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2,304.07327
OpenAssistant Conversations -- Democratizing Large Language Model Alignment
['Andreas Köpf', 'Yannic Kilcher', 'Dimitri von Rütte', 'Sotiris Anagnostidis', 'Zhi-Rui Tam', 'Keith Stevens', 'Abdullah Barhoum', 'Nguyen Minh Duc', 'Oliver Stanley', 'Richárd Nagyfi', 'Shahul ES', 'Sameer Suri', 'David Glushkov', 'Arnav Dantuluri', 'Andrew Maguire', 'Christoph Schuhmann', 'Huu Nguyen', 'Alexander Ma...
['cs.CL', 'cs.AI', 'I.2']
Aligning large language models (LLMs) with human preferences has proven to drastically improve usability and has driven rapid adoption as demonstrated by ChatGPT. Alignment techniques such as supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) greatly reduce the required skill and domain ...
2023-04-14T18:01:29Z
Published in NeurIPS 2023 Datasets and Benchmarks
null
null
OpenAssistant Conversations - Democratizing Large Language Model Alignment
['Andreas Kopf', 'Yannic Kilcher', 'Dimitri von Rutte', 'Sotiris Anagnostidis', 'Zhi Rui Tam', 'K. Stevens', 'Abdullah Barhoum', 'Nguyen Minh Duc', 'Oliver Stanley', "Rich'ard Nagyfi", 'ES Shahul', 'Sameer Suri', 'David Glushkov', 'A. Dantuluri', 'Andrew Maguire', 'Christoph Schuhmann', 'Huu Nguyen', 'A. Mattick']
2,023
Neural Information Processing Systems
641
54
['Computer Science']
2,304.07666
ArguGPT: evaluating, understanding and identifying argumentative essays generated by GPT models
['Yikang Liu', 'Ziyin Zhang', 'Wanyang Zhang', 'Shisen Yue', 'Xiaojing Zhao', 'Xinyuan Cheng', 'Yiwen Zhang', 'Hai Hu']
['cs.CL']
AI generated content (AIGC) presents considerable challenge to educators around the world. Instructors need to be able to detect such text generated by large language models, either with the naked eye or with the help of some tools. There is also growing need to understand the lexical, syntactic and stylistic features ...
2023-04-16T01:50:26Z
null
null
null
null
null
null
null
null
null
null
2,304.07805
EasyNER: A Customizable Easy-to-Use Pipeline for Deep Learning- and Dictionary-based Named Entity Recognition from Medical Text
['Rafsan Ahmed', 'Petter Berntsson', 'Alexander Skafte', 'Salma Kazemi Rashed', 'Marcus Klang', 'Adam Barvesten', 'Ola Olde', 'William Lindholm', 'Antton Lamarca Arrizabalaga', 'Pierre Nugues', 'Sonja Aits']
['q-bio.QM', 'cs.CL', '92-04, 92-08, 68T50', 'J.3; I.2.7; H.3.3']
Background Medical research generates millions of publications and it is a great challenge for researchers to utilize this information in full since its scale and complexity greatly surpasses human reading capabilities. Automated text mining can help extract and connect information spread across this large body of lite...
2023-04-16T15:17:56Z
null
null
null
null
null
null
null
null
null
null
2,304.07854
Towards Better Instruction Following Language Models for Chinese: Investigating the Impact of Training Data and Evaluation
['Yunjie Ji', 'Yan Gong', 'Yong Deng', 'Yiping Peng', 'Qiang Niu', 'Baochang Ma', 'Xiangang Li']
['cs.CL']
Recently, significant public efforts have been directed towards developing low-cost models with capabilities akin to ChatGPT, thereby fostering the growth of open-source conversational models. However, there remains a scarcity of comprehensive and in-depth evaluations of these models' performance. In this study, we exa...
2023-04-16T18:37:39Z
null
null
null
Towards Better Instruction Following Language Models for Chinese: Investigating the Impact of Training Data and Evaluation
['Yunjie Ji', 'Yan Gong', 'Yong Deng', 'Yiping Peng', 'Qiang Niu', 'Baochang Ma', 'Xiangang Li']
2,023
arXiv.org
25
57
['Computer Science']
2,304.0788
Sabiá: Portuguese Large Language Models
['Ramon Pires', 'Hugo Abonizio', 'Thales Sales Almeida', 'Rodrigo Nogueira']
['cs.CL', 'cs.AI']
As the capabilities of language models continue to advance, it is conceivable that "one-size-fits-all" model will remain as the main paradigm. For instance, given the vast number of languages worldwide, many of which are low-resource, the prevalent practice is to pretrain a single model on multiple languages. In this p...
2023-04-16T20:11:19Z
null
null
10.1007/978-3-031-45392-2_15
null
null
null
null
null
null
null
2,304.08069
DETRs Beat YOLOs on Real-time Object Detection
['Yian Zhao', 'Wenyu Lv', 'Shangliang Xu', 'Jinman Wei', 'Guanzhong Wang', 'Qingqing Dang', 'Yi Liu', 'Jie Chen']
['cs.CV']
The YOLO series has become the most popular framework for real-time object detection due to its reasonable trade-off between speed and accuracy. However, we observe that the speed and accuracy of YOLOs are negatively affected by the NMS. Recently, end-to-end Transformer-based detectors (DETRs) have provided an alternat...
2023-04-17T08:30:02Z
null
null
null
DETRs Beat YOLOs on Real-time Object Detection
['Wenyu Lv', 'Shangliang Xu', 'Yian Zhao', 'Guanzhong Wang', 'Jinman Wei', 'Cheng Cui', 'Yuning Du', 'Qingqing Dang', 'Yi Liu']
2,023
Computer Vision and Pattern Recognition
1,027
61
['Computer Science']
2,304.08085
InstructUIE: Multi-task Instruction Tuning for Unified Information Extraction
['Xiao Wang', 'Weikang Zhou', 'Can Zu', 'Han Xia', 'Tianze Chen', 'Yuansen Zhang', 'Rui Zheng', 'Junjie Ye', 'Qi Zhang', 'Tao Gui', 'Jihua Kang', 'Jingsheng Yang', 'Siyuan Li', 'Chunsai Du']
['cs.CL', 'cs.AI']
Large language models have unlocked strong multi-task capabilities from reading instructive prompts. However, recent studies have shown that existing large models still have difficulty with information extraction tasks. For example, gpt-3.5-turbo achieved an F1 score of 18.22 on the Ontonotes dataset, which is signific...
2023-04-17T09:00:50Z
null
null
null
null
null
null
null
null
null
null
2,304.08177
Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca
['Yiming Cui', 'Ziqing Yang', 'Xin Yao']
['cs.CL', 'cs.HC', 'cs.LG']
Large Language Models (LLMs), such as ChatGPT and GPT-4, have dramatically transformed natural language processing research and shown promising strides towards Artificial General Intelligence (AGI). Nonetheless, the high costs associated with training and deploying LLMs present substantial obstacles to transparent, acc...
2023-04-17T11:39:53Z
21 pages
null
null
Efficient and Effective Text Encoding for Chinese LLaMA and Alpaca
['Yiming Cui', 'Ziqing Yang', 'Xin Yao']
2,023
arXiv.org
318
34
['Computer Science']
2,304.0846
LongForm: Effective Instruction Tuning with Reverse Instructions
['Abdullatif Köksal', 'Timo Schick', 'Anna Korhonen', 'Hinrich Schütze']
['cs.CL', 'cs.AI', 'cs.LG']
Instruction tuning enables language models to more effectively generalize and better follow user intent. However, obtaining instruction data is costly and challenging. Prior work employs methods such as expensive human annotation, crowd-sourced datasets with alignment issues, and generating noisy examples via LLMs. We ...
2023-04-17T17:36:35Z
EMNLP 2024 Findings. This version extends the training with recent LLMs, evaluation with new metrics, and NLU tasks
null
null
LongForm: Effective Instruction Tuning with Reverse Instructions
['Abdullatif Köksal', 'Timo Schick', 'A. Korhonen', 'Hinrich Schütze']
2,023
Conference on Empirical Methods in Natural Language Processing
40
85
['Computer Science']
2,304.08485
Visual Instruction Tuning
['Haotian Liu', 'Chunyuan Li', 'Qingyang Wu', 'Yong Jae Lee']
['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG']
Instruction tuning large language models (LLMs) using machine-generated instruction-following data has improved zero-shot capabilities on new tasks, but the idea is less explored in the multimodal field. In this paper, we present the first attempt to use language-only GPT-4 to generate multimodal language-image instruc...
2023-04-17T17:59:25Z
NeurIPS 2023 Oral; project page: https://llava-vl.github.io/
null
null
Visual Instruction Tuning
['Haotian Liu', 'Chunyuan Li', 'Qingyang Wu', 'Yong Jae Lee']
2,023
Neural Information Processing Systems
4,950
63
['Computer Science']
2,304.08818
Align your Latents: High-Resolution Video Synthesis with Latent Diffusion Models
['Andreas Blattmann', 'Robin Rombach', 'Huan Ling', 'Tim Dockhorn', 'Seung Wook Kim', 'Sanja Fidler', 'Karsten Kreis']
['cs.CV', 'cs.LG']
Latent Diffusion Models (LDMs) enable high-quality image synthesis while avoiding excessive compute demands by training a diffusion model in a compressed lower-dimensional latent space. Here, we apply the LDM paradigm to high-resolution video generation, a particularly resource-intensive task. We first pre-train an LDM...
2023-04-18T08:30:32Z
Conference on Computer Vision and Pattern Recognition (CVPR) 2023. Project page: https://research.nvidia.com/labs/toronto-ai/VideoLDM/
null
null
Align Your Latents: High-Resolution Video Synthesis with Latent Diffusion Models
['A. Blattmann', 'Robin Rombach', 'Huan Ling', 'Tim Dockhorn', 'Seung Wook Kim', 'S. Fidler', 'Karsten Kreis']
2,023
Computer Vision and Pattern Recognition
1,108
121
['Computer Science']
2,304.0887
UPGPT: Universal Diffusion Model for Person Image Generation, Editing and Pose Transfer
['Soon Yau Cheong', 'Armin Mustafa', 'Andrew Gilbert']
['cs.CV', 'cs.AI']
Text-to-image models (T2I) such as StableDiffusion have been used to generate high quality images of people. However, due to the random nature of the generation process, the person has a different appearance e.g. pose, face, and clothing, despite using the same text prompt. The appearance inconsistency makes T2I unsuit...
