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2,302.02412 | Mixture of Diffusers for scene composition and high resolution image
generation | ['Álvaro Barbero Jiménez'] | ['cs.CV', 'cs.AI', 'cs.LG', 'I.2.6'] | Diffusion methods have been proven to be very effective to generate images
while conditioning on a text prompt. However, and although the quality of the
generated images is unprecedented, these methods seem to struggle when trying
to generate specific image compositions. In this paper we present Mixture of
Diffusers, a... | 2023-02-05T15:49:26Z | null | null | null | null | null | null | null | null | null | null |
2,302.02503 | Leaving Reality to Imagination: Robust Classification via Generated
Datasets | ['Hritik Bansal', 'Aditya Grover'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.MM'] | Recent research on robustness has revealed significant performance gaps
between neural image classifiers trained on datasets that are similar to the
test set, and those that are from a naturally shifted distribution, such as
sketches, paintings, and animations of the object categories observed during
training. Prior wo... | 2023-02-05T22:49:33Z | 22 pages, 12 Figures, 9 Tables. Results for ImageNet-C, and finetuned
generative model are included now | null | null | null | null | null | null | null | null | null |
2,302.02615 | Rethinking Out-of-distribution (OOD) Detection: Masked Image Modeling is
All You Need | ['Jingyao Li', 'Pengguang Chen', 'Shaozuo Yu', 'Zexin He', 'Shu Liu', 'Jiaya Jia'] | ['cs.CV'] | The core of out-of-distribution (OOD) detection is to learn the
in-distribution (ID) representation, which is distinguishable from OOD samples.
Previous work applied recognition-based methods to learn the ID features, which
tend to learn shortcuts instead of comprehensive representations. In this work,
we find surprisi... | 2023-02-06T08:24:41Z | This paper is accepted by CVPR2023 and our codes are released here:
https://github.com/JulietLJY/MOOD | null | null | null | null | null | null | null | null | null |
2,302.02662 | Grounding Large Language Models in Interactive Environments with Online
Reinforcement Learning | ['Thomas Carta', 'Clément Romac', 'Thomas Wolf', 'Sylvain Lamprier', 'Olivier Sigaud', 'Pierre-Yves Oudeyer'] | ['cs.LG'] | Recent works successfully leveraged Large Language Models' (LLM) abilities to
capture abstract knowledge about world's physics to solve decision-making
problems. Yet, the alignment between LLMs' knowledge and the environment can be
wrong and limit functional competence due to lack of grounding. In this paper,
we study ... | 2023-02-06T10:01:08Z | null | PMLR 202 (2023):3676-3713 | null | null | null | null | null | null | null | null |
2,302.03169 | Data Selection for Language Models via Importance Resampling | ['Sang Michael Xie', 'Shibani Santurkar', 'Tengyu Ma', 'Percy Liang'] | ['cs.CL', 'cs.LG'] | Selecting a suitable pretraining dataset is crucial for both general-domain
(e.g., GPT-3) and domain-specific (e.g., Codex) language models (LMs). We
formalize this problem as selecting a subset of a large raw unlabeled dataset
to match a desired target distribution given unlabeled target samples. Due to
the scale and ... | 2023-02-06T23:57:56Z | NeurIPS 2023 | null | null | Data Selection for Language Models via Importance Resampling | ['Sang Michael Xie', 'Shibani Santurkar', 'Tengyu Ma', 'Percy Liang'] | 2,023 | Neural Information Processing Systems | 196 | 97 | ['Computer Science'] |
2,302.03241 | Continual Pre-training of Language Models | ['Zixuan Ke', 'Yijia Shao', 'Haowei Lin', 'Tatsuya Konishi', 'Gyuhak Kim', 'Bing Liu'] | ['cs.CL', 'cs.AI', 'cs.LG', 'cs.NE'] | Language models (LMs) have been instrumental for the rapid advance of natural
language processing. This paper studies continual pre-training of LMs, in
particular, continual domain-adaptive pre-training (or continual DAP-training).
Existing research has shown that further pre-training an LM using a domain
corpus to ada... | 2023-02-07T03:57:55Z | https://github.com/UIC-Liu-Lab/ContinualLM | ICLR 2023 | null | Continual Pre-training of Language Models | ['Zixuan Ke', 'Yijia Shao', 'Haowei Lin', 'Tatsuya Konishi', 'Gyuhak Kim', 'Bin Liu'] | 2,023 | International Conference on Learning Representations | 140 | 81 | ['Computer Science'] |
2,302.0354 | Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal
Supervision | ['Eugene Kharitonov', 'Damien Vincent', 'Zalán Borsos', 'Raphaël Marinier', 'Sertan Girgin', 'Olivier Pietquin', 'Matt Sharifi', 'Marco Tagliasacchi', 'Neil Zeghidour'] | ['cs.SD', 'eess.AS'] | We introduce SPEAR-TTS, a multi-speaker text-to-speech (TTS) system that can
be trained with minimal supervision. By combining two types of discrete speech
representations, we cast TTS as a composition of two sequence-to-sequence
tasks: from text to high-level semantic tokens (akin to "reading") and from
semantic token... | 2023-02-07T15:48:31Z | null | null | null | null | null | null | null | null | null | null |
2,302.04026 | An Empirical Comparison of Pre-Trained Models of Source Code | ['Changan Niu', 'Chuanyi Li', 'Vincent Ng', 'Dongxiao Chen', 'Jidong Ge', 'Bin Luo'] | ['cs.SE'] | While a large number of pre-trained models of source code have been
successfully developed and applied to a variety of software engineering (SE)
tasks in recent years, our understanding of these pre-trained models is
arguably fairly limited. With the goal of advancing our understanding of these
models, we perform the f... | 2023-02-08T12:57:46Z | ICSE 2023 | null | null | An Empirical Comparison of Pre-Trained Models of Source Code | ['Changan Niu', 'Chuanyi Li', 'Vincent Ng', 'Dongxiao Chen', 'Jidong Ge', 'B. Luo'] | 2,023 | International Conference on Software Engineering | 75 | 74 | ['Computer Science'] |
2,302.04611 | A Text-guided Protein Design Framework | ['Shengchao Liu', 'Yanjing Li', 'Zhuoxinran Li', 'Anthony Gitter', 'Yutao Zhu', 'Jiarui Lu', 'Zhao Xu', 'Weili Nie', 'Arvind Ramanathan', 'Chaowei Xiao', 'Jian Tang', 'Hongyu Guo', 'Anima Anandkumar'] | ['cs.LG', 'cs.AI', 'q-bio.QM', 'stat.ML'] | Current AI-assisted protein design mainly utilizes protein sequential and
structural information. Meanwhile, there exists tremendous knowledge curated by
humans in the text format describing proteins' high-level functionalities. Yet,
whether the incorporation of such text data can help protein design tasks has
not been... | 2023-02-09T12:59:16Z | null | null | 10.1038/s42256-025-01011-z | A Text-guided Protein Design Framework | ['Shengchao Liu', 'Yutao Zhu', 'Jiarui Lu', 'Zhao Xu', 'Weili Nie', 'A. Gitter', 'Chaowei Xiao', 'Jian Tang', 'Hongyu Guo', 'Anima Anandkumar'] | 2,023 | Nat. Mac. Intell. | 70 | 145 | ['Computer Science', 'Biology', 'Mathematics'] |
2,302.04973 | Invariant Slot Attention: Object Discovery with Slot-Centric Reference
Frames | ['Ondrej Biza', 'Sjoerd van Steenkiste', 'Mehdi S. M. Sajjadi', 'Gamaleldin F. Elsayed', 'Aravindh Mahendran', 'Thomas Kipf'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Automatically discovering composable abstractions from raw perceptual data is
a long-standing challenge in machine learning. Recent slot-based neural
networks that learn about objects in a self-supervised manner have made
exciting progress in this direction. However, they typically fall short at
adequately capturing sp... | 2023-02-09T23:25:28Z | Accepted at ICML 2023. Project page: https://invariantsa.github.io/ | null | null | null | null | null | null | null | null | null |
2,302.0529 | Removing Structured Noise with Diffusion Models | ['Tristan S. W. Stevens', 'Hans van Gorp', 'Faik C. Meral', 'Junseob Shin', 'Jason Yu', 'Jean-Luc Robert', 'Ruud J. G. van Sloun'] | ['cs.LG', 'eess.IV', 'eess.SP'] | Solving ill-posed inverse problems requires careful formulation of prior
beliefs over the signals of interest and an accurate description of their
manifestation into noisy measurements. Handcrafted signal priors based on e.g.
