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08/31/2023
TouchStone: Evaluating Vision-Language Models by Language Models
Large vision-language models (LVLMs) have recently witnessed rapid advan...
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08/24/2023
Qwen-VL: A Frontier Large Vision-Language Model with Versatile Abilities
We introduce the Qwen-VL series, a set of large-scale vision-language mo...
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08/14/2023
#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models
Foundation language models obtain the instruction-following ability thro...
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05/24/2023
ExpertPrompting: Instructing Large Language Models to be Distinguished Experts
The answering quality of an aligned large language model (LLM) can be dr...
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05/18/2023
ONE-PEACE: Exploring One General Representation Model Toward Unlimited Modalities
In this work, we explore a scalable way for building a general represent...
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12/19/2022
Transferring General Multimodal Pretrained Models to Text Recognition
This paper proposes a new method, OFA-OCR, to transfer multimodal pretra...
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12/08/2022
OFASys: A Multi-Modal Multi-Task Learning System for Building Generalist Models
Generalist models, which are capable of performing diverse multi-modal t...
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11/02/2022
Chinese CLIP: Contrastive Vision-Language Pretraining in Chinese
The tremendous success of CLIP (Radford et al., 2021) has promoted the r...
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08/04/2022
Prompt Tuning for Generative Multimodal Pretrained Models
Prompt tuning has become a new paradigm for model tuning and it has demo...
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06/04/2022
Instance-wise Prompt Tuning for Pretrained Language Models
Prompt Learning has recently gained great popularity in bridging the gap...
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03/23/2022
Modality Competition: What Makes Joint Training of Multi-modal Network Fail in Deep Learning? (Provably)
Despite the remarkable success of deep multi-modal learning in practice,...
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02/07/2022
Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
In this work, we pursue a unified paradigm for multimodal pretraining to...
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11/26/2021
KNAS: Green Neural Architecture Search
Many existing neural architecture search (NAS) solutions rely on downstr...
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10/08/2021
M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining
Recent expeditious developments in deep learning algorithms, distributed...
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05/31/2021
Exploring Sparse Expert Models and Beyond
Mixture-of-Experts (MoE) models can achieve promising results with outra...
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05/31/2021
Connecting Language and Vision for Natural Language-Based Vehicle Retrieval
Vehicle search is one basic task for the efficient traffic management in...
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05/31/2021
Sketch and Refine: Towards Faithful and Informative Table-to-Text Generation
Table-to-text generation refers to generating a descriptive text from a ...
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05/28/2021
Learning Relation Alignment for Calibrated Cross-modal Retrieval
Despite the achievements of large-scale multimodal pre-training approach...
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05/26/2021
CogView: Mastering Text-to-Image Generation via Transformers
Text-to-Image generation in the general domain has long been an open pro...
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03/01/2021
M6: A Chinese Multimodal Pretrainer
In this work, we construct the largest dataset for multimodal pretrainin...
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09/28/2020
Graph-based Multi-hop Reasoning for Long Text Generation
Long text generation is an important but challenging task.The main probl...
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03/30/2020
InterBERT: Vision-and-Language Interaction for Multi-modal Pretraining
Multi-modal pretraining for learning high-level multi-modal representati...
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12/25/2019
Explicit Sparse Transformer: Concentrated Attention Through Explicit Selection
Self-attention based Transformer has demonstrated the state-of-the-art p...
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11/16/2019
Understanding and Improving Layer Normalization
Layer normalization (LayerNorm) is a technique to normalize the distribu...
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08/15/2019
Towards Knowledge-Based Recommender Dialog System
In this paper, we propose a novel end-to-end framework called KBRD, whic...
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06/05/2019
Imitation Learning for Non-Autoregressive Neural Machine Translation
Non-autoregressive translation models (NAT) have achieved impressive inf...
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03/29/2019
Towards Knowledge-Based Personalized Product Description Generation in E-commerce
Quality product descriptions are critical for providing competitive cust...
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09/10/2018
A Deep Reinforced Sequence-to-Set Model for Multi-Label Text Classification
Multi-label text classification (MLTC) aims to assign multiple labels to...
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09/02/2018
Future-Prediction-Based Model for Neural Machine Translation
We propose a novel model for Neural Machine Translation (NMT). Different...
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08/27/2018
An Auto-Encoder Matching Model for Learning Utterance-Level Semantic Dependency in Dialogue Generation
Generating semantically coherent responses is still a major challenge in...
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08/26/2018
Semantic-Unit-Based Dilated Convolution for Multi-Label Text Classification
We propose a novel model for multi-label text classification, which is b...
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08/22/2018
Learning When to Concentrate or Divert Attention: Self-Adaptive Attention Temperature for Neural Machine Translation
Most of the Neural Machine Translation (NMT) models are based on the seq...
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06/10/2018
Deconvolution-Based Global Decoding for Neural Machine Translation
A great proportion of sequence-to-sequence (Seq2Seq) models for Neural M...
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05/13/2018
Bag-of-Words as Target for Neural Machine Translation
A sentence can be translated into more than one correct sentences. Howev...
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05/13/2018
Autoencoder as Assistant Supervisor: Improving Text Representation for Chinese Social Media Text Summarization
Most of the current abstractive text summarization models are based on t...
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05/10/2018
Global Encoding for Abstractive Summarization
In neural abstractive summarization, the conventional sequence-to-sequen...
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05/03/2018
A Hierarchical End-to-End Model for Jointly Improving Text Summarization and Sentiment Classification
Text summarization and sentiment classification both aim to capture the ...
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02/06/2018
Decoding-History-Based Adaptive Control of Attention for Neural Machine Translation
Attention-based sequence-to-sequence model has proved successful in Neur...
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02/05/2018