b'Yaliang Li'

research

∙ 09/05/2023

Data-Juicer: A One-Stop Data Processing System for Large Language Models

The immense evolution in Large Language Models (LLMs) has underscored th...

0 Daoyuan Chen, et al. ∙

research

∙ 09/01/2023

FederatedScope-LLM: A Comprehensive Package for Fine-tuning Large Language Models in Federated Learning

LLMs have demonstrated great capabilities in various NLP tasks. Differen...

0 Weirui Kuang, et al. ∙

research

∙ 08/29/2023

Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation

Large language models (LLMs) have emerged as a new paradigm for Text-to-...

0 Dawei Gao, et al. ∙

research

∙ 08/16/2023

TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series

This work summarizes two strategies for completing time-series (TS) task...

0 Chenxi Sun, et al. ∙

research

∙ 07/16/2023

Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study

Despite the superior performance, Large Language Models (LLMs) require s...

0 Peiyu Liu, et al. ∙

research

∙ 05/18/2023

Counterfactual Debiasing for Generating Factually Consistent Text Summaries

Despite substantial progress in abstractive text summarization to genera...

0 Chenhe Dong, et al. ∙

research

∙ 05/04/2023

Efficient Personalized Federated Learning via Sparse Model-Adaptation

Federated Learning (FL) aims to train machine learning models for multip...

0 Daoyuan Chen, et al. ∙

research

∙ 04/11/2023

HPN: Personalized Federated Hyperparameter Optimization

Numerous research studies in the field of federated learning (FL) have a...

0 Anda Cheng, et al. ∙

research

∙ 03/24/2023

LONGNN: Spectral GNNs with Learnable Orthonormal Basis

In recent years, a plethora of spectral graph neural networks (GNN) meth...

0 Qian Tao, et al. ∙

research

∙ 03/23/2023

FS-Real: Towards Real-World Cross-Device Federated Learning

Federated Learning (FL) aims to train high-quality models in collaborati...

0 Daoyuan Chen, et al. ∙

research

∙ 02/03/2023

Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks

In this work, besides improving prediction accuracy, we study whether pe...

0 Zeyu Qin, et al. ∙

research

∙ 12/12/2022

Collaborating Heterogeneous Natural Language Processing Tasks via Federated Learning

The increasing privacy concerns on personal private text data promote th...

0 Chenhe Dong, et al. ∙

research

∙ 10/21/2022

Privacy-Preserved Neural Graph Similarity Learning

To develop effective and efficient graph similarity learning (GSL) model...

0 Yupeng Hou, et al. ∙

research

∙ 07/05/2022

Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing

Big data processing at the production scale presents a highly complex en...

0 Chenghao Lyu, et al. ∙

research

∙ 06/13/2022

Towards Universal Sequence Representation Learning for Recommender Systems

In order to develop effective sequential recommenders, a series of seque...

0 Yupeng Hou, et al. ∙

research

∙ 06/08/2022

FedHPO-B: A Benchmark Suite for Federated Hyperparameter Optimization

Hyperparameter optimization (HPO) is crucial for machine learning algori...

0 Zhen Wang, et al. ∙

research

∙ 06/08/2022

pFL-Bench: A Comprehensive Benchmark for Personalized Federated Learning

Personalized Federated Learning (pFL), which utilizes and deploys distin...

0 Daoyuan Chen, et al. ∙

research

∙ 06/07/2022

Federated Hetero-Task Learning

To investigate the heterogeneity of federated learning in real-world sce...

0 Liuyi Yao, et al. ∙

research

∙ 06/06/2022

ID-Agnostic User Behavior Pre-training for Sequential Recommendation

Recently, sequential recommendation has emerged as a widely studied topi...

0 Shanlei Mu, et al. ∙

research

∙ 05/27/2022

EvenNet: Ignoring Odd-Hop Neighbors Improves Robustness of Graph Neural Networks

Graph Neural Networks (GNNs) have received extensive research attention ...

0 Runlin Lei, et al. ∙

research

∙ 04/12/2022

FederatedScope-GNN: Towards a Unified, Comprehensive and Efficient Package for Federated Graph Learning

The incredible development of federated learning (FL) has benefited vari...

0 Zhen Wang, et al. ∙

research

∙ 04/11/2022

FederatedScope: A Comprehensive and Flexible Federated Learning Platform via Message Passing

Although remarkable progress has been made by the existing federated lea...

0 Yuexiang Xie, et al. ∙

research

∙ 12/27/2021

Towards Personalized Answer Generation in E-Commerce via Multi-Perspective Preference Modeling

Recently, Product Question Answering (PQA) on E-Commerce platforms has a...

