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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
2,303.09435 | Jump to Conclusions: Short-Cutting Transformers With Linear
Transformations | ['Alexander Yom Din', 'Taelin Karidi', 'Leshem Choshen', 'Mor Geva'] | ['cs.CL'] | Transformer-based language models create hidden representations of their
inputs at every layer, but only use final-layer representations for prediction.
This obscures the internal decision-making process of the model and the utility
of its intermediate representations. One way to elucidate this is to cast the
hidden re... | 2023-03-16T16:10:16Z | null | LREC-COLING 2024 | null | Jump to Conclusions: Short-Cutting Transformers with Linear Transformations | ['Alexander Yom Din', 'Taelin Karidi', 'Leshem Choshen', 'Mor Geva'] | 2,023 | International Conference on Language Resources and Evaluation | 68 | 35 | ['Computer Science'] |
2,303.0954 | SemDeDup: Data-efficient learning at web-scale through semantic
deduplication | ['Amro Abbas', 'Kushal Tirumala', 'Dániel Simig', 'Surya Ganguli', 'Ari S. Morcos'] | ['cs.LG', 'cs.AI', 'cs.CV'] | Progress in machine learning has been driven in large part by massive
increases in data. However, large web-scale datasets such as LAION are largely
uncurated beyond searches for exact duplicates, potentially leaving much
redundancy. Here, we introduce SemDeDup, a method which leverages embeddings
from pre-trained mode... | 2023-03-16T17:53:24Z | null | null | null | SemDeDup: Data-efficient learning at web-scale through semantic deduplication | ['Amro Abbas', 'Kushal Tirumala', 'Daniel Simig', 'S. Ganguli', 'Ari S. Morcos'] | 2,023 | arXiv.org | 183 | 49 | ['Computer Science'] |
2,303.09556 | Efficient Diffusion Training via Min-SNR Weighting Strategy | ['Tiankai Hang', 'Shuyang Gu', 'Chen Li', 'Jianmin Bao', 'Dong Chen', 'Han Hu', 'Xin Geng', 'Baining Guo'] | ['cs.CV'] | Denoising diffusion models have been a mainstream approach for image
generation, however, training these models often suffers from slow convergence.
In this paper, we discovered that the slow convergence is partly due to
conflicting optimization directions between timesteps. To address this issue,
we treat the diffusio... | 2023-03-16T17:59:56Z | null | null | null | Efficient Diffusion Training via Min-SNR Weighting Strategy | ['Tiankai Hang', 'Shuyang Gu', 'Chen Li', 'Jianmin Bao', 'Dong Chen', 'Han Hu', 'Xin Geng', 'B. Guo'] | 2,023 | IEEE International Conference on Computer Vision | 163 | 61 | ['Computer Science'] |
2,303.09859 | Trained on 100 million words and still in shape: BERT meets British
National Corpus | ['David Samuel', 'Andrey Kutuzov', 'Lilja Øvrelid', 'Erik Velldal'] | ['cs.CL'] | While modern masked language models (LMs) are trained on ever larger corpora,
we here explore the effects of down-scaling training to a modestly-sized but
representative, well-balanced, and publicly available English text source --
the British National Corpus. We show that pre-training on this carefully
curated corpus ... | 2023-03-17T09:53:33Z | Accepted to EACL 2023 | null | null | null | null | null | null | null | null | null |
2,303.10008 | Configurable EBEN: Extreme Bandwidth Extension Network to enhance
body-conducted speech capture | ['Julien Hauret', 'Thomas Joubaud', 'Véronique Zimpfer', 'Éric Bavu'] | ['eess.AS', 'cs.SD'] | This paper presents a configurable version of Extreme Bandwidth Extension
Network (EBEN), a Generative Adversarial Network (GAN) designed to improve
audio captured with body-conduction microphones. We show that although these
microphones significantly reduce environmental noise, this insensitivity to
ambient noise happ... | 2023-03-17T14:31:24Z | Accepted in IEEE/ACM Transactions on Audio, Speech and Language
Processing on 14/08/2023 | IEEE/ACM Transactions on Audio, Speech, and Language Processing
(2023 - Volume: 31) - pp. 3499 - 3512 | 10.1109/TASLP.2023.3313433 | Configurable EBEN: Extreme Bandwidth Extension Network to Enhance Body-Conducted Speech Capture | ['Hauret Julien', 'Jo Thomas', 'V. Zimpfer', 'Bavu Éric'] | 2,023 | IEEE/ACM Transactions on Audio Speech and Language Processing | 7 | 103 | ['Computer Science', 'Engineering'] |
2,303.1013 | GPTs are GPTs: An Early Look at the Labor Market Impact Potential of
Large Language Models | ['Tyna Eloundou', 'Sam Manning', 'Pamela Mishkin', 'Daniel Rock'] | ['econ.GN', 'cs.AI', 'cs.CY', 'q-fin.EC'] | We investigate the potential implications of large language models (LLMs),
such as Generative Pre-trained Transformers (GPTs), on the U.S. labor market,
focusing on the increased capabilities arising from LLM-powered software
compared to LLMs on their own. Using a new rubric, we assess occupations based
on their alignm... | 2023-03-17T17:15:20Z | null | null | null | GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models | ['Tyna Eloundou', 'Sam Manning', 'Pamela Mishkin', 'Daniel Rock'] | 2,023 | arXiv.org | 405 | 92 | ['Economics', 'Computer Science'] |
2,303.10512 | AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning | ['Qingru Zhang', 'Minshuo Chen', 'Alexander Bukharin', 'Nikos Karampatziakis', 'Pengcheng He', 'Yu Cheng', 'Weizhu Chen', 'Tuo Zhao'] | ['cs.CL', 'cs.LG'] | Fine-tuning large pre-trained language models on downstream tasks has become
an important paradigm in NLP. However, common practice fine-tunes all of the
parameters in a pre-trained model, which becomes prohibitive when a large
number of downstream tasks are present. Therefore, many fine-tuning methods are
proposed to ... | 2023-03-18T22:36:25Z | The 11th International Conference on Learning Representations (ICLR
2023) | null | null | null | null | null | null | null | null | null |
2,303.10893 | Character, Word, or Both? Revisiting the Segmentation Granularity for
Chinese Pre-trained Language Models | ['Xinnian Liang', 'Zefan Zhou', 'Hui Huang', 'Shuangzhi Wu', 'Tong Xiao', 'Muyun Yang', 'Zhoujun Li', 'Chao Bian'] | ['cs.CL'] | Pretrained language models (PLMs) have shown marvelous improvements across
various NLP tasks. Most Chinese PLMs simply treat an input text as a sequence
of characters, and completely ignore word information. Although Whole Word
Masking can alleviate this, the semantics in words is still not well
represented. In this pa... | 2023-03-20T06:20:03Z | preprint | null | null | null | null | null | null | null | null | null |
2,303.10955 | Attacks Against Security Context in 5G Network | ['Zhiwei Cui', 'Baojiang Cui', 'Li Su', 'Haitao Du', 'Hongxin Wang', 'Junsong Fu'] | ['cs.CR'] | The security context used in 5G authentication is generated during the
Authentication and Key Agreement (AKA) procedure and stored in both the user
equipment (UE) and the network sides for the subsequent fast registration
procedure. Given its importance, it is imperative to formally analyze the
security mechanism of th... | 2023-03-20T09:30:26Z | The 6th International Symposium on Mobile Internet Security (MobiSec
22) | null | null | null | null | null | null | null | null | null |
2,303.11101 | Coreset Sampling from Open-Set for Fine-Grained Self-Supervised Learning | ['Sungnyun Kim', 'Sangmin Bae', 'Se-Young Yun'] | ['cs.CV'] | Deep learning in general domains has constantly been extended to
domain-specific tasks requiring the recognition of fine-grained
characteristics. However, real-world applications for fine-grained tasks suffer
from two challenges: a high reliance on expert knowledge for annotation and
necessity of a versatile model for ... | 2023-03-20T13:38:29Z | CVPR 2023 | null | null | null | null | null | null | null | null | null |
2,303.11301 | VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking | ['Yukang Chen', 'Jianhui Liu', 'Xiangyu Zhang', 'Xiaojuan Qi', 'Jiaya Jia'] | ['cs.CV'] | 3D object detectors usually rely on hand-crafted proxies, e.g., anchors or
centers, and translate well-studied 2D frameworks to 3D. Thus, sparse voxel
features need to be densified and processed by dense prediction heads, which
inevitably costs extra computation. In this paper, we instead propose VoxelNext
for fully sp... | 2023-03-20T17:40:44Z | In CVPR 2023, Code and models are available at
https://github.com/dvlab-research/VoxelNeXt | null | null | VoxelNeXt: Fully Sparse VoxelNet for 3D Object Detection and Tracking | ['Yukang Chen', 'Jianhui Liu', 'Xiangyu Zhang', 'Xiaojuan Qi', 'Jiaya Jia'] | 2,023 | Computer Vision and Pattern Recognition | 259 | 63 | ['Computer Science'] |
2,303.11328 | Zero-1-to-3: Zero-shot One Image to 3D Object | ['Ruoshi Liu', 'Rundi Wu', 'Basile Van Hoorick', 'Pavel Tokmakov', 'Sergey Zakharov', 'Carl Vondrick'] | ['cs.CV', 'cs.GR', 'cs.RO'] | We introduce Zero-1-to-3, a framework for changing the camera viewpoint of an
object given just a single RGB image. To perform novel view synthesis in this
under-constrained setting, we capitalize on the geometric priors that
large-scale diffusion models learn about natural images. Our conditional
diffusion model uses ... | 2023-03-20T17:59:50Z | Website: https://zero123.cs.columbia.edu/ | null | null | null | null | null | null | null | null | null |
2,303.11331 | EVA-02: A Visual Representation for Neon Genesis | ['Yuxin Fang', 'Quan Sun', 'Xinggang Wang', 'Tiejun Huang', 'Xinlong Wang', 'Yue Cao'] | ['cs.CV', 'cs.CL'] | We launch EVA-02, a next-generation Transformer-based visual representation
pre-trained to reconstruct strong and robust language-aligned vision features
via masked image modeling. With an updated plain Transformer architecture as
well as extensive pre-training from an open & accessible giant CLIP vision
encoder, EVA-0... | 2023-03-20T17:59:59Z | v2: Fix some known issues & typos. v1: To Asuka. Code & Models:
https://github.com/baaivision/EVA/tree/master/EVA-02 | Image and Vision Computing. Volume 149, September 2024, 105171 | 10.1016/j.imavis.2024.105171 | null | null | null | null | null | null | null |
2,303.11408 | Stable Bias: Analyzing Societal Representations in Diffusion Models | ['Alexandra Sasha Luccioni', 'Christopher Akiki', 'Margaret Mitchell', 'Yacine Jernite'] | ['cs.CY'] | As machine learning-enabled Text-to-Image (TTI) systems are becoming
increasingly prevalent and seeing growing adoption as commercial services,
characterizing the social biases they exhibit is a necessary first step to
lowering their risk of discriminatory outcomes. This evaluation, however, is
