b'Xiaodong Liu'

research

∙ 08/29/2023

Decentralized Multi-agent Reinforcement Learning based State-of-Charge Balancing Strategy for Distributed Energy Storage System

This paper develops a Decentralized Multi-Agent Reinforcement Learning (...

0 Zheng Xiong, 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

∙ 05/23/2023

Pre-training Multi-task Contrastive Learning Models for Scientific Literature Understanding

Scientific literature understanding tasks have gained significant attent...

0 Yu Zhang, et al. ∙

research

∙ 05/21/2023

Model-Generated Pretraining Signals Improves Zero-Shot Generalization of Text-to-Text Transformers

This paper explores the effectiveness of model-generated signals in impr...

0 Linyuan Gong, et al. ∙

research

∙ 05/04/2023

Chain-of-Skills: A Configurable Model for Open-domain Question Answering

The retrieval model is an indispensable component for real-world knowled...

0 Kaixin Ma, et al. ∙

research

∙ 04/17/2023

Bridging Discrete and Backpropagation: Straight-Through and Beyond

Backpropagation, the cornerstone of deep learning, is limited to computi...

0 Liyuan Liu, et al. ∙

research

∙ 03/28/2023

Pre-training Transformers for Knowledge Graph Completion

Learning transferable representation of knowledge graphs (KGs) is challe...

0 Sanxing Chen, et al. ∙

research

∙ 02/20/2023

Deep Vision in Analysis and Recognition of Radar Data: Achievements, Advancements and Challenges

Radars are widely used to obtain echo information for effective predicti...

0 Qi Liu, 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

∙ 12/15/2022

Efficient Long Sequence Modeling via State Space Augmented Transformer

Transformer models have achieved superior performance in various natural...

0 Simiao Zuo, et al. ∙

research

∙ 10/31/2022

AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning

Standard fine-tuning of large pre-trained language models (PLMs) for dow...

0 Yaqing Wang, et al. ∙

research

∙ 10/22/2022

Open-domain Question Answering via Chain of Reasoning over Heterogeneous Knowledge

We propose a novel open-domain question answering (ODQA) framework for a...

0 Kaixin Ma, et al. ∙

research

∙ 10/14/2022

AutoMoE: Neural Architecture Search for Efficient Sparsely Activated Transformers

Neural architecture search (NAS) has demonstrated promising results on i...

1 Ganesh Jawahar, et al. ∙

research

∙ 10/11/2022

Task-Aware Specialization for Efficient and Robust Dense Retrieval for Open-Domain Question Answering

Given its effectiveness on knowledge-intensive natural language processi...

0 Hao Cheng, et al. ∙

research

∙ 09/06/2022

PTSEFormer: Progressive Temporal-Spatial Enhanced TransFormer Towards Video Object Detection

Recent years have witnessed a trend of applying context frames to boost ...

0 Han Wang, et al. ∙

research

∙ 08/30/2022

Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models

Deep generative models (DGMs) are data-eager. Essentially, it is because...

6 Yong Zhong, et al. ∙

research

∙ 05/24/2022

AdaMix: Mixture-of-Adapter for Parameter-efficient Tuning of Large Language Models

Fine-tuning large-scale pre-trained language models to downstream tasks ...

0 Yaqing Wang, 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

∙ 04/13/2022

METRO: Efficient Denoising Pretraining of Large Scale Autoencoding Language Models with Model Generated Signals

We present an efficient method of pretraining large-scale autoencoding l...

0 Payal Bajaj, et al. ∙

research

∙ 03/07/2022

Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

Hyperparameter (HP) tuning in deep learning is an expensive process, pro...

2 Greg Yang, 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

∙ 02/06/2022

No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models

Recent research has shown the existence of significant redundancy in lar...

0 Chen Liang, et al. ∙

research

∙ 02/02/2022

Spectral and Energy Efficiency of DCO-OFDM in Visible Light Communication Systems with Finite-Alphabet Inputs

The bound of the information transmission rate of direct current biased ...

0 Ruixin Yang, et al. ∙

research

∙ 01/29/2022

AutoDistil: Few-shot Task-agnostic Neural Architecture Search for Distilling Large Language Models

Knowledge distillation (KD) methods compress large models into smaller s...

6 Dongkuan Xu, et al. ∙

research

∙ 12/15/2021

Knowledge-Rich Self-Supervised Entity Linking

Entity linking faces significant challenges, such as prolific variations...

0 Sheng Zhang, et al. ∙

research

∙ 12/15/2021

Fine-Tuning Large Neural Language Models for Biomedical Natural Language Processing

Motivation: A perennial challenge for biomedical researchers and clinica...

0 Robert Tinn, 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

∙ 11/04/2021

CLUES: Few-Shot Learning Evaluation in Natural Language Understanding

Most recent progress in natural language understanding (NLU) has been dr...