5 Yang Deng, et al. ∙

research

∙ 10/16/2021

HRKD: Hierarchical Relational Knowledge Distillation for Cross-domain Language Model Compression

On many natural language processing tasks, large pre-trained language mo...

0 Chenhe Dong, et al. ∙

research

∙ 08/30/2021

Factual Consistency Evaluation for Text Summarization via Counterfactual Estimation

Despite significant progress has been achieved in text summarization, fa...

0 Yuexiang Xie, et al. ∙

research

∙ 07/09/2021

Automated Graph Learning via Population Based Self-Tuning GCN

Owing to the remarkable capability of extracting effective graph embeddi...

0 Ronghang Zhu, et al. ∙

research

∙ 06/02/2021

Differential Privacy for Text Analytics via Natural Text Sanitization

Texts convey sophisticated knowledge. However, texts also convey sensiti...

0 Xiang Yue, et al. ∙

research

∙ 05/20/2021

Unified Conversational Recommendation Policy Learning via Graph-based Reinforcement Learning

Conversational recommender systems (CRS) enable the traditional recommen...

0 Yang Deng, et al. ∙

research

∙ 04/12/2021

Contextualized Knowledge-aware Attentive Neural Network: Enhancing Answer Selection with Knowledge

Answer selection, which is involved in many natural language processing ...

0 Yang Deng, et al. ∙

research

∙ 01/20/2021

Learning to Augment for Data-Scarce Domain BERT Knowledge Distillation

Despite pre-trained language models such as BERT have achieved appealing...

0 Lingyun Feng, et al. ∙

research

∙ 01/04/2021

CRSLab: An Open-Source Toolkit for Building Conversational Recommender System

In recent years, conversational recommender system (CRS) has received mu...

0 Kun Zhou, et al. ∙

research

∙ 01/04/2021

A Pluggable Learned Index Method via Sampling and Gap Insertion

Database indexes facilitate data retrieval and benefit broad application...

0 Yaliang Li, et al. ∙

research

∙ 12/02/2020

Meta-KD: A Meta Knowledge Distillation Framework for Language Model Compression across Domains

Pre-trained language models have been applied to various NLP tasks with ...

0 Haojie Pan, et al. ∙

research

∙ 11/18/2020

EasyTransfer – A Simple and Scalable Deep Transfer Learning Platform for NLP Applications

The literature has witnessed the success of applying deep Transfer Learn...

63 Minghui Qiu, et al. ∙

research

∙ 11/03/2020

RecBole: Towards a Unified, Comprehensive and Efficient Framework for Recommendation Algorithms

In recent years, there are a large number of recommendation algorithms p...

0 Wayne Xin Zhao, et al. ∙

research

∙ 07/29/2020

Interactive Feature Generation via Learning Adjacency Tensor of Feature Graph

To automate the generation of interactive features, recent methods are p...

3 Yuexiang Xie, et al. ∙

research

∙ 07/04/2020

Simple and Deep Graph Convolutional Networks

Graph convolutional networks (GCNs) are a powerful deep learning approac...

0 Ming Chen, et al. ∙

research

∙ 05/21/2020

Sequential Recommendation with Self-Attentive Multi-Adversarial Network

Recently, deep learning has made significant progress in the task of seq...

0 Ruiyang Ren, et al. ∙

research

∙ 04/21/2020

Relabel the Noise: Joint Extraction of Entities and Relations via Cooperative Multiagents

Distant supervision based methods for entity and relation extraction hav...

0 Daoyuan Chen, et al. ∙

research

∙ 04/07/2020

Practical Data Poisoning Attack against Next-Item Recommendation

Online recommendation systems make use of a variety of information sourc...

0 Hengtong Zhang, et al. ∙

research

∙ 02/05/2020

A Survey on Causal Inference

Causal inference is a critical research topic across many domains, such ...

25 Liuyi Yao, et al. ∙

research

∙ 01/13/2020

AdaBERT: Task-Adaptive BERT Compression with Differentiable Neural Architecture Search

Large pre-trained language models such as BERT have shown their effectiv...

0 Daoyuan Chen, et al. ∙

research

∙ 01/03/2020

Automated Relational Meta-learning

In order to efficiently learn with small amount of data on new tasks, me...

6 Huaxiu Yao, et al. ∙

research

∙ 11/22/2019

Joint Learning of Answer Selection and Answer Summary Generation in Community Question Answering

Community question answering (CQA) gains increasing popularity in both a...

0 Yang Deng, 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

∙ 04/26/2019

Towards Data Poisoning Attack against Knowledge Graph Embedding

Knowledge graph embedding (KGE) is a technique for learning continuous e...

0 Hengtong Zhang, 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

∙ 11/01/2018

On the Generation of Medical Question-Answer Pairs

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

0 Sheng Shen, et al. ∙

Yaliang Li

Featured Co-authors