sparsity are increasingly replaced by data-driven deep generative models, and
several groups h... | 2023-01-20T23:42:25Z | 20 pages, 8 figures, Transactions on Machine Learning Research | Transactions on Machine Learning Research (2025): 2835-8856 | null | null | null | null | null | null | null | null |
2,302.05442 | Scaling Vision Transformers to 22 Billion Parameters | ['Mostafa Dehghani', 'Josip Djolonga', 'Basil Mustafa', 'Piotr Padlewski', 'Jonathan Heek', 'Justin Gilmer', 'Andreas Steiner', 'Mathilde Caron', 'Robert Geirhos', 'Ibrahim Alabdulmohsin', 'Rodolphe Jenatton', 'Lucas Beyer', 'Michael Tschannen', 'Anurag Arnab', 'Xiao Wang', 'Carlos Riquelme', 'Matthias Minderer', 'Joan... | ['cs.CV', 'cs.AI', 'cs.LG'] | The scaling of Transformers has driven breakthrough capabilities for language
models. At present, the largest large language models (LLMs) contain upwards of
100B parameters. Vision Transformers (ViT) have introduced the same
architecture to image and video modelling, but these have not yet been
successfully scaled to ... | 2023-02-10T18:58:21Z | null | null | null | null | null | null | null | null | null | null |
2,302.05496 | MaskSketch: Unpaired Structure-guided Masked Image Generation | ['Dina Bashkirova', 'Jose Lezama', 'Kihyuk Sohn', 'Kate Saenko', 'Irfan Essa'] | ['cs.CV', 'cs.AI'] | Recent conditional image generation methods produce images of remarkable
diversity, fidelity and realism. However, the majority of these methods allow
conditioning only on labels or text prompts, which limits their level of
control over the generation result. In this paper, we introduce MaskSketch, an
image generation ... | 2023-02-10T20:27:02Z | null | null | null | null | null | null | null | null | null | null |
2,302.05527 | CodeBERTScore: Evaluating Code Generation with Pretrained Models of Code | ['Shuyan Zhou', 'Uri Alon', 'Sumit Agarwal', 'Graham Neubig'] | ['cs.SE', 'cs.LG', 'cs.PL'] | Since the rise of neural natural-language-to-code models (NL->Code) that can
generate long expressions and statements rather than a single next-token, one
of the major problems has been reliably evaluating their generated output. In
this paper, we propose CodeBERTScore: an evaluation metric for code generation,
which b... | 2023-02-10T22:12:05Z | null | null | null | CodeBERTScore: Evaluating Code Generation with Pretrained Models of Code | ['Shuyan Zhou', 'Uri Alon', 'Sumit Agarwal', 'Graham Neubig'] | 2,023 | Conference on Empirical Methods in Natural Language Processing | 114 | 43 | ['Computer Science'] |
2,302.05543 | Adding Conditional Control to Text-to-Image Diffusion Models | ['Lvmin Zhang', 'Anyi Rao', 'Maneesh Agrawala'] | ['cs.CV', 'cs.AI', 'cs.GR', 'cs.HC', 'cs.MM'] | We present ControlNet, a neural network architecture to add spatial
conditioning controls to large, pretrained text-to-image diffusion models.
ControlNet locks the production-ready large diffusion models, and reuses their
deep and robust encoding layers pretrained with billions of images as a strong
backbone to learn a... | 2023-02-10T23:12:37Z | Codes and Supplementary Material:
https://github.com/lllyasviel/ControlNet | null | null | null | null | null | null | null | null | null |
2,302.05981 | MarioGPT: Open-Ended Text2Level Generation through Large Language Models | ['Shyam Sudhakaran', 'Miguel González-Duque', 'Claire Glanois', 'Matthias Freiberger', 'Elias Najarro', 'Sebastian Risi'] | ['cs.AI', 'cs.CL', 'cs.LG'] | Procedural Content Generation (PCG) is a technique to generate complex and
diverse environments in an automated way. However, while generating content
with PCG methods is often straightforward, generating meaningful content that
reflects specific intentions and constraints remains challenging. Furthermore,
many PCG alg... | 2023-02-12T19:12:24Z | null | null | null | null | null | null | null | null | null | null |
2,302.06579 | AbLit: A Resource for Analyzing and Generating Abridged Versions of
English Literature | ['Melissa Roemmele', 'Kyle Shaffer', 'Katrina Olsen', 'Yiyi Wang', 'Steve DeNeefe'] | ['cs.CL'] | Creating an abridged version of a text involves shortening it while
maintaining its linguistic qualities. In this paper, we examine this task from
an NLP perspective for the first time. We present a new resource, AbLit, which
is derived from abridged versions of English literature books. The dataset
captures passage-le... | 2023-02-13T18:33:26Z | Accepted at EACL 2023 | null | null | null | null | null | null | null | null | null |
2,302.06675 | Symbolic Discovery of Optimization Algorithms | ['Xiangning Chen', 'Chen Liang', 'Da Huang', 'Esteban Real', 'Kaiyuan Wang', 'Yao Liu', 'Hieu Pham', 'Xuanyi Dong', 'Thang Luong', 'Cho-Jui Hsieh', 'Yifeng Lu', 'Quoc V. Le'] | ['cs.LG', 'cs.AI', 'cs.CL', 'cs.CV', 'cs.NE'] | We present a method to formulate algorithm discovery as program search, and
apply it to discover optimization algorithms for deep neural network training.
We leverage efficient search techniques to explore an infinite and sparse
program space. To bridge the large generalization gap between proxy and target
tasks, we al... | 2023-02-13T20:27:30Z | 30 pages, Lion is successfully deployed in production systems. We
also add comparison with other automatically discovered optimizers | null | null | null | null | null | null | null | null | null |
2,302.06992 | Hard-aware Instance Adaptive Self-training for Unsupervised Cross-domain
Semantic Segmentation | ['Chuang Zhu', 'Kebin Liu', 'Wenqi Tang', 'Ke Mei', 'Jiaqi Zou', 'Tiejun Huang'] | ['cs.CV'] | The divergence between labeled training data and unlabeled testing data is a
significant challenge for recent deep learning models. Unsupervised domain
adaptation (UDA) attempts to solve such problem. Recent works show that
self-training is a powerful approach to UDA. However, existing methods have
difficulty in balanc... | 2023-02-14T11:52:26Z | arXiv admin note: text overlap with arXiv:2008.12197 | null | null | null | null | null | null | null | null | null |
2,302.07387 | PolyFormer: Referring Image Segmentation as Sequential Polygon
Generation | ['Jiang Liu', 'Hui Ding', 'Zhaowei Cai', 'Yuting Zhang', 'Ravi Kumar Satzoda', 'Vijay Mahadevan', 'R. Manmatha'] | ['cs.CV'] | In this work, instead of directly predicting the pixel-level segmentation
masks, the problem of referring image segmentation is formulated as sequential
polygon generation, and the predicted polygons can be later converted into
segmentation masks. This is enabled by a new sequence-to-sequence framework,
Polygon Transfo... | 2023-02-14T23:00:25Z | CVPR 2023. Project Page: https://polyformer.github.io/ | null | null | null | null | null | null | null | null | null |
2,302.07452 | How to Train Your DRAGON: Diverse Augmentation Towards Generalizable
Dense Retrieval | ['Sheng-Chieh Lin', 'Akari Asai', 'Minghan Li', 'Barlas Oguz', 'Jimmy Lin', 'Yashar Mehdad', 'Wen-tau Yih', 'Xilun Chen'] | ['cs.IR', 'cs.CL'] | Various techniques have been developed in recent years to improve dense
retrieval (DR), such as unsupervised contrastive learning and pseudo-query
generation. Existing DRs, however, often suffer from effectiveness tradeoffs
between supervised and zero-shot retrieval, which some argue was due to the
limited model capaci... | 2023-02-15T03:53:26Z | null | null | null | null | null | null | null | null | null | null |
2,302.07515 | TiZero: Mastering Multi-Agent Football with Curriculum Learning and
Self-Play | ['Fanqi Lin', 'Shiyu Huang', 'Tim Pearce', 'Wenze Chen', 'Wei-Wei Tu'] | ['cs.AI', 'cs.LG', 'cs.MA'] | Multi-agent football poses an unsolved challenge in AI research. Existing
work has focused on tackling simplified scenarios of the game, or else
leveraging expert demonstrations. In this paper, we develop a multi-agent
system to play the full 11 vs. 11 game mode, without demonstrations. This game
mode contains aspects ... | 2023-02-15T08:19:18Z | The 22nd International Conference on Autonomous Agents and Multiagent
Systems(AAMAS2023) | null | null | null | null | null | null | null | null | null |
2,302.07817 | Tri-Perspective View for Vision-Based 3D Semantic Occupancy Prediction | ['Yuanhui Huang', 'Wenzhao Zheng', 'Yunpeng Zhang', 'Jie Zhou', 'Jiwen Lu'] | ['cs.CV', 'cs.AI', 'cs.LG'] | Modern methods for vision-centric autonomous driving perception widely adopt
the bird's-eye-view (BEV) representation to describe a 3D scene. Despite its
better efficiency than voxel representation, it has difficulty describing the
fine-grained 3D structure of a scene with a single plane. To address this, we
propose a ... | 2023-02-15T17:58:10Z | Accepted to CVPR 2023. Code is available at
https://github.com/wzzheng/TPVFormer | null | null | null | null | null | null | null | null | null |
2,302.08091 | Do We Still Need Clinical Language Models? | ['Eric Lehman', 'Evan Hernandez', 'Diwakar Mahajan', 'Jonas Wulff', 'Micah J. Smith', 'Zachary Ziegler', 'Daniel Nadler', 'Peter Szolovits', 'Alistair Johnson', 'Emily Alsentzer'] | ['cs.CL'] | Although recent advances in scaling large language models (LLMs) have
resulted in improvements on many NLP tasks, it remains unclear whether these
models trained primarily with general web text are the right tool in highly
specialized, safety critical domains such as clinical text. Recent results have
suggested that LL... | 2023-02-16T05:08:34Z | null | null | null | null | null | null | null | null | null | null |
2,302.08113 | MultiDiffusion: Fusing Diffusion Paths for Controlled Image Generation | ['Omer Bar-Tal', 'Lior Yariv', 'Yaron Lipman', 'Tali Dekel'] | ['cs.CV'] | Recent advances in text-to-image generation with diffusion models present
transformative capabilities in image quality. However, user controllability of
the generated image, and fast adaptation to new tasks still remains an open
challenge, currently mostly addressed by costly and long re-training and
fine-tuning or ad-... | 2023-02-16T06:28:29Z | null | null | null | null | null | null | null | null | null | null |