2023-04-18T10:05:37Z
null
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops 2023
null
null
null
null
null
null
null
null
2,304.09121
Fast Neural Scene Flow
['Xueqian Li', 'Jianqiao Zheng', 'Francesco Ferroni', 'Jhony Kaesemodel Pontes', 'Simon Lucey']
['cs.CV']
Neural Scene Flow Prior (NSFP) is of significant interest to the vision community due to its inherent robustness to out-of-distribution (OOD) effects and its ability to deal with dense lidar points. The approach utilizes a coordinate neural network to estimate scene flow at runtime, without any training. However, it is...
2023-04-18T16:37:18Z
17 pages, 11 figures, 6 tables
null
null
Fast Neural Scene Flow
['Xueqian Li', 'Jianqiao Zheng', 'Francesco Ferroni', 'J. K. Pontes', 'S. Lucey']
2,023
IEEE International Conference on Computer Vision
27
87
['Computer Science']
2,304.09542
Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agents
['Weiwei Sun', 'Lingyong Yan', 'Xinyu Ma', 'Shuaiqiang Wang', 'Pengjie Ren', 'Zhumin Chen', 'Dawei Yin', 'Zhaochun Ren']
['cs.CL', 'cs.IR']
Large Language Models (LLMs) have demonstrated remarkable zero-shot generalization across various language-related tasks, including search engines. However, existing work utilizes the generative ability of LLMs for Information Retrieval (IR) rather than direct passage ranking. The discrepancy between the pre-training o...
2023-04-19T10:16:03Z
EMNLP 2023
null
null
Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agent
['Weiwei Sun', 'Lingyong Yan', 'Xinyu Ma', 'Pengjie Ren', 'Dawei Yin', 'Z. Ren']
2,023
Conference on Empirical Methods in Natural Language Processing
315
46
['Computer Science']
2,304.09871
A Theory on Adam Instability in Large-Scale Machine Learning
['Igor Molybog', 'Peter Albert', 'Moya Chen', 'Zachary DeVito', 'David Esiobu', 'Naman Goyal', 'Punit Singh Koura', 'Sharan Narang', 'Andrew Poulton', 'Ruan Silva', 'Binh Tang', 'Diana Liskovich', 'Puxin Xu', 'Yuchen Zhang', 'Melanie Kambadur', 'Stephen Roller', 'Susan Zhang']
['cs.LG', 'cs.AI', 'math.OC']
We present a theory for the previously unexplained divergent behavior noticed in the training of large language models. We argue that the phenomenon is an artifact of the dominant optimization algorithm used for training, called Adam. We observe that Adam can enter a state in which the parameter update vector has a rel...
2023-04-19T06:15:11Z
null
null
null
A Theory on Adam Instability in Large-Scale Machine Learning
['Igor Molybog', 'Peter Albert', 'Moya Chen', 'Zachary DeVito', 'David Esiobu', 'Naman Goyal', 'Punit Singh Koura', 'Sharan Narang', 'Andrew Poulton', 'Ruan Silva', 'Binh Tang', 'Diana Liskovich', 'Puxin Xu', 'Yuchen Zhang', 'M. Kambadur', 'Stephen Roller', 'Susan Zhang']
2,023
arXiv.org
35
30
['Computer Science', 'Mathematics']
2,304.10447
Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Health
['Shaoxiong Ji', 'Tianlin Zhang', 'Kailai Yang', 'Sophia Ananiadou', 'Erik Cambria', 'Jörg Tiedemann']
['cs.CL']
Pretrained language models have been used in various natural language processing applications. In the mental health domain, domain-specific language models are pretrained and released, which facilitates the early detection of mental health conditions. Social posts, e.g., on Reddit, are usually long documents. However, ...
2023-04-20T16:43:56Z
null
null
null
Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Health
['Shaoxiong Ji', 'Tianlin Zhang', 'Kailai Yang', 'S. Ananiadou', 'E. Cambria', 'J. Tiedemann']
2,023
arXiv.org
29
35
['Computer Science']
2,304.10567
Optical Emission Model for Binary Black Hole Merger Remnants Travelling through Discs of Active Galactic Nuclei
['J. C. Rodríguez-Ramírez', 'C. R. Bom', 'B. Fraga', 'R. Nemmen']
['astro-ph.HE', 'astro-ph.GA']
Active galactic nuclei (AGNs) have been proposed as plausible sites for hosting a sizable fraction of the binary black hole (BBH) mergers measured through gravitational waves (GWs) by the LIGO-Virgo-Kagra (LVK) experiment. These GWs could be accompanied by radiation feedback due to the interaction of the BBH merger rem...
2023-04-20T18:00:08Z
15 pages, 9 figures. Accepted for publication in Monthly Notices of the Royal Astronomical Society
null
10.1093/mnras/stad3575
null
null
null
null
null
null
null
2,304.10592
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
['Deyao Zhu', 'Jun Chen', 'Xiaoqian Shen', 'Xiang Li', 'Mohamed Elhoseiny']
['cs.CV']
The recent GPT-4 has demonstrated extraordinary multi-modal abilities, such as directly generating websites from handwritten text and identifying humorous elements within images. These features are rarely observed in previous vision-language models. However, the technical details behind GPT-4 continue to remain undiscl...
2023-04-20T18:25:35Z
Project Website: https://minigpt-4.github.io/; Code, Pretrained Model, and Dataset: https://github.com/Vision-CAIR/MiniGPT-4; Deyao Zhu and Jun Chen contributed equally to this work
null
null
MiniGPT-4: Enhancing Vision-Language Understanding with Advanced Large Language Models
['Deyao Zhu', 'Jun Chen', 'Xiaoqian Shen', 'Xiang Li', 'Mohamed Elhoseiny']
2,023
International Conference on Learning Representations
2,080
62
['Computer Science']
2,304.10765
BPJDet: Extended Object Representation for Generic Body-Part Joint Detection
['Huayi Zhou', 'Fei Jiang', 'Jiaxin Si', 'Yue Ding', 'Hongtao Lu']
['cs.CV']
Detection of human body and its parts has been intensively studied. However, most of CNNs-based detectors are trained independently, making it difficult to associate detected parts with body. In this paper, we focus on the joint detection of human body and its parts. Specifically, we propose a novel extended object rep...
2023-04-21T06:23:08Z
extended journal version of arXiv:2212.07652. Accepted by TPAMI2024
null
null
null
null
null
null
null
null
null
2,304.11029
CLaMP: Contrastive Language-Music Pre-training for Cross-Modal Symbolic Music Information Retrieval
['Shangda Wu', 'Dingyao Yu', 'Xu Tan', 'Maosong Sun']
['cs.SD', 'cs.IR', 'eess.AS']
We introduce CLaMP: Contrastive Language-Music Pre-training, which learns cross-modal representations between natural language and symbolic music using a music encoder and a text encoder trained jointly with a contrastive loss. To pre-train CLaMP, we collected a large dataset of 1.4 million music-text pairs. It employe...
2023-04-21T15:23:00Z
11 pages, 5 figures, 5 tables, accepted by ISMIR 2023
null
null
CLaMP: Contrastive Language-Music Pre-training for Cross-Modal Symbolic Music Information Retrieval
['Shangda Wu', 'Dingyao Yu', 'Xu Tan', 'Maosong Sun']
2,023
International Society for Music Information Retrieval Conference
15
43
['Computer Science', 'Engineering']
2,304.11077
HeRo: RoBERTa and Longformer Hebrew Language Models
['Vitaly Shalumov', 'Harel Haskey']
['cs.CL', 'cs.AI']
In this paper, we fill in an existing gap in resources available to the Hebrew NLP community by providing it with the largest so far pre-train dataset HeDC4, a state-of-the-art pre-trained language model HeRo for standard length inputs and an efficient transformer LongHeRo for long input sequences. The HeRo model was e...
2023-04-18T05:56:32Z
null
null
null
null
null
null
null
null
null
null
2,304.11158
Emergent and Predictable Memorization in Large Language Models
['Stella Biderman', 'USVSN Sai Prashanth', 'Lintang Sutawika', 'Hailey Schoelkopf', 'Quentin Anthony', 'Shivanshu Purohit', 'Edward Raff']
['cs.CL']
Memorization, or the tendency of large language models (LLMs) to output entire sequences from their training data verbatim, is a key concern for safely deploying language models. In particular, it is vital to minimize a model's memorization of sensitive datapoints such as those containing personal identifiable informat...
2023-04-21T17:58:31Z
null
null
null
Emergent and Predictable Memorization in Large Language Models
['Stella Biderman', 'USVSN Sai Prashanth', 'Lintang Sutawika', 'Hailey Schoelkopf', 'Quentin G. Anthony', 'Shivanshu Purohit', 'Edward Raf']
2,023
Neural Information Processing Systems
125
63
['Computer Science']
2,304.11277
PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel
['Yanli Zhao', 'Andrew Gu', 'Rohan Varma', 'Liang Luo', 'Chien-Chin Huang', 'Min Xu', 'Less Wright', 'Hamid Shojanazeri', 'Myle Ott', 'Sam Shleifer', 'Alban Desmaison', 'Can Balioglu', 'Pritam Damania', 'Bernard Nguyen', 'Geeta Chauhan', 'Yuchen Hao', 'Ajit Mathews', 'Shen Li']
['cs.DC', 'cs.AI', 'cs.LG', 'cs.PF']
It is widely acknowledged that large models have the potential to deliver superior performance across a broad range of domains. Despite the remarkable progress made in the field of machine learning systems research, which has enabled the development and exploration of large models, such abilities remain confined to a s...
