synthesize images in an iterative
fashion while conditioning on text prompts. We find that their synthesis
behavior quali... | 2022-11-02T17:43:04Z | null | null | null | null | null | null | null | null | null | null |
2,211.01335 | Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese | ['An Yang', 'Junshu Pan', 'Junyang Lin', 'Rui Men', 'Yichang Zhang', 'Jingren Zhou', 'Chang Zhou'] | ['cs.CV', 'cs.CL'] | The tremendous success of CLIP (Radford et al., 2021) has promoted the
research and application of contrastive learning for vision-language
pretraining. In this work, we construct a large-scale dataset of image-text
pairs in Chinese, where most data are retrieved from publicly available
datasets, and we pretrain Chines... | 2022-11-02T17:47:23Z | null | null | null | Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese | ['An Yang', 'Junshu Pan', 'Junyang Lin', 'Rui Men', 'Yichang Zhang', 'Jingren Zhou', 'Chang Zhou'] | 2,022 | arXiv.org | 116 | 81 | ['Computer Science'] |
2,211.01355 | MT-GenEval: A Counterfactual and Contextual Dataset for Evaluating
Gender Accuracy in Machine Translation | ['Anna Currey', 'Maria Nădejde', 'Raghavendra Pappagari', 'Mia Mayer', 'Stanislas Lauly', 'Xing Niu', 'Benjamin Hsu', 'Georgiana Dinu'] | ['cs.CL'] | As generic machine translation (MT) quality has improved, the need for
targeted benchmarks that explore fine-grained aspects of quality has increased.
In particular, gender accuracy in translation can have implications in terms of
output fluency, translation accuracy, and ethics. In this paper, we introduce
MT-GenEval,... | 2022-11-02T17:55:43Z | Accepted at EMNLP 2022. Data and code:
https://github.com/amazon-research/machine-translation-gender-eval | null | null | null | null | null | null | null | null | null |
2,211.01786 | Crosslingual Generalization through Multitask Finetuning | ['Niklas Muennighoff', 'Thomas Wang', 'Lintang Sutawika', 'Adam Roberts', 'Stella Biderman', 'Teven Le Scao', 'M Saiful Bari', 'Sheng Shen', 'Zheng-Xin Yong', 'Hailey Schoelkopf', 'Xiangru Tang', 'Dragomir Radev', 'Alham Fikri Aji', 'Khalid Almubarak', 'Samuel Albanie', 'Zaid Alyafeai', 'Albert Webson', 'Edward Raff', ... | ['cs.CL', 'cs.AI', 'cs.LG'] | Multitask prompted finetuning (MTF) has been shown to help large language
models generalize to new tasks in a zero-shot setting, but so far explorations
of MTF have focused on English data and models. We apply MTF to the pretrained
multilingual BLOOM and mT5 model families to produce finetuned variants called
BLOOMZ an... | 2022-11-03T13:19:32Z | 9 main pages (119 with appendix), 16 figures and 11 tables | null | null | null | null | null | null | null | null | null |
2,211.02001 | Estimating the Carbon Footprint of BLOOM, a 176B Parameter Language
Model | ['Alexandra Sasha Luccioni', 'Sylvain Viguier', 'Anne-Laure Ligozat'] | ['cs.LG'] | Progress in machine learning (ML) comes with a cost to the environment, given
that training ML models requires significant computational resources, energy
and materials. In the present article, we aim to quantify the carbon footprint
of BLOOM, a 176-billion parameter language model, across its life cycle. We
estimate t... | 2022-11-03T17:13:48Z | null | null | null | null | null | null | null | null | null | null |