2,302.08357 | Boundary Guided Learning-Free Semantic Control with Diffusion Models | ['Ye Zhu', 'Yu Wu', 'Zhiwei Deng', 'Olga Russakovsky', 'Yan Yan'] | ['cs.CV'] | Applying pre-trained generative denoising diffusion models (DDMs) for
downstream tasks such as image semantic editing usually requires either
fine-tuning DDMs or learning auxiliary editing networks in the existing
literature. In this work, we present our BoundaryDiffusion method for
efficient, effective and light-weigh... | 2023-02-16T15:21:46Z | NeurIPS 2023. 27 pages including appendices, code at
https://github.com/L-YeZhu/BoundaryDiffusion | null | null | Boundary Guided Learning-Free Semantic Control with Diffusion Models | ['Ye Zhu', 'Yuehua Wu', 'Zhiwei Deng', 'Olga Russakovsky', 'Yan Yan'] | 2,023 | Neural Information Processing Systems | 23 | 72 | ['Computer Science'] |
2,302.08387 | LEALLA: Learning Lightweight Language-agnostic Sentence Embeddings with
Knowledge Distillation | ['Zhuoyuan Mao', 'Tetsuji Nakagawa'] | ['cs.CL'] | Large-scale language-agnostic sentence embedding models such as LaBSE (Feng
et al., 2022) obtain state-of-the-art performance for parallel sentence
alignment. However, these large-scale models can suffer from inference speed
and computation overhead. This study systematically explores learning
language-agnostic sentenc... | 2023-02-16T16:05:34Z | EACL 2023 main conference; LEALLA models:
https://www.kaggle.com/models/google/lealla (modified url in v2 of this
paper) | null | null | null | null | null | null | null | null | null |
2,302.08453 | T2I-Adapter: Learning Adapters to Dig out More Controllable Ability for
Text-to-Image Diffusion Models | ['Chong Mou', 'Xintao Wang', 'Liangbin Xie', 'Yanze Wu', 'Jian Zhang', 'Zhongang Qi', 'Ying Shan', 'Xiaohu Qie'] | ['cs.CV', 'cs.AI', 'cs.LG', 'cs.MM'] | The incredible generative ability of large-scale text-to-image (T2I) models
has demonstrated strong power of learning complex structures and meaningful
semantics. However, relying solely on text prompts cannot fully take advantage
of the knowledge learned by the model, especially when flexible and accurate
controlling ... | 2023-02-16T17:56:08Z | Tech Report. GitHub: https://github.com/TencentARC/T2I-Adapter | null | null | null | null | null | null | null | null | null |
2,302.08468 | LEVER: Learning to Verify Language-to-Code Generation with Execution | ['Ansong Ni', 'Srini Iyer', 'Dragomir Radev', 'Ves Stoyanov', 'Wen-tau Yih', 'Sida I. Wang', 'Xi Victoria Lin'] | ['cs.LG', 'cs.CL', 'cs.PL', 'cs.SE'] | The advent of large language models trained on code (code LLMs) has led to
significant progress in language-to-code generation. State-of-the-art
approaches in this area combine LLM decoding with sample pruning and reranking
using test cases or heuristics based on the execution results. However, it is
challenging to obt... | 2023-02-16T18:23:22Z | ICML'23; code available at https://github.com/niansong1996/lever | null | null | null | null | null | null | null | null | null |
2,302.08624 | InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis | ['Kevin Scaria', 'Himanshu Gupta', 'Siddharth Goyal', 'Saurabh Arjun Sawant', 'Swaroop Mishra', 'Chitta Baral'] | ['cs.CL', 'cs.LG'] | We introduce InstructABSA, an instruction learning paradigm for Aspect-Based
Sentiment Analysis (ABSA) subtasks. Our method introduces positive, negative,
and neutral examples to each training sample, and instruction tune the model
(Tk-Instruct) for ABSA subtasks, yielding significant performance improvements.
Experime... | 2023-02-16T23:29:22Z | 4 pages, 3 figures, 9 tables, 9 appendix pages | null | null | InstructABSA: Instruction Learning for Aspect Based Sentiment Analysis | ['Kevin Scaria', 'Himanshu Gupta', 'Saurabh Arjun Sawant', 'Swaroop Mishra', 'Chitta Baral'] | 2,023 | North American Chapter of the Association for Computational Linguistics | 34 | 89 | ['Computer Science'] |
2,302.08956 | AfriSenti: A Twitter Sentiment Analysis Benchmark for African Languages | ['Shamsuddeen Hassan Muhammad', 'Idris Abdulmumin', 'Abinew Ali Ayele', 'Nedjma Ousidhoum', 'David Ifeoluwa Adelani', 'Seid Muhie Yimam', "Ibrahim Sa'id Ahmad", 'Meriem Beloucif', 'Saif M. Mohammad', 'Sebastian Ruder', 'Oumaima Hourrane', 'Pavel Brazdil', 'Felermino Dário Mário António Ali', 'Davis David', 'Salomey Ose... | ['cs.CL'] | Africa is home to over 2,000 languages from more than six language families
and has the highest linguistic diversity among all continents. These include 75
languages with at least one million speakers each. Yet, there is little NLP
research conducted on African languages. Crucial to enabling such research is
the availa... | 2023-02-17T15:40:12Z | 14 pages, 3 Figures, 10 Tables | null | null | null | null | null | null | null | null | null |
2,302.08958 | Towards Unifying Medical Vision-and-Language Pre-training via Soft
Prompts | ['Zhihong Chen', 'Shizhe Diao', 'Benyou Wang', 'Guanbin Li', 'Xiang Wan'] | ['cs.CV'] | Medical vision-and-language pre-training (Med-VLP) has shown promising
improvements on many downstream medical tasks owing to its applicability to
extracting generic representations from medical images and texts. Practically,
there exist two typical types, \textit{i.e.}, the fusion-encoder type and the
dual-encoder typ... | 2023-02-17T15:43:42Z | Work in progress | null | null | null | null | null | null | null | null | null |
2,302.09432 | BBT-Fin: Comprehensive Construction of Chinese Financial Domain
Pre-trained Language Model, Corpus and Benchmark | ['Dakuan Lu', 'Hengkui Wu', 'Jiaqing Liang', 'Yipei Xu', 'Qianyu He', 'Yipeng Geng', 'Mengkun Han', 'Yingsi Xin', 'Yanghua Xiao'] | ['cs.CL'] | To advance Chinese financial natural language processing (NLP), we introduce
BBT-FinT5, a new Chinese financial pre-training language model based on the T5
model. To support this effort, we have built BBT-FinCorpus, a large-scale
financial corpus with approximately 300GB of raw text from four different
sources. In gene... | 2023-02-18T22:20:37Z | Changed author order | null | null | BBT-Fin: Comprehensive Construction of Chinese Financial Domain Pre-trained Language Model, Corpus and Benchmark | ['Dakuan Lu', 'Jiaqing Liang', 'Yipei Xu', 'Qi He', 'Yipeng Geng', 'Mengkun Han', 'Ying Xin', 'Hengkui Wu', 'Yanghua Xiao'] | 2,023 | arXiv.org | 62 | 34 | ['Computer Science'] |
2,302.09611 | Exploring the Potential of Machine Translation for Generating Named
Entity Datasets: A Case Study between Persian and English | ['Amir Sartipi', 'Afsaneh Fatemi'] | ['cs.CL', 'cs.AI'] | This study focuses on the generation of Persian named entity datasets through
the application of machine translation on English datasets. The generated
datasets were evaluated by experimenting with one monolingual and one
multilingual transformer model. Notably, the CoNLL 2003 dataset has achieved
the highest F1 score ... | 2023-02-19T16:12:21Z | null | 2023 9th International Conference on Web Research (ICWR), 2023,
368-372 | 10.1109/ICWR57742.2023.10139222 | null | null | null | null | null | null | null |
2,302.10166 | Learning Deep Semantics for Test Completion | ['Pengyu Nie', 'Rahul Banerjee', 'Junyi Jessy Li', 'Raymond J. Mooney', 'Milos Gligoric'] | ['cs.SE', 'cs.CL', 'cs.LG'] | Writing tests is a time-consuming yet essential task during software
development. We propose to leverage recent advances in deep learning for text
and code generation to assist developers in writing tests. We formalize the
novel task of test completion to automatically complete the next statement in a
test method based... | 2023-02-20T18:53:56Z | Accepted as a conference paper in ICSE 2023 | null | null | null | null | null | null | null | null | null |
2,302.10866 | Hyena Hierarchy: Towards Larger Convolutional Language Models | ['Michael Poli', 'Stefano Massaroli', 'Eric Nguyen', 'Daniel Y. Fu', 'Tri Dao', 'Stephen Baccus', 'Yoshua Bengio', 'Stefano Ermon', 'Christopher Ré'] | ['cs.LG', 'cs.CL'] | Recent advances in deep learning have relied heavily on the use of large
Transformers due to their ability to learn at scale. However, the core building
block of Transformers, the attention operator, exhibits quadratic cost in
sequence length, limiting the amount of context accessible. Existing
subquadratic methods bas... | 2023-02-21T18:29:25Z | Additional details | null | null | null | null | null | null | null | null | null |
2,302.11824 | MossFormer: Pushing the Performance Limit of Monaural Speech Separation
using Gated Single-Head Transformer with Convolution-Augmented Joint
Self-Attentions | ['Shengkui Zhao', 'Bin Ma'] | ['cs.SD', 'cs.LG', 'eess.AS'] | Transformer based models have provided significant performance improvements
in monaural speech separation. However, there is still a performance gap
compared to a recent proposed upper bound. The major limitation of the current
dual-path Transformer models is the inefficient modelling of long-range
elemental interactio... | 2023-02-23T07:17:12Z | 5 pages, 3 figures, accepted by ICASSP 2023 | null | null | null | null | null | null | null | null | null |
2,302.12189 | HL Dataset: Visually-grounded Description of Scenes, Actions and
Rationales | ['Michele Cafagna', 'Kees van Deemter', 'Albert Gatt'] | ['cs.CL', 'cs.CV'] | Current captioning datasets focus on object-centric captions, describing the
visible objects in the image, e.g. "people eating food in a park". Although
these datasets are useful to evaluate the ability of Vision & Language models
to recognize and describe visual content, they do not support controlled
experiments invo... | 2023-02-23T17:30:18Z | null | null | null | HL Dataset: Visually-grounded Description of Scenes, Actions and Rationales | ['Michele Cafagna', 'K. V. Deemter', 'Albert Gatt'] | 2,023 | International Conference on Natural Language Generation | 4 | 51 | ['Computer Science'] |
2,302.12242 | Side Adapter Network for Open-Vocabulary Semantic Segmentation | ['Mengde Xu', 'Zheng Zhang', 'Fangyun Wei', 'Han Hu', 'Xiang Bai'] | ['cs.CV', 'cs.AI'] | This paper presents a new framework for open-vocabulary semantic segmentation
with the pre-trained vision-language model, named Side Adapter Network (SAN).