2023-04-21T23:52:27Z
null
null
null
PyTorch FSDP: Experiences on Scaling Fully Sharded Data Parallel
['Yanli Zhao', 'A. Gu', 'R. Varma', 'Liangchen Luo', 'Chien-chin Huang', 'Min Xu', 'Less Wright', 'Hamid Shojanazeri', 'Myle Ott', 'Sam Shleifer', 'Alban Desmaison', 'Can Balioglu', 'Bernard Nguyen', 'Geeta Chauhan', 'Y. Hao', 'Shen Li']
2,023
Proceedings of the VLDB Endowment
352
36
['Computer Science']
2,304.1134
Semantic Specialization for Knowledge-based Word Sense Disambiguation
['Sakae Mizuki', 'Naoaki Okazaki']
['cs.CL']
A promising approach for knowledge-based Word Sense Disambiguation (WSD) is to select the sense whose contextualized embeddings computed for its definition sentence are closest to those computed for a target word in a given sentence. This approach relies on the similarity of the \textit{sense} and \textit{context} embe...
2023-04-22T07:40:23Z
Accepted by EACL 2023. 14 pages
null
null
null
null
null
null
null
null
null
2,304.1137
SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval
['Haitao Li', 'Qingyao Ai', 'Jia Chen', 'Qian Dong', 'Yueyue Wu', 'Yiqun Liu', 'Chong Chen', 'Qi Tian']
['cs.IR', 'cs.CL']
Legal case retrieval, which aims to find relevant cases for a query case, plays a core role in the intelligent legal system. Despite the success that pre-training has achieved in ad-hoc retrieval tasks, effective pre-training strategies for legal case retrieval remain to be explored. Compared with general documents, le...
2023-04-22T10:47:01Z
10 pages, accepted by SIGIR 2023
null
null
SAILER: Structure-aware Pre-trained Language Model for Legal Case Retrieval
['Haitao Li', 'Qingyao Ai', 'Jia Chen', 'Qian Dong', 'Yueyue Wu', 'Y. Liu', 'C. Chen', 'Qi Tian']
2,023
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
79
45
['Computer Science']
2,304.11389
Transformer-Based Language Model Surprisal Predicts Human Reading Times Best with About Two Billion Training Tokens
['Byung-Doh Oh', 'William Schuler']
['cs.CL']
Recent psycholinguistic studies have drawn conflicting conclusions about the relationship between the quality of a language model and the ability of its surprisal estimates to predict human reading times, which has been speculated to be due to the large gap in both the amount of training data and model capacity across ...
2023-04-22T12:50:49Z
Findings of the Association for Computational Linguistics: EMNLP 2023
null
null
Transformer-Based Language Model Surprisal Predicts Human Reading Times Best with About Two Billion Training Tokens
['Byung-Doh Oh', 'William Schuler']
2,023
Conference on Empirical Methods in Natural Language Processing
31
31
['Computer Science']
2,304.11434
L3Cube-IndicSBERT: A simple approach for learning cross-lingual sentence representations using multilingual BERT
['Samruddhi Deode', 'Janhavi Gadre', 'Aditi Kajale', 'Ananya Joshi', 'Raviraj Joshi']
['cs.CL', 'cs.LG']
The multilingual Sentence-BERT (SBERT) models map different languages to common representation space and are useful for cross-language similarity and mining tasks. We propose a simple yet effective approach to convert vanilla multilingual BERT models into multilingual sentence BERT models using synthetic corpus. We sim...
2023-04-22T15:45:40Z
null
null
null
L3Cube-IndicSBERT: A simple approach for learning cross-lingual sentence representations using multilingual BERT
['Samruddhi Deode', 'Janhavi Gadre', 'Aditi Kajale', 'Ananya Joshi', 'Raviraj Joshi']
2,023
Pacific Asia Conference on Language, Information and Computation
22
43
['Computer Science']
2,304.12244
WizardLM: Empowering large pre-trained language models to follow complex instructions
['Can Xu', 'Qingfeng Sun', 'Kai Zheng', 'Xiubo Geng', 'Pu Zhao', 'Jiazhan Feng', 'Chongyang Tao', 'Qingwei Lin', 'Daxin Jiang']
['cs.CL', 'cs.AI']
Training large language models (LLMs) with open-domain instruction following data brings colossal success. However, manually creating such instruction data is very time-consuming and labor-intensive. Moreover, humans may struggle to produce high-complexity instructions. In this paper, we show an avenue for creating lar...
2023-04-24T16:31:06Z
large language model, instruction fine-tune
The Twelfth International Conference on Learning Representations (ICLR 2024)
null
WizardLM: Empowering Large Pre-Trained Language Models to Follow Complex Instructions
['Can Xu', 'Qingfeng Sun', 'Kai Zheng', 'Xiubo Geng', 'Pu Zhao', 'Jiazhan Feng', 'Chongyang Tao', 'Daxin Jiang']
2,023
International Conference on Learning Representations
1,112
53
['Computer Science']
2,304.12294
Explicit Correspondence Matching for Generalizable Neural Radiance Fields
['Yuedong Chen', 'Haofei Xu', 'Qianyi Wu', 'Chuanxia Zheng', 'Tat-Jen Cham', 'Jianfei Cai']
['cs.CV']
We present a new generalizable NeRF method that is able to directly generalize to new unseen scenarios and perform novel view synthesis with as few as two source views. The key to our approach lies in the explicitly modeled correspondence matching information, so as to provide the geometry prior to the prediction of Ne...
2023-04-24T17:46:01Z
Code and pre-trained models: https://github.com/donydchen/matchnerf Project Page: https://donydchen.github.io/matchnerf/
null
null
null
null
null
null
null
null
null
2,304.12306
Segment Anything in Medical Images
['Jun Ma', 'Yuting He', 'Feifei Li', 'Lin Han', 'Chenyu You', 'Bo Wang']
['eess.IV', 'cs.CV']
Medical image segmentation is a critical component in clinical practice, facilitating accurate diagnosis, treatment planning, and disease monitoring. However, existing methods, often tailored to specific modalities or disease types, lack generalizability across the diverse spectrum of medical image segmentation tasks. ...
2023-04-24T17:56:12Z
null
Nature Communications 15, 654 (2024)
10.1038/s41467-024-44824-z
Segment anything in medical images
['Jun Ma', 'Yuting He', 'Feifei Li', 'Li-Jun Han', 'Chenyu You', 'Bo Wang']
2,023
Nature Communications
532
139
['Engineering', 'Computer Science', 'Medicine']
2,304.1262
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
['Junde Wu', 'Wei Ji', 'Yuanpei Liu', 'Huazhu Fu', 'Min Xu', 'Yanwu Xu', 'Yueming Jin']
['cs.CV']
The Segment Anything Model (SAM) has recently gained popularity in the field of image segmentation due to its impressive capabilities in various segmentation tasks and its prompt-based interface. However, recent studies and individual experiments have shown that SAM underperforms in medical image segmentation, since th...
2023-04-25T07:34:22Z
Code released at: https://github.com/KidsWithTokens/Medical-SAM-Adapter
null
null
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
['Junde Wu', 'Rao Fu', 'Huihui Fang', 'Yuanpei Liu', 'Zhao-Yang Wang', 'Yanwu Xu', 'Yueming Jin', 'T. Arbel']
2,023
Medical Image Analysis
509
77
['Computer Science', 'Medicine']
2,304.12891
Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification
['Jussi Leinonen', 'Ulrich Hamann', 'Daniele Nerini', 'Urs Germann', 'Gabriele Franch']
['physics.ao-ph', 'cs.LG', 'eess.IV', 'I.2.10; J.2']
Diffusion models have been widely adopted in image generation, producing higher-quality and more diverse samples than generative adversarial networks (GANs). We introduce a latent diffusion model (LDM) for precipitation nowcasting - short-term forecasting based on the latest observational data. The LDM is more stable a...
2023-04-25T15:03:15Z
18 pages, 6 figures. Submitted for publication
null
null
Latent diffusion models for generative precipitation nowcasting with accurate uncertainty quantification
['J. Leinonen', 'U. Hamann', 'D. Nerini', 'U. Germann', 'Gabriele Franch']
2,023
arXiv.org
56
53
['Physics', 'Computer Science', 'Engineering']
2,304.13013
Stable and low-precision training for large-scale vision-language models
['Mitchell Wortsman', 'Tim Dettmers', 'Luke Zettlemoyer', 'Ari Morcos', 'Ali Farhadi', 'Ludwig Schmidt']
['cs.LG', 'cs.CV']
We introduce new methods for 1) accelerating and 2) stabilizing training for large language-vision models. 1) For acceleration, we introduce SwitchBack, a linear layer for int8 quantized training which provides a speed-up of 13-25% while matching the performance of bfloat16 training within 0.1 percentage points for the...
2023-04-25T17:38:18Z
NeurIPS 2023
null
null
Stable and low-precision training for large-scale vision-language models
['Mitchell Wortsman', 'Tim Dettmers', 'Luke Zettlemoyer', 'Ari S. Morcos', 'Ali Farhadi', 'Ludwig Schmidt']
2,023
Neural Information Processing Systems
44
81
['Computer Science']
2,304.13705
Learning Fine-Grained Bimanual Manipulation with Low-Cost Hardware
['Tony Z. Zhao', 'Vikash Kumar', 'Sergey Levine', 'Chelsea Finn']
['cs.RO', 'cs.LG']
Fine manipulation tasks, such as threading cable ties or slotting a battery, are notoriously difficult for robots because they require precision, careful coordination of contact forces, and closed-loop visual feedback. Performing these tasks typically requires high-end robots, accurate sensors, or careful calibration, ...
2023-04-23T19:10:53Z
null
null
null
null
null
null
null
null
null
null
2,304.13734
The Internal State of an LLM Knows When It's Lying
['Amos Azaria', 'Tom Mitchell']
['cs.CL', 'cs.AI', 'cs.LG']
While Large Language Models (LLMs) have shown exceptional performance in various tasks, one of their most prominent drawbacks is generating inaccurate or false information with a confident tone. In this paper, we provide evidence that the LLM's internal state can be used to reveal the truthfulness of statements. This i...
2023-04-26T02:49:38Z
null
null
null
null
null
null
null
null
null
null
2,304.13994
SweCTRL-Mini: a data-transparent Transformer-based large language model for controllable text generation in Swedish
['Dmytro Kalpakchi', 'Johan Boye']
['cs.CL']
We present SweCTRL-Mini, a large Swedish language model that can be used for inference and fine-tuning on a single consumer-grade GPU. The model is based on the CTRL architecture by Keskar, McCann, Varshney, Xiong, and Socher (2019), which means that users of the SweCTRL-Mini model can control the genre of the generate...