made more difficult by t... | 2023-03-20T19:32:49Z | Accepted to NeurIPS Datasets and Benchmarks 2023 (spotlight) | null | null | Stable Bias: Analyzing Societal Representations in Diffusion Models | ['A. Luccioni', 'Christopher Akiki', 'Margaret Mitchell', 'Yacine Jernite'] | 2,023 | arXiv.org | 161 | 101 | ['Computer Science'] |
2,303.11589 | LayoutDiffusion: Improving Graphic Layout Generation by Discrete
Diffusion Probabilistic Models | ['Junyi Zhang', 'Jiaqi Guo', 'Shizhao Sun', 'Jian-Guang Lou', 'Dongmei Zhang'] | ['cs.CV'] | Creating graphic layouts is a fundamental step in graphic designs. In this
work, we present a novel generative model named LayoutDiffusion for automatic
layout generation. As layout is typically represented as a sequence of discrete
tokens, LayoutDiffusion models layout generation as a discrete denoising
diffusion proc... | 2023-03-21T04:41:02Z | Accepted by ICCV2023, project page: https://layoutdiffusion.github.io | null | null | null | null | null | null | null | null | null |
2,303.11897 | TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation
with Question Answering | ['Yushi Hu', 'Benlin Liu', 'Jungo Kasai', 'Yizhong Wang', 'Mari Ostendorf', 'Ranjay Krishna', 'Noah A Smith'] | ['cs.CV'] | Despite thousands of researchers, engineers, and artists actively working on
improving text-to-image generation models, systems often fail to produce images
that accurately align with the text inputs. We introduce TIFA (Text-to-Image
Faithfulness evaluation with question Answering), an automatic evaluation
metric that ... | 2023-03-21T14:41:02Z | Accepted to ICCV 2023 | null | null | TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering | ['Yushi Hu', 'Benlin Liu', 'Jungo Kasai', 'Yizhong Wang', 'Mari Ostendorf', 'Ranjay Krishna', 'Noah A. Smith'] | 2,023 | IEEE International Conference on Computer Vision | 239 | 64 | ['Computer Science'] |
2,303.12188 | Toward Accurate Interpretable Predictions of Materials Properties within
Transformer Language Models | ['Vadim Korolev', 'Pavel Protsenko'] | ['cond-mat.mtrl-sci', 'physics.comp-ph'] | Property prediction accuracy has long been a key parameter of machine
learning in materials informatics. Accordingly, advanced models showing
state-of-the-art performance turn into highly parameterized black boxes missing
interpretability. Here, we present an elegant way to make their reasoning
transparent. Human-reada... | 2023-03-21T20:33:12Z | 17 pages, 5 figures, 1 table | null | 10.1016/j.patter.2023.100803 | null | null | null | null | null | null | null |
2,303.12659 | Posthoc Interpretation via Quantization | ['Francesco Paissan', 'Cem Subakan', 'Mirco Ravanelli'] | ['cs.AI', 'cs.LG', 'cs.SD', 'eess.AS'] | In this paper, we introduce a new approach, called Posthoc Interpretation via
Quantization (PIQ), for interpreting decisions made by trained classifiers. Our
method utilizes vector quantization to transform the representations of a
classifier into a discrete, class-specific latent space. The class-specific
codebooks ac... | 2023-03-22T15:37:43Z | Francesco Paissan and Cem Subakan contributed equally | null | null | Posthoc Interpretation via Quantization | ['Cem Subakan', 'F. Paissan', 'M. Ravanelli'] | 2,023 | arXiv.org | 7 | 33 | ['Computer Science', 'Engineering'] |
2,303.12665 | Can We Identify Stance Without Target Arguments? A Study for Rumour
Stance Classification | ['Yue Li', 'Carolina Scarton'] | ['cs.CL'] | Considering a conversation thread, rumour stance classification aims to
identify the opinion (e.g. agree or disagree) of replies towards a target
(rumour story). Although the target is expected to be an essential component in
traditional stance classification, we show that rumour stance classification
datasets contain ... | 2023-03-22T15:44:15Z | This paper has been accepted by The 2024 Joint International
Conference on Computational Linguistics, Language Resources and Evaluation
(LREC-COLING 2024) | null | null | null | null | null | null | null | null | null |
2,303.12733 | On the De-duplication of LAION-2B | ['Ryan Webster', 'Julien Rabin', 'Loic Simon', 'Frederic Jurie'] | ['cs.CV', 'cs.AI'] | Generative models, such as DALL-E, Midjourney, and Stable Diffusion, have
societal implications that extend beyond the field of computer science. These
models require large image databases like LAION-2B, which contain two billion
images. At this scale, manual inspection is difficult and automated analysis is
challengin... | 2023-03-17T17:39:06Z | null | null | null | On the De-duplication of LAION-2B | ['Ryan Webster', 'J. Rabin', 'Loïc Simon', 'F. Jurie'] | 2,023 | arXiv.org | 42 | 25 | ['Computer Science'] |
2,303.13071 | PanoHead: Geometry-Aware 3D Full-Head Synthesis in 360$^{\circ}$ | ['Sizhe An', 'Hongyi Xu', 'Yichun Shi', 'Guoxian Song', 'Umit Ogras', 'Linjie Luo'] | ['cs.CV'] | Synthesis and reconstruction of 3D human head has gained increasing interests
in computer vision and computer graphics recently. Existing state-of-the-art 3D
generative adversarial networks (GANs) for 3D human head synthesis are either
limited to near-frontal views or hard to preserve 3D consistency in large view
angle... | 2023-03-23T06:54:34Z | CVPR 2023. Project Page:https://sizhean.github.io/panohead | null | null | null | null | null | null | null | null | null |
2,303.13117 | RLOR: A Flexible Framework of Deep Reinforcement Learning for Operation
Research | ['Ching Pui Wan', 'Tung Li', 'Jason Min Wang'] | ['math.OC', 'cs.LG', 'cs.NE'] | Reinforcement learning has been applied in operation research and has shown
promise in solving large combinatorial optimization problems. However, existing
works focus on developing neural network architectures for certain problems.
These works lack the flexibility to incorporate recent advances in
reinforcement learni... | 2023-03-23T09:07:30Z | 21 pages | null | null | RLOR: A Flexible Framework of Deep Reinforcement Learning for Operation Research | ['Ching Pui Wan', 'Tung Li', 'Jason Min Wang'] | 2,023 | arXiv.org | 2 | 31 | ['Computer Science', 'Mathematics'] |
2,303.1331 | SwissBERT: The Multilingual Language Model for Switzerland | ['Jannis Vamvas', 'Johannes Graën', 'Rico Sennrich'] | ['cs.CL'] | We present SwissBERT, a masked language model created specifically for
processing Switzerland-related text. SwissBERT is a pre-trained model that we
adapted to news articles written in the national languages of Switzerland --
German, French, Italian, and Romansh. We evaluate SwissBERT on natural language
understanding ... | 2023-03-23T14:44:47Z | SwissText 2023 [v3: Changed template because the proceedings moved to
a different publisher. Same content.] | null | null | null | null | null | null | null | null | null |
2,303.1334 | Increasing Textual Context Size Boosts Medical Image-Text Matching | ['Idan Glassberg', 'Tom Hope'] | ['cs.LG', 'cs.CV'] | This short technical report demonstrates a simple technique that yields state
of the art results in medical image-text matching tasks. We analyze the use of
OpenAI's CLIP, a general image-text matching model, and observe that CLIP's
limited textual input size has negative impact on downstream performance in the
medical... | 2023-03-23T15:20:05Z | null | null | null | null | null | null | null | null | null | null |
2,303.13375 | Capabilities of GPT-4 on Medical Challenge Problems | ['Harsha Nori', 'Nicholas King', 'Scott Mayer McKinney', 'Dean Carignan', 'Eric Horvitz'] | ['cs.CL', 'cs.AI'] | Large language models (LLMs) have demonstrated remarkable capabilities in
natural language understanding and generation across various domains, including
medicine. We present a comprehensive evaluation of GPT-4, a state-of-the-art
LLM, on medical competency examinations and benchmark datasets. GPT-4 is a
general-purpos... | 2023-03-20T16:18:38Z | 35 pages, 15 figures; added GPT-4-base model results and discussion | null | null | null | null | null | null | null | null | null |
2,303.13408 | Paraphrasing evades detectors of AI-generated text, but retrieval is an
effective defense | ['Kalpesh Krishna', 'Yixiao Song', 'Marzena Karpinska', 'John Wieting', 'Mohit Iyyer'] | ['cs.CL', 'cs.CR', 'cs.LG'] | The rise in malicious usage of large language models, such as fake content
creation and academic plagiarism, has motivated the development of approaches
that identify AI-generated text, including those based on watermarking or
outlier detection. However, the robustness of these detection algorithms to
paraphrases of AI... | 2023-03-23T16:29:27Z | NeurIPS 2023 camera ready (32 pages). Code, models, data available in
https://github.com/martiansideofthemoon/ai-detection-paraphrases | null | null | null | null | null | null | null | null | null |
2,303.13439 | Text2Video-Zero: Text-to-Image Diffusion Models are Zero-Shot Video
Generators | ['Levon Khachatryan', 'Andranik Movsisyan', 'Vahram Tadevosyan', 'Roberto Henschel', 'Zhangyang Wang', 'Shant Navasardyan', 'Humphrey Shi'] | ['cs.CV'] | Recent text-to-video generation approaches rely on computationally heavy
training and require large-scale video datasets. In this paper, we introduce a
new task of zero-shot text-to-video generation and propose a low-cost approach
(without any training or optimization) by leveraging the power of existing
text-to-image ... | 2023-03-23T17:01:59Z | The project is available at:
https://github.com/Picsart-AI-Research/Text2Video-Zero | null | null | null | null | null | null | null | null | null |
2,303.1407 | ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model
Meta-AI (LLaMA) Using Medical Domain Knowledge | ['Yunxiang Li', 'Zihan Li', 'Kai Zhang', 'Ruilong Dan', 'Steve Jiang', 'You Zhang'] | ['cs.CL'] | The primary aim of this research was to address the limitations observed in
the medical knowledge of prevalent large language models (LLMs) such as
ChatGPT, by creating a specialized language model with enhanced accuracy in
medical advice. We achieved this by adapting and refining the large language
model meta-AI (LLaM... | 2023-03-24T15:29:16Z | null | null | null | null | null | null | null | null | null | null |
2,303.14087 | OPDMulti: Openable Part Detection for Multiple Objects | ['Xiaohao Sun', 'Hanxiao Jiang', 'Manolis Savva', 'Angel Xuan Chang'] | ['cs.CV'] | Openable part detection is the task of detecting the openable parts of an
object in a single-view image, and predicting corresponding motion parameters.
