b'Michael Zeng'

research

∙ 05/24/2023

ComSL: A Composite Speech-Language Model for End-to-End Speech-to-Text Translation

Joint speech-language training is challenging due to the large demand fo...

0 Chenyang Le, et al. ∙

research

∙ 05/23/2023

i-Code Studio: A Configurable and Composable Framework for Integrative AI

Artificial General Intelligence (AGI) requires comprehensive understandi...

0 Yuwei Fang, et al. ∙

research

∙ 05/21/2023

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data

The convergence of text, visual, and audio data is a key step towards hu...

0 ZiYi Yang, et al. ∙

research

∙ 05/19/2023

Any-to-Any Generation via Composable Diffusion

We present Composable Diffusion (CoDi), a novel generative model capable...

3 Zineng Tang, et al. ∙

research

∙ 05/17/2023

Evolving the Digital Industrial Infrastructure for Production: Steps Taken and the Road Ahead

The Internet of Production (IoP) leverages concepts such as digital shad...

0 Jan Pennekamp, et al. ∙

research

∙ 05/04/2023

Automatic Prompt Optimization with "Gradient Descent" and Beam Search

Large Language Models (LLMs) have shown impressive performance as genera...

0 Reid Pryzant, et al. ∙

research

∙ 03/20/2023

MM-REACT: Prompting ChatGPT for Multimodal Reasoning and Action

We propose MM-REACT, a system paradigm that integrates ChatGPT with a po...

0 Zhengyuan Yang, et al. ∙

research

∙ 03/20/2023

Code-Switching Text Generation and Injection in Mandarin-English ASR

Code-switching speech refers to a means of expression by mixing two or m...

0 Haibin Yu, et al. ∙

research

∙ 10/28/2022

A comprehensive study on self-supervised distillation for speaker representation learning

In real application scenarios, it is often challenging to obtain a large...

0 Zhengyang Chen, et al. ∙

research

∙ 09/21/2022

Generate rather than Retrieve: Large Language Models are Strong Context Generators

Knowledge-intensive tasks, such as open-domain question answering (QA), ...

0 Wenhao Yu, et al. ∙

research

∙ 06/03/2022

Visual Clues: Bridging Vision and Language Foundations for Image Paragraph Captioning

People say, "A picture is worth a thousand words". Then how can we get t...

0 Yujia Xie, et al. ∙

research

∙ 05/18/2022

Automatic Rule Induction for Efficient Semi-Supervised Learning

Semi-supervised learning has shown promise in allowing NLP models to gen...

0 Reid Pryzant, et al. ∙

research

∙ 05/03/2022

i-Code: An Integrative and Composable Multimodal Learning Framework

Human intelligence is multimodal; we integrate visual, linguistic, and a...

1 ZiYi Yang, et al. ∙

research

∙ 04/13/2022

Impossible Triangle: What's Next for Pre-trained Language Models?

Recent development of large-scale pre-trained language models (PLM) have...

0 Chenguang Zhu, et al. ∙

research

∙ 01/13/2022

CLIP-Event: Connecting Text and Images with Event Structures

Vision-language (V+L) pretraining models have achieved great success in ...

6 Manling Li, et al. ∙

research

∙ 12/10/2021

Sequence-level self-learning with multiple hypotheses

In this work, we develop new self-learning techniques with an attention-...

0 Kenichi Kumatani, et al. ∙

research

∙ 12/08/2021

MLP Architectures for Vision-and-Language Modeling: An Empirical Study

We initiate the first empirical study on the use of MLP architectures fo...

2 Yixin Nie, et al. ∙

research

∙ 12/06/2021

Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention

Most of today's AI systems focus on using self-attention mechanisms and ...

3 Yichong Xu, et al. ∙

research

∙ 11/22/2021

Florence: A New Foundation Model for Computer Vision

Automated visual understanding of our diverse and open world demands com...

4 Lu Yuan, et al. ∙

research

∙ 11/03/2021

An Empirical Study of Training End-to-End Vision-and-Language Transformers

Vision-and-language (VL) pre-training has proven to be highly effective ...

0 Zi-Yi Dou, et al. ∙

research

∙ 10/26/2021

WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing

Self-supervised learning (SSL) achieves great success in speech recognit...

0 Sanyuan Chen, et al. ∙

research

∙ 10/23/2021

Optimizing Alignment of Speech and Language Latent Spaces for End-to-End Speech Recognition and Understanding

The advances in attention-based encoder-decoder (AED) networks have brou...

1 Wei Wang, et al. ∙

research

∙ 10/19/2021

PI(t)D(t) Control and Motion Profiling for Omnidirectional Mobile Robots

Recently, a trend is emerging toward human-servicing autonomous mobile r...

0 Michael Zeng, et al. ∙

research

∙ 10/16/2021

Leveraging Knowledge in Multilingual Commonsense Reasoning

Commonsense reasoning (CSR) requires the model to be equipped with gener...

0 Yuwei Fang, et al. ∙

research

∙ 10/13/2021

Dict-BERT: Enhancing Language Model Pre-training with Dictionary

Pre-trained language models (PLMs) aim to learn universal language repre...