2023-04-27T07:32:37Z
Added information about training tokenizer
null
null
null
null
null
null
null
null
null
2,304.14108
DataComp: In search of the next generation of multimodal datasets
['Samir Yitzhak Gadre', 'Gabriel Ilharco', 'Alex Fang', 'Jonathan Hayase', 'Georgios Smyrnis', 'Thao Nguyen', 'Ryan Marten', 'Mitchell Wortsman', 'Dhruba Ghosh', 'Jieyu Zhang', 'Eyal Orgad', 'Rahim Entezari', 'Giannis Daras', 'Sarah Pratt', 'Vivek Ramanujan', 'Yonatan Bitton', 'Kalyani Marathe', 'Stephen Mussmann', 'Ri...
['cs.CV', 'cs.CL', 'cs.LG']
Multimodal datasets are a critical component in recent breakthroughs such as Stable Diffusion and GPT-4, yet their design does not receive the same research attention as model architectures or training algorithms. To address this shortcoming in the ML ecosystem, we introduce DataComp, a testbed for dataset experiments ...
2023-04-27T11:37:18Z
NeurIPS 2023 Datasets and Benchmarks Track
null
null
DataComp: In search of the next generation of multimodal datasets
['S. Gadre', 'Gabriel Ilharco', 'Alex Fang', 'J. Hayase', 'G. Smyrnis', 'Thao Nguyen', 'Ryan Marten', 'Mitchell Wortsman', 'Dhruba Ghosh', 'Jieyu Zhang', 'E. Orgad', 'R. Entezari', 'Giannis Daras', 'Sarah Pratt', 'Vivek Ramanujan', 'Yonatan Bitton', 'K. Marathe', 'Stephen Mussmann', 'R. Vencu', 'Mehdi Cherti', 'Ranjay ...
2,023
Neural Information Processing Systems
452
183
['Computer Science']
2,304.14178
mPLUG-Owl: Modularization Empowers Large Language Models with Multimodality
['Qinghao Ye', 'Haiyang Xu', 'Guohai Xu', 'Jiabo Ye', 'Ming Yan', 'Yiyang Zhou', 'Junyang Wang', 'Anwen Hu', 'Pengcheng Shi', 'Yaya Shi', 'Chenliang Li', 'Yuanhong Xu', 'Hehong Chen', 'Junfeng Tian', 'Qi Qian', 'Ji Zhang', 'Fei Huang', 'Jingren Zhou']
['cs.CL', 'cs.CV', 'cs.LG']
Large language models (LLMs) have demonstrated impressive zero-shot abilities on a variety of open-ended tasks, while recent research has also explored the use of LLMs for multi-modal generation. In this study, we introduce mPLUG-Owl, a novel training paradigm that equips LLMs with multi-modal abilities through modular...
2023-04-27T13:27:01Z
Working in Process
null
null
null
null
null
null
null
null
null
2,304.14402
LaMini-LM: A Diverse Herd of Distilled Models from Large-Scale Instructions
['Minghao Wu', 'Abdul Waheed', 'Chiyu Zhang', 'Muhammad Abdul-Mageed', 'Alham Fikri Aji']
['cs.CL']
Large language models (LLMs) with instruction fine-tuning demonstrate superior generative capabilities. However, these models are resource-intensive. To alleviate this issue, we explore distilling knowledge from instruction-tuned LLMs into much smaller ones. To this end, we carefully develop a large set of 2.58M instru...
2023-04-27T17:58:49Z
21 pages, 8 figures, 17 tables, accepted by EACL2024 main conference
null
null
null
null
null
null
null
null
null
2,304.1501
LLaMA-Adapter V2: Parameter-Efficient Visual Instruction Model
['Peng Gao', 'Jiaming Han', 'Renrui Zhang', 'Ziyi Lin', 'Shijie Geng', 'Aojun Zhou', 'Wei Zhang', 'Pan Lu', 'Conghui He', 'Xiangyu Yue', 'Hongsheng Li', 'Yu Qiao']
['cs.CV', 'cs.AI', 'cs.CL', 'cs.LG', 'cs.MM']
How to efficiently transform large language models (LLMs) into instruction followers is recently a popular research direction, while training LLM for multi-modal reasoning remains less explored. Although the recent LLaMA-Adapter demonstrates the potential to handle visual inputs with LLMs, it still cannot generalize we...
2023-04-28T17:59:25Z
Code and models are available at https://github.com/ZrrSkywalker/LLaMA-Adapter
null
null
null
null
null
null
null
null
null
2,305.00434
EVREAL: Towards a Comprehensive Benchmark and Analysis Suite for Event-based Video Reconstruction
['Burak Ercan', 'Onur Eker', 'Aykut Erdem', 'Erkut Erdem']
['cs.CV']
Event cameras are a new type of vision sensor that incorporates asynchronous and independent pixels, offering advantages over traditional frame-based cameras such as high dynamic range and minimal motion blur. However, their output is not easily understandable by humans, making the reconstruction of intensity images fr...
2023-04-30T09:28:38Z
19 pages, 9 figures. Has been accepted for publication at the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Vancouver, 2023. The project page can be found at https://ercanburak.github.io/evreal.html
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pages 3942-3951. 2023
10.1109/CVPRW59228.2023.00410
null
null
null
null
null
null
null
2,305.0045
SMILE: Single-turn to Multi-turn Inclusive Language Expansion via ChatGPT for Mental Health Support
['Huachuan Qiu', 'Hongliang He', 'Shuai Zhang', 'Anqi Li', 'Zhenzhong Lan']
['cs.CL', 'cs.CY']
Developing specialized dialogue systems for mental health support requires multi-turn conversation data, which has recently garnered increasing attention. However, gathering and releasing large-scale, real-life multi-turn conversations that could facilitate advancements in mental health support presents challenges in d...
2023-04-30T11:26:10Z
accepted to the EMNLP 2024 Findings
null
null
SMILE: Single-turn to Multi-turn Inclusive Language Expansion via ChatGPT for Mental Health Support
['Huachuan Qiu', 'Hongliang He', 'Shuai Zhang', 'Anqi Li', 'Zhenzhong Lan']
2,023
Conference on Empirical Methods in Natural Language Processing
29
57
['Computer Science']
2,305.00787
GeneFace++: Generalized and Stable Real-Time Audio-Driven 3D Talking Face Generation
['Zhenhui Ye', 'Jinzheng He', 'Ziyue Jiang', 'Rongjie Huang', 'Jiawei Huang', 'Jinglin Liu', 'Yi Ren', 'Xiang Yin', 'Zejun Ma', 'Zhou Zhao']
['cs.CV']
Generating talking person portraits with arbitrary speech audio is a crucial problem in the field of digital human and metaverse. A modern talking face generation method is expected to achieve the goals of generalized audio-lip synchronization, good video quality, and high system efficiency. Recently, neural radiance f...
2023-05-01T12:24:09Z
18 Pages, 7 figures
null
null
GeneFace++: Generalized and Stable Real-Time Audio-Driven 3D Talking Face Generation
['Zhenhui Ye', 'Jinzheng He', 'Ziyue Jiang', 'Rongjie Huang', 'Jia-Bin Huang', 'Jinglin Liu', 'Yixiang Ren', 'Xiang Yin', 'Zejun Ma', 'Zhou Zhao']
2,023
arXiv.org
31
51
['Computer Science']
2,305.00969
CryCeleb: A Speaker Verification Dataset Based on Infant Cry Sounds
['David Budaghyan', 'Charles C. Onu', 'Arsenii Gorin', 'Cem Subakan', 'Doina Precup']
['cs.SD', 'cs.AI', 'cs.CL', 'eess.AS']
This paper describes the Ubenwa CryCeleb dataset - a labeled collection of infant cries - and the accompanying CryCeleb 2023 task, which is a public speaker verification challenge based on cry sounds. We released more than 6 hours of manually segmented cry sounds from 786 newborns for academic use, aiming to encourage ...
2023-05-01T17:56:32Z
ICASSP 2024
null
null
CryCeleb: A Speaker Verification Dataset Based on Infant Cry Sounds
['David Budaghyan', 'Arsenii Gorin', 'Cem Subakan', 'Charles C. Onu']
2,023
IEEE International Conference on Acoustics, Speech, and Signal Processing
7
20
['Computer Science', 'Engineering']
2,305.01099
Logion: Machine Learning for Greek Philology
['Charlie Cowen-Breen', 'Creston Brooks', 'Johannes Haubold', 'Barbara Graziosi']
['cs.CL', 'cs.LG', 'I.2.7']
This paper presents machine-learning methods to address various problems in Greek philology. After training a BERT model on the largest premodern Greek dataset used for this purpose to date, we identify and correct previously undetected errors made by scribes in the process of textual transmission, in what is, to our k...
2023-05-01T21:56:25Z
14 pages, 4 figures
null
null
Logion: Machine Learning for Greek Philology
['Charlie Cowen-Breen', 'Creston Brooks', 'Johannes Haubold', 'B. Graziosi']
2,023
arXiv.org
5
28
['Computer Science']
2,305.01115
In-Context Learning Unlocked for Diffusion Models
['Zhendong Wang', 'Yifan Jiang', 'Yadong Lu', 'Yelong Shen', 'Pengcheng He', 'Weizhu Chen', 'Zhangyang Wang', 'Mingyuan Zhou']
['cs.CV']
We present Prompt Diffusion, a framework for enabling in-context learning in diffusion-based generative models. Given a pair of task-specific example images, such as depth from/to image and scribble from/to image, and a text guidance, our model automatically understands the underlying task and performs the same task on...
2023-05-01T23:03:37Z
null
null
null
In-Context Learning Unlocked for Diffusion Models
['Zhendong Wang', 'Yifan Jiang', 'Yadong Lu', 'Yelong Shen', 'Pengcheng He', 'Weizhu Chen', 'Zhangyang Wang', 'Mingyuan Zhou']
2,023
Neural Information Processing Systems
78
75
['Computer Science']
2,305.0121
Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation
['Jiawei Liu', 'Chunqiu Steven Xia', 'Yuyao Wang', 'Lingming Zhang']
['cs.SE', 'cs.CL', 'cs.LG']
Program synthesis has been long studied with recent approaches focused on directly using the power of Large Language Models (LLMs) to generate code. Programming benchmarks, with curated synthesis problems and test-cases, are used to measure the performance of various LLMs on code synthesis. However, these test-cases ca...