Prior work investigated the unrealistic setting where all input images only
contain a single openable object. We generalize this task to scenes with
multiple objects e... | 2023-03-24T15:52:20Z | null | null | null | null | null | null | null | null | null | null |
2,303.14158 | BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown
Objects | ['Bowen Wen', 'Jonathan Tremblay', 'Valts Blukis', 'Stephen Tyree', 'Thomas Muller', 'Alex Evans', 'Dieter Fox', 'Jan Kautz', 'Stan Birchfield'] | ['cs.CV', 'cs.AI', 'cs.GR', 'cs.RO'] | We present a near real-time method for 6-DoF tracking of an unknown object
from a monocular RGBD video sequence, while simultaneously performing neural 3D
reconstruction of the object. Our method works for arbitrary rigid objects,
even when visual texture is largely absent. The object is assumed to be
segmented in the ... | 2023-03-24T17:13:49Z | CVPR 2023 | null | null | BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects | ['Bowen Wen', 'Jonathan Tremblay', 'Valts Blukis', 'Stephen Tyree', 'T. Muller', 'Alex Evans', 'D. Fox', 'J. Kautz', 'Stan Birchfield'] | 2,023 | Computer Vision and Pattern Recognition | 139 | 89 | ['Computer Science'] |
2,303.14177 | Scaling Expert Language Models with Unsupervised Domain Discovery | ['Suchin Gururangan', 'Margaret Li', 'Mike Lewis', 'Weijia Shi', 'Tim Althoff', 'Noah A. Smith', 'Luke Zettlemoyer'] | ['cs.CL', 'cs.AI'] | Large language models are typically trained densely: all parameters are
updated with respect to all inputs. This requires synchronization of billions
of parameters across thousands of GPUs. We introduce a simple but effective
method to asynchronously train large, sparse language models on arbitrary text
corpora. Our me... | 2023-03-24T17:38:58Z | null | null | null | null | null | null | null | null | null | null |
2,303.14189 | FastViT: A Fast Hybrid Vision Transformer using Structural
Reparameterization | ['Pavan Kumar Anasosalu Vasu', 'James Gabriel', 'Jeff Zhu', 'Oncel Tuzel', 'Anurag Ranjan'] | ['cs.CV'] | The recent amalgamation of transformer and convolutional designs has led to
steady improvements in accuracy and efficiency of the models. In this work, we
introduce FastViT, a hybrid vision transformer architecture that obtains the
state-of-the-art latency-accuracy trade-off. To this end, we introduce a novel
token mix... | 2023-03-24T17:58:32Z | ICCV 2023 | null | null | FastViT: A Fast Hybrid Vision Transformer using Structural Reparameterization | ['Pavan Kumar Anasosalu Vasu', 'J. Gabriel', 'Jeff J. Zhu', 'Oncel Tuzel', 'Anurag Ranjan'] | 2,023 | IEEE International Conference on Computer Vision | 168 | 79 | ['Computer Science'] |
2,303.14588 | Fine-Tashkeel: Finetuning Byte-Level Models for Accurate Arabic Text
Diacritization | ['Bashar Al-Rfooh', 'Gheith Abandah', 'Rami Al-Rfou'] | ['cs.CL'] | Most of previous work on learning diacritization of the Arabic language
relied on training models from scratch. In this paper, we investigate how to
leverage pre-trained language models to learn diacritization. We finetune
token-free pre-trained multilingual models (ByT5) to learn to predict and
insert missing diacriti... | 2023-03-25T23:41:33Z | null | null | null | null | null | null | null | null | null | null |
2,303.14822 | MGTBench: Benchmarking Machine-Generated Text Detection | ['Xinlei He', 'Xinyue Shen', 'Zeyuan Chen', 'Michael Backes', 'Yang Zhang'] | ['cs.CR', 'cs.LG'] | Nowadays, powerful large language models (LLMs) such as ChatGPT have
demonstrated revolutionary power in a variety of tasks. Consequently, the
detection of machine-generated texts (MGTs) is becoming increasingly crucial as
LLMs become more advanced and prevalent. These models have the ability to
generate human-like lan... | 2023-03-26T21:12:36Z | null | null | null | null | null | null | null | null | null | null |
2,303.15056 | ChatGPT Outperforms Crowd-Workers for Text-Annotation Tasks | ['Fabrizio Gilardi', 'Meysam Alizadeh', 'Maël Kubli'] | ['cs.CL', 'cs.CY'] | Many NLP applications require manual data annotations for a variety of tasks,
notably to train classifiers or evaluate the performance of unsupervised
models. Depending on the size and degree of complexity, the tasks may be
conducted by crowd-workers on platforms such as MTurk as well as trained
annotators, such as res... | 2023-03-27T09:59:48Z | Gilardi, Fabrizio, Meysam Alizadeh, and Ma\"el Kubli. 2023. "ChatGPT
Outperforms Crowd Workers for Text-Annotation Tasks". Proceedings of the
National Academy of Sciences 120(30): e2305016120 | null | 10.1073/pnas.2305016120 | null | null | null | null | null | null | null |
2,303.15343 | Sigmoid Loss for Language Image Pre-Training | ['Xiaohua Zhai', 'Basil Mustafa', 'Alexander Kolesnikov', 'Lucas Beyer'] | ['cs.CV', 'cs.AI'] | We propose a simple pairwise Sigmoid loss for Language-Image Pre-training
(SigLIP). Unlike standard contrastive learning with softmax normalization, the
sigmoid loss operates solely on image-text pairs and does not require a global
view of the pairwise similarities for normalization. The sigmoid loss
simultaneously all... | 2023-03-27T15:53:01Z | ICCV'23 Oral. arXiv v2: fix typo in pseudocode; v3: clarify t vs t'
init; v4: add SigLIP Base, Large, Shape-Optimized 400M results. Models
released at: https://github.com/google-research/big_vision. Xiaohua and Lucas
contributed equally | null | null | null | null | null | null | null | null | null |
2,303.15389 | EVA-CLIP: Improved Training Techniques for CLIP at Scale | ['Quan Sun', 'Yuxin Fang', 'Ledell Wu', 'Xinlong Wang', 'Yue Cao'] | ['cs.CV'] | Contrastive language-image pre-training, CLIP for short, has gained
increasing attention for its potential in various scenarios. In this paper, we
propose EVA-CLIP, a series of models that significantly improve the efficiency
and effectiveness of CLIP training. Our approach incorporates new techniques
for representatio... | 2023-03-27T17:02:21Z | To Rei and the moon. Code & Models:
https://github.com/baaivision/EVA/tree/master/EVA-CLIP | null | null | EVA-CLIP: Improved Training Techniques for CLIP at Scale | ['Quan Sun', 'Yuxin Fang', 'Ledell Yu Wu', 'Xinlong Wang', 'Yue Cao'] | 2,023 | arXiv.org | 513 | 51 | ['Computer Science'] |
2,303.15422 | KPEval: Towards Fine-Grained Semantic-Based Keyphrase Evaluation | ['Di Wu', 'Da Yin', 'Kai-Wei Chang'] | ['cs.CL'] | Despite the significant advancements in keyphrase extraction and keyphrase
generation methods, the predominant approach for evaluation mainly relies on
exact matching with human references. This scheme fails to recognize systems
that generate keyphrases semantically equivalent to the references or diverse
keyphrases th... | 2023-03-27T17:45:38Z | ACL 2024 (Findings) | null | null | null | null | null | null | null | null | null |
2,303.15435 | The Stable Signature: Rooting Watermarks in Latent Diffusion Models | ['Pierre Fernandez', 'Guillaume Couairon', 'Hervé Jégou', 'Matthijs Douze', 'Teddy Furon'] | ['cs.CV', 'cs.AI'] | Generative image modeling enables a wide range of applications but raises
ethical concerns about responsible deployment. This paper introduces an active
strategy combining image watermarking and Latent Diffusion Models. The goal is
for all generated images to conceal an invisible watermark allowing for future
detection... | 2023-03-27T17:57:33Z | Published at ICCV 2023. Code at
https://github.com/facebookresearch/stable_signature - webpage at
https://pierrefdz.github.io/publications/stablesignature | null | null | null | null | null | null | null | null | null |
2,303.15446 | SwiftFormer: Efficient Additive Attention for Transformer-based
Real-time Mobile Vision Applications | ['Abdelrahman Shaker', 'Muhammad Maaz', 'Hanoona Rasheed', 'Salman Khan', 'Ming-Hsuan Yang', 'Fahad Shahbaz Khan'] | ['cs.CV'] | Self-attention has become a defacto choice for capturing global context in
various vision applications. However, its quadratic computational complexity
with respect to image resolution limits its use in real-time applications,
especially for deployment on resource-constrained mobile devices. Although
hybrid approaches ... | 2023-03-27T17:59:58Z | Accepted at ICCV 2023 | null | null | null | null | null | null | null | null | null |
2,303.15621 | ChatGPT as a Factual Inconsistency Evaluator for Text Summarization | ['Zheheng Luo', 'Qianqian Xie', 'Sophia Ananiadou'] | ['cs.CL'] | The performance of text summarization has been greatly boosted by pre-trained
language models. A main concern of existing methods is that most generated
summaries are not factually inconsistent with their source documents. To
alleviate the problem, many efforts have focused on developing effective
factuality evaluation... | 2023-03-27T22:30:39Z | ongoing work, 12 pages, 4 figures | null | null | null | null | null | null | null | null | null |
2,303.15935 | When Brain-inspired AI Meets AGI | ['Lin Zhao', 'Lu Zhang', 'Zihao Wu', 'Yuzhong Chen', 'Haixing Dai', 'Xiaowei Yu', 'Zhengliang Liu', 'Tuo Zhang', 'Xintao Hu', 'Xi Jiang', 'Xiang Li', 'Dajiang Zhu', 'Dinggang Shen', 'Tianming Liu'] | ['cs.AI'] | Artificial General Intelligence (AGI) has been a long-standing goal of
humanity, with the aim of creating machines capable of performing any
intellectual task that humans can do. To achieve this, AGI researchers draw
inspiration from the human brain and seek to replicate its principles in
intelligent machines. Brain-in... | 2023-03-28T12:46:38Z | null | null | null | When Brain-inspired AI Meets AGI | ['Lin Zhao', 'Lu Zhang', 'Zihao Wu', 'Yuzhong Chen', 'Haixing Dai', 'Xiao-Xing Yu', 'Zheng Liu', 'Tuo Zhang', 'Xintao Hu', 'Xi Jiang', 'Xiang Li', 'Dajiang Zhu', 'Dinggang Shen', 'Tianming Liu'] | 2,023 | Meta-Radiology | 91 | 130 | ['Computer Science'] |
2,303.15937 | PosterLayout: A New Benchmark and Approach for Content-aware
Visual-Textual Presentation Layout | ['HsiaoYuan Hsu', 'Xiangteng He', 'Yuxin Peng', 'Hao Kong', 'Qing Zhang'] | ['cs.CV'] | Content-aware visual-textual presentation layout aims at arranging spatial
space on the given canvas for pre-defined elements, including text, logo, and
underlay, which is a key to automatic template-free creative graphic design. In
practical applications, e.g., poster designs, the canvas is originally
non-empty, and b... | 2023-03-28T12:48:36Z | Accepted to CVPR 2023. Dataset and code are available at
https://github.com/PKU-ICST-MIPL/PosterLayout-CVPR2023 | null | null | PosterLayout: A New Benchmark and Approach for Content-Aware Visual-Textual Presentation Layout | ['Hsiao-An Hsu', 'Xiangteng He', 'Yuxin Peng', 'Hao-Song Kong', 'Qing Zhang'] | 2,023 | Computer Vision and Pattern Recognition | 37 | 23 | ['Computer Science'] |
2,303.1616 | One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer | ['Jing Lin', 'Ailing Zeng', 'Haoqian Wang', 'Lei Zhang', 'Yu Li'] | ['cs.CV'] | Whole-body mesh recovery aims to estimate the 3D human body, face, and hands
parameters from a single image. It is challenging to perform this task with a
single network due to resolution issues, i.e., the face and hands are usually
located in extremely small regions. Existing works usually detect hands and
faces, enla... | 2023-03-28T17:24:42Z | Accepted to CVPR2023; Top-1 on AGORA SMPLX benchmark; Project Page:
https://osx-ubody.github.io/ | null | null | One-Stage 3D Whole-Body Mesh Recovery with Component Aware Transformer | ['Jing-de Lin', 'Ailing Zeng', 'Haoqian Wang', 'Lei Zhang', 'Y. Li'] | 2,023 | Computer Vision and Pattern Recognition | 106 | 77 | ['Computer Science'] |
2,303.16199 | LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init
Attention | ['Renrui Zhang', 'Jiaming Han', 'Chris Liu', 'Peng Gao', 'Aojun Zhou', 'Xiangfei Hu', 'Shilin Yan', 'Pan Lu', 'Hongsheng Li', 'Yu Qiao'] | ['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG', 'cs.MM'] | We present LLaMA-Adapter, a lightweight adaption method to efficiently
fine-tune LLaMA into an instruction-following model. Using 52K self-instruct
demonstrations, LLaMA-Adapter only introduces 1.2M learnable parameters upon
the frozen LLaMA 7B model, and costs less than one hour for fine-tuning on 8
A100 GPUs. Specifi... | 2023-03-28T17:59:12Z | Accepted by ICLR 2024. Code is available at
https://github.com/OpenGVLab/LLaMA-Adapter | null | null | LLaMA-Adapter: Efficient Fine-tuning of Language Models with Zero-init Attention | ['Renrui Zhang', 'Jiaming Han', 'Aojun Zhou', 'Xiangfei Hu', 'Shilin Yan', 'Pan Lu', 'Hongsheng Li', 'Peng Gao', 'Y. Qiao'] | 2,023 | arXiv.org | 788 | 137 | ['Computer Science'] |
2,303.16634 | G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment | ['Yang Liu', 'Dan Iter', 'Yichong Xu', 'Shuohang Wang', 'Ruochen Xu', 'Chenguang Zhu'] | ['cs.CL', 'cs.AI'] | The quality of texts generated by natural language generation (NLG) systems
is hard to measure automatically. Conventional reference-based metrics, such as
BLEU and ROUGE, have been shown to have relatively low correlation with human
judgments, especially for tasks that require creativity and diversity. Recent
studies ... | 2023-03-29T12:46:54Z | null | null | null | G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment | ['Yang Liu', 'Dan Iter', 'Yichong Xu', 'Shuo Wang', 'Ruochen Xu', 'Chenguang Zhu'] | 2,023 | Conference on Empirical Methods in Natural Language Processing | 1,216 | 40 | ['Computer Science'] |
2,303.16727 | VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking | ['Limin Wang', 'Bingkun Huang', 'Zhiyu Zhao', 'Zhan Tong', 'Yinan He', 'Yi Wang', 'Yali Wang', 'Yu Qiao'] | ['cs.CV', 'cs.LG'] | Scale is the primary factor for building a powerful foundation model that
could well generalize to a variety of downstream tasks. However, it is still
challenging to train video foundation models with billions of parameters. This
paper shows that video masked autoencoder (VideoMAE) is a scalable and general
self-superv... | 2023-03-29T14:28:41Z | CVPR 2023 camera-ready version | null | null | null | null | null | null | null | null | null |
2,303.16755 | Training Language Models with Language Feedback at Scale | ['Jérémy Scheurer', 'Jon Ander Campos', 'Tomasz Korbak', 'Jun Shern Chan', 'Angelica Chen', 'Kyunghyun Cho', 'Ethan Perez'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Pretrained language models often generate outputs that are not in line with
human preferences, such as harmful text or factually incorrect summaries.
Recent work approaches the above issues by learning from a simple form of human
feedback: comparisons between pairs of model-generated outputs. However,
comparison feedba... | 2023-03-28T17:04:15Z | Published in TMLR: https://openreview.net/forum?id=xo3hI5MwvU | null | null | null | null | null | null | null | null | null |
2,303.169 | InceptionNeXt: When Inception Meets ConvNeXt | ['Weihao Yu', 'Pan Zhou', 'Shuicheng Yan', 'Xinchao Wang'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Inspired by the long-range modeling ability of ViTs, large-kernel
convolutions are widely studied and adopted recently to enlarge the receptive
field and improve model performance, like the remarkable work ConvNeXt which
employs 7x7 depthwise convolution. Although such depthwise operator only
consumes a few FLOPs, it l... | 2023-03-29T17:59:58Z | CVPR 2024. Code: https://github.com/sail-sg/inceptionnext | null | null | null | null | null | null | null | null | null |
2,303.17009 | A comparative evaluation of image-to-image translation methods for stain
transfer in histopathology | ['Igor Zingman', 'Sergio Frayle', 'Ivan Tankoyeu', 'Segrey Sukhanov', 'Fabian Heinemann'] | ['eess.IV', 'cs.CV', 'cs.LG'] | Image-to-image translation (I2I) methods allow the generation of artificial
images that share the content of the original image but have a different style.
With the advances in Generative Adversarial Networks (GANs)-based methods, I2I
methods enabled the generation of artificial images that are indistinguishable
from n... | 2023-03-29T20:27:49Z | 17 pages, 3 figures, 5 tables, accepted to Medical Imaging with Deep
Learning (MIDL) 2023, to be published in Proceedings of Machine Learning
Research | null | null | A comparative evaluation of image-to-image translation methods for stain transfer in histopathology | ['I. Zingman', 'Sergio Frayle', 'Ivan Tankoyeu', 'Segrey Sukhanov', 'Fabian Heinemann'] | 2,023 | International Conference on Medical Imaging with Deep Learning | 13 | 46 | ['Engineering', 'Computer Science'] |
2,303.17183 | The Nordic Pile: A 1.2TB Nordic Dataset for Language Modeling | ['Joey Öhman', 'Severine Verlinden', 'Ariel Ekgren', 'Amaru Cuba Gyllensten', 'Tim Isbister', 'Evangelia Gogoulou', 'Fredrik Carlsson', 'Magnus Sahlgren'] | ['cs.CL', 'cs.AI'] | Pre-training Large Language Models (LLMs) require massive amounts of text
data, and the performance of the LLMs typically correlates with the scale and
quality of the datasets. This means that it may be challenging to build LLMs
for smaller languages such as Nordic ones, where the availability of text
corpora is limite... | 2023-03-30T06:42:22Z | null | null | null | The Nordic Pile: A 1.2TB Nordic Dataset for Language Modeling | ['Joey Ohman', 'S. Verlinden', 'Ariel Ekgren', 'Amaru Cuba Gyllensten', 'T. Isbister', 'Evangelia Gogoulou', 'F. Carlsson', 'Magnus Sahlgren'] | 2,023 | arXiv.org | 11 | 21 | ['Computer Science'] |
2,303.17546 | PAIR-Diffusion: A Comprehensive Multimodal Object-Level Image Editor | ['Vidit Goel', 'Elia Peruzzo', 'Yifan Jiang', 'Dejia Xu', 'Xingqian Xu', 'Nicu Sebe', 'Trevor Darrell', 'Zhangyang Wang', 'Humphrey Shi'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Generative image editing has recently witnessed extremely fast-paced growth.
Some works use high-level conditioning such as text, while others use low-level
conditioning. Nevertheless, most of them lack fine-grained control over the
properties of the different objects present in the image, i.e. object-level
image editi... | 2023-03-30T17:13:56Z | Accepted in CVPR 2024, Project page
https://vidit98.github.io/publication/conference-paper/pair_diff.html | null | null | null | null | null | null | null | null | null |
2,303.17564 | BloombergGPT: A Large Language Model for Finance | ['Shijie Wu', 'Ozan Irsoy', 'Steven Lu', 'Vadim Dabravolski', 'Mark Dredze', 'Sebastian Gehrmann', 'Prabhanjan Kambadur', 'David Rosenberg', 'Gideon Mann'] | ['cs.LG', 'cs.AI', 'cs.CL', 'q-fin.GN'] | The use of NLP in the realm of financial technology is broad and complex,
with applications ranging from sentiment analysis and named entity recognition
to question answering. Large Language Models (LLMs) have been shown to be
effective on a variety of tasks; however, no LLM specialized for the financial
domain has bee... | 2023-03-30T17:30:36Z | Updated to include Training Chronicles (Appendix C) | null | null | null | null | null | null | null | null | null |
2,303.17568 | CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual
Benchmarking on HumanEval-X | ['Qinkai Zheng', 'Xiao Xia', 'Xu Zou', 'Yuxiao Dong', 'Shan Wang', 'Yufei Xue', 'Zihan Wang', 'Lei Shen', 'Andi Wang', 'Yang Li', 'Teng Su', 'Zhilin Yang', 'Jie Tang'] | ['cs.LG', 'cs.AI', 'cs.SE'] | Large pre-trained code generation models, such as OpenAI Codex, can generate
syntax- and function-correct code, making the coding of programmers more
productive and our pursuit of artificial general intelligence closer. In this
paper, we introduce CodeGeeX, a multilingual model with 13 billion parameters
for code gener... | 2023-03-30T17:34:01Z | null | null | null | null | null | null | null | null | null | null |
2,303.1776 | CAMEL: Communicative Agents for "Mind" Exploration of Large Language
Model Society | ['Guohao Li', 'Hasan Abed Al Kader Hammoud', 'Hani Itani', 'Dmitrii Khizbullin', 'Bernard Ghanem'] | ['cs.AI', 'cs.CL', 'cs.CY', 'cs.LG', 'cs.MA'] | The rapid advancement of chat-based language models has led to remarkable
progress in complex task-solving. However, their success heavily relies on
human input to guide the conversation, which can be challenging and
time-consuming. This paper explores the potential of building scalable
techniques to facilitate autonom... | 2023-03-31T01:09:00Z | Accepted at NeurIPS'2023, 77 pages, project website:
https://www.camel-ai.org, github repository:
https://github.com/camel-ai/camel | null | null | null | null | null | null | null | null | null |
2,303.18027 | Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations | ['Jungo Kasai', 'Yuhei Kasai', 'Keisuke Sakaguchi', 'Yutaro Yamada', 'Dragomir Radev'] | ['cs.CL'] | As large language models (LLMs) gain popularity among speakers of diverse
languages, we believe that it is crucial to benchmark them to better understand
model behaviors, failures, and limitations in languages beyond English. In this
work, we evaluate LLM APIs (ChatGPT, GPT-3, and GPT-4) on the Japanese national
medica... | 2023-03-31T13:04:47Z | Added results from the March 2023 exam | null | null | Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinations | ['Jungo Kasai', 'Y. Kasai', 'Keisuke Sakaguchi', 'Yutaro Yamada', 'Dragomir R. Radev'] | 2,023 | arXiv.org | 107 | 82 | ['Computer Science'] |
2,303.1824 | Where are we in the search for an Artificial Visual Cortex for Embodied
Intelligence? | ['Arjun Majumdar', 'Karmesh Yadav', 'Sergio Arnaud', 'Yecheng Jason Ma', 'Claire Chen', 'Sneha Silwal', 'Aryan Jain', 'Vincent-Pierre Berges', 'Pieter Abbeel', 'Jitendra Malik', 'Dhruv Batra', 'Yixin Lin', 'Oleksandr Maksymets', 'Aravind Rajeswaran', 'Franziska Meier'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.RO'] | We present the largest and most comprehensive empirical study of pre-trained
visual representations (PVRs) or visual 'foundation models' for Embodied AI.
First, we curate CortexBench, consisting of 17 different tasks spanning
locomotion, navigation, dexterous, and mobile manipulation. Next, we
systematically evaluate e... | 2023-03-31T17:56:33Z | Project website: https://eai-vc.github.io | null | null | Where are we in the search for an Artificial Visual Cortex for Embodied Intelligence? | ['Arjun Majumdar', 'Karmesh Yadav', 'Sergio Arnaud', 'Yecheng Jason Ma', 'Claire Chen', 'Sneha Silwal', 'Aryan Jain', 'Vincent-Pierre Berges', 'P. Abbeel', 'J. Malik', 'Dhruv Batra', 'Yixin Lin', 'Oleksandr Maksymets', 'A. Rajeswaran', 'Franziska Meier'] | 2,023 | Neural Information Processing Systems | 185 | 83 | ['Computer Science'] |
2,303.18248 | Towards Flexible Multi-modal Document Models | ['Naoto Inoue', 'Kotaro Kikuchi', 'Edgar Simo-Serra', 'Mayu Otani', 'Kota Yamaguchi'] | ['cs.CV'] | Creative workflows for generating graphical documents involve complex
inter-related tasks, such as aligning elements, choosing appropriate fonts, or
employing aesthetically harmonious colors. In this work, we attempt at building
a holistic model that can jointly solve many different design tasks. Our model,
which we de... | 2023-03-31T17:59:56Z | To be published in CVPR2023 (highlight), project page:
https://cyberagentailab.github.io/flex-dm | null | null | Towards Flexible Multi-modal Document Models | ['Naoto Inoue', 'Kotaro Kikuchi', 'E. Simo-Serra', 'Mayu Otani', 'Kota Yamaguchi'] | 2,023 | Computer Vision and Pattern Recognition | 22 | 58 | ['Computer Science'] |
2,304.00869 | GreekBART: The First Pretrained Greek Sequence-to-Sequence Model | ['Iakovos Evdaimon', 'Hadi Abdine', 'Christos Xypolopoulos', 'Stamatis Outsios', 'Michalis Vazirgiannis', 'Giorgos Stamou'] | ['cs.CL'] | The era of transfer learning has revolutionized the fields of Computer Vision
and Natural Language Processing, bringing powerful pretrained models with
exceptional performance across a variety of tasks. Specifically, Natural
Language Processing tasks have been dominated by transformer-based language
models. In Natural ... | 2023-04-03T10:48:51Z | null | null | null | GreekBART: The First Pretrained Greek Sequence-to-Sequence Model | ['Iakovos Evdaimon', 'Hadi Abdine', 'Christos Xypolopoulos', 'Stamatis Outsios', 'M. Vazirgiannis', 'G. Stamou'] | 2,023 | International Conference on Language Resources and Evaluation | 7 | 44 | ['Computer Science'] |
2,304.00958 | DrBERT: A Robust Pre-trained Model in French for Biomedical and Clinical
domains | ['Yanis Labrak', 'Adrien Bazoge', 'Richard Dufour', 'Mickael Rouvier', 'Emmanuel Morin', 'Béatrice Daille', 'Pierre-Antoine Gourraud'] | ['cs.CL'] | In recent years, pre-trained language models (PLMs) achieve the best
performance on a wide range of natural language processing (NLP) tasks. While
the first models were trained on general domain data, specialized ones have
emerged to more effectively treat specific domains. In this paper, we propose
an original study o... | 2023-04-03T13:25:53Z | Accepted at ACL 2023 | null | null | DrBERT: A Robust Pre-trained Model in French for Biomedical and Clinical domains | ['Yanis Labrak', 'Adrien Bazoge', 'Richard Dufour', 'Mickael Rouvier', 'E. Morin', 'B. Daille', 'P. Gourraud'] | 2,023 | bioRxiv | 57 | 43 | ['Computer Science', 'Biology'] |
2,304.01186 | Follow Your Pose: Pose-Guided Text-to-Video Generation using Pose-Free
Videos | ['Yue Ma', 'Yingqing He', 'Xiaodong Cun', 'Xintao Wang', 'Siran Chen', 'Ying Shan', 'Xiu Li', 'Qifeng Chen'] | ['cs.CV'] | Generating text-editable and pose-controllable character videos have an
imperious demand in creating various digital human. Nevertheless, this task has
been restricted by the absence of a comprehensive dataset featuring paired
video-pose captions and the generative prior models for videos. In this work,
we design a nov... | 2023-04-03T17:55:14Z | Project page: https://follow-your-pose.github.io/; Github repository:
https://github.com/mayuelala/FollowYourPose | null | null | null | null | null | null | null | null | null |
2,304.01196 | Baize: An Open-Source Chat Model with Parameter-Efficient Tuning on
Self-Chat Data | ['Canwen Xu', 'Daya Guo', 'Nan Duan', 'Julian McAuley'] | ['cs.CL', 'cs.AI'] | Chat models, such as ChatGPT, have shown impressive capabilities and have
been rapidly adopted across numerous domains. However, these models are only
accessible through a restricted API, creating barriers for new research and
progress in the field. We propose a pipeline that can automatically generate a
high-quality m... | 2023-04-03T17:59:09Z | Baize v2; EMNLP 2023 | null | null | null | null | null | null | null | null | null |
2,304.01234 | Prediction of solar wind speed by applying convolutional neural network
to potential field source surface (PFSS) magnetograms | ['Rong Lin', 'Zhekai Luo', 'Jiansen He', 'Lun Xie', 'Chuanpeng Hou', 'Shuwei Chen'] | ['astro-ph.SR', 'astro-ph.EP', 'cs.LG', 'physics.plasm-ph', 'physics.space-ph'] | An accurate solar wind speed model is important for space weather
predictions, catastrophic event warnings, and other issues concerning solar
wind - magnetosphere interaction. In this work, we construct a model based on
convolutional neural network (CNN) and Potential Field Source Surface (PFSS)
magnetograms, consideri... | 2023-04-03T06:54:22Z | null | null | null | null | null | null | null | null | null | null |
2,304.01373 | Pythia: A Suite for Analyzing Large Language Models Across Training and
Scaling | ['Stella Biderman', 'Hailey Schoelkopf', 'Quentin Anthony', 'Herbie Bradley', "Kyle O'Brien", 'Eric Hallahan', 'Mohammad Aflah Khan', 'Shivanshu Purohit', 'USVSN Sai Prashanth', 'Edward Raff', 'Aviya Skowron', 'Lintang Sutawika', 'Oskar van der Wal'] | ['cs.CL'] | How do large language models (LLMs) develop and evolve over the course of
training? How do these patterns change as models scale? To answer these
questions, we introduce \textit{Pythia}, a suite of 16 LLMs all trained on
public data seen in the exact same order and ranging in size from 70M to 12B
parameters. We provide... | 2023-04-03T20:58:15Z | Code at https://github.com/EleutherAI/pythia | null | null | null | null | null | null | null | null | null |
2,304.01559 | G2PTL: A Pre-trained Model for Delivery Address and its Applications in
Logistics System | ['Lixia Wu', 'Jianlin Liu', 'Junhong Lou', 'Haoyuan Hu', 'Jianbin Zheng', 'Haomin Wen', 'Chao Song', 'Shu He'] | ['cs.AI'] | Text-based delivery addresses, as the data foundation for logistics systems,
contain abundant and crucial location information. How to effectively encode
the delivery address is a core task to boost the performance of downstream
tasks in the logistics system. Pre-trained Models (PTMs) designed for Natural
Language Proc... | 2023-04-04T06:33:03Z | null | null | null | G2PTL: A Pre-trained Model for Delivery Address and its Applications in Logistics System | ['Lixia Wu', 'Jianlin Liu', 'Junhong Lou', 'Haoyuan Hu', 'Jianbin Zheng', 'Haomin Wen', 'Chao Song', 'Shu He'] | 2,023 | arXiv.org | 5 | 52 | ['Computer Science'] |
2,304.01665 | Mastering Symbolic Operations: Augmenting Language Models with Compiled
Neural Networks | ['Yixuan Weng', 'Minjun Zhu', 'Fei Xia', 'Bin Li', 'Shizhu He', 'Kang Liu', 'Jun Zhao'] | ['cs.CL'] | Language models' (LMs) proficiency in handling deterministic symbolic
reasoning and rule-based tasks remains limited due to their dependency implicit
learning on textual data. To endow LMs with genuine rule comprehension
abilities, we propose "Neural Comprehension" - a framework that synergistically
integrates compiled... | 2023-04-04T09:50:07Z | Accepted in ICLR 2024 | null | null | null | null | null | null | null | null | null |
2,304.01702 | Deep Learning Based Joint Beamforming Design in IRS-Assisted Secure
Communications | ['Chi Zhang', 'Yiliang Liu', 'Hsiao-Hwa Chen'] | ['cs.IT', 'eess.SP', 'math.IT'] | In this article, physical layer security (PLS) in an intelligent reflecting
surface (IRS) assisted multiple-input multiple-output multiple antenna
eavesdropper (MIMOME) system is studied. In particular, we consider a practical
scenario without instantaneous channel state information (CSI) of the
eavesdropper and assume... | 2023-04-04T10:57:24Z | null | null | null | Deep Learning Based Joint Beamforming Design in IRS-Assisted Secure Communications | ['Chi Zhang', 'Yiliang Liu', 'Hsiao-Hwa Chen'] | 2,023 | IEEE Transactions on Vehicular Technology | 5 | 17 | ['Computer Science', 'Engineering', 'Mathematics'] |
2,304.01922 | Resources and Few-shot Learners for In-context Learning in Slavic
Languages | ['Michal Štefánik', 'Marek Kadlčík', 'Piotr Gramacki', 'Petr Sojka'] | ['cs.CL'] | Despite the rapid recent progress in creating accurate and compact in-context
learners, most recent work focuses on in-context learning (ICL) for tasks in
English. However, the ability to interact with users of languages outside
English presents a great potential for broadening the applicability of language
technologie... | 2023-04-04T16:16:25Z | EACL 2023 SlavicNLP Long Paper. New instructional templates and
models are available on
https://github.com/fewshot-goes-multilingual/slavic-incontext-learning | null | null | null | null | null | null | null | null | null |
2,304.01982 | Rethinking the Role of Token Retrieval in Multi-Vector Retrieval | ['Jinhyuk Lee', 'Zhuyun Dai', 'Sai Meher Karthik Duddu', 'Tao Lei', 'Iftekhar Naim', 'Ming-Wei Chang', 'Vincent Y. Zhao'] | ['cs.CL', 'cs.IR'] | Multi-vector retrieval models such as ColBERT [Khattab and Zaharia, 2020]
allow token-level interactions between queries and documents, and hence achieve
state of the art on many information retrieval benchmarks. However, their
non-linear scoring function cannot be scaled to millions of documents,
necessitating a three... | 2023-04-04T17:37:06Z | NeurIPS 2023. Code available at
https://github.com/google-deepmind/xtr | null | null | null | null | null | null | null | null | null |
2,304.02122 | OpenContrails: Benchmarking Contrail Detection on GOES-16 ABI | ['Joe Yue-Hei Ng', 'Kevin McCloskey', 'Jian Cui', 'Vincent R. Meijer', 'Erica Brand', 'Aaron Sarna', 'Nita Goyal', 'Christopher Van Arsdale', 'Scott Geraedts'] | ['cs.CV'] | Contrails (condensation trails) are line-shaped ice clouds caused by aircraft
and are likely the largest contributor of aviation-induced climate change.
Contrail avoidance is potentially an inexpensive way to significantly reduce
the climate impact of aviation. An automated contrail detection system is an
essential too... | 2023-04-04T21:03:46Z | null | null | null | null | null | null | null | null | null | null |
2,304.02541 | PWESuite: Phonetic Word Embeddings and Tasks They Facilitate | ['Vilém Zouhar', 'Kalvin Chang', 'Chenxuan Cui', 'Nathaniel Carlson', 'Nathaniel Robinson', 'Mrinmaya Sachan', 'David Mortensen'] | ['cs.CL'] | Mapping words into a fixed-dimensional vector space is the backbone of modern
NLP. While most word embedding methods successfully encode semantic
information, they overlook phonetic information that is crucial for many tasks.
We develop three methods that use articulatory features to build phonetically
informed word em... | 2023-04-05T16:03:42Z | LREC-COLING 2024 | null | null | null | null | null | null | null | null | null |
2,304.02643 | Segment Anything | ['Alexander Kirillov', 'Eric Mintun', 'Nikhila Ravi', 'Hanzi Mao', 'Chloe Rolland', 'Laura Gustafson', 'Tete Xiao', 'Spencer Whitehead', 'Alexander C. Berg', 'Wan-Yen Lo', 'Piotr Dollár', 'Ross Girshick'] | ['cs.CV', 'cs.AI', 'cs.LG'] | We introduce the Segment Anything (SA) project: a new task, model, and
dataset for image segmentation. Using our efficient model in a data collection
loop, we built the largest segmentation dataset to date (by far), with over 1
billion masks on 11M licensed and privacy respecting images. The model is
designed and train... | 2023-04-05T17:59:46Z | Project web-page: https://segment-anything.com | null | null | Segment Anything | ['A. Kirillov', 'Eric Mintun', 'Nikhila Ravi', 'Hanzi Mao', 'Chloé Rolland', 'Laura Gustafson', 'Tete Xiao', 'Spencer Whitehead', 'A. Berg', 'Wan-Yen Lo', 'Piotr Dollár', 'Ross B. Girshick'] | 2,023 | IEEE International Conference on Computer Vision | 7,487 | 148 | ['Computer Science'] |
2,304.03208 | Cerebras-GPT: Open Compute-Optimal Language Models Trained on the
Cerebras Wafer-Scale Cluster | ['Nolan Dey', 'Gurpreet Gosal', 'Zhiming', 'Chen', 'Hemant Khachane', 'William Marshall', 'Ribhu Pathria', 'Marvin Tom', 'Joel Hestness'] | ['cs.LG', 'cs.CL'] | We study recent research advances that improve large language models through
efficient pre-training and scaling, and open datasets and tools. We combine
these advances to introduce Cerebras-GPT, a family of open compute-optimal
language models scaled from 111M to 13B parameters. We train Cerebras-GPT
models on the Eleu... | 2023-04-06T16:43:16Z | 13 pages main text, 16 pages appendix, 13 figures | null | null | Cerebras-GPT: Open Compute-Optimal Language Models Trained on the Cerebras Wafer-Scale Cluster | ['Nolan Dey', 'G. Gosal', 'Zhiming Chen', 'Hemant Khachane', 'William Marshall', 'Ribhu Pathria', 'Marvin Tom', 'Joel Hestness'] | 2,023 | arXiv.org | 108 | 57 | ['Computer Science'] |
2,304.03277 | Instruction Tuning with GPT-4 | ['Baolin Peng', 'Chunyuan Li', 'Pengcheng He', 'Michel Galley', 'Jianfeng Gao'] | ['cs.CL', 'cs.AI'] | Prior work has shown that finetuning large language models (LLMs) using
machine-generated instruction-following data enables such models to achieve
remarkable zero-shot capabilities on new tasks, and no human-written
instructions are needed. In this paper, we present the first attempt to use
GPT-4 to generate instructi... | 2023-04-06T17:58:09Z | 8 pages. Work in progress. Project page:
https://instruction-tuning-with-gpt-4.github.io | null | null | null | null | null | null | null | null | null |
2,304.03284 | SegGPT: Segmenting Everything In Context | ['Xinlong Wang', 'Xiaosong Zhang', 'Yue Cao', 'Wen Wang', 'Chunhua Shen', 'Tiejun Huang'] | ['cs.CV'] | We present SegGPT, a generalist model for segmenting everything in context.
We unify various segmentation tasks into a generalist in-context learning
framework that accommodates different kinds of segmentation data by
transforming them into the same format of images. The training of SegGPT is
formulated as an in-contex... | 2023-04-06T17:59:57Z | Code and Demo: https://github.com/baaivision/Painter | null | null | null | null | null | null | null | null | null |
2,304.03941 | Towards Realistic Ultrasound Fetal Brain Imaging Synthesis | ['Michelle Iskandar', 'Harvey Mannering', 'Zhanxiang Sun', 'Jacqueline Matthew', 'Hamideh Kerdegari', 'Laura Peralta', 'Miguel Xochicale'] | ['eess.IV', 'cs.CV', 'cs.LG', 'physics.med-ph'] | Prenatal ultrasound imaging is the first-choice modality to assess fetal
health. Medical image datasets for AI and ML methods must be diverse (i.e.
diagnoses, diseases, pathologies, scanners, demographics, etc), however there
are few public ultrasound fetal imaging datasets due to insufficient amounts of
clinical data,... | 2023-04-08T07:07:20Z | 3 pages, 1 figure | null | null | null | null | null | null | null | null | null |
2,304.0425 | Editable User Profiles for Controllable Text Recommendation | ['Sheshera Mysore', 'Mahmood Jasim', 'Andrew McCallum', 'Hamed Zamani'] | ['cs.IR', 'cs.CL', 'cs.HC', 'cs.LG'] | Methods for making high-quality recommendations often rely on learning latent
representations from interaction data. These methods, while performant, do not
provide ready mechanisms for users to control the recommendation they receive.
Our work tackles this problem by proposing LACE, a novel concept value
bottleneck mo... | 2023-04-09T14:52:18Z | SIGIR-2023 paper with extended results | null | null | null | null | null | null | null | null | null |
2,304.04461 | Modernizing Old Photos Using Multiple References via Photorealistic
Style Transfer | ['Agus Gunawan', 'Soo Ye Kim', 'Hyeonjun Sim', 'Jae-Ho Lee', 'Munchurl Kim'] | ['cs.CV', 'cs.GR'] | This paper firstly presents old photo modernization using multiple references
by performing stylization and enhancement in a unified manner. In order to
modernize old photos, we propose a novel multi-reference-based old photo
modernization (MROPM) framework consisting of a network MROPM-Net and a novel
synthetic data g... | 2023-04-10T09:01:20Z | Accepted to CVPR 2023. Website:
https://kaist-viclab.github.io/old-photo-modernization | null | null | Modernizing Old Photos Using Multiple References via Photorealistic Style Transfer | ['Agus Gunawan', 'S. Kim', 'Hyeonjun Sim', 'Jaehyup Lee', 'Munchurl Kim'] | 2,023 | Computer Vision and Pattern Recognition | 10 | 58 | ['Computer Science'] |
2,304.04662 | SELFormer: Molecular Representation Learning via SELFIES Language Models | ['Atakan Yüksel', 'Erva Ulusoy', 'Atabey Ünlü', 'Tunca Doğan'] | ['q-bio.QM', 'cs.LG', '68T07', 'I.2.1; I.2.6; I.5.4'] | Automated computational analysis of the vast chemical space is critical for
numerous fields of research such as drug discovery and material science.
Representation learning techniques have recently been employed with the primary
objective of generating compact and informative numerical expressions of
complex data. One ... | 2023-04-10T15:38:25Z | 22 pages, 4 figures, 8 tables | null | null | SELFormer: molecular representation learning via SELFIES language models | ['Atakan Yüksel', 'Erva Ulusoy', 'Atabey Ünlü', 'Gamze Deniz', 'Tunca Dogan'] | 2,023 | Machine Learning: Science and Technology | 61 | 80 | ['Biology', 'Computer Science', 'Physics'] |
2,304.0482 | Binary Latent Diffusion | ['Ze Wang', 'Jiang Wang', 'Zicheng Liu', 'Qiang Qiu'] | ['cs.CV'] | In this paper, we show that a binary latent space can be explored for compact
yet expressive image representations. We model the bi-directional mappings
between an image and the corresponding latent binary representation by training
an auto-encoder with a Bernoulli encoding distribution. On the one hand, the
binary lat... | 2023-04-10T19:03:28Z | null | null | null | null | null | null | null | null | null | null |
2,304.05277 | Graph-based Topology Reasoning for Driving Scenes | ['Tianyu Li', 'Li Chen', 'Huijie Wang', 'Yang Li', 'Jiazhi Yang', 'Xiangwei Geng', 'Shengyin Jiang', 'Yuting Wang', 'Hang Xu', 'Chunjing Xu', 'Junchi Yan', 'Ping Luo', 'Hongyang Li'] | ['cs.CV'] | Understanding the road genome is essential to realize autonomous driving.
This highly intelligent problem contains two aspects - the connection
relationship of lanes, and the assignment relationship between lanes and
traffic elements, where a comprehensive topology reasoning method is vacant. On
one hand, previous map ... | 2023-04-11T15:23:29Z | null | null | null | Graph-based Topology Reasoning for Driving Scenes | ['Tianyu Li', 'Li Chen', 'Xiangwei Geng', 'Huijie Wang', 'Yang Li', 'Zhenbo Liu', 'Shen Jiang', 'Yuting Wang', 'Hang Xu', 'Chunjing Xu', 'Feng Wen', 'Ping Luo', 'Jun Yan', 'W. Zhang', 'Xiaogang Wang', 'Y. Qiao', 'Hongyang Li'] | 2,023 | null | 37 | 72 | ['Computer Science'] |
2,304.05302 | RRHF: Rank Responses to Align Language Models with Human Feedback
without tears | ['Zheng Yuan', 'Hongyi Yuan', 'Chuanqi Tan', 'Wei Wang', 'Songfang Huang', 'Fei Huang'] | ['cs.CL'] | Reinforcement Learning from Human Feedback (RLHF) facilitates the alignment
of large language models with human preferences, significantly enhancing the
quality of interactions between humans and models. InstructGPT implements RLHF
through several stages, including Supervised Fine-Tuning (SFT), reward model
training, a... | 2023-04-11T15:53:40Z | ArXiv version For NeurIPS 2023 accepted paper: RRHF: Rank Responses
to Align Language Models with Human Feedback | null | null | null | null | null | null | null | null | null |
2,304.05376 | ChemCrow: Augmenting large-language models with chemistry tools | ['Andres M Bran', 'Sam Cox', 'Oliver Schilter', 'Carlo Baldassari', 'Andrew D White', 'Philippe Schwaller'] | ['physics.chem-ph', 'stat.ML'] | Over the last decades, excellent computational chemistry tools have been
developed. Integrating them into a single platform with enhanced accessibility
could help reaching their full potential by overcoming steep learning curves.
Recently, large-language models (LLMs) have shown strong performance in tasks
across domai... | 2023-04-11T17:41:13Z | Experimental results | null | null | null | null | null | null | null | null | null |
2,304.05457 | CAvity DEtection Tool (CADET): Pipeline for automatic detection of X-ray
cavities in hot galactic and cluster atmospheres | ['Tomáš Plšek', 'Norbert Werner', 'Martin Topinka', 'Aurora Simionescu'] | ['astro-ph.HE', 'astro-ph.GA'] | The study of jet-inflated X-ray cavities provides a powerful insight into the
energetics of hot galactic atmospheres and radio-mechanical AGN feedback. By
estimating the volumes of X-ray cavities, the total energy and thus also the
corresponding mechanical jet power required for their inflation can be derived.
Properly... | 2023-04-11T19:09:24Z | null | null | null | CAvity DEtection Tool (CADET): Pipeline for automatic detection of X-ray cavities in hot galactic and cluster atmospheres | ['T. Plvsek', 'N. Werner', 'M. Topinka', 'A. Simionescu'] | 2,023 | null | 1 | 8 | ['Physics'] |
2,304.05754 | Self-Supervised Learning with Cluster-Aware-DINO for High-Performance
Robust Speaker Verification | ['Bing Han', 'Zhengyang Chen', 'Yanmin Qian'] | ['cs.SD', 'eess.AS'] | Automatic speaker verification task has made great achievements using deep
learning approaches with the large-scale manually annotated dataset. However,
it's very difficult and expensive to collect a large amount of well-labeled
data for system building. In this paper, we propose a novel and advanced
self-supervised le... | 2023-04-12T10:32:29Z | Submitted to TASLP in July 19, 2022 | null | null | Self-Supervised Learning With Cluster-Aware-DINO for High-Performance Robust Speaker Verification | ['Bing Han', 'Zhengyang Chen', 'Y. Qian'] | 2,023 | IEEE/ACM Transactions on Audio Speech and Language Processing | 21 | 72 | ['Computer Science', 'Engineering'] |
2,304.05884 | Unicom: Universal and Compact Representation Learning for Image
Retrieval | ['Xiang An', 'Jiankang Deng', 'Kaicheng Yang', 'Jaiwei Li', 'Ziyong Feng', 'Jia Guo', 'Jing Yang', 'Tongliang Liu'] | ['cs.CV'] | Modern image retrieval methods typically rely on fine-tuning pre-trained
encoders to extract image-level descriptors. However, the most widely used
models are pre-trained on ImageNet-1K with limited classes. The pre-trained
feature representation is therefore not universal enough to generalize well to
the diverse open-... | 2023-04-12T14:25:52Z | Accepted at ICLR2023 | null | null | null | null | null | null | null | null | null |
2,304.05977 | ImageReward: Learning and Evaluating Human Preferences for Text-to-Image
Generation | ['Jiazheng Xu', 'Xiao Liu', 'Yuchen Wu', 'Yuxuan Tong', 'Qinkai Li', 'Ming Ding', 'Jie Tang', 'Yuxiao Dong'] | ['cs.CV', 'cs.LG'] | We present a comprehensive solution to learn and improve text-to-image models
from human preference feedback. To begin with, we build ImageReward -- the
first general-purpose text-to-image human preference reward model -- to
effectively encode human preferences. Its training is based on our systematic
annotation pipeli... | 2023-04-12T16:58:13Z | 32 pages | null | null | null | null | null | null | null | null | null |
2,304.0614 | An Edit Friendly DDPM Noise Space: Inversion and Manipulations | ['Inbar Huberman-Spiegelglas', 'Vladimir Kulikov', 'Tomer Michaeli'] | ['cs.CV', 'cs.LG'] | Denoising diffusion probabilistic models (DDPMs) employ a sequence of white
Gaussian noise samples to generate an image. In analogy with GANs, those noise
maps could be considered as the latent code associated with the generated
image. However, this native noise space does not possess a convenient
structure, and is thu... | 2023-04-12T19:47:13Z | CVPR 2024. Code and examples are available at
https://github.com/inbarhub/DDPM_inversion | null | null | null | null | null | null | null | null | null |
2,304.06364 | AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models | ['Wanjun Zhong', 'Ruixiang Cui', 'Yiduo Guo', 'Yaobo Liang', 'Shuai Lu', 'Yanlin Wang', 'Amin Saied', 'Weizhu Chen', 'Nan Duan'] | ['cs.CL', 'cs.AI'] | Evaluating the general abilities of foundation models to tackle human-level
tasks is a vital aspect of their development and application in the pursuit of
Artificial General Intelligence (AGI). Traditional benchmarks, which rely on
artificial datasets, may not accurately represent human-level capabilities. In
this pape... | 2023-04-13T09:39:30Z | 19 pages | null | null | null | null | null | null | null | null | null |