Our approach models the semantic segmentation task as a region recognition
problem. A side network is attached to a frozen CLIP model with two branches:
one for pre... | 2023-02-23T18:58:28Z | CVPR2023 Highlight | null | null | null | null | null | null | null | null | null |
2,302.12288 | ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth | ['Shariq Farooq Bhat', 'Reiner Birkl', 'Diana Wofk', 'Peter Wonka', 'Matthias Müller'] | ['cs.CV'] | This paper tackles the problem of depth estimation from a single image.
Existing work either focuses on generalization performance disregarding metric
scale, i.e. relative depth estimation, or state-of-the-art results on specific
datasets, i.e. metric depth estimation. We propose the first approach that
combines both w... | 2023-02-23T19:13:10Z | null | null | null | ZoeDepth: Zero-shot Transfer by Combining Relative and Metric Depth | ['S. Bhat', 'R. Birkl', 'Diana Wofk', 'Peter Wonka', 'Matthias Muller'] | 2,023 | arXiv.org | 517 | 51 | ['Computer Science'] |
2,302.12433 | ProofNet: Autoformalizing and Formally Proving Undergraduate-Level
Mathematics | ['Zhangir Azerbayev', 'Bartosz Piotrowski', 'Hailey Schoelkopf', 'Edward W. Ayers', 'Dragomir Radev', 'Jeremy Avigad'] | ['cs.CL', 'cs.AI', 'cs.LO'] | We introduce ProofNet, a benchmark for autoformalization and formal proving
of undergraduate-level mathematics. The ProofNet benchmarks consists of 371
examples, each consisting of a formal theorem statement in Lean 3, a natural
language theorem statement, and a natural language proof. The problems are
primarily drawn ... | 2023-02-24T03:28:46Z | null | null | null | ProofNet: Autoformalizing and Formally Proving Undergraduate-Level Mathematics | ['Zhangir Azerbayev', 'Bartosz Piotrowski', 'Hailey Schoelkopf', 'Edward W. Ayers', 'Dragomir R. Radev', 'J. Avigad'] | 2,023 | arXiv.org | 84 | 39 | ['Computer Science'] |
2,302.13149 | STACC: Code Comment Classification using SentenceTransformers | ['Ali Al-Kaswan', 'Maliheh Izadi', 'Arie van Deursen'] | ['cs.SE', 'cs.AI', 'cs.CL'] | Code comments are a key resource for information about software artefacts.
Depending on the use case, only some types of comments are useful. Thus,
automatic approaches to classify these comments have been proposed. In this
work, we address this need by proposing, STACC, a set of
SentenceTransformers-based binary class... | 2023-02-25T20:24:58Z | null | null | null | null | null | null | null | null | null | null |
2,302.13173 | MetaAID 2.0: An Extensible Framework for Developing Metaverse
Applications via Human-controllable Pre-trained Models | ['Hongyin Zhu'] | ['cs.CL'] | Pre-trained models (PM) have achieved promising results in content
generation. However, the space for human creativity and imagination is endless,
and it is still unclear whether the existing models can meet the needs.
Model-generated content faces uncontrollable responsibility and potential
unethical problems. This pa... | 2023-02-25T21:42:31Z | null | null | null | MetaAID 2.0: An Extensible Framework for Developing Metaverse Applications via Human-controllable Pre-trained Models | ['Hongyin Zhu'] | 2,023 | arXiv.org | 6 | 43 | ['Computer Science'] |
2,302.13372 | Localizing Moments in Long Video Via Multimodal Guidance | ['Wayner Barrios', 'Mattia Soldan', 'Alberto Mario Ceballos-Arroyo', 'Fabian Caba Heilbron', 'Bernard Ghanem'] | ['cs.CV', 'cs.AI', 'cs.LG'] | The recent introduction of the large-scale, long-form MAD and Ego4D datasets
has enabled researchers to investigate the performance of current
state-of-the-art methods for video grounding in the long-form setup, with
interesting findings: current grounding methods alone fail at tackling this
challenging task and setup ... | 2023-02-26T18:19:24Z | null | Proceedings of the IEEE/CVF International Conference on Computer
Vision (ICCV) 2023 | null | null | null | null | null | null | null | null |
2,302.13403 | Tweets Under the Rubble: Detection of Messages Calling for Help in
Earthquake Disaster | ['Cagri Toraman', 'Izzet Emre Kucukkaya', 'Oguzhan Ozcelik', 'Umitcan Sahin'] | ['cs.SI', 'cs.CL', 'cs.IR'] | The importance of social media is again exposed in the recent tragedy of the
2023 Turkey and Syria earthquake. Many victims who were trapped under the
rubble called for help by posting messages in Twitter. We present an
interactive tool to provide situational awareness for missing and trapped
people, and disaster relie... | 2023-02-26T20:55:19Z | null | null | null | null | null | null | null | null | null | null |
2,302.13498 | Pretraining De-Biased Language Model with Large-scale Click Logs for
Document Ranking | ['Xiangsheng Li', 'Xiaoshu Chen', 'Kunliang Wei', 'Bin Hu', 'Lei Jiang', 'Zeqian Huang', 'Zhanhui Kang'] | ['cs.IR'] | Pre-trained language models have achieved great success in various
large-scale information retrieval tasks. However, most of pretraining tasks are
based on counterfeit retrieval data where the query produced by the tailored
rule is assumed as the user's issued query on the given document or passage.
Therefore, we explo... | 2023-02-27T03:47:07Z | null | null | null | null | null | null | null | null | null | null |
2,302.13756 | Multi-Feature Integration for Perception-Dependent Examination-Bias
Estimation | ['Xiaoshu Chen', 'Xiangsheng Li', 'Kunliang Wei', 'Bin Hu', 'Lei Jiang', 'Zeqian Huang', 'Zhanhui Kang'] | ['cs.IR'] | Eliminating examination bias accurately is pivotal to apply click-through
data to train an unbiased ranking model. However, most examination-bias
estimators are limited to the hypothesis of Position-Based Model (PBM), which
supposes that the calculation of examination bias only depends on the rank of
the document. Rece... | 2023-02-27T13:34:38Z | null | null | null | null | null | null | null | null | null | null |
2,302.13848 | ELITE: Encoding Visual Concepts into Textual Embeddings for Customized
Text-to-Image Generation | ['Yuxiang Wei', 'Yabo Zhang', 'Zhilong Ji', 'Jinfeng Bai', 'Lei Zhang', 'Wangmeng Zuo'] | ['cs.CV'] | In addition to the unprecedented ability in imaginary creation, large
text-to-image models are expected to take customized concepts in image
generation. Existing works generally learn such concepts in an
optimization-based manner, yet bringing excessive computation or memory burden.
In this paper, we instead propose a ... | 2023-02-27T14:49:53Z | Accepted by ICCV 2023, oral presentation. Code:
https://github.com/csyxwei/ELITE | null | null | null | null | null | null | null | null | null |
2,302.13971 | LLaMA: Open and Efficient Foundation Language Models | ['Hugo Touvron', 'Thibaut Lavril', 'Gautier Izacard', 'Xavier Martinet', 'Marie-Anne Lachaux', 'Timothée Lacroix', 'Baptiste Rozière', 'Naman Goyal', 'Eric Hambro', 'Faisal Azhar', 'Aurelien Rodriguez', 'Armand Joulin', 'Edouard Grave', 'Guillaume Lample'] | ['cs.CL'] | We introduce LLaMA, a collection of foundation language models ranging from
7B to 65B parameters. We train our models on trillions of tokens, and show that
it is possible to train state-of-the-art models using publicly available
datasets exclusively, without resorting to proprietary and inaccessible
datasets. In partic... | 2023-02-27T17:11:15Z | null | null | null | null | null | null | null | null | null | null |
2,302.1422 | Are Character-level Translations Worth the Wait? Comparing ByT5 and mT5
for Machine Translation | ['Lukas Edman', 'Gabriele Sarti', 'Antonio Toral', 'Gertjan van Noord', 'Arianna Bisazza'] | ['cs.CL'] | Pretrained character-level and byte-level language models have been shown to
be competitive with popular subword models across a range of Natural Language
Processing (NLP) tasks. However, there has been little research on their
effectiveness for neural machine translation (NMT), particularly within the
popular pretrain... | 2023-02-28T00:50:19Z | This version of our work is a pre-MIT Press publication version | null | 10.1162/tacl_a_00651 | Are Character-level Translations Worth the Wait? Comparing ByT5 and mT5 for Machine Translation | ['Lukas Edman', 'Gabriele Sarti', 'Antonio Toral', 'Gertjan van Noord', 'Arianna Bisazza'] | 2,023 | Transactions of the Association for Computational Linguistics | 14 | 54 | ['Computer Science'] |
2,302.14231 | CHGNet: Pretrained universal neural network potential for
charge-informed atomistic modeling | ['Bowen Deng', 'Peichen Zhong', 'KyuJung Jun', 'Janosh Riebesell', 'Kevin Han', 'Christopher J. Bartel', 'Gerbrand Ceder'] | ['cond-mat.mtrl-sci', 'cs.LG'] | The simulation of large-scale systems with complex electron interactions
remains one of the greatest challenges for the atomistic modeling of materials.