2,211.03263 | AfroLM: A Self-Active Learning-based Multilingual Pretrained Language
Model for 23 African Languages | ['Bonaventure F. P. Dossou', 'Atnafu Lambebo Tonja', 'Oreen Yousuf', 'Salomey Osei', 'Abigail Oppong', 'Iyanuoluwa Shode', 'Oluwabusayo Olufunke Awoyomi', 'Chris Chinenye Emezue'] | ['cs.CL', 'cs.AI', 'cs.LG'] | In recent years, multilingual pre-trained language models have gained
prominence due to their remarkable performance on numerous downstream Natural
Language Processing tasks (NLP). However, pre-training these large multilingual
language models requires a lot of training data, which is not available for
African Language... | 2022-11-07T02:15:25Z | Third Workshop on Simple and Efficient Natural Language Processing,
EMNLP 2022 | null | null | null | null | null | null | null | null | null |
2,211.03295 | MogaNet: Multi-order Gated Aggregation Network | ['Siyuan Li', 'Zedong Wang', 'Zicheng Liu', 'Cheng Tan', 'Haitao Lin', 'Di Wu', 'Zhiyuan Chen', 'Jiangbin Zheng', 'Stan Z. Li'] | ['cs.CV', 'cs.AI'] | By contextualizing the kernel as global as possible, Modern ConvNets have
shown great potential in computer vision tasks. However, recent progress on
multi-order game-theoretic interaction within deep neural networks (DNNs)
reveals the representation bottleneck of modern ConvNets, where the expressive
interactions have... | 2022-11-07T04:31:17Z | ICLR 2024. Preprint V4 (35 pages, fixed typos). Code and models refer
to https://github.com/Westlake-AI/MogaNet | null | null | null | null | null | null | null | null | null |
2,211.03375 | AlphaPose: Whole-Body Regional Multi-Person Pose Estimation and Tracking
in Real-Time | ['Hao-Shu Fang', 'Jiefeng Li', 'Hongyang Tang', 'Chao Xu', 'Haoyi Zhu', 'Yuliang Xiu', 'Yong-Lu Li', 'Cewu Lu'] | ['cs.CV'] | Accurate whole-body multi-person pose estimation and tracking is an important
yet challenging topic in computer vision. To capture the subtle actions of
humans for complex behavior analysis, whole-body pose estimation including the
face, body, hand and foot is essential over conventional body-only pose
estimation. In t... | 2022-11-07T09:15:38Z | Documents for AlphaPose, accepted to TPAMI | null | null | null | null | null | null | null | null | null |
2,211.03442 | Named Entity Recognition in Indian court judgments | ['Prathamesh Kalamkar', 'Astha Agarwal', 'Aman Tiwari', 'Smita Gupta', 'Saurabh Karn', 'Vivek Raghavan'] | ['cs.CL', 'cs.AI'] | Identification of named entities from legal texts is an essential building
block for developing other legal Artificial Intelligence applications. Named
Entities in legal texts are slightly different and more fine-grained than
commonly used named entities like Person, Organization, Location etc. In this
paper, we introd... | 2022-11-07T10:44:44Z | to be published in NLLP 2022 Workshop at EMNLP | null | null | Named Entity Recognition in Indian court judgments | ['Prathamesh Kalamkar', 'Astha Agarwal', 'Aman Tiwari', 'Smita Gupta', 'S. Karn', 'Vivek Raghavan'] | 2,022 | NLLP | 53 | 37 | ['Computer Science'] |
2,211.04054 | ATCO2 corpus: A Large-Scale Dataset for Research on Automatic Speech
Recognition and Natural Language Understanding of Air Traffic Control