0 Wenhao Yu, et al. ∙

research

∙ 10/12/2021

Large-scale Self-Supervised Speech Representation Learning for Automatic Speaker Verification

The speech representations learned from large-scale unlabeled data have ...

0 Zhengyang Chen, et al. ∙

research

∙ 10/08/2021

KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering

Current Open-Domain Question Answering (ODQA) model paradigm often conta...

0 Donghan Yu, et al. ∙

research

∙ 09/01/2021

Does Knowledge Help General NLU? An Empirical Study

It is often observed in knowledge-centric tasks (e.g., common sense ques...

4 Ruochen Xu, et al. ∙

research

∙ 07/25/2021

A Joint and Domain-Adaptive Approach to Spoken Language Understanding

Spoken Language Understanding (SLU) is composed of two subtasks: intent ...

1 Linhao Zhang, et al. ∙

research

∙ 02/22/2021

Generating Human Readable Transcript for Automatic Speech Recognition with Pre-trained Language Model

Modern Automatic Speech Recognition (ASR) systems can achieve high perfo...

10 Junwei Liao, et al. ∙

research

∙ 02/12/2021

Improving Zero-shot Neural Machine Translation on Language-specific Encoders-Decoders

Recently, universal neural machine translation (NMT) with shared encoder...

12 Junwei Liao, et al. ∙

research

∙ 02/11/2021

Speech-language Pre-training for End-to-end Spoken Language Understanding

End-to-end (E2E) spoken language understanding (SLU) can infer semantics...

9 Yao Qian, et al. ∙

research

∙ 01/19/2021

UniSpeech: Unified Speech Representation Learning with Labeled and Unlabeled Data

In this paper, we propose a unified pre-training approach called UniSpee...

21 Chengyi Wang, et al. ∙

research

∙ 12/09/2020

Fusing Context Into Knowledge Graph for Commonsense Reasoning

Commonsense reasoning requires a model to make presumptions about world ...

14 Yichong Xu, et al. ∙

research

∙ 10/21/2020

LSTM-LM with Long-Term History for First-Pass Decoding in Conversational Speech Recognition

LSTM language models (LSTM-LMs) have been proven to be powerful and yiel...

0 Xie Chen, et al. ∙

research

∙ 10/18/2020

Mixed-Lingual Pre-training for Cross-lingual Summarization

Cross-lingual Summarization (CLS) aims at producing a summary in the tar...

7 Ruochen Xu, et al. ∙

research

∙ 10/05/2020

Semi-Supervised Speech-Language Joint Pre-Training for Spoken Language Understanding

Spoken language understanding (SLU) requires a model to analyze input ac...

0 Yu-An Chung, et al. ∙

research

∙ 10/02/2020

JAKET: Joint Pre-training of Knowledge Graph and Language Understanding

Knowledge graphs (KGs) contain rich information about world knowledge, e...

0 Donghan Yu, et al. ∙

research

∙ 06/27/2020

Mind The Facts: Knowledge-Boosted Coherent Abstractive Text Summarization

Neural models have become successful at producing abstractive summaries ...

0 Beliz Gunel, et al. ∙

research

∙ 06/03/2020

Meta Dialogue Policy Learning

Dialog policy determines the next-step actions for agents and hence is c...

0 Yumo Xu, et al. ∙

research

∙ 04/29/2020

Data Augmentation for Spoken Language Understanding via Pretrained Models

The training of spoken language understanding (SLU) models often faces t...

0 Baolin Peng, et al. ∙

research

∙ 04/09/2020

Improving Readability for Automatic Speech Recognition Transcription

Modern Automatic Speech Recognition (ASR) systems can achieve high perfo...

0 Junwei Liao, et al. ∙

research

∙ 04/04/2020

End-to-End Abstractive Summarization for Meetings

With the abundance of automatic meeting transcripts, meeting summarizati...

1 Chenguang Zhu, et al. ∙

research

∙ 03/19/2020

Boosting Factual Correctness of Abstractive Summarization

A commonly observed problem with abstractive summarization is the distor...

0 Chenguang Zhu, et al. ∙

research

∙ 03/19/2020

Boosting Factual Correctness of Abstractive Summarization with Knowledge Graph

A commonly observed problem with abstractive summarization is the distor...

0 Chenguang Zhu, et al. ∙

research

∙ 02/27/2020

Few-shot Natural Language Generation for Task-Oriented Dialog

As a crucial component in task-oriented dialog systems, the Natural Lang...

0 Baolin Peng, et al. ∙

research

∙ 01/03/2020

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising

Text summarization aims to extract essential information from a piece of...

0 ZiYi Yang, et al. ∙

research

∙ 12/25/2019

Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization

Lead bias is a common phenomenon in news summarization, where early part...

0 Chenguang Zhu, et al. ∙

research

∙ 09/26/2019

SIM: A Slot-Independent Neural Model for Dialogue State Tracking

Dialogue state tracking is an important component in task-oriented dialo...

0 Chenguang Zhu, et al. ∙

research

∙ 05/03/2019

Meeting Transcription Using Virtual Microphone Arrays

We describe a system that generates speaker-annotated transcripts of mee...

0 Takuya Yoshioka, et al. ∙

Michael Zeng

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