Wayne Xin Zhao

research

∙ 08/24/2023

Unified Data Management and Comprehensive Performance Evaluation for Urban Spatial-Temporal Prediction [Experiment, Analysis Benchmark]

The field of urban spatial-temporal prediction is advancing rapidly with...

0 Jiawei Jiang, et al. ∙

research

∙ 08/01/2023

Towards Effective Ancient Chinese Translation: Dataset, Model, and Evaluation

Interpreting ