b'Li Dong'

research

∙ 09/20/2023

Kosmos-2.5: A Multimodal Literate Model

We present Kosmos-2.5, a multimodal literate model for machine reading o...

0 Tengchao Lv, et al. ∙

research

∙ 09/11/2023

Large Language Model for Science: A Study on P vs. NP

In this work, we use large language models (LLMs) to augment and acceler...

0 Qingxiu Dong, et al. ∙

research

∙ 09/03/2023

Large AI Model Empowered Multimodal Semantic Communications

Multimodal signals, including text, audio, image and video, can be integ...

0 Feibo Jiang, et al. ∙

research

∙ 08/29/2023

LAMBO: Large Language Model Empowered Edge Intelligence

Next-generation edge intelligence is anticipated to bring huge benefits ...

0 Li Dong, et al. ∙

research

∙ 08/08/2023

Evil Operation: Breaking Speaker Recognition with PaddingBack

Machine Learning as a Service (MLaaS) has gained popularity due to advan...

0 Zhe Ye, et al. ∙

research

∙ 08/04/2023

Universal Defensive Underpainting Patch: Making Your Text Invisible to Optical Character Recognition

Optical Character Recognition (OCR) enables automatic text extraction fr...

0 Jiacheng Deng, et al. ∙

research

∙ 07/17/2023

Retentive Network: A Successor to Transformer for Large Language Models

In this work, we propose Retentive Network (RetNet) as a foundation arch...

0 Yutao Sun, et al. ∙

research

∙ 07/07/2023

Large AI Model-Based Semantic Communications

Semantic communication (SC) is an emerging intelligent paradigm, offerin...

0 Feibo Jiang, et al. ∙

research

∙ 07/05/2023

LongNet: Scaling Transformers to 1,000,000,000 Tokens

Scaling sequence length has become a critical demand in the era of large...

0 Jiayu Ding, et al. ∙

research

∙ 06/28/2023

Fake the Real: Backdoor Attack on Deep Speech Classification via Voice Conversion

Deep speech classification has achieved tremendous success and greatly p...

0 Zhe Ye, et al. ∙

research

∙ 06/26/2023

Kosmos-2: Grounding Multimodal Large Language Models to the World

We introduce Kosmos-2, a Multimodal Large Language Model (MLLM), enablin...

0 Zhiliang Peng, et al. ∙

research

∙ 06/14/2023

Knowledge Distillation of Large Language Models

Knowledge Distillation (KD) is a promising technique for reducing the hi...

0 Yuxian Gu, et al. ∙

research

∙ 06/12/2023

Augmenting Language Models with Long-Term Memory

Existing large language models (LLMs) can only afford fix-sized inputs d...

0 Weizhi Wang, et al. ∙

research

∙ 05/16/2023

Pre-Training to Learn in Context

In-context learning, where pre-trained language models learn to perform ...

0 Yuxian Gu, et al. ∙

research

∙ 02/28/2023

Generic-to-Specific Distillation of Masked Autoencoders

Large vision Transformers (ViTs) driven by self-supervised pre-training ...

0 Wei Huang, et al. ∙

research

∙ 02/27/2023

Language Is Not All You Need: Aligning Perception with Language Models

A big convergence of language, multimodal perception, action, and world ...

0 Shaohan Huang, et al. ∙

research

∙ 12/21/2022

Language Models as Inductive Reasoners

Inductive reasoning is a core component of human intelligence. In the pa...

0 Zonglin Yang, et al. ∙

research

∙ 12/20/2022

Why Can GPT Learn In-Context? Language Models Secretly Perform Gradient Descent as Meta-Optimizers

Large pretrained language models have shown surprising In-Context Learni...

0 Damai Dai, et al. ∙

research

∙ 12/20/2022

A Length-Extrapolatable Transformer

Position modeling plays a critical role in Transformers. In this paper, ...

0 Yutao Sun, et al. ∙

research

∙ 12/20/2022

GanLM: Encoder-Decoder Pre-training with an Auxiliary Discriminator

Pre-trained models have achieved remarkable success in natural language ...

0 Jian Yang, et al. ∙

research

∙ 12/19/2022

Optimizing Prompts for Text-to-Image Generation

Well-designed prompts can guide text-to-image models to generate amazing...

0 Yaru Hao, et al. ∙

research

∙ 12/13/2022

Structured Prompting: Scaling In-Context Learning to 1,000 Examples

Large language models have exhibited intriguing in-context learning capa...

0 Yaru Hao, et al. ∙

research

∙ 12/01/2022

Extensible Prompts for Language Models

We propose eXtensible Prompt (X-Prompt) for prompting a large language m...

0 Tao Ge, et al. ∙

research

∙ 11/23/2022

TorchScale: Transformers at Scale

Large Transformers have achieved state-of-the-art performance across man...

0 Shuming Ma, et al. ∙

research

∙ 10/27/2022

Joint Optimization of Deployment and Trajectory in UAV and IRS-Assisted IoT Data Collection System

Unmanned aerial vehicles (UAVs) can be applied in many Internet of Thing...

0 Li Dong, et al. ∙

research

∙ 10/26/2022

Beyond English-Centric Bitexts for Better Multilingual Language Representation Learning

In this paper, we elaborate upon recipes for building multilingual repre...

0 Barun Patra, et al. ∙

research

∙ 10/19/2022

A Unified View of Masked Image Modeling

Masked image modeling has demonstrated great potential to eliminate the ...

0 Zhiliang Peng, et al. ∙

research

∙ 10/17/2022

Non-Contrastive Learning Meets Language-Image Pre-Training

Contrastive language-image pre-training (CLIP) serves as a de-facto stan...

1 Jinghao Zhou, et al. ∙

research

∙ 10/13/2022

CROP: Zero-shot Cross-lingual Named Entity Recognition with Multilingual Labeled Sequence Translation

Named entity recognition (NER) suffers from the scarcity of annotated tr...

0 Jian Yang, et al. ∙

research

∙ 10/12/2022

Foundation Transformers

A big convergence of model architectures across language, vision, speech...

26 Hongyu Wang, et al. ∙

research

∙ 09/26/2022

Exploiting Hybrid Active and Passive Multiple Access via Slotted ALOHA-Driven Backscatter Communications

In conventional backscatter communication (BackCom) systems, time divisi...

0 Gu Bowen, et al. ∙

research

∙ 09/03/2022

Semi-Supervised Semantic Segmentation with Cross Teacher Training

Convolutional neural networks can achieve remarkable performance in sema...

0 Hui Xiao, et al. ∙

research

∙ 08/22/2022

Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks

A big convergence of language, vision, and multimodal pretraining is eme...

6 Wenhui Wang, et al. ∙

research

∙ 08/12/2022

BEiT v2: Masked Image Modeling with Vector-Quantized Visual Tokenizers

Masked image modeling (MIM) has demonstrated impressive results in self-...

0 Zhiliang Peng, et al. ∙

research

∙ 06/30/2022

Detecting and Recovering Adversarial Examples from Extracting Non-robust and Highly Predictive Adversarial Perturbations

Deep neural networks (DNNs) have been shown to be vulnerable against adv...

25 Mingyu Dong, et al. ∙

research

∙ 06/13/2022

Language Models are General-Purpose Interfaces

Foundation models have received much attention due to their effectivenes...

0 Yaru Hao, et al. ∙

research

∙ 06/02/2022

VL-BEiT: Generative Vision-Language Pretraining

We introduce a vision-language foundation model called VL-BEiT, which is...

0 Hangbo Bao, et al. ∙

research

∙ 06/01/2022

THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption

As more and more pre-trained language models adopt on-cloud deployment, ...

0 Tianyu Chen, et al. ∙

research

∙ 05/22/2022

Exploiting Constructive Interference for Backscatter Communication Systems

Backscatter communication (BackCom), one of the core technologies to rea...

0 Gu Bowen, et al. ∙

research

∙ 05/20/2022

Prototypical Calibration for Few-shot Learning of Language Models

In-context learning of GPT-like models has been recognized as fragile ac...

0 Zhixiong Han, et al. ∙

research

∙ 05/20/2022

Visually-Augmented Language Modeling

Human language is grounded on multimodal knowledge including visual know...

0 Weizhi Wang, et al. ∙

research

∙ 05/16/2022

Transferability of Adversarial Attacks on Synthetic Speech Detection

Synthetic speech detection is one of the most important research problem...

0 Jiacheng Deng, et al. ∙

research

∙ 05/01/2022

Many a little Makes a Mickle: Probing Backscattering Energy Recycling for Backscatter Communications

In this paper, we investigate and analyze full-duplex-based backscatter ...

0 Gu Bowen, et al. ∙

research

∙ 04/20/2022

On the Representation Collapse of Sparse Mixture of Experts

Sparse mixture of experts provides larger model capacity while requiring...

0 Zewen Chi, et al. ∙

research

∙ 04/18/2022

StableMoE: Stable Routing Strategy for Mixture of Experts

The Mixture-of-Experts (MoE) technique can scale up the model size of Tr...

0 Damai Dai, et al. ∙

research

∙ 03/14/2022

CLIP Models are Few-shot Learners: Empirical Studies on VQA and Visual Entailment

CLIP has shown a remarkable zero-shot capability on a wide range of visi...

0 Haoyu Song, et al. ∙

research

∙ 03/01/2022

DeepNet: Scaling Transformers to 1,000 Layers

In this paper, we propose a simple yet effective method to stabilize ext...

0 Hongyu Wang, et al. ∙

research

∙ 02/27/2022

Controllable Natural Language Generation with Contrastive Prefixes

To guide the generation of large pretrained language models (LM), previo...

9 Jing Qian, et al. ∙

research

∙ 02/17/2022

A Survey of Knowledge-Intensive NLP with Pre-Trained Language Models

With the increasing of model capacity brought by pre-trained language mo...

0 Da Yin, et al. ∙

research

∙ 02/07/2022

Corrupted Image Modeling for Self-Supervised Visual Pre-Training

We introduce Corrupted Image Modeling (CIM) for self-supervised visual p...

0 Yuxin Fang, et al. ∙

Li Dong

Featured Co-authors