2 Subhabrata Mukherjee, et al. ∙

research

∙ 10/16/2021

Open Domain Question Answering over Virtual Documents: A Unified Approach for Data and Text

Due to its potential for a universal interface over both data and text, ...

0 Kaixin Ma, et al. ∙

research

∙ 10/12/2021

LiST: Lite Self-training Makes Efficient Few-shot Learners

We present a new method LiST for efficient fine-tuning of large pre-trai...

9 Yaqing Wang, et al. ∙

research

∙ 10/08/2021

Taming Sparsely Activated Transformer with Stochastic Experts

Sparsely activated models (SAMs), such as Mixture-of-Experts (MoE), can ...

2 Simiao Zuo, et al. ∙

research

∙ 09/24/2021

SEED: Semantic Graph based Deep detection for type-4 clone

Background: Type-4 clones refer to a pair of code snippets with similar ...

0 Zhipeng Xue, et al. ∙

research

∙ 09/15/2021

ARCH: Efficient Adversarial Regularized Training with Caching

Adversarial regularization can improve model generalization in many natu...

0 Simiao Zuo, et al. ∙

research

∙ 09/03/2021

A multi-frequency sampling method for the inverse source problems with sparse measurements

We consider the inverse source problems with multi-frequency sparse near...

0 Xiaodong Liu, et al. ∙

research

∙ 08/16/2021

Robust Beamforming Design for Rate Splitting Multiple Access-Aided MISO Visible Light Communications

This paper addresses robust beamforming design for rate splitting multip...

0 Shuai Ma, et al. ∙

research

∙ 07/01/2021

Modified sampling method with near field measurements

This paper investigates the inverse scattering problems using sampling m...

0 Xiaodong Liu, et al. ∙

research

∙ 06/21/2021

Data completion algorithms and their applications in inverse acoustic scattering with limited-aperture backscattering data

We introduce two data completion algorithms for the limited-aperture pro...

0 Fangfang Dou, et al. ∙

research

∙ 05/25/2021

Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization

The Lottery Ticket Hypothesis suggests that an over-parametrized network...

0 Chen Liang, et al. ∙

research

∙ 04/12/2021

Targeted Adversarial Training for Natural Language Understanding

We present a simple yet effective Targeted Adversarial Training (TAT) al...

0 Lis Pereira, et al. ∙

research

∙ 04/11/2021

Adversarial Training as Stackelberg Game: An Unrolled Optimization Approach

Adversarial training has been shown to improve the generalization perfor...

0 Simiao Zuo, et al. ∙

research

∙ 04/10/2021

Unveiling personnel movement in a larger indoor area with a non-overlapping multi-camera system

Surveillance cameras are widely applied for indoor occupancy measurement...

19 Ping Zhang, et al. ∙

research

∙ 03/22/2021

ConfInLog: Leveraging Software Logs to Infer Configuration Constraints

Misconfigurations have become the dominant causes of software failures i...

0 Shulin Zhou, et al. ∙

research

∙ 03/20/2021

Token-wise Curriculum Learning for Neural Machine Translation

Existing curriculum learning approaches to Neural Machine Translation (N...

0 Chen Liang, et al. ∙

research

∙ 03/11/2021

Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multiple Data Sources

Air pollution has altered the Earth radiation balance, disturbed the eco...

0 Guannan Geng, et al. ∙

research

∙ 02/23/2021

A discontinuous Galerkin method based on a hierarchical orthogonal basis for Lagrangian hydrodynamics on curvilinear grids

We present a new high-order accurate Lagrangian discontinuous Galerkin (...

0 Xiaodong Liu, et al. ∙

research

∙ 02/17/2021

DepOwl: Detecting Dependency Bugs to Prevent Compatibility Failures

Applications depend on libraries to avoid reinventing the wheel. Librari...

0 Zhouyang Jia, et al. ∙

research

∙ 01/01/2021

Reader-Guided Passage Reranking for Open-Domain Question Answering

Current open-domain question answering (QA) systems often follow a Retri...

0 Yuning Mao, et al. ∙

research

∙ 01/01/2021

UnitedQA: A Hybrid Approach for Open Domain Question Answering

To date, most of recent work under the retrieval-reader framework for op...

0 Hao Cheng, et al. ∙

research

∙ 01/01/2021

NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned

We review the EfficientQA competition from NeurIPS 2020. The competition...

15 Sewon Min, et al. ∙

research

∙ 10/23/2020

Posterior Differential Regularization with f-divergence for Improving Model Robustness

We address the problem of enhancing model robustness through regularizat...

0 Hao Cheng, et al. ∙

Xiaodong Liu

Featured Co-authors