Communications | ['Juan Zuluaga-Gomez', 'Karel Veselý', 'Igor Szöke', 'Alexander Blatt', 'Petr Motlicek', 'Martin Kocour', 'Mickael Rigault', 'Khalid Choukri', 'Amrutha Prasad', 'Seyyed Saeed Sarfjoo', 'Iuliia Nigmatulina', 'Claudia Cevenini', 'Pavel Kolčárek', 'Allan Tart', 'Jan Černocký', 'Dietrich Klakow'] | ['cs.CL', 'cs.AI', 'cs.SD', 'eess.AS'] | Personal assistants, automatic speech recognizers and dialogue understanding
systems are becoming more critical in our interconnected digital world. A clear
example is air traffic control (ATC) communications. ATC aims at guiding
aircraft and controlling the airspace in a safe and optimal manner. These
voice-based dial... | 2022-11-08T07:26:45Z | Manuscript under review; The code is available at:
https://github.com/idiap/atco2-corpus | null | null | null | null | null | null | null | null | null |
2,211.04279 | Detecting Shortcuts in Medical Images -- A Case Study in Chest X-rays | ['Amelia Jiménez-Sánchez', 'Dovile Juodelyte', 'Bethany Chamberlain', 'Veronika Cheplygina'] | ['cs.CV'] | The availability of large public datasets and the increased amount of
computing power have shifted the interest of the medical community to
high-performance algorithms. However, little attention is paid to the quality
of the data and their annotations. High performance on benchmark datasets may
be reported without cons... | 2022-11-08T14:36:33Z | Submitted to ISBI 2023 | null | null | null | null | null | null | null | null | null |
2,211.04673 | Syntax-Aware On-the-Fly Code Completion | ['Wannita Takerngsaksiri', 'Chakkrit Tantithamthavorn', 'Yuan-Fang Li'] | ['cs.SE', 'cs.AI'] | Code completion aims to help improve developers' productivity by suggesting
the next code tokens from a given context. Various approaches have been
proposed to incorporate abstract syntax tree (AST) information for model
training, ensuring that code completion is aware of the syntax of the
programming languages. Howeve... | 2022-11-09T04:24:18Z | 17 pages, Under Review at IEEE Transactions on Software Engineering | null | null | Syntax-Aware On-the-Fly Code Completion | ['Wannita Takerngsaksiri', 'C. Tantithamthavorn', 'Yuan-Fang Li'] | 2,022 | Information and Software Technology | 19 | 55 | ['Computer Science'] |
2,211.04846 | Grid-free Harmonic Retrieval and Model Order Selection using Deep
Convolutional Neural Networks | ['Steffen Schieler', 'Sebastian Semper', 'Reza Faramarzahangari', 'Michael Döbereiner', 'Christian Schneider', 'R. Thomä'] | ['eess.SP'] | Harmonic retrieval techniques are the foundation of radio channel sounding,
estimation, and modeling. This paper introduces a Deep Learning approach for
joint delay- and Doppler estimation from frequency and time samples of a radio
channel transfer function. Our work estimates the two-dimensional parameters
from a sign... | 2022-11-09T12:33:31Z | version accepted at EuCAP 2024 | null | null | null | null | null | null | null | null | null |
2,211.04894 | Exploring Video Quality Assessment on User Generated Contents from
Aesthetic and Technical Perspectives | ['Haoning Wu', 'Erli Zhang', 'Liang Liao', 'Chaofeng Chen', 'Jingwen Hou', 'Annan Wang', 'Wenxiu Sun', 'Qiong Yan', 'Weisi Lin'] | ['cs.CV', 'cs.LG', 'cs.MM', 'eess.IV'] | The rapid increase in user-generated-content (UGC) videos calls for the
development of effective video quality assessment (VQA) algorithms. However,
the objective of the UGC-VQA problem is still ambiguous and can be viewed from
two perspectives: the technical perspective, measuring the perception of
distortions; and th... | 2022-11-09T13:55:50Z | null | null | null | Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives | ['Haoning Wu', 'Erli Zhang', 'Liang Liao', 'Chaofeng Chen', 'Jingwen Hou', 'Annan Wang', 'Wenxiu Sun', 'Qiong Yan', 'Weisi Lin'] | 2,022 | IEEE International Conference on Computer Vision | 171 | 78 | ['Computer Science', 'Engineering'] |
2,211.04928 | miCSE: Mutual Information Contrastive Learning for Low-shot Sentence
Embeddings | ['Tassilo Klein', 'Moin Nabi'] | ['cs.CL', 'cs.LG'] | This paper presents miCSE, a mutual information-based contrastive learning
framework that significantly advances the state-of-the-art in few-shot sentence
embedding. The proposed approach imposes alignment between the attention
pattern of different views during contrastive learning. Learning sentence
embeddings with mi... | 2022-11-09T14:57:37Z | Accepted to ACL 2023 | null | null | miCSE: Mutual Information Contrastive Learning for Low-shot Sentence Embeddings | ['T. Klein', 'Moin Nabi'] | 2,022 | Annual Meeting of the Association for Computational Linguistics | 17 | 66 | ['Computer Science'] |
2,211.051 | BLOOM: A 176B-Parameter Open-Access Multilingual Language Model | ['BigScience Workshop', ':', 'Teven Le Scao', 'Angela Fan', 'Christopher Akiki', 'Ellie Pavlick', 'Suzana Ilić', 'Daniel Hesslow', 'Roman Castagné', 'Alexandra Sasha Luccioni', 'François Yvon', 'Matthias Gallé', 'Jonathan Tow', 'Alexander M. Rush', 'Stella Biderman', 'Albert Webson', 'Pawan Sasanka Ammanamanchi', 'Thom... | ['cs.CL'] | Large language models (LLMs) have been shown to be able to perform new tasks
based on a few demonstrations or natural language instructions. While these
capabilities have led to widespread adoption, most LLMs are developed by
resource-rich organizations and are frequently kept from the public. As a step
towards democra... | 2022-11-09T18:48:09Z | null | null | null | null | null | null | null | null | null | null |
2,211.05105 | Safe Latent Diffusion: Mitigating Inappropriate Degeneration in
Diffusion Models | ['Patrick Schramowski', 'Manuel Brack', 'Björn Deiseroth', 'Kristian Kersting'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Text-conditioned image generation models have recently achieved astonishing
results in image quality and text alignment and are consequently employed in a
fast-growing number of applications. Since they are highly data-driven, relying
on billion-sized datasets randomly scraped from the internet, they also suffer,
as we... | 2022-11-09T18:54:25Z | Proceedings of the 22nd IEEE/CVF Conference on Computer Vision and
Pattern Recognition (CVPR), 2023 | null | null | Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models | ['P. Schramowski', 'Manuel Brack', 'Bjorn Deiseroth', 'K. Kersting'] | 2,022 | Computer Vision and Pattern Recognition | 312 | 60 | ['Computer Science'] |
2,211.05344 | LERT: A Linguistically-motivated Pre-trained Language Model | ['Yiming Cui', 'Wanxiang Che', 'Shijin Wang', 'Ting Liu'] | ['cs.CL', 'cs.LG'] | Pre-trained Language Model (PLM) has become a representative foundation model
in the natural language processing field. Most PLMs are trained with