Although classical force fields often fail to describe the coupling between
electronic states and ionic rearrangements, the more accurate
\textit{ab-initio} molecular ... | 2023-02-28T01:30:06Z | null | null | null | CHGNet: Pretrained universal neural network potential for charge-informed atomistic modeling | ['B. Deng', 'Peichen Zhong', 'KyuJung Jun', 'K. Han', 'Christopher J. Bartel', 'G. Ceder'] | 2,023 | arXiv.org | 27 | 94 | ['Physics', 'Computer Science'] |
2,302.14367 | BrainBERT: Self-supervised representation learning for intracranial
recordings | ['Christopher Wang', 'Vighnesh Subramaniam', 'Adam Uri Yaari', 'Gabriel Kreiman', 'Boris Katz', 'Ignacio Cases', 'Andrei Barbu'] | ['cs.LG', 'eess.SP', 'q-bio.NC'] | We create a reusable Transformer, BrainBERT, for intracranial recordings
bringing modern representation learning approaches to neuroscience. Much like
in NLP and speech recognition, this Transformer enables classifying complex
concepts, i.e., decoding neural data, with higher accuracy and with much less
data by being p... | 2023-02-28T07:40:37Z | 9 pages, 6 figures, ICLR 2023 | null | null | null | null | null | null | null | null | null |
2,302.70971 | null | [] | [''] | null | null | null | null | null | null | null | null | null | null | null | null |
2,303.00628 | MuAViC: A Multilingual Audio-Visual Corpus for Robust Speech Recognition
and Robust Speech-to-Text Translation | ['Mohamed Anwar', 'Bowen Shi', 'Vedanuj Goswami', 'Wei-Ning Hsu', 'Juan Pino', 'Changhan Wang'] | ['cs.CL', 'eess.AS'] | We introduce MuAViC, a multilingual audio-visual corpus for robust speech
recognition and robust speech-to-text translation providing 1200 hours of
audio-visual speech in 9 languages. It is fully transcribed and covers 6
English-to-X translation as well as 6 X-to-English translation directions. To
the best of our knowl... | 2023-03-01T16:31:01Z | null | null | null | null | null | null | null | null | null | null |
2,303.00716 | Aligning benchmark datasets for table structure recognition | ['Brandon Smock', 'Rohith Pesala', 'Robin Abraham'] | ['cs.CV', 'cs.LG'] | Benchmark datasets for table structure recognition (TSR) must be carefully
processed to ensure they are annotated consistently. However, even if a
dataset's annotations are self-consistent, there may be significant
inconsistency across datasets, which can harm the performance of models trained
and evaluated on them. In... | 2023-03-01T18:20:24Z | null | null | null | null | null | null | null | null | null | null |
2,303.00848 | Understanding Diffusion Objectives as the ELBO with Simple Data
Augmentation | ['Diederik P. Kingma', 'Ruiqi Gao'] | ['cs.LG', 'cs.AI', 'stat.ML'] | To achieve the highest perceptual quality, state-of-the-art diffusion models
are optimized with objectives that typically look very different from the
maximum likelihood and the Evidence Lower Bound (ELBO) objectives. In this
work, we reveal that diffusion model objectives are actually closely related to
the ELBO.
Sp... | 2023-03-01T22:36:05Z | null | null | null | null | null | null | null | null | null | null |
2,303.00915 | BiomedCLIP: a multimodal biomedical foundation model pretrained from
fifteen million scientific image-text pairs | ['Sheng Zhang', 'Yanbo Xu', 'Naoto Usuyama', 'Hanwen Xu', 'Jaspreet Bagga', 'Robert Tinn', 'Sam Preston', 'Rajesh Rao', 'Mu Wei', 'Naveen Valluri', 'Cliff Wong', 'Andrea Tupini', 'Yu Wang', 'Matt Mazzola', 'Swadheen Shukla', 'Lars Liden', 'Jianfeng Gao', 'Angela Crabtree', 'Brian Piening', 'Carlo Bifulco', 'Matthew P. ... | ['cs.CV', 'cs.CL'] | Biomedical data is inherently multimodal, comprising physical measurements
and natural language narratives. A generalist biomedical AI model needs to
simultaneously process different modalities of data, including text and images.
Therefore, training an effective generalist biomedical model requires
high-quality multimo... | 2023-03-02T02:20:04Z | The models are released at https://aka.ms/biomedclip | null | null | null | null | null | null | null | null | null |
2,303.01037 | Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages | ['Yu Zhang', 'Wei Han', 'James Qin', 'Yongqiang Wang', 'Ankur Bapna', 'Zhehuai Chen', 'Nanxin Chen', 'Bo Li', 'Vera Axelrod', 'Gary Wang', 'Zhong Meng', 'Ke Hu', 'Andrew Rosenberg', 'Rohit Prabhavalkar', 'Daniel S. Park', 'Parisa Haghani', 'Jason Riesa', 'Ginger Perng', 'Hagen Soltau', 'Trevor Strohman', 'Bhuvana Ramab... | ['cs.CL', 'cs.SD', 'eess.AS'] | We introduce the Universal Speech Model (USM), a single large model that
performs automatic speech recognition (ASR) across 100+ languages. This is
achieved by pre-training the encoder of the model on a large unlabeled
multilingual dataset of 12 million (M) hours spanning over 300 languages, and
fine-tuning on a smalle... | 2023-03-02T07:47:18Z | 20 pages, 7 figures, 8 tables | null | null | Google USM: Scaling Automatic Speech Recognition Beyond 100 Languages | ['Yu Zhang', 'Wei Han', 'James Qin', 'Yongqiang Wang', 'Ankur Bapna', 'Zhehuai Chen', 'Nanxin Chen', 'Bo Li', 'Vera Axelrod', 'Gary Wang', 'Zhong Meng', 'Ke Hu', 'A. Rosenberg', 'Rohit Prabhavalkar', 'Daniel S. Park', 'Parisa Haghani', 'Jason Riesa', 'Ginger Perng', 'H. Soltau', 'Trevor Strohman', 'B. Ramabhadran', 'Ta... | 2,023 | arXiv.org | 270 | 90 | ['Computer Science', 'Engineering'] |
2,303.01263 | Unnoticeable Backdoor Attacks on Graph Neural Networks | ['Enyan Dai', 'Minhua Lin', 'Xiang Zhang', 'Suhang Wang'] | ['cs.CR', 'cs.LG'] | Graph Neural Networks (GNNs) have achieved promising results in various tasks
such as node classification and graph classification. Recent studies find that
GNNs are vulnerable to adversarial attacks. However, effective backdoor attacks
on graphs are still an open problem. In particular, backdoor attack poisons the
gra... | 2023-02-11T01:50:58Z | null | null | 10.1145/3543507.3583392 | null | null | null | null | null | null | null |
2,303.01469 | Consistency Models | ['Yang Song', 'Prafulla Dhariwal', 'Mark Chen', 'Ilya Sutskever'] | ['cs.LG', 'cs.CV', 'stat.ML'] | Diffusion models have significantly advanced the fields of image, audio, and
video generation, but they depend on an iterative sampling process that causes
slow generation. To overcome this limitation, we propose consistency models, a
new family of models that generate high quality samples by directly mapping
noise to ... | 2023-03-02T18:30:16Z | ICML 2023 | null | null | Consistency Models | ['Yang Song', 'Prafulla Dhariwal', 'Mark Chen', 'I. Sutskever'] | 2,023 | International Conference on Machine Learning | 983 | 88 | ['Computer Science', 'Mathematics'] |
2,303.0161 | Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable
Transformers | ['Tianlong Chen', 'Zhenyu Zhang', 'Ajay Jaiswal', 'Shiwei Liu', 'Zhangyang Wang'] | ['cs.LG'] | Despite their remarkable achievement, gigantic transformers encounter
significant drawbacks, including exorbitant computational and memory footprints
during training, as well as severe collapse evidenced by a high degree of
parameter redundancy. Sparsely-activated Mixture-of-Experts (SMoEs) have shown
promise to mitiga... | 2023-03-02T22:12:51Z | Codes and models are available in
https://github.com/VITA-Group/Random-MoE-as-Dropout | null | null | Sparse MoE as the New Dropout: Scaling Dense and Self-Slimmable Transformers | ['Tianlong Chen', 'Zhenyu (Allen) Zhang', 'Ajay Jaiswal', 'Shiwei Liu', 'Zhangyang Wang'] | 2,023 | International Conference on Learning Representations | 50 | 99 | ['Computer Science'] |
2,303.03004 | xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code
Understanding, Generation, Translation and Retrieval | ['Mohammad Abdullah Matin Khan', 'M Saiful Bari', 'Xuan Long Do', 'Weishi Wang', 'Md Rizwan Parvez', 'Shafiq Joty'] | ['cs.CL'] | Recently, pre-trained large language models (LLMs) have shown impressive
abilities in generating codes from natural language descriptions, repairing
buggy codes, translating codes between languages, and retrieving relevant code
segments. However, the evaluation of these models has often been performed in a
scattered wa... | 2023-03-06T10:08:51Z | Code & Data available at https://github.com/ntunlp/xCodeEval,
https://huggingface.co/datasets/NTU-NLP-sg/xCodeEval. Evaluation framework
available at https://github.com/ntunlp/execeval | null | null | null | null | null | null | null | null | null |
2,303.03307 | Learning Efficient Coding of Natural Images with Maximum Manifold
Capacity Representations | ['Thomas Yerxa', 'Yilun Kuang', 'Eero Simoncelli', 'SueYeon Chung'] | ['cs.CV', 'q-bio.NC'] | The efficient coding hypothesis proposes that the response properties of
sensory systems are adapted to the statistics of their inputs such that they
capture maximal information about the environment, subject to biological
constraints. While elegant, information theoretic properties are notoriously
difficult to measure... | 2023-03-06T17:26:30Z | Accepted at NeurIPS 2023 | null | null | Learning Efficient Coding of Natural Images with Maximum Manifold Capacity Representations | ['Thomas E. Yerxa', 'Yilun Kuang', 'E. Simoncelli', 'SueYeon Chung'] | 2,023 | null | 0 | 75 | ['Computer Science', 'Biology'] |