2023-05-02T05:46:48Z
null
null
null
Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation
['Jiawei Liu', 'Chun Xia', 'Yuyao Wang', 'Lingming Zhang']
2,023
Neural Information Processing Systems
973
92
['Computer Science']
2,305.01569
Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation
['Yuval Kirstain', 'Adam Polyak', 'Uriel Singer', 'Shahbuland Matiana', 'Joe Penna', 'Omer Levy']
['cs.CV', 'cs.AI']
The ability to collect a large dataset of human preferences from text-to-image users is usually limited to companies, making such datasets inaccessible to the public. To address this issue, we create a web app that enables text-to-image users to generate images and specify their preferences. Using this web app we build...
2023-05-02T16:18:11Z
null
null
null
Pick-a-Pic: An Open Dataset of User Preferences for Text-to-Image Generation
['Yuval Kirstain', 'Adam Polyak', 'Uriel Singer', 'Shahbuland Matiana', 'Joe Penna', 'Omer Levy']
2,023
Neural Information Processing Systems
420
20
['Computer Science']
2,305.01625
Unlimiformer: Long-Range Transformers with Unlimited Length Input
['Amanda Bertsch', 'Uri Alon', 'Graham Neubig', 'Matthew R. Gormley']
['cs.CL']
Since the proposal of transformers, these models have been limited to bounded input lengths, because of their need to attend to every token in the input. In this work, we propose Unlimiformer: a general approach that wraps any existing pretrained encoder-decoder transformer, and offloads the cross-attention computation...
2023-05-02T17:35:08Z
NeurIPS 2023
null
null
null
null
null
null
null
null
null
2,305.01628
The Benefits of Bad Advice: Autocontrastive Decoding across Model Layers
['Ariel Gera', 'Roni Friedman', 'Ofir Arviv', 'Chulaka Gunasekara', 'Benjamin Sznajder', 'Noam Slonim', 'Eyal Shnarch']
['cs.CL', 'cs.LG']
Applying language models to natural language processing tasks typically relies on the representations in the final model layer, as intermediate hidden layer representations are presumed to be less informative. In this work, we argue that due to the gradual improvement across model layers, additional information can be ...
2023-05-02T17:42:37Z
9 pages, 8 figures; To be published in ACL 2023
null
null
The Benefits of Bad Advice: Autocontrastive Decoding across Model Layers
['Ariel Gera', 'Roni Friedman', 'Ofir Arviv', 'Chulaka Gunasekara', 'B. Sznajder', 'N. Slonim', 'Eyal Shnarch']
2,023
Annual Meeting of the Association for Computational Linguistics
22
34
['Computer Science']
2,305.01979
Glitch in the Matrix: A Large Scale Benchmark for Content Driven Audio-Visual Forgery Detection and Localization
['Zhixi Cai', 'Shreya Ghosh', 'Abhinav Dhall', 'Tom Gedeon', 'Kalin Stefanov', 'Munawar Hayat']
['cs.CV']
Most deepfake detection methods focus on detecting spatial and/or spatio-temporal changes in facial attributes and are centered around the binary classification task of detecting whether a video is real or fake. This is because available benchmark datasets contain mostly visual-only modifications present in the entiret...
2023-05-03T08:48:45Z
The paper is under consideration/review at Computer Vision and Image Understanding Journal
null
null
"Glitch in the Matrix!": A Large Scale Benchmark for Content Driven Audio-Visual Forgery Detection and Localization
['Zhixi Cai', 'Shreya Ghosh', 'Tom Gedeon', 'Abhinav Dhall', 'Kalin Stefanov', 'Munawar Hayat']
2,023
Computer Vision and Image Understanding
29
112
['Computer Science']
2,305.02265
A Neural Divide-and-Conquer Reasoning Framework for Image Retrieval from Linguistically Complex Text
['Yunxin Li', 'Baotian Hu', 'Yuxin Ding', 'Lin Ma', 'Min Zhang']
['cs.CL']
Pretrained Vision-Language Models (VLMs) have achieved remarkable performance in image retrieval from text. However, their performance drops drastically when confronted with linguistically complex texts that they struggle to comprehend. Inspired by the Divide-and-Conquer algorithm and dual-process theory, in this paper...
2023-05-03T16:55:00Z
Accepted to ACL 2023 Main Conference
null
null
null
null
null
null
null
null
null
2,305.02301
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
['Cheng-Yu Hsieh', 'Chun-Liang Li', 'Chih-Kuan Yeh', 'Hootan Nakhost', 'Yasuhisa Fujii', 'Alexander Ratner', 'Ranjay Krishna', 'Chen-Yu Lee', 'Tomas Pfister']
['cs.CL', 'cs.AI', 'cs.LG']
Deploying large language models (LLMs) is challenging because they are memory inefficient and compute-intensive for practical applications. In reaction, researchers train smaller task-specific models by either finetuning with human labels or distilling using LLM-generated labels. However, finetuning and distillation re...
2023-05-03T17:50:56Z
Accepted to Findings of ACL 2023
null
null
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
['Cheng-Yu Hsieh', 'Chun-Liang Li', 'Chih-Kuan Yeh', 'Hootan Nakhost', 'Yasuhisa Fujii', 'Alexander J. Ratner', 'Ranjay Krishna', 'Chen-Yu Lee', 'Tomas Pfister']
2,023
Annual Meeting of the Association for Computational Linguistics
563
57
['Computer Science']
2,305.02309
CodeGen2: Lessons for Training LLMs on Programming and Natural Languages
['Erik Nijkamp', 'Hiroaki Hayashi', 'Caiming Xiong', 'Silvio Savarese', 'Yingbo Zhou']
['cs.LG']
Large language models (LLMs) have demonstrated remarkable abilities in representation learning for program synthesis and understanding tasks. The quality of the learned representations appears to be dictated by the neural scaling laws as a function of the number of model parameters and observations, while imposing uppe...
2023-05-03T17:55:25Z
null
null
null
null
null
null
null
null
null
null
2,305.0233
Robot Goes Fishing: Rapid, High-Resolution Biological Hotspot Mapping in Coral Reefs with Vision-Guided Autonomous Underwater Vehicles
['Daniel Yang', 'Levi Cai', 'Stewart Jamieson', 'Yogesh Girdhar']
['cs.RO', 'cs.CV']
Coral reefs are fast-changing and complex ecosystems that are crucial to monitor and study. Biological hotspot detection can help coral reef managers prioritize limited resources for monitoring and intervention tasks. Here, we explore the use of autonomous underwater vehicles (AUVs) with cameras, coupled with visual de...
2023-05-03T16:12:47Z
CV4Animals Workshop at CVPR 2023
null
null
null
null
null
null
null
null
null
2,305.02459
Transfer and Active Learning for Dissonance Detection: Addressing the Rare-Class Challenge
['Vasudha Varadarajan', 'Swanie Juhng', 'Syeda Mahwish', 'Xiaoran Liu', 'Jonah Luby', 'Christian Luhmann', 'H. Andrew Schwartz']
['cs.CL', 'cs.LG']
While transformer-based systems have enabled greater accuracies with fewer training examples, data acquisition obstacles still persist for rare-class tasks -- when the class label is very infrequent (e.g. < 5% of samples). Active learning has in general been proposed to alleviate such challenges, but choice of selectio...
2023-05-03T23:29:05Z
null
null
null
null
null
null
null
null
null
null
2,305.02463
Shap-E: Generating Conditional 3D Implicit Functions
['Heewoo Jun', 'Alex Nichol']
['cs.CV', 'cs.LG']
We present Shap-E, a conditional generative model for 3D assets. Unlike recent work on 3D generative models which produce a single output representation, Shap-E directly generates the parameters of implicit functions that can be rendered as both textured meshes and neural radiance fields. We train Shap-E in two stages:...
2023-05-03T23:59:13Z
23 pages, 13 figures
null
null
null
null
null
null
null
null
null
2,305.02606
Re$^3$Dial: Retrieve, Reorganize and Rescale Dialogue Corpus for Long-Turn Open-Domain Dialogue Pre-training
['Jiaxin Wen', 'Hao Zhou', 'Jian Guan', 'Minlie Huang']
['cs.CL']
Pre-training on large-scale open-domain dialogue data can substantially improve the performance of dialogue models. However, the pre-trained dialogue model's ability to utilize long-range context is limited due to the scarcity of long-turn dialogue sessions. Most dialogues in existing pre-training corpora contain fewer...
2023-05-04T07:28:23Z
EMNLP 2023 Main Coference
null
null
Re³Dial: Retrieve, Reorganize and Rescale Conversations for Long-Turn Open-Domain Dialogue Pre-training
['Jiaxin Wen', 'Hao Zhou', 'Jian Guan', 'Minlie Huang']
2,023
Conference on Empirical Methods in Natural Language Processing
0
49
['Computer Science']
2,305.02765
HiFi-Codec: Group-residual Vector quantization for High Fidelity Audio Codec
['Dongchao Yang', 'Songxiang Liu', 'Rongjie Huang', 'Jinchuan Tian', 'Chao Weng', 'Yuexian Zou']
['cs.SD', 'eess.AS']
Audio codec models are widely used in audio communication as a crucial technique for compressing audio into discrete representations. Nowadays, audio codec models are increasingly utilized in generation fields as intermediate representations. For instance, AudioLM is an audio generation model that uses the discrete rep...
2023-05-04T12:11:13Z
The second version of HiFi-Codec
null
null
null
null
null
null
null
null
null
2,305.02869
Masked Structural Growth for 2x Faster Language Model Pre-training
['Yiqun Yao', 'Zheng Zhang', 'Jing Li', 'Yequan Wang']
['cs.CL']
Accelerating large language model pre-training is a critical issue in present research. In this paper, we focus on speeding up pre-training by progressively growing from a small Transformer structure to a large one. There are two main research problems associated with progressive growth: determining the optimal growth ...