linguistic-agnostic pre-training tasks on the surface form of the text, such as
the masked language model (MLM). To further empower the PLMs with richer
linguistic features,... | 2022-11-10T05:09:16Z | 11 pages | null | null | LERT: A Linguistically-motivated Pre-trained Language Model | ['Yiming Cui', 'Wanxiang Che', 'Shijin Wang', 'Ting Liu'] | 2,022 | arXiv.org | 25 | 35 | ['Computer Science'] |
2,211.05778 | InternImage: Exploring Large-Scale Vision Foundation Models with
Deformable Convolutions | ['Wenhai Wang', 'Jifeng Dai', 'Zhe Chen', 'Zhenhang Huang', 'Zhiqi Li', 'Xizhou Zhu', 'Xiaowei Hu', 'Tong Lu', 'Lewei Lu', 'Hongsheng Li', 'Xiaogang Wang', 'Yu Qiao'] | ['cs.CV'] | Compared to the great progress of large-scale vision transformers (ViTs) in
recent years, large-scale models based on convolutional neural networks (CNNs)
are still in an early state. This work presents a new large-scale CNN-based
foundation model, termed InternImage, which can obtain the gain from increasing
parameter... | 2022-11-10T18:59:04Z | Accepted to CVPR 2023 | null | null | InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions | ['Wenhai Wang', 'Jifeng Dai', 'Zhe Chen', 'Zhenhang Huang', 'Zhiqi Li', 'Xizhou Zhu', 'Xiaowei Hu', 'Tong Lu', 'Lewei Lu', 'Hongsheng Li', 'Xiaogang Wang', 'Y. Qiao'] | 2,022 | Computer Vision and Pattern Recognition | 700 | 107 | ['Computer Science'] |
2,211.06088 | RepGhost: A Hardware-Efficient Ghost Module via Re-parameterization | ['Chengpeng Chen', 'Zichao Guo', 'Haien Zeng', 'Pengfei Xiong', 'Jian Dong'] | ['cs.CV'] | Feature reuse has been a key technique in light-weight convolutional neural
networks (CNNs) architecture design. Current methods usually utilize a
concatenation operator to keep large channel numbers cheaply (thus large
network capacity) by reusing feature maps from other layers. Although
concatenation is parameters- a... | 2022-11-11T09:44:23Z | tech report | null | null | null | null | null | null | null | null | null |
2,211.0622 | OneFormer: One Transformer to Rule Universal Image Segmentation | ['Jitesh Jain', 'Jiachen Li', 'MangTik Chiu', 'Ali Hassani', 'Nikita Orlov', 'Humphrey Shi'] | ['cs.CV'] | Universal Image Segmentation is not a new concept. Past attempts to unify
image segmentation in the last decades include scene parsing, panoptic
segmentation, and, more recently, new panoptic architectures. However, such
panoptic architectures do not truly unify image segmentation because they need
to be trained indivi... | 2022-11-10T18:56:04Z | Project Page: https://praeclarumjj3.github.io/oneformer | null | null | OneFormer: One Transformer to Rule Universal Image Segmentation | ['Jitesh Jain', 'Jiacheng Li', 'M. Chiu', 'Ali Hassani', 'Nikita Orlov', 'Humphrey Shi'] | 2,022 | Computer Vision and Pattern Recognition | 349 | 62 | ['Computer Science'] |
2,211.06597 | OpenGait: Revisiting Gait Recognition Toward Better Practicality | ['Chao Fan', 'Junhao Liang', 'Chuanfu Shen', 'Saihui Hou', 'Yongzhen Huang', 'Shiqi Yu'] | ['cs.CV'] | Gait recognition is one of the most critical long-distance identification
technologies and increasingly gains popularity in both research and industry
communities. Despite the significant progress made in indoor datasets, much
evidence shows that gait recognition techniques perform poorly in the wild.
More importantly,... | 2022-11-12T07:24:29Z | null | null | null | OpenGait: Revisiting Gait Recognition Toward Better Practicality | ['Chao Fan', 'Junhao Liang', 'Chuanfu Shen', 'Saihui Hou', 'Yongzhen Huang', 'Shiqi Yu'] | 2,022 | Computer Vision and Pattern Recognition | 137 | 51 | ['Computer Science'] |
2,211.06627 | MARLIN: Masked Autoencoder for facial video Representation LearnINg | ['Zhixi Cai', 'Shreya Ghosh', 'Kalin Stefanov', 'Abhinav Dhall', 'Jianfei Cai', 'Hamid Rezatofighi', 'Reza Haffari', 'Munawar Hayat'] | ['cs.CV'] | This paper proposes a self-supervised approach to learn universal facial
representations from videos, that can transfer across a variety of facial
analysis tasks such as Facial Attribute Recognition (FAR), Facial Expression
Recognition (FER), DeepFake Detection (DFD), and Lip Synchronization (LS). Our
proposed framewor... | 2022-11-12T10:29:05Z | CVPR 2023 | null | null | MARLIN: Masked Autoencoder for facial video Representation LearnINg | ['Zhixi Cai', 'Shreya Ghosh', 'Kalin Stefanov', 'Abhinav Dhall', 'Jianfei Cai', 'Hamid Rezatofighi', 'Reza Haffari', 'Munawar Hayat'] | 2,022 | Computer Vision and Pattern Recognition | 62 | 90 | ['Computer Science'] |
2,211.06679 | AltCLIP: Altering the Language Encoder in CLIP for Extended Language
Capabilities | ['Zhongzhi Chen', 'Guang Liu', 'Bo-Wen Zhang', 'Fulong Ye', 'Qinghong Yang', 'Ledell Wu'] | ['cs.CL'] | In this work, we present a conceptually simple and effective method to train
a strong bilingual/multilingual multimodal representation model. Starting from
the pre-trained multimodal representation model CLIP released by OpenAI, we
altered its text encoder with a pre-trained multilingual text encoder XLM-R,
and aligned... | 2022-11-12T14:48:55Z | null | null | null | null | null | null | null | null | null | null |
2,211.06687 | Large-scale Contrastive Language-Audio Pretraining with Feature Fusion
and Keyword-to-Caption Augmentation | ['Yusong Wu', 'Ke Chen', 'Tianyu Zhang', 'Yuchen Hui', 'Marianna Nezhurina', 'Taylor Berg-Kirkpatrick', 'Shlomo Dubnov'] | ['cs.SD', 'eess.AS'] | Contrastive learning has shown remarkable success in the field of multimodal
representation learning. In this paper, we propose a pipeline of contrastive
language-audio pretraining to develop an audio representation by combining
audio data with natural language descriptions. To accomplish this target, we
first release ... | 2022-11-12T15:25:20Z | null | null | null | null | null | null | null | null | null | null |
2,211.06892 | OverFlow: Putting flows on top of neural transducers for better TTS | ['Shivam Mehta', 'Ambika Kirkland', 'Harm Lameris', 'Jonas Beskow', 'Éva Székely', 'Gustav Eje Henter'] | ['eess.AS', 'cs.HC', 'cs.LG', 'cs.SD', '68T07', 'I.2.7; I.2.6; G.3; H.5.5'] | Neural HMMs are a type of neural transducer recently proposed for
sequence-to-sequence modelling in text-to-speech. They combine the best
features of classic statistical speech synthesis and modern neural TTS,
requiring less data and fewer training updates, and are less prone to gibberish
output caused by neural attent... | 2022-11-13T12:53:05Z | 5 pages, 2 figures. Accepted for publication at Interspeech 2023 | null | 10.21437/Interspeech.2023-1996 | null | null | null | null | null | null | null |
2,211.07044 | SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for
Self-Supervised Learning in Earth Observation | ['Yi Wang', 'Nassim Ait Ali Braham', 'Zhitong Xiong', 'Chenying Liu', 'Conrad M Albrecht', 'Xiao Xiang Zhu'] | ['cs.CV', 'cs.AI'] | Self-supervised pre-training bears potential to generate expressive
representations without human annotation. Most pre-training in Earth
observation (EO) are based on ImageNet or medium-size, labeled remote sensing
(RS) datasets. We share an unlabeled RS dataset SSL4EO-S12 (Self-Supervised
Learning for Earth Observatio... | 2022-11-13T23:38:27Z | Accepted by IEEE Geoscience and Remote Sensing Magazine. 18 pages | null | null | SSL4EO-S12: A Large-Scale Multi-Modal, Multi-Temporal Dataset for Self-Supervised Learning in Earth Observation | ['Yi Wang', 'Nassim Ait Ali Braham', 'Zhitong Xiong', 'Chenying Liu', 'C. Albrecht', 'Xiao Xiang Zhu'] | 2,022 | arXiv.org | 73 | 54 | ['Computer Science'] |
2,211.07292 | A Novel Sampling Scheme for Text- and Image-Conditional Image Synthesis
in Quantized Latent Spaces | ['Dominic Rampas', 'Pablo Pernias', 'Marc Aubreville'] | ['cs.CV', 'cs.LG'] | Recent advancements in the domain of text-to-image synthesis have culminated
in a multitude of enhancements pertaining to quality, fidelity, and diversity.