2,303.03565 | CLIP-Layout: Style-Consistent Indoor Scene Synthesis with Semantic
Furniture Embedding | ['Jingyu Liu', 'Wenhan Xiong', 'Ian Jones', 'Yixin Nie', 'Anchit Gupta', 'Barlas Oğuz'] | ['cs.CV'] | Indoor scene synthesis involves automatically picking and placing furniture
appropriately on a floor plan, so that the scene looks realistic and is
functionally plausible. Such scenes can serve as homes for immersive 3D
experiences, or be used to train embodied agents. Existing methods for this
task rely on labeled cat... | 2023-03-07T00:26:02Z | Changed paper template and cleaned up tables | null | null | CLIP-Layout: Style-Consistent Indoor Scene Synthesis with Semantic Furniture Embedding | ['Jingyu Liu', 'Wenhan Xiong', 'Ian Jones', 'Yixin Nie', 'Anchit Gupta', 'Barlas Ouguz'] | 2,023 | arXiv.org | 15 | 49 | ['Computer Science'] |
2,303.03667 | Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks | ['Jierun Chen', 'Shiu-hong Kao', 'Hao He', 'Weipeng Zhuo', 'Song Wen', 'Chul-Ho Lee', 'S. -H. Gary Chan'] | ['cs.CV'] | To design fast neural networks, many works have been focusing on reducing the
number of floating-point operations (FLOPs). We observe that such reduction in
FLOPs, however, does not necessarily lead to a similar level of reduction in
latency. This mainly stems from inefficiently low floating-point operations per
second... | 2023-03-07T06:05:30Z | Accepted to CVPR 2023 | null | null | null | null | null | null | null | null | null |
2,303.0375 | Preparing the Vuk'uzenzele and ZA-gov-multilingual South African
multilingual corpora | ['Richard Lastrucci', 'Isheanesu Dzingirai', 'Jenalea Rajab', 'Andani Madodonga', 'Matimba Shingange', 'Daniel Njini', 'Vukosi Marivate'] | ['cs.CL'] | This paper introduces two multilingual government themed corpora in various
South African languages. The corpora were collected by gathering the South
African Government newspaper (Vuk'uzenzele), as well as South African
government speeches (ZA-gov-multilingual), that are translated into all 11
South African official l... | 2023-03-07T09:20:09Z | Accepted and to appear at Fourth workshop on Resources for African
Indigenous Languages (RAIL) at EACL 2023 | null | null | null | null | null | null | null | null | null |
2,303.03915 | The BigScience ROOTS Corpus: A 1.6TB Composite Multilingual Dataset | ['Hugo Laurençon', 'Lucile Saulnier', 'Thomas Wang', 'Christopher Akiki', 'Albert Villanova del Moral', 'Teven Le Scao', 'Leandro Von Werra', 'Chenghao Mou', 'Eduardo González Ponferrada', 'Huu Nguyen', 'Jörg Frohberg', 'Mario Šaško', 'Quentin Lhoest', 'Angelina McMillan-Major', 'Gerard Dupont', 'Stella Biderman', 'Ann... | ['cs.CL', 'cs.AI', 'I.2.7'] | As language models grow ever larger, the need for large-scale high-quality
text datasets has never been more pressing, especially in multilingual
settings. The BigScience workshop, a 1-year international and multidisciplinary
initiative, was formed with the goal of researching and training large language
models as a va... | 2023-03-07T14:25:44Z | NeurIPS 2022, Datasets and Benchmarks Track | null | null | null | null | null | null | null | null | null |
2,303.04132 | Exploiting Asymmetry for Synthetic Training Data Generation: SynthIE and
the Case of Information Extraction | ['Martin Josifoski', 'Marija Sakota', 'Maxime Peyrard', 'Robert West'] | ['cs.CL', 'cs.AI', 'cs.LG'] | Large language models (LLMs) have great potential for synthetic data
generation. This work shows that useful data can be synthetically generated
even for tasks that cannot be solved directly by LLMs: for problems with
structured outputs, it is possible to prompt an LLM to perform the task in the
reverse direction, by g... | 2023-03-07T18:48:55Z | Accepted at EMNLP 2023 | null | null | null | null | null | null | null | null | null |
2,303.04137 | Diffusion Policy: Visuomotor Policy Learning via Action Diffusion | ['Cheng Chi', 'Zhenjia Xu', 'Siyuan Feng', 'Eric Cousineau', 'Yilun Du', 'Benjamin Burchfiel', 'Russ Tedrake', 'Shuran Song'] | ['cs.RO'] | This paper introduces Diffusion Policy, a new way of generating robot
behavior by representing a robot's visuomotor policy as a conditional denoising
diffusion process. We benchmark Diffusion Policy across 12 different tasks from
4 different robot manipulation benchmarks and find that it consistently
outperforms existi... | 2023-03-07T18:50:03Z | An extended journal version of the original RSS2023 paper | null | null | null | null | null | null | null | null | null |
2,303.04143 | Can We Scale Transformers to Predict Parameters of Diverse ImageNet
Models? | ['Boris Knyazev', 'Doha Hwang', 'Simon Lacoste-Julien'] | ['cs.LG', 'cs.AI', 'cs.CV', 'stat.ML'] | Pretraining a neural network on a large dataset is becoming a cornerstone in
machine learning that is within the reach of only a few communities with
large-resources. We aim at an ambitious goal of democratizing pretraining.
Towards that goal, we train and release a single neural network that can
predict high quality I... | 2023-03-07T18:56:59Z | ICML 2023, camera ready (7 tables with extra results added), code and
models are at https://github.com/SamsungSAILMontreal/ghn3 | null | null | null | null | null | null | null | null | null |
2,303.04336 | QuickSRNet: Plain Single-Image Super-Resolution Architecture for Faster
Inference on Mobile Platforms | ['Guillaume Berger', 'Manik Dhingra', 'Antoine Mercier', 'Yashesh Savani', 'Sunny Panchal', 'Fatih Porikli'] | ['eess.IV', 'cs.CV', 'cs.LG'] | In this work, we present QuickSRNet, an efficient super-resolution
architecture for real-time applications on mobile platforms. Super-resolution
clarifies, sharpens, and upscales an image to higher resolution. Applications
such as gaming and video playback along with the ever-improving display
capabilities of TVs, smar... | 2023-03-08T02:19:54Z | Camera-ready version (CVPR workshop - MAI'23) | null | null | QuickSRNet: Plain Single-Image Super-Resolution Architecture for Faster Inference on Mobile Platforms | ['Guillaume Berger', 'Manik Dhingra', 'Antoine Mercier', 'Yash Savani', 'Sunny Panchal', 'F. Porikli'] | 2,023 | 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) | 5 | 46 | ['Computer Science', 'Engineering'] |
2,303.04634 | Transformer-based Image Generation from Scene Graphs | ['Renato Sortino', 'Simone Palazzo', 'Concetto Spampinato'] | ['cs.CV'] | Graph-structured scene descriptions can be efficiently used in generative
models to control the composition of the generated image. Previous approaches
are based on the combination of graph convolutional networks and adversarial
methods for layout prediction and image generation, respectively. In this work,
we show how... | 2023-03-08T14:54:51Z | null | null | null | null | null | null | null | null | null | null |
2,303.04671 | Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation
Models | ['Chenfei Wu', 'Shengming Yin', 'Weizhen Qi', 'Xiaodong Wang', 'Zecheng Tang', 'Nan Duan'] | ['cs.CV'] | ChatGPT is attracting a cross-field interest as it provides a language
interface with remarkable conversational competency and reasoning capabilities
across many domains. However, since ChatGPT is trained with languages, it is
currently not capable of processing or generating images from the visual world.
At the same t... | 2023-03-08T15:50:02Z | null | null | null | Visual ChatGPT: Talking, Drawing and Editing with Visual Foundation Models | ['Chenfei Wu', 'Sheng-Kai Yin', 'Weizhen Qi', 'Xiaodong Wang', 'Zecheng Tang', 'Nan Duan'] | 2,023 | arXiv.org | 649 | 62 | ['Computer Science'] |
2,303.04715 | Extending the Pre-Training of BLOOM for Improved Support of Traditional
Chinese: Models, Methods and Results | ['Philipp Ennen', 'Po-Chun Hsu', 'Chan-Jan Hsu', 'Chang-Le Liu', 'Yen-Chen Wu', 'Yin-Hsiang Liao', 'Chin-Tung Lin', 'Da-Shan Shiu', 'Wei-Yun Ma'] | ['cs.CL', 'cs.AI'] | In this paper we present the multilingual language model BLOOM-zh that
features enhanced support for Traditional Chinese. BLOOM-zh has its origins in
the open-source BLOOM models presented by BigScience in 2022. Starting from
released models, we extended the pre-training of BLOOM by additional 7.4
billion tokens in Tra... | 2023-03-08T16:53:19Z | null | null | null | Extending the Pre-Training of BLOOM for Improved Support of Traditional Chinese: Models, Methods and Results | ['Philipp Ennen', 'Po-chun Hsu', 'Chan-Jan Hsu', 'Chang-Le Liu', 'Yen-Chen Wu', 'Yin-Hsiang Liao', 'Chin-Tung Lin', 'Da-shan Shiu', 'Wei-Yun Ma'] | 2,023 | arXiv.org | 11 | 64 | ['Computer Science'] |
2,303.04995 | Text-Visual Prompting for Efficient 2D Temporal Video Grounding | ['Yimeng Zhang', 'Xin Chen', 'Jinghan Jia', 'Sijia Liu', 'Ke Ding'] | ['cs.CV', 'cs.AI'] | In this paper, we study the problem of temporal video grounding (TVG), which
aims to predict the starting/ending time points of moments described by a text
sentence within a long untrimmed video. Benefiting from fine-grained 3D visual
features, the TVG techniques have achieved remarkable progress in recent years.