2023-05-04T14:28:39Z
ICLR 2024 camera ready
null
null
null
null
null
null
null
null
null
2,305.03058
Plug-and-Play Multilingual Few-shot Spoken Words Recognition
['Aaqib Saeed', 'Vasileios Tsouvalas']
['eess.AS', 'cs.LG', 'cs.SD']
As technology advances and digital devices become prevalent, seamless human-machine communication is increasingly gaining significance. The growing adoption of mobile, wearable, and other Internet of Things (IoT) devices has changed how we interact with these smart devices, making accurate spoken words recognition a cr...
2023-05-03T18:58:14Z
Code: https://github.com/FewshotML/plix
null
null
null
null
null
null
null
null
null
2,305.03111
Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs
['Jinyang Li', 'Binyuan Hui', 'Ge Qu', 'Jiaxi Yang', 'Binhua Li', 'Bowen Li', 'Bailin Wang', 'Bowen Qin', 'Rongyu Cao', 'Ruiying Geng', 'Nan Huo', 'Xuanhe Zhou', 'Chenhao Ma', 'Guoliang Li', 'Kevin C. C. Chang', 'Fei Huang', 'Reynold Cheng', 'Yongbin Li']
['cs.CL']
Text-to-SQL parsing, which aims at converting natural language instructions into executable SQLs, has gained increasing attention in recent years. In particular, Codex and ChatGPT have shown impressive results in this task. However, most of the prevalent benchmarks, i.e., Spider, and WikiSQL, focus on database schema w...
2023-05-04T19:02:29Z
NeurIPS 2023
null
null
null
null
null
null
null
null
null
2,305.03393
Optimized Table Tokenization for Table Structure Recognition
['Maksym Lysak', 'Ahmed Nassar', 'Nikolaos Livathinos', 'Christoph Auer', 'Peter Staar']
['cs.CV']
Extracting tables from documents is a crucial task in any document conversion pipeline. Recently, transformer-based models have demonstrated that table-structure can be recognized with impressive accuracy using Image-to-Markup-Sequence (Im2Seq) approaches. Taking only the image of a table, such models predict a sequenc...
2023-05-05T09:38:47Z
Accepted to ICDAR 2023, 12 pages, 6 figures
null
null
null
null
null
null
null
null
null
2,305.03695
Vera: A General-Purpose Plausibility Estimation Model for Commonsense Statements
['Jiacheng Liu', 'Wenya Wang', 'Dianzhuo Wang', 'Noah A. Smith', 'Yejin Choi', 'Hannaneh Hajishirzi']
['cs.CL', 'cs.AI']
Despite the much discussed capabilities of today's language models, they are still prone to silly and unexpected commonsense failures. We consider a retrospective verification approach that reflects on the correctness of LM outputs, and introduce Vera, a general-purpose model that estimates the plausibility of declarat...
2023-05-05T17:15:32Z
EMNLP 2023 main conference
null
null
null
null
null
null
null
null
null
2,305.03726
Otter: A Multi-Modal Model with In-Context Instruction Tuning
['Bo Li', 'Yuanhan Zhang', 'Liangyu Chen', 'Jinghao Wang', 'Jingkang Yang', 'Ziwei Liu']
['cs.CV', 'cs.CL']
Large language models (LLMs) have demonstrated significant universal capabilities as few/zero-shot learners in various tasks due to their pre-training on vast amounts of text data, as exemplified by GPT-3, which boosted to InstrctGPT and ChatGPT, effectively following natural language instructions to accomplish real-wo...
2023-05-05T17:59:46Z
Technical Report
null
null
null
null
null
null
null
null
null
2,305.0388
NorBench -- A Benchmark for Norwegian Language Models
['David Samuel', 'Andrey Kutuzov', 'Samia Touileb', 'Erik Velldal', 'Lilja Øvrelid', 'Egil Rønningstad', 'Elina Sigdel', 'Anna Palatkina']
['cs.CL']
We present NorBench: a streamlined suite of NLP tasks and probes for evaluating Norwegian language models (LMs) on standardized data splits and evaluation metrics. We also introduce a range of new Norwegian language models (both encoder and encoder-decoder based). Finally, we compare and analyze their performance, alon...
2023-05-06T00:20:24Z
Accepted to NoDaLiDa 2023
null
null
null
null
null
null
null
null
null
2,305.03907
Listen to Look into the Future: Audio-Visual Egocentric Gaze Anticipation
['Bolin Lai', 'Fiona Ryan', 'Wenqi Jia', 'Miao Liu', 'James M. Rehg']
['cs.CV']
Egocentric gaze anticipation serves as a key building block for the emerging capability of Augmented Reality. Notably, gaze behavior is driven by both visual cues and audio signals during daily activities. Motivated by this observation, we introduce the first model that leverages both the video and audio modalities for...
2023-05-06T02:53:13Z
30 pages
null
null
null
null
null
null
null
null
null
2,305.0395
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval
['Shengyao Zhuang', 'Linjun Shou', 'Guido Zuccon']
['cs.IR']
Effective cross-lingual dense retrieval methods that rely on multilingual pre-trained language models (PLMs) need to be trained to encompass both the relevance matching task and the cross-language alignment task. However, cross-lingual data for training is often scarcely available. In this paper, rather than using more...
2023-05-06T06:34:21Z
SIGIR2023 short paper
null
10.1145/3539618.3591952
Augmenting Passage Representations with Query Generation for Enhanced Cross-Lingual Dense Retrieval
['Shengyao Zhuang', 'Linjun Shou', 'G. Zuccon']
2,023
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval
8
48
['Computer Science']
2,305.03981
Pre-training Language Model as a Multi-perspective Course Learner
['Beiduo Chen', 'Shaohan Huang', 'Zihan Zhang', 'Wu Guo', 'Zhenhua Ling', 'Haizhen Huang', 'Furu Wei', 'Weiwei Deng', 'Qi Zhang']
['cs.CL']
ELECTRA, the generator-discriminator pre-training framework, has achieved impressive semantic construction capability among various downstream tasks. Despite the convincing performance, ELECTRA still faces the challenges of monotonous training and deficient interaction. Generator with only masked language modeling (MLM...
2023-05-06T09:02:10Z
Accepted as Findings of ACL 2023
null
null
null
null
null
null
null
null
null
2,305.04175
Text-to-Image Diffusion Models can be Easily Backdoored through Multimodal Data Poisoning
['Shengfang Zhai', 'Yinpeng Dong', 'Qingni Shen', 'Shi Pu', 'Yuejian Fang', 'Hang Su']
['cs.CR', 'cs.CV', 'cs.MM']
With the help of conditioning mechanisms, the state-of-the-art diffusion models have achieved tremendous success in guided image generation, particularly in text-to-image synthesis. To gain a better understanding of the training process and potential risks of text-to-image synthesis, we perform a systematic investigati...
2023-05-07T03:21:28Z
Carmera-ready version. To appear in ACM MM 2023. Code will be released at: https://github.com/sf-zhai/BadT2I
null
null
Text-to-Image Diffusion Models can be Easily Backdoored through Multimodal Data Poisoning
['Shengfang Zhai', 'Yinpeng Dong', 'Qingni Shen', 'Shih-Chieh Pu', 'Yuejian Fang', 'Hang Su']
2,023
ACM Multimedia
77
46
['Computer Science']
2,305.04177
MIReAD: Simple Method for Learning High-quality Representations from Scientific Documents
['Anastasia Razdaibiedina', 'Alexander Brechalov']
['cs.CL', 'cs.AI']
Learning semantically meaningful representations from scientific documents can facilitate academic literature search and improve performance of recommendation systems. Pre-trained language models have been shown to learn rich textual representations, yet they cannot provide powerful document-level representations for s...
2023-05-07T03:29:55Z
ACL 2023 (short paper)
null
null
null
null
null
null
null
null
null
2,305.04183
OpenViVQA: Task, Dataset, and Multimodal Fusion Models for Visual Question Answering in Vietnamese
['Nghia Hieu Nguyen', 'Duong T. D. Vo', 'Kiet Van Nguyen', 'Ngan Luu-Thuy Nguyen']
['cs.CL']
In recent years, visual question answering (VQA) has attracted attention from the research community because of its highly potential applications (such as virtual assistance on intelligent cars, assistant devices for blind people, or information retrieval from document images using natural language as queries) and chal...
2023-05-07T03:59:31Z
submitted to Elsevier
null
10.1016/j.inffus.2023.101868
null
null
null
null
null
null
null
2,305.04365
LatinCy: Synthetic Trained Pipelines for Latin NLP
['Patrick J. Burns']
['cs.CL']
This paper introduces LatinCy, a set of trained general purpose Latin-language "core" pipelines for use with the spaCy natural language processing framework. The models are trained on a large amount of available Latin data, including all five of the Latin Universal Dependency treebanks, which have been preprocessed to ...
2023-05-07T19:59:01Z
10 pages, 1 table, 4 figures
null
null
null
null
null
null
null
null
null
2,305.0453
A Multi-Modal Context Reasoning Approach for Conditional Inference on Joint Textual and Visual Clues
['Yunxin Li', 'Baotian Hu', 'Xinyu Chen', 'Yuxin Ding', 'Lin Ma', 'Min Zhang']
['cs.CL']
Conditional inference on joint textual and visual clues is a multi-modal reasoning task that textual clues provide prior permutation or external knowledge, which are complementary with visual content and pivotal to deducing the correct option. Previous methods utilizing pretrained vision-language models (VLMs) have ach...
2023-05-08T08:05:40Z
Accepted to ACL 2023 Main Conference
null
null
A Multi-Modal Context Reasoning Approach for Conditional Inference on Joint Textual and Visual Clues
['Yunxin Li', 'Baotian Hu', 'Xinyu Chen', 'Yuxin Ding', 'Lin Ma', 'Min Zhang']
2,023
Annual Meeting of the Association for Computational Linguistics
15
56
['Computer Science']
2,305.04919
DiffuseStyleGesture: Stylized Audio-Driven Co-Speech Gesture Generation with Diffusion Models
['Sicheng Yang', 'Zhiyong Wu', 'Minglei Li', 'Zhensong Zhang', 'Lei Hao', 'Weihong Bao', 'Ming Cheng', 'Long Xiao']
['cs.HC', 'cs.MM']
The art of communication beyond speech there are gestures. The automatic co-speech gesture generation draws much attention in computer animation. It is a challenging task due to the diversity of gestures and the difficulty of matching the rhythm and semantics of the gesture to the corresponding speech. To address these...