Contemporary techniques enable the generation of highly intricate visuals which
rapidly approach near-photorealistic quality. Nevertheless, as progress is
achieved,... | 2022-11-14T11:52:55Z | null | null | null | null | null | null | null | null | null | null |
2,211.07302 | MedleyVox: An Evaluation Dataset for Multiple Singing Voices Separation | ['Chang-Bin Jeon', 'Hyeongi Moon', 'Keunwoo Choi', 'Ben Sangbae Chon', 'Kyogu Lee'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Separation of multiple singing voices into each voice is a rarely studied
area in music source separation research. The absence of a benchmark dataset
has hindered its progress. In this paper, we present an evaluation dataset and
provide baseline studies for multiple singing voices separation. First, we
introduce Medle... | 2022-11-14T12:27:35Z | 5 pages, 3 figures, 6 tables, To appear in ICASSP 2023 (camera-ready
version) | null | null | null | null | null | null | null | null | null |
2,211.07591 | Imagination is All You Need! Curved Contrastive Learning for Abstract
Sequence Modeling Utilized on Long Short-Term Dialogue Planning | ['Justus-Jonas Erker', 'Stefan Schaffer', 'Gerasimos Spanakis'] | ['cs.CL'] | Inspired by the curvature of space-time (Einstein, 1921), we introduce Curved
Contrastive Learning (CCL), a novel representation learning technique for
learning the relative turn distance between utterance pairs in multi-turn
dialogues. The resulting bi-encoder models can guide transformers as a response
ranking model ... | 2022-11-14T18:16:48Z | Accepted in ACL 2023 Findings | null | null | null | null | null | null | null | null | null |
2,211.07636 | EVA: Exploring the Limits of Masked Visual Representation Learning at
Scale | ['Yuxin Fang', 'Wen Wang', 'Binhui Xie', 'Quan Sun', 'Ledell Wu', 'Xinggang Wang', 'Tiejun Huang', 'Xinlong Wang', 'Yue Cao'] | ['cs.CV', 'cs.CL', 'cs.LG'] | We launch EVA, a vision-centric foundation model to explore the limits of
visual representation at scale using only publicly accessible data. EVA is a
vanilla ViT pre-trained to reconstruct the masked out image-text aligned vision
features conditioned on visible image patches. Via this pretext task, we can
efficiently ... | 2022-11-14T18:59:52Z | v2: (i) fix / update EVA IN-1K variants results. (ii) add / update
EVA-CLIP results. (iii) add Appendix. (iv) release all the code and models at
https://github.com/baaivision/EVA | null | null | null | null | null | null | null | null | null |
2,211.08192 | RobBERT-2022: Updating a Dutch Language Model to Account for Evolving
Language Use | ['Pieter Delobelle', 'Thomas Winters', 'Bettina Berendt'] | ['cs.CL', 'cs.LG'] | Large transformer-based language models, e.g. BERT and GPT-3, outperform
previous architectures on most natural language processing tasks. Such language
models are first pre-trained on gigantic corpora of text and later used as
base-model for finetuning on a particular task. Since the pre-training step is
usually not r... | 2022-11-15T14:55:53Z | 9 pages, 1 figure, 3 tables | null | null | RobBERT-2022: Updating a Dutch Language Model to Account for Evolving Language Use | ['Pieter Delobelle', 'Thomas Winters', 'Bettina Berendt'] | 2,022 | arXiv.org | 6 | 36 | ['Computer Science'] |
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