b'Nan Du'

research

∙ 09/06/2023

Everyone Deserves A Reward: Learning Customized Human Preferences

Reward models (RMs) are crucial in aligning large language models (LLMs)...

1 Pengyu Cheng, et al. ∙

research

∙ 08/25/2023

Chunk, Align, Select: A Simple Long-sequence Processing Method for Transformers

Although dominant in natural language processing, transformer-based mode...

0 Jiawen Xie, et al. ∙

research

∙ 05/29/2023

Brainformers: Trading Simplicity for Efficiency

Transformers are central to recent successes in natural language process...

0 Yanqi Zhou, et al. ∙

research

∙ 05/24/2023

Flan-MoE: Scaling Instruction-Finetuned Language Models with Sparse Mixture of Experts

The explosive growth of language models and their applications have led ...

0 Sheng Shen, et al. ∙

research

∙ 05/20/2023

Lifelong Language Pretraining with Distribution-Specialized Experts

Pretraining on a large-scale corpus has become a standard method to buil...

0 Wuyang Chen, et al. ∙

research

∙ 05/17/2023

DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining

The mixture proportions of pretraining data domains (e.g., Wikipedia, bo...

0 Sang Michael Xie, et al. ∙

research

∙ 04/11/2023

Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference

We propose Conditional Adapter (CoDA), a parameter-efficient transfer le...

0 Tao Lei, et al. ∙

research

∙ 02/17/2023

Massively Multilingual Shallow Fusion with Large Language Models

While large language models (LLM) have made impressive progress in natur...

0 Ke Hu, et al. ∙

research

∙ 12/19/2022

Review of security techniques for memristor computing systems

Neural network (NN) algorithms have become the dominant tool in visual o...

0 Minhui Zou, et al. ∙

research

∙ 10/07/2022

Physics inspired compact modelling of BiFeO_3 based memristors for hardware security applications

With the advent of the Internet of Things, nanoelectronic devices or mem...

0 Sahitya Yarragolla, et al. ∙

research

∙ 10/06/2022

ReAct: Synergizing Reasoning and Acting in Language Models

While large language models (LLMs) have demonstrated impressive capabili...

7 Shunyu Yao, et al. ∙

research

∙ 04/05/2022

PaLM: Scaling Language Modeling with Pathways

Large language models have been shown to achieve remarkable performance ...

6 Aakanksha Chowdhery, et al. ∙

research

∙ 02/18/2022

Mixture-of-Experts with Expert Choice Routing

Sparsely-activated Mixture-of-experts (MoE) models allow the number of p...

0 Yanqi Zhou, et al. ∙

research

∙ 02/17/2022

Designing Effective Sparse Expert Models

Scale has opened new frontiers in natural language processing – but at a...

0 Barret Zoph, et al. ∙

research

∙ 12/13/2021

GLaM: Efficient Scaling of Language Models with Mixture-of-Experts

Scaling language models with more data, compute and parameters has drive...

4 Nan Du, et al. ∙

research

∙ 09/03/2021

Finetuned Language Models Are Zero-Shot Learners

This paper explores a simple method for improving the zero-shot learning...

0 Jason Wei, et al. ∙

research

∙ 05/10/2021

R2D2: Relational Text Decoding with Transformers

We propose a novel framework for modeling the interaction between graphi...

0 Aryan Arbabi, et al. ∙

research

∙ 03/12/2020

The Medical Scribe: Corpus Development and Model Performance Analyses

There is a growing interest in creating tools to assist in clinical note...

0 Izhak Shafran, et al. ∙

research

∙ 12/04/2019

Deep Physiological State Space Model for Clinical Forecasting

Clinical forecasting based on electronic medical records (EMR) can uncov...

0 Yuan Xue, et al. ∙

research

∙ 08/30/2019

Learning to Infer Entities, Properties and their Relations from Clinical Conversations

Recently we proposed the Span Attribute Tagging (SAT) Model (Du et al., ...

0 Nan Du, et al. ∙

research

∙ 06/20/2019

Multi-Grained Named Entity Recognition

This paper presents a novel framework, MGNER, for Multi-Grained Named En...

0 Congying Xia, et al. ∙

research

∙ 06/05/2019

Extracting Symptoms and their Status from Clinical Conversations

This paper describes novel models tailored for a new application, that o...

0 Nan Du, et al. ∙

research

∙ 12/31/2018

SynonymNet: Multi-context Bilateral Matching for Entity Synonyms

Being able to automatically discover synonymous entities from a large fr...

0 Chenwei Zhang, et al. ∙

research

∙ 12/22/2018

Joint Slot Filling and Intent Detection via Capsule Neural Networks

Being able to recognize words as slots and detect the intent of an utter...

0 Chenwei Zhang, et al. ∙

research

∙ 12/06/2018

Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question Answering

Answer selection and knowledge base question answering (KBQA) are two im...

0 Yang Deng, et al. ∙

research

∙ 11/28/2018

Statistical Robust Chinese Remainder Theorem for Multiple Numbers: Wrapped Gaussian Mixture Model

Generalized Chinese Remainder Theorem (CRT) has been shown to be a power...

0 Nan Du, et al. ∙

research

∙ 11/12/2018

Learning Temporal Point Processes via Reinforcement Learning

Social goods, such as healthcare, smart city, and information networks, ...

0 Shuang Li, et al. ∙

research

∙ 11/01/2018

On the Generation of Medical Question-Answer Pairs

Question answering (QA) has achieved promising progress recently. Howeve...

0 Sheng Shen, et al. ∙

research

∙ 10/14/2018

Finding Similar Medical Questions from Question Answering Websites

The past few years have witnessed the flourishing of crowdsourced medica...

0 Yaliang Li, et al. ∙

research

∙ 09/27/2018

When Truth Discovery Meets Medical Knowledge Graph: Estimating Trustworthiness Degree for Medical Knowledge Condition

Medical knowledge graph is the core component for various medical applic...

0 Yang Deng, et al. ∙

research

∙ 08/15/2018

AnatomyNet: Deep 3D Squeeze-and-excitation U-Nets for fast and fully automated whole-volume anatomical segmentation

Radiation therapy (RT) is a common treatment for head and neck (HaN) can...

10 Wentao Zhu, et al. ∙

research

∙ 08/15/2018

AnatomyNet: Deep Learning for Fast and Fully Automated Whole-volume Segmentation of Head and Neck Anatomy

Methods: Our deep learning model, called AnatomyNet, segments OARs from ...

0 Wentao Zhu, et al. ∙

research

∙ 10/22/2017

Bringing Semantic Structures to User Intent Detection in Online Medical Queries

The Internet has revolutionized healthcare by offering medical informati...

0 Chenwei Zhang, et al. ∙

research

∙ 05/20/2016

Variational hybridization and transformation for large inaccurate noisy-or networks

Variational inference provides approximations to the computationally int...

0 Yusheng Xie, et al. ∙

research

∙ 12/08/2013

Budgeted Influence Maximization for Multiple Products

The typical algorithmic problem in viral marketing aims to identify a se...

0 Nan Du, et al. ∙

Nan Du

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