Howev... | 2023-03-09T02:38:32Z | Accepted to the CVPR 2023 and code released
(https://github.com/intel/TVP) | null | null | null | null | null | null | null | null | null |
2,303.05334 | Natural scene reconstruction from fMRI signals using generative latent
diffusion | ['Furkan Ozcelik', 'Rufin VanRullen'] | ['cs.CV', 'cs.AI', 'q-bio.NC'] | In neural decoding research, one of the most intriguing topics is the
reconstruction of perceived natural images based on fMRI signals. Previous
studies have succeeded in re-creating different aspects of the visuals, such as
low-level properties (shape, texture, layout) or high-level features (category
of objects, desc... | 2023-03-09T15:24:26Z | null | null | null | Natural scene reconstruction from fMRI signals using generative latent diffusion | ['Furkan Ozcelik', 'Rufin VanRullen'] | 2,023 | Scientific Reports | 88 | 51 | ['Medicine', 'Computer Science', 'Biology'] |
2,303.05499 | Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set
Object Detection | ['Shilong Liu', 'Zhaoyang Zeng', 'Tianhe Ren', 'Feng Li', 'Hao Zhang', 'Jie Yang', 'Qing Jiang', 'Chunyuan Li', 'Jianwei Yang', 'Hang Su', 'Jun Zhu', 'Lei Zhang'] | ['cs.CV'] | In this paper, we present an open-set object detector, called Grounding DINO,
by marrying Transformer-based detector DINO with grounded pre-training, which
can detect arbitrary objects with human inputs such as category names or
referring expressions. The key solution of open-set object detection is
introducing languag... | 2023-03-09T18:52:16Z | Code will be available at
https://github.com/IDEA-Research/GroundingDINO | null | null | null | null | null | null | null | null | null |
2,303.05657 | Tag2Text: Guiding Vision-Language Model via Image Tagging | ['Xinyu Huang', 'Youcai Zhang', 'Jinyu Ma', 'Weiwei Tian', 'Rui Feng', 'Yuejie Zhang', 'Yaqian Li', 'Yandong Guo', 'Lei Zhang'] | ['cs.CV'] | This paper presents Tag2Text, a vision language pre-training (VLP) framework,
which introduces image tagging into vision-language models to guide the
learning of visual-linguistic features. In contrast to prior works which
utilize object tags either manually labeled or automatically detected with an
off-the-shelf detec... | 2023-03-10T02:16:35Z | Accepted by ICLR 2024 | null | null | null | null | null | null | null | null | null |
2,303.05983 | Accountable Textual-Visual Chat Learns to Reject Human Instructions in
Image Re-creation | ['Zhiwei Zhang', 'Yuliang Liu'] | ['cs.CV', 'cs.AI'] | The recent success of ChatGPT and GPT-4 has drawn widespread attention to
multimodal dialogue systems. However, there is a lack of datasets in the
academic community that can effectively evaluate the multimodal generation
capabilities of Visual Language Models (VLMs) in textual-visual chat tasks. In
this paper, we addr... | 2023-03-10T15:35:11Z | TMLR, Survey Certification | null | null | null | null | null | null | null | null | null |
2,303.06135 | Rewarding Chatbots for Real-World Engagement with Millions of Users | ['Robert Irvine', 'Douglas Boubert', 'Vyas Raina', 'Adian Liusie', 'Ziyi Zhu', 'Vineet Mudupalli', 'Aliaksei Korshuk', 'Zongyi Liu', 'Fritz Cremer', 'Valentin Assassi', 'Christie-Carol Beauchamp', 'Xiaoding Lu', 'Thomas Rialan', 'William Beauchamp'] | ['cs.CL', 'cs.AI', 'cs.LG'] | The emergence of pretrained large language models has led to the deployment
of a range of social chatbots for chitchat. Although these chatbots demonstrate
language ability and fluency, they are not guaranteed to be engaging and can
struggle to retain users. This work investigates the development of social
chatbots tha... | 2023-03-10T18:53:52Z | null | null | null | null | null | null | null | null | null | null |
2,303.06146 | StyleGANEX: StyleGAN-Based Manipulation Beyond Cropped Aligned Faces | ['Shuai Yang', 'Liming Jiang', 'Ziwei Liu', 'Chen Change Loy'] | ['cs.CV', 'cs.LG'] | Recent advances in face manipulation using StyleGAN have produced impressive
results. However, StyleGAN is inherently limited to cropped aligned faces at a
fixed image resolution it is pre-trained on. In this paper, we propose a simple
and effective solution to this limitation by using dilated convolutions to
rescale t... | 2023-03-10T18:59:33Z | ICCV 2023. Code: https://github.com/williamyang1991/StyleGANEX
Project page: https://www.mmlab-ntu.com/project/styleganex/ | null | null | StyleGANEX: StyleGAN-Based Manipulation Beyond Cropped Aligned Faces | ['Shuai Yang', 'Liming Jiang', 'Ziwei Liu', 'Chen Change Loy'] | 2,023 | IEEE International Conference on Computer Vision | 24 | 46 | ['Computer Science'] |
2,303.06318 | A Hybrid Tensor-Expert-Data Parallelism Approach to Optimize
Mixture-of-Experts Training | ['Siddharth Singh', 'Olatunji Ruwase', 'Ammar Ahmad Awan', 'Samyam Rajbhandari', 'Yuxiong He', 'Abhinav Bhatele'] | ['cs.LG', 'cs.AI', 'cs.DC', 'cs.PF'] | Mixture-of-Experts (MoE) is a neural network architecture that adds sparsely
activated expert blocks to a base model, increasing the number of parameters
without impacting computational costs. However, current distributed deep
learning frameworks are limited in their ability to train high-quality MoE
models with large ... | 2023-03-11T05:38:15Z | null | null | 10.1145/3577193.3593704 | null | null | null | null | null | null | null |
2,303.06349 | Resurrecting Recurrent Neural Networks for Long Sequences | ['Antonio Orvieto', 'Samuel L Smith', 'Albert Gu', 'Anushan Fernando', 'Caglar Gulcehre', 'Razvan Pascanu', 'Soham De'] | ['cs.LG'] | Recurrent Neural Networks (RNNs) offer fast inference on long sequences but
are hard to optimize and slow to train. Deep state-space models (SSMs) have
recently been shown to perform remarkably well on long sequence modeling tasks,
and have the added benefits of fast parallelizable training and RNN-like fast
inference.... | 2023-03-11T08:53:11Z | 30 pages, 9 figures | null | null | null | null | null | null | null | null | null |
2,303.06458 | ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and
Multilingual Natural Language Generation | ['Bang Yang', 'Fenglin Liu', 'Yuexian Zou', 'Xian Wu', 'Yaowei Wang', 'David A. Clifton'] | ['cs.CL', 'cs.AI', 'cs.CV'] | Natural Language Generation (NLG) accepts input data in the form of images,
videos, or text and generates corresponding natural language text as output.
Existing NLG methods mainly adopt a supervised approach and rely heavily on
coupled data-to-text pairs. However, for many targeted scenarios and for
non-English langua... | 2023-03-11T17:14:33Z | Accepted by TPAMI (Our code and data are available at
https://github.com/yangbang18/ZeroNLG) | null | null | ZeroNLG: Aligning and Autoencoding Domains for Zero-Shot Multimodal and Multilingual Natural Language Generation | ['Bang Yang', 'Fenglin Liu', 'Yuexian Zou', 'Xian Wu', 'Yaowei Wang', 'D. Clifton'] | 2,023 | IEEE Transactions on Pattern Analysis and Machine Intelligence | 9 | 107 | ['Computer Science', 'Medicine'] |
2,303.06555 | One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale | ['Fan Bao', 'Shen Nie', 'Kaiwen Xue', 'Chongxuan Li', 'Shi Pu', 'Yaole Wang', 'Gang Yue', 'Yue Cao', 'Hang Su', 'Jun Zhu'] | ['cs.LG', 'cs.CV'] | This paper proposes a unified diffusion framework (dubbed UniDiffuser) to fit
all distributions relevant to a set of multi-modal data in one model. Our key
insight is -- learning diffusion models for marginal, conditional, and joint
distributions can be unified as predicting the noise in the perturbed data,
where the p... | 2023-03-12T03:38:39Z | Accepted to ICML2023 | null | null | null | null | null | null | null | null | null |
2,303.0724 | PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical
Documents | ['Weixiong Lin', 'Ziheng Zhao', 'Xiaoman Zhang', 'Chaoyi Wu', 'Ya Zhang', 'Yanfeng Wang', 'Weidi Xie'] | ['cs.CV', 'cs.CL', 'cs.LG', 'cs.MM'] | Foundation models trained on large-scale dataset gain a recent surge in CV
and NLP. In contrast, development in biomedical domain lags far behind due to
data scarcity. To address this issue, we build and release PMC-OA, a biomedical
dataset with 1.6M image-caption pairs collected from PubMedCentral's OpenAccess
subset,... | 2023-03-13T16:13:16Z | 10 pages, 3 figures | null | null | PMC-CLIP: Contrastive Language-Image Pre-training using Biomedical Documents | ['Weixiong Lin', 'Ziheng Zhao', 'Xiaoman Zhang', 'Chaoyi Wu', 'Ya Zhang', 'Yanfeng Wang', 'Weidi Xie'] | 2,023 | International Conference on Medical Image Computing and Computer-Assisted Intervention | 159 | 32 | ['Computer Science'] |
2,303.07345 | Erasing Concepts from Diffusion Models | ['Rohit Gandikota', 'Joanna Materzynska', 'Jaden Fiotto-Kaufman', 'David Bau'] | ['cs.CV'] | Motivated by recent advancements in text-to-image diffusion, we study erasure
of specific concepts from the model's weights. While Stable Diffusion has shown
promise in producing explicit or realistic artwork, it has raised concerns
regarding its potential for misuse. We propose a fine-tuning method that can
erase a vi... | 2023-03-13T17:59:55Z | null | null | null | null | null | null | null | null | null | null |
2,303.07399 | RTMPose: Real-Time Multi-Person Pose Estimation based on MMPose | ['Tao Jiang', 'Peng Lu', 'Li Zhang', 'Ningsheng Ma', 'Rui Han', 'Chengqi Lyu', 'Yining Li', 'Kai Chen'] | ['cs.CV'] | Recent studies on 2D pose estimation have achieved excellent performance on
public benchmarks, yet its application in the industrial community still