2023-05-08T17:54:58Z
11 pages, 9 figures, IJCAI 2023
null
null
DiffuseStyleGesture: Stylized Audio-Driven Co-Speech Gesture Generation with Diffusion Models
['Sicheng Yang', 'Zhiyong Wu', 'Minglei Li', 'Zhensong Zhang', 'Lei Hao', 'Weihong Bao', 'Ming Cheng', 'Long Xiao']
2,023
International Joint Conference on Artificial Intelligence
71
56
['Computer Science']
2,305.04928
From Zero to Hero: Harnessing Transformers for Biomedical Named Entity Recognition in Zero- and Few-shot Contexts
['Miloš Košprdić', 'Nikola Prodanović', 'Adela Ljajić', 'Bojana Bašaragin', 'Nikola Milošević']
['cs.CL', 'cs.AI', 'cs.IR']
Supervised named entity recognition (NER) in the biomedical domain depends on large sets of annotated texts with the given named entities. The creation of such datasets can be time-consuming and expensive, while extraction of new entities requires additional annotation tasks and retraining the model. To address these c...
2023-05-05T12:14:22Z
Collaboration between Bayer Pharma R&D and Serbian Institute for Artificial Intelligence Research and Development. Artificial Intelligence in Medicine (2024)
null
10.1016/j.artmed.2024.102970
From Zero to Hero: Harnessing Transformers for Biomedical Named Entity Recognition in Zero- and Few-shot Contexts
['Milos Kosprdic', 'Nikola Prodanović', 'Adela Ljajić', 'Bojana Bašaragin', 'Nikola Milosevic']
2,023
Artif. Intell. Medicine
7
64
['Medicine', 'Computer Science']
2,305.05065
Recommender Systems with Generative Retrieval
['Shashank Rajput', 'Nikhil Mehta', 'Anima Singh', 'Raghunandan H. Keshavan', 'Trung Vu', 'Lukasz Heldt', 'Lichan Hong', 'Yi Tay', 'Vinh Q. Tran', 'Jonah Samost', 'Maciej Kula', 'Ed H. Chi', 'Maheswaran Sathiamoorthy']
['cs.IR', 'cs.LG']
Modern recommender systems perform large-scale retrieval by first embedding queries and item candidates in the same unified space, followed by approximate nearest neighbor search to select top candidates given a query embedding. In this paper, we propose a novel generative retrieval approach, where the retrieval model ...
2023-05-08T21:48:17Z
To appear in The 37th Conference on Neural Information Processing Systems (NeurIPS 2023)
null
null
null
null
null
null
null
null
null
2,305.05084
Fast Conformer with Linearly Scalable Attention for Efficient Speech Recognition
['Dima Rekesh', 'Nithin Rao Koluguri', 'Samuel Kriman', 'Somshubra Majumdar', 'Vahid Noroozi', 'He Huang', 'Oleksii Hrinchuk', 'Krishna Puvvada', 'Ankur Kumar', 'Jagadeesh Balam', 'Boris Ginsburg']
['eess.AS', 'cs.SD']
Conformer-based models have become the dominant end-to-end architecture for speech processing tasks. With the objective of enhancing the conformer architecture for efficient training and inference, we carefully redesigned Conformer with a novel downsampling schema. The proposed model, named Fast Conformer(FC), is 2.8x ...
2023-05-08T22:54:07Z
Accepted at ASRU 2023
null
null
Fast Conformer With Linearly Scalable Attention For Efficient Speech Recognition
['D. Rekesh', 'Samuel Kriman', 'Somshubra Majumdar', 'V. Noroozi', 'He Juang', 'Oleksii Hrinchuk', 'Ankur Kumar', 'Boris Ginsburg']
2,023
Automatic Speech Recognition & Understanding
92
34
['Engineering', 'Computer Science']
2,305.05255
Emolysis: A Multimodal Open-Source Group Emotion Analysis and Visualization Toolkit
['Shreya Ghosh', 'Zhixi Cai', 'Parul Gupta', 'Garima Sharma', 'Abhinav Dhall', 'Munawar Hayat', 'Tom Gedeon']
['cs.HC']
Automatic group emotion recognition plays an important role in understanding complex human-human interaction. This paper introduces, Emolysis, a Python-based, standalone open-source group emotion analysis toolkit for use in different social situations upon getting consent from the users. Given any input video, Emolysis...
2023-05-09T08:23:12Z
Accepted by ACII Demo 2024. Both Shreya Ghosh and Zhixi Cai contributed equally to this research
null
null
null
null
null
null
null
null
null
2,305.0528
VCSUM: A Versatile Chinese Meeting Summarization Dataset
['Han Wu', 'Mingjie Zhan', 'Haochen Tan', 'Zhaohui Hou', 'Ding Liang', 'Linqi Song']
['cs.CL', 'cs.AI']
Compared to news and chat summarization, the development of meeting summarization is hugely decelerated by the limited data. To this end, we introduce a versatile Chinese meeting summarization dataset, dubbed VCSum, consisting of 239 real-life meetings, with a total duration of over 230 hours. We claim our dataset is v...
2023-05-09T09:07:15Z
Findings of ACL 2023 (long paper). GitHub: https://github.com/hahahawu/VCSum
null
null
null
null
null
null
null
null
null
2,305.05322
TPS++: Attention-Enhanced Thin-Plate Spline for Scene Text Recognition
['Tianlun Zheng', 'Zhineng Chen', 'Jinfeng Bai', 'Hongtao Xie', 'Yu-Gang Jiang']
['cs.CV']
Text irregularities pose significant challenges to scene text recognizers. Thin-Plate Spline (TPS)-based rectification is widely regarded as an effective means to deal with them. Currently, the calculation of TPS transformation parameters purely depends on the quality of regressed text borders. It ignores the text cont...
2023-05-09T10:16:43Z
Accepted by IJCAI 2023
null
null
TPS++: Attention-Enhanced Thin-Plate Spline for Scene Text Recognition
['Tianlun Zheng', 'Zhineng Chen', 'Jinfeng Bai', 'Hongtao Xie', 'Yu-Gang Jiang']
2,023
International Joint Conference on Artificial Intelligence
19
56
['Computer Science']
2,305.05401
Learn to Sing by Listening: Building Controllable Virtual Singer by Unsupervised Learning from Voice Recordings
['Wei Xue', 'Yiwen Wang', 'Qifeng Liu', 'Yike Guo']
['cs.SD', 'eess.AS']
The virtual world is being established in which digital humans are created indistinguishable from real humans. Producing their audio-related capabilities is crucial since voice conveys extensive personal characteristics. We aim to create a controllable audio-form virtual singer; however, supervised modeling and control...
2023-05-09T12:45:45Z
null
null
null
Learn to Sing by Listening: Building Controllable Virtual Singer by Unsupervised Learning from Voice Recordings
['Wei Xue', 'Yiwen Wang', 'Qi-fei Liu', 'Yi-Ting Guo']
2,023
arXiv.org
1
64
['Computer Science', 'Engineering']
2,305.05471
Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good
['Fernando Gonzalez', 'Zhijing Jin', 'Bernhard Schölkopf', 'Tom Hope', 'Mrinmaya Sachan', 'Rada Mihalcea']
['cs.CL']
With the recent advances in natural language processing (NLP), a vast number of applications have emerged across various use cases. Among the plethora of NLP applications, many academic researchers are motivated to do work that has a positive social impact, in line with the recent initiatives of NLP for Social Good (NL...
2023-05-09T14:16:25Z
EMNLP 2023 Findings
null
null
null
null
null
null
null
null
null
2,305.05486
MAUPQA: Massive Automatically-created Polish Question Answering Dataset
['Piotr Rybak']
['cs.CL']
Recently, open-domain question answering systems have begun to rely heavily on annotated datasets to train neural passage retrievers. However, manually annotating such datasets is both difficult and time-consuming, which limits their availability for less popular languages. In this work, we experiment with several meth...
2023-05-09T14:36:04Z
null
null
null
null
null
null
null
null
null
null
2,305.05858
Vārta: A Large-Scale Headline-Generation Dataset for Indic Languages
['Rahul Aralikatte', 'Ziling Cheng', 'Sumanth Doddapaneni', 'Jackie Chi Kit Cheung']
['cs.CL']
We present V\=arta, a large-scale multilingual dataset for headline generation in Indic languages. This dataset includes 41.8 million news articles in 14 different Indic languages (and English), which come from a variety of high-quality sources. To the best of our knowledge, this is the largest collection of curated ar...
2023-05-10T03:07:17Z
Findings of ACL 2023
null
null
null
null
null
null
null
null
null
2,305.0614
CrudeBERT: Applying Economic Theory towards fine-tuning Transformer-based Sentiment Analysis Models to the Crude Oil Market
['Himmet Kaplan', 'Ralf-Peter Mundani', 'Heiko Rölke', 'Albert Weichselbraun']
['cs.IR', 'cs.LG', 'H.3; H.4; I.2.7']
Predicting market movements based on the sentiment of news media has a long tradition in data analysis. With advances in natural language processing, transformer architectures have emerged that enable contextually aware sentiment classification. Nevertheless, current methods built for the general financial market such ...
2023-05-10T13:42:56Z
null
Proceedings of the 25th International Conference on Enterprise Information Systems (ICEIS 2023), pages 324-334
10.5220/0011749600003467
null
null
null
null
null
null
null
2,305.06156
The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation
['Dung Nguyen Manh', 'Nam Le Hai', 'Anh T. V. Dau', 'Anh Minh Nguyen', 'Khanh Nghiem', 'Jin Guo', 'Nghi D. Q. Bui']
['cs.CL', 'cs.AI', 'cs.PL', 'cs.SE']
We present The Vault, a dataset of high-quality code-text pairs in multiple programming languages for training large language models to understand and generate code. We present methods for thoroughly extracting samples that use both rule-based and deep learning-based methods to ensure that they contain high-quality pai...
2023-05-09T09:35:03Z
Accepted at EMNLP 2023, Long Findings
null
null
null
null
null
null
null
null
null
2,305.06161
StarCoder: may the source be with you!