2,304.06706 | Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields | ['Jonathan T. Barron', 'Ben Mildenhall', 'Dor Verbin', 'Pratul P. Srinivasan', 'Peter Hedman'] | ['cs.CV', 'cs.GR', 'cs.LG'] | Neural Radiance Field training can be accelerated through the use of
grid-based representations in NeRF's learned mapping from spatial coordinates
to colors and volumetric density. However, these grid-based approaches lack an
explicit understanding of scale and therefore often introduce aliasing, usually
in the form of... | 2023-04-13T17:55:12Z | Project page: https://jonbarron.info/zipnerf/ | null | null | Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fields | ['J. Barron', 'B. Mildenhall', 'Dor Verbin', 'Pratul P. Srinivasan', 'Peter Hedman'] | 2,023 | IEEE International Conference on Computer Vision | 513 | 40 | ['Computer Science'] |
2,304.06715 | Evaluating the Robustness of Interpretability Methods through
Explanation Invariance and Equivariance | ['Jonathan Crabbé', 'Mihaela van der Schaar'] | ['cs.LG', 'cs.AI', 'cs.CG'] | Interpretability methods are valuable only if their explanations faithfully
describe the explained model. In this work, we consider neural networks whose
predictions are invariant under a specific symmetry group. This includes
popular architectures, ranging from convolutional to graph neural networks. Any
explanation t... | 2023-04-13T17:59:03Z | Presented at NeurIPS 2023 | null | null | Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance | ['Jonathan Crabbe', 'M. Schaar'] | 2,023 | Neural Information Processing Systems | 7 | 104 | ['Computer Science'] |
2,304.06716 | STU-Net: Scalable and Transferable Medical Image Segmentation Models
Empowered by Large-Scale Supervised Pre-training | ['Ziyan Huang', 'Haoyu Wang', 'Zhongying Deng', 'Jin Ye', 'Yanzhou Su', 'Hui Sun', 'Junjun He', 'Yun Gu', 'Lixu Gu', 'Shaoting Zhang', 'Yu Qiao'] | ['cs.CV'] | Large-scale models pre-trained on large-scale datasets have profoundly
advanced the development of deep learning. However, the state-of-the-art models
for medical image segmentation are still small-scale, with their parameters
only in the tens of millions. Further scaling them up to higher orders of
magnitude is rarely... | 2023-04-13T17:59:13Z | null | null | null | null | null | null | null | null | null | null |
2,304.06718 | Segment Everything Everywhere All at Once | ['Xueyan Zou', 'Jianwei Yang', 'Hao Zhang', 'Feng Li', 'Linjie Li', 'Jianfeng Wang', 'Lijuan Wang', 'Jianfeng Gao', 'Yong Jae Lee'] | ['cs.CV'] | In this work, we present SEEM, a promptable and interactive model for
segmenting everything everywhere all at once in an image, as shown in Fig.1. In
SEEM, we propose a novel decoding mechanism that enables diverse prompting for
all types of segmentation tasks, aiming at a universal segmentation interface
that behaves ... | 2023-04-13T17:59:40Z | null | null | null | null | null | null | null | null | null | null |
2,304.06762 | Shall We Pretrain Autoregressive Language Models with Retrieval? A
Comprehensive Study | ['Boxin Wang', 'Wei Ping', 'Peng Xu', 'Lawrence McAfee', 'Zihan Liu', 'Mohammad Shoeybi', 'Yi Dong', 'Oleksii Kuchaiev', 'Bo Li', 'Chaowei Xiao', 'Anima Anandkumar', 'Bryan Catanzaro'] | ['cs.CL', 'cs.AI', 'cs.IR', 'cs.LG'] | Large decoder-only language models (LMs) can be largely improved in terms of
perplexity by retrieval (e.g., RETRO), but its impact on text generation
quality and downstream task accuracy is unclear. Thus, it is still an open
question: shall we pretrain large autoregressive LMs with retrieval? To answer
it, we perform a... | 2023-04-13T18:04:19Z | EMNLP 2023 | null | null | Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study | ['Boxin Wang', 'Wei Ping', 'P. Xu', 'Lawrence C. McAfee', 'Zihan Liu', 'M. Shoeybi', 'Yi Dong', 'Oleksii Kuchaiev', 'Bo Li', 'Chaowei Xiao', 'Anima Anandkumar', 'Bryan Catanzaro'] | 2,023 | Conference on Empirical Methods in Natural Language Processing | 60 | 70 | ['Computer Science'] |
2,304.06767 | RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment | ['Hanze Dong', 'Wei Xiong', 'Deepanshu Goyal', 'Yihan Zhang', 'Winnie Chow', 'Rui Pan', 'Shizhe Diao', 'Jipeng Zhang', 'Kashun Shum', 'Tong Zhang'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CV', 'stat.ML'] | Generative foundation models are susceptible to implicit biases that can
arise from extensive unsupervised training data. Such biases can produce
suboptimal samples, skewed outcomes, and unfairness, with potentially serious
consequences. Consequently, aligning these models with human ethics and
preferences is an essent... | 2023-04-13T18:22:40Z | 29 pages, 12 figures, Published in Transactions on Machine Learning
Research (TMLR) | null | null | null | null | null | null | null | null | null |
2,304.06795 | Efficient Sequence Transduction by Jointly Predicting Tokens and
Durations | ['Hainan Xu', 'Fei Jia', 'Somshubra Majumdar', 'He Huang', 'Shinji Watanabe', 'Boris Ginsburg'] | ['eess.AS', 'cs.CL', 'cs.LG', 'cs.SD'] | This paper introduces a novel Token-and-Duration Transducer (TDT)
architecture for sequence-to-sequence tasks. TDT extends conventional
RNN-Transducer architectures by jointly predicting both a token and its
duration, i.e. the number of input frames covered by the emitted token. This is
achieved by using a joint networ... | 2023-04-13T19:38:27Z | null | null | null | Efficient Sequence Transduction by Jointly Predicting Tokens and Durations | ['Hainan Xu', 'Fei Jia', 'Somshubra Majumdar', 'Hengguan Huang', 'Shinji Watanabe', 'Boris Ginsburg'] | 2,023 | International Conference on Machine Learning | 26 | 41 | ['Computer Science', 'Engineering'] |
2,304.06875 | nanoLM: an Affordable LLM Pre-training Benchmark via Accurate Loss
Prediction across Scales | ['Yiqun Yao', 'Siqi fan', 'Xiusheng Huang', 'Xuezhi Fang', 'Xiang Li', 'Ziyi Ni', 'Xin Jiang', 'Xuying Meng', 'Peng Han', 'Shuo Shang', 'Kang Liu', 'Aixin Sun', 'Yequan Wang'] | ['cs.CL', 'cs.LG'] | As language models scale up, it becomes increasingly expensive to verify
research ideas because conclusions on small models do not trivially transfer to
large ones. A possible solution is to establish a generic system that
accurately predicts certain metrics for large models without training them.
Existing scaling laws... | 2023-04-14T00:45:01Z | This is a modified and extended version of our previous Mu-scaling
work released in April 2023 (see v1) | null | null | nanoLM: an Affordable LLM Pre-training Benchmark via Accurate Loss Prediction across Scales | ['Yiqun Yao', 'Yequan Wang'] | 2,023 | null | 6 | 38 | ['Computer Science'] |
2,304.06939 | Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with
Text | ['Wanrong Zhu', 'Jack Hessel', 'Anas Awadalla', 'Samir Yitzhak Gadre', 'Jesse Dodge', 'Alex Fang', 'Youngjae Yu', 'Ludwig Schmidt', 'William Yang Wang', 'Yejin Choi'] | ['cs.CV', 'cs.CL'] | In-context vision and language models like Flamingo support arbitrarily
interleaved sequences of images and text as input. This format not only enables
few-shot learning via interleaving independent supervised (image, text)
examples, but also, more complex prompts involving interaction between images,
e.g., "What do im... | 2023-04-14T06:17:46Z | NeurIPS D&B 2023. Project homepage: https://github.com/allenai/mmc4 | null | null | null | null | null | null | null | null | null |
2,304.06975 | HuaTuo: Tuning LLaMA Model with Chinese Medical Knowledge | ['Haochun Wang', 'Chi Liu', 'Nuwa Xi', 'Zewen Qiang', 'Sendong Zhao', 'Bing Qin', 'Ting Liu'] | ['cs.CL'] | Large Language Models (LLMs), such as the LLaMA model, have demonstrated
their effectiveness in various general-domain natural language processing (NLP)
tasks. Nevertheless, LLMs have not yet performed optimally in biomedical domain
tasks due to the need for medical expertise in the responses. In response to
this chall... | 2023-04-14T07:54:17Z | LLaMA-based Chinese Medical model - HuaTuo. Model, code and training
data are available at https://github.com/SCIR-HI/Huatuo-Llama-Med-Chinese | null | null | null | null | null | null | null | null | null |
2,304.07193 | DINOv2: Learning Robust Visual Features without Supervision | ['Maxime Oquab', 'Timothée Darcet', 'Théo Moutakanni', 'Huy Vo', 'Marc Szafraniec', 'Vasil Khalidov', 'Pierre Fernandez', 'Daniel Haziza', 'Francisco Massa', 'Alaaeldin El-Nouby', 'Mahmoud Assran', 'Nicolas Ballas', 'Wojciech Galuba', 'Russell Howes', 'Po-Yao Huang', 'Shang-Wen Li', 'Ishan Misra', 'Michael Rabbat', 'Va... | ['cs.CV'] | The recent breakthroughs in natural language processing for model pretraining
on large quantities of data have opened the way for similar foundation models
in computer vision. These models could greatly simplify the use of images in
any system by producing all-purpose visual features, i.e., features that work
across im... | 2023-04-14T15:12:19Z | null | null | null | DINOv2: Learning Robust Visual Features without Supervision | ['M. Oquab', 'Timothée Darcet', 'Théo Moutakanni', 'Huy Q. Vo', 'Marc Szafraniec', 'Vasil Khalidov', 'Pierre Fernandez', 'Daniel Haziza', 'Francisco Massa', 'Alaaeldin El-Nouby', 'Mahmoud Assran', 'Nicolas Ballas', 'Wojciech Galuba', 'Russ Howes', 'Po-Yao (Bernie) Huang', 'Shang-Wen Li', 'Ishan Misra', 'Michael G. Rabb... | 2,023 | Trans. Mach. Learn. Res. | 3,536 | 140 | ['Computer Science'] |
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