suffers from heavy model parameters and high latency. In order to bridge this
gap, we empirically explore key factors in pose estimation including paradigm,
model architec... | 2023-03-13T18:26:11Z | null | null | null | null | null | null | null | null | null | null |
2,303.07519 | Architext: Language-Driven Generative Architecture Design | ['Theodoros Galanos', 'Antonios Liapis', 'Georgios N. Yannakakis'] | ['cs.CL', 'cs.LG'] | Architectural design is a highly complex practice that involves a wide
diversity of disciplines, technologies, proprietary design software, expertise,
and an almost infinite number of constraints, across a vast array of design
tasks. Enabling intuitive, accessible, and scalable design processes is an
important step tow... | 2023-03-13T23:11:05Z | 21 pages | null | null | null | null | null | null | null | null | null |
2,303.07865 | Predicting the Geolocation of Tweets Using transformer models on
Customized Data | ['Kateryna Lutsai', 'Christoph H. Lampert'] | ['cs.CL', 'cs.AI', 'cs.IR', 'cs.LG', '68T50', 'I.2.7'] | This research is aimed to solve the tweet/user geolocation prediction task
and provide a flexible methodology for the geotagging of textual big data. The
suggested approach implements neural networks for natural language processing
(NLP) to estimate the location as coordinate pairs (longitude, latitude) and
two-dimensi... | 2023-03-14T12:56:47Z | 31 pages, 5 tables, 9 figures | JOSIS. 29 (2024) 69-99 | 10.5311/JOSIS.2024.29.295 | null | null | null | null | null | null | null |
2,303.08084 | Editing Implicit Assumptions in Text-to-Image Diffusion Models | ['Hadas Orgad', 'Bahjat Kawar', 'Yonatan Belinkov'] | ['cs.CV'] | Text-to-image diffusion models often make implicit assumptions about the
world when generating images. While some assumptions are useful (e.g., the sky
is blue), they can also be outdated, incorrect, or reflective of social biases
present in the training data. Thus, there is a need to control these
assumptions without ... | 2023-03-14T17:14:21Z | Project page: https://time-diffusion.github.io/ | null | null | Editing Implicit Assumptions in Text-to-Image Diffusion Models | ['Hadas Orgad', 'Bahjat Kawar', 'Yonatan Belinkov'] | 2,023 | IEEE International Conference on Computer Vision | 91 | 80 | ['Computer Science'] |
2,303.08085 | Alias-Free Convnets: Fractional Shift Invariance via Polynomial
Activations | ['Hagay Michaeli', 'Tomer Michaeli', 'Daniel Soudry'] | ['cs.CV', 'eess.IV'] | Although CNNs are believed to be invariant to translations, recent works have
shown this is not the case, due to aliasing effects that stem from downsampling
layers. The existing architectural solutions to prevent aliasing are partial
since they do not solve these effects, that originate in non-linearities. We
propose ... | 2023-03-14T17:16:16Z | The paper was accepted to CVPR 2023. Our code is available at
https://github.com/hmichaeli/alias_free_convnets/ | null | null | Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activations | ['H. Michaeli', 'T. Michaeli', 'Daniel Soudry'] | 2,023 | Computer Vision and Pattern Recognition | 16 | 36 | ['Computer Science', 'Engineering'] |
2,303.08131 | A Simple Framework for Open-Vocabulary Segmentation and Detection | ['Hao Zhang', 'Feng Li', 'Xueyan Zou', 'Shilong Liu', 'Chunyuan Li', 'Jianfeng Gao', 'Jianwei Yang', 'Lei Zhang'] | ['cs.CV'] | We present OpenSeeD, a simple Open-vocabulary Segmentation and Detection
framework that jointly learns from different segmentation and detection
datasets. To bridge the gap of vocabulary and annotation granularity, we first
introduce a pre-trained text encoder to encode all the visual concepts in two
tasks and learn a ... | 2023-03-14T17:58:34Z | A Simple Framework for Open-Vocabulary Segmentation and Detection | null | null | A Simple Framework for Open-Vocabulary Segmentation and Detection | ['Hao Zhang', 'Feng Li', 'Xueyan Zou', 'Siyi Liu', 'Chun-yue Li', 'Jianfeng Gao', 'Jianwei Yang', 'Lei Zhang'] | 2,023 | IEEE International Conference on Computer Vision | 162 | 64 | ['Computer Science'] |
2,303.08179 | MEDBERT.de: A Comprehensive German BERT Model for the Medical Domain | ['Keno K. Bressem', 'Jens-Michalis Papaioannou', 'Paul Grundmann', 'Florian Borchert', 'Lisa C. Adams', 'Leonhard Liu', 'Felix Busch', 'Lina Xu', 'Jan P. Loyen', 'Stefan M. Niehues', 'Moritz Augustin', 'Lennart Grosser', 'Marcus R. Makowski', 'Hugo JWL. Aerts', 'Alexander Löser'] | ['cs.CL', 'cs.AI'] | This paper presents medBERTde, a pre-trained German BERT model specifically
designed for the German medical domain. The model has been trained on a large
corpus of 4.7 Million German medical documents and has been shown to achieve
new state-of-the-art performance on eight different medical benchmarks covering
a wide ra... | 2023-03-14T18:58:08Z | Keno K. Bressem and Jens-Michalis Papaioannou and Paul Grundmann
contributed equally | Expert Systems with Applications 2024;237(21):121598 | 10.1016/j.eswa.2023.121598 | MEDBERT.de: A Comprehensive German BERT Model for the Medical Domain | ['K. Bressem', 'Jens-Michalis Papaioannou', 'Paul Grundmann', 'Florian Borchert', 'L. Adams', 'Leonhard Liu', 'Felix Busch', 'Lina Xu', 'J. P. Loyen', 'S. Niehues', 'Moritz Augustin', 'Lennart Grosser', 'M. Makowski', 'H. Aerts', 'A. Loser'] | 2,023 | Expert systems with applications | 34 | 29 | ['Computer Science'] |
2,303.0832 | VideoFusion: Decomposed Diffusion Models for High-Quality Video
Generation | ['Zhengxiong Luo', 'Dayou Chen', 'Yingya Zhang', 'Yan Huang', 'Liang Wang', 'Yujun Shen', 'Deli Zhao', 'Jingren Zhou', 'Tieniu Tan'] | ['cs.CV'] | A diffusion probabilistic model (DPM), which constructs a forward diffusion
process by gradually adding noise to data points and learns the reverse
denoising process to generate new samples, has been shown to handle complex
data distribution. Despite its recent success in image synthesis, applying DPMs
to video generat... | 2023-03-15T02:16:39Z | Accepted to CVPR2023 | null | null | null | null | null | null | null | null | null |
2,303.08682 | RSFNet: A White-Box Image Retouching Approach using Region-Specific
Color Filters | ['Wenqi Ouyang', 'Yi Dong', 'Xiaoyang Kang', 'Peiran Ren', 'Xin Xu', 'Xuansong Xie'] | ['cs.CV'] | Retouching images is an essential aspect of enhancing the visual appeal of
photos. Although users often share common aesthetic preferences, their
retouching methods may vary based on their individual preferences. Therefore,
there is a need for white-box approaches that produce satisfying results and
enable users to con... | 2023-03-15T15:11:31Z | Accepted by ICCV 2023 | null | null | null | null | null | null | null | null | null |
2,303.08774 | GPT-4 Technical Report | ['OpenAI', 'Josh Achiam', 'Steven Adler', 'Sandhini Agarwal', 'Lama Ahmad', 'Ilge Akkaya', 'Florencia Leoni Aleman', 'Diogo Almeida', 'Janko Altenschmidt', 'Sam Altman', 'Shyamal Anadkat', 'Red Avila', 'Igor Babuschkin', 'Suchir Balaji', 'Valerie Balcom', 'Paul Baltescu', 'Haiming Bao', 'Mohammad Bavarian', 'Jeff Belgu... | ['cs.CL', 'cs.AI'] | We report the development of GPT-4, a large-scale, multimodal model which can
accept image and text inputs and produce text outputs. While less capable than
humans in many real-world scenarios, GPT-4 exhibits human-level performance on
various professional and academic benchmarks, including passing a simulated bar
exam... | 2023-03-15T17:15:04Z | 100 pages; updated authors list; fixed author names and added
citation | null | null | null | null | null | null | null | null | null |
2,303.0881 | BiFormer: Vision Transformer with Bi-Level Routing Attention | ['Lei Zhu', 'Xinjiang Wang', 'Zhanghan Ke', 'Wayne Zhang', 'Rynson Lau'] | ['cs.CV'] | As the core building block of vision transformers, attention is a powerful
tool to capture long-range dependency. However, such power comes at a cost: it
incurs a huge computation burden and heavy memory footprint as pairwise token
interaction across all spatial locations is computed. A series of works attempt
to allev... | 2023-03-15T17:58:46Z | CVPR 2023 camera-ready | null | null | null | null | null | null | null | null | null |
2,303.08896 | SelfCheckGPT: Zero-Resource Black-Box Hallucination Detection for
Generative Large Language Models | ['Potsawee Manakul', 'Adian Liusie', 'Mark J. F. Gales'] | ['cs.CL'] | Generative Large Language Models (LLMs) such as GPT-3 are capable of
generating highly fluent responses to a wide variety of user prompts. However,
LLMs are known to hallucinate facts and make non-factual statements which can
undermine trust in their output. Existing fact-checking approaches either
require access to th... | 2023-03-15T19:31:21Z | EMNLP 2023 (main conference) | null | null | null | null | null | null | null | null | null |
2,303.09014 | ART: Automatic multi-step reasoning and tool-use for large language
models | ['Bhargavi Paranjape', 'Scott Lundberg', 'Sameer Singh', 'Hannaneh Hajishirzi', 'Luke Zettlemoyer', 'Marco Tulio Ribeiro'] | ['cs.CL'] | Large language models (LLMs) can perform complex reasoning in few- and
zero-shot settings by generating intermediate chain of thought (CoT) reasoning
steps. Further, each reasoning step can rely on external tools to support
computation beyond the core LLM capabilities (e.g. search/running code). Prior
work on CoT promp... | 2023-03-16T01:04:45Z | null | null | null | null | null | null | null | null | null | null |
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