['Raymond Li', 'Loubna Ben Allal', 'Yangtian Zi', 'Niklas Muennighoff', 'Denis Kocetkov', 'Chenghao Mou', 'Marc Marone', 'Christopher Akiki', 'Jia Li', 'Jenny Chim', 'Qian Liu', 'Evgenii Zheltonozhskii', 'Terry Yue Zhuo', 'Thomas Wang', 'Olivier Dehaene', 'Mishig Davaadorj', 'Joel Lamy-Poirier', 'João Monteiro', 'Oleh ...
['cs.CL', 'cs.AI', 'cs.PL', 'cs.SE']
The BigCode community, an open-scientific collaboration working on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder and StarCoderBase: 15.5B parameter models with 8K context length, infilling capabilities and fast large-batch inference enabled by multi-query attention. Sta...
2023-05-09T08:16:42Z
null
null
null
null
null
null
null
null
null
null
2,305.06274
Context-Aware Document Simplification
['Liam Cripwell', 'Joël Legrand', 'Claire Gardent']
['cs.CL']
To date, most work on text simplification has focused on sentence-level inputs. Early attempts at document simplification merely applied these approaches iteratively over the sentences of a document. However, this fails to coherently preserve the discourse structure, leading to suboptimal output quality. Recently, stra...
2023-05-10T16:06:36Z
Accepted to Findings of ACL 2023
null
null
null
null
null
null
null
null
null
2,305.06355
VideoChat: Chat-Centric Video Understanding
['KunChang Li', 'Yinan He', 'Yi Wang', 'Yizhuo Li', 'Wenhai Wang', 'Ping Luo', 'Yali Wang', 'Limin Wang', 'Yu Qiao']
['cs.CV', 'cs.CL']
In this paper, we initiate an attempt of developing an end-to-end chat-centric video understanding system, coined as VideoChat. It integrates video foundation models and large language models via a learnable neural interface, excelling in spatiotemporal reasoning, event localization, and causal relationship inference. ...
2023-05-10T17:59:04Z
Technical report
null
null
VideoChat: Chat-Centric Video Understanding
['Kunchang Li', 'Yinan He', 'Yi Wang', 'Yizhuo Li', 'Wen Wang', 'Ping Luo', 'Yali Wang', 'Limin Wang', 'Yu Qiao']
2,023
arXiv.org
586
66
['Computer Science']
2,305.065
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
['Wenliang Dai', 'Junnan Li', 'Dongxu Li', 'Anthony Meng Huat Tiong', 'Junqi Zhao', 'Weisheng Wang', 'Boyang Li', 'Pascale Fung', 'Steven Hoi']
['cs.CV', 'cs.LG']
Large-scale pre-training and instruction tuning have been successful at creating general-purpose language models with broad competence. However, building general-purpose vision-language models is challenging due to the rich input distributions and task diversity resulting from the additional visual input. Although visi...
2023-05-11T00:38:10Z
preprint
null
null
InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning
['Wenliang Dai', 'Junnan Li', 'Dongxu Li', 'A. M. H. Tiong', 'Junqi Zhao', 'Weisheng Wang', 'Boyang Albert Li', 'Pascale Fung', 'Steven C. H. Hoi']
2,023
Neural Information Processing Systems
2,105
52
['Computer Science']
2,305.06721
Advancing Neural Encoding of Portuguese with Transformer Albertina PT-*
['João Rodrigues', 'Luís Gomes', 'João Silva', 'António Branco', 'Rodrigo Santos', 'Henrique Lopes Cardoso', 'Tomás Osório']
['cs.CL']
To advance the neural encoding of Portuguese (PT), and a fortiori the technological preparation of this language for the digital age, we developed a Transformer-based foundation model that sets a new state of the art in this respect for two of its variants, namely European Portuguese from Portugal (PT-PT) and American ...
2023-05-11T10:56:20Z
null
null
10.1007/978-3-031-49008-8_35
null
null
null
null
null
null
null
2,305.06897
AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
['Odunayo Ogundepo', 'Tajuddeen R. Gwadabe', 'Clara E. Rivera', 'Jonathan H. Clark', 'Sebastian Ruder', 'David Ifeoluwa Adelani', 'Bonaventure F. P. Dossou', 'Abdou Aziz DIOP', 'Claytone Sikasote', 'Gilles Hacheme', 'Happy Buzaaba', 'Ignatius Ezeani', 'Rooweither Mabuya', 'Salomey Osei', 'Chris Emezue', 'Albert Njoroge...
['cs.CL', 'cs.AI', 'cs.IR']
African languages have far less in-language content available digitally, making it challenging for question answering systems to satisfy the information needs of users. Cross-lingual open-retrieval question answering (XOR QA) systems -- those that retrieve answer content from other languages while serving people in the...
2023-05-11T15:34:53Z
null
null
null
AfriQA: Cross-lingual Open-Retrieval Question Answering for African Languages
['Odunayo Ogundepo', 'T. Gwadabe', 'Clara Rivera', 'J. Clark', 'Sebastian Ruder', 'David Ifeoluwa Adelani', 'Bonaventure F. P. Dossou', 'Abdoulahat Diop', 'Claytone Sikasote', 'Gilles Hacheme', 'Happy Buzaaba', 'Ignatius M Ezeani', 'Rooweither Mabuya', 'Salomey Osei', 'Chris C. Emezue', 'A. Kahira', 'Shamsuddeen Hassan...
2,023
Conference on Empirical Methods in Natural Language Processing
16
62
['Computer Science']
2,305.07015
Exploiting Diffusion Prior for Real-World Image Super-Resolution
['Jianyi Wang', 'Zongsheng Yue', 'Shangchen Zhou', 'Kelvin C. K. Chan', 'Chen Change Loy']
['cs.CV']
We present a novel approach to leverage prior knowledge encapsulated in pre-trained text-to-image diffusion models for blind super-resolution (SR). Specifically, by employing our time-aware encoder, we can achieve promising restoration results without altering the pre-trained synthesis model, thereby preserving the gen...
2023-05-11T17:55:25Z
Accepted by IJCV'2024. Some Figs are compressed due to size limits. Uncompressed ver.: https://github.com/IceClear/StableSR/releases/download/UncompressedPDF/StableSR_IJCV_Uncompressed.pdf. Project page: https://iceclear.github.io/projects/stablesr/
null
null
null
null
null
null
null
null
null
2,305.07017
An Inverse Scaling Law for CLIP Training
['Xianhang Li', 'Zeyu Wang', 'Cihang Xie']
['cs.CV']
CLIP, one of the pioneering foundation models that connect images and text, has enabled many recent breakthroughs in computer vision. However, its associated training cost is prohibitively high, imposing a significant barrier to its widespread exploration. In this paper, we present a surprising finding that there exist...
2023-05-11T17:56:09Z
NeurIPS 2023 camera-ready
null
null
null
null
null
null
null
null
null
2,305.07027
EfficientViT: Memory Efficient Vision Transformer with Cascaded Group Attention
['Xinyu Liu', 'Houwen Peng', 'Ningxin Zheng', 'Yuqing Yang', 'Han Hu', 'Yixuan Yuan']
['cs.CV']
Vision transformers have shown great success due to their high model capabilities. However, their remarkable performance is accompanied by heavy computation costs, which makes them unsuitable for real-time applications. In this paper, we propose a family of high-speed vision transformers named EfficientViT. We find tha...
2023-05-11T17:59:41Z
CVPR 2023
null
null
null
null
null
null
null
null
null
2,305.07152
Intuitive Surgical SurgToolLoc Challenge Results: 2022-2023
['Aneeq Zia', 'Max Berniker', 'Rogerio Garcia Nespolo', 'Conor Perreault', 'Kiran Bhattacharyya', 'Xi Liu', 'Ziheng Wang', 'Satoshi Kondo', 'Satoshi Kasai', 'Kousuke Hirasawa', 'Bo Liu', 'David Austin', 'Yiheng Wang', 'Michal Futrega', 'Jean-Francois Puget', 'Zhenqiang Li', 'Yoichi Sato', 'Ryo Fujii', 'Ryo Hachiuma', '...
['cs.CV']
Robotic assisted (RA) surgery promises to transform surgical intervention. Intuitive Surgical is committed to fostering these changes and the machine learning models and algorithms that will enable them. With these goals in mind we have invited the surgical data science community to participate in a yearly competition ...
2023-05-11T21:44:39Z
null
null
null
null
null
null
null
null
null
null
2,305.07243
Better speech synthesis through scaling
['James Betker']
['cs.SD', 'cs.CL', 'eess.AS']
In recent years, the field of image generation has been revolutionized by the application of autoregressive transformers and DDPMs. These approaches model the process of image generation as a step-wise probabilistic processes and leverage large amounts of compute and data to learn the image distribution. This methodolo...
2023-05-12T04:19:49Z
null
null
null
Better speech synthesis through scaling
['James Betker']
2,023
arXiv.org
73
19
['Computer Science', 'Engineering']
2,305.07372
Interactive Text-to-SQL Generation via Editable Step-by-Step Explanations
['Yuan Tian', 'Zheng Zhang', 'Zheng Ning', 'Toby Jia-Jun Li', 'Jonathan K. Kummerfeld', 'Tianyi Zhang']
['cs.DB', 'cs.CL', 'I.2.7']
Relational databases play an important role in business, science, and more. However, many users cannot fully unleash the analytical power of relational databases, because they are not familiar with database languages such as SQL. Many techniques have been proposed to automatically generate SQL from natural language, bu...
2023-05-12T10:45:29Z
Accepted to EMNLP 2023
null
null
null
null
null
null
null
null
null
2,305.07489
Benchmarks and leaderboards for sound demixing tasks
['Roman Solovyev', 'Alexander Stempkovskiy', 'Tatiana Habruseva']
['cs.SD', 'cs.LG', 'eess.AS']
Music demixing is the task of separating different tracks from the given single audio signal into components, such as drums, bass, and vocals from the rest of the accompaniment. Separation of sources is useful for a range of areas, including entertainment and hearing aids. In this paper, we introduce two new benchmarks...
2023-05-12T14:00:26Z
null
null
null
null
null
null
null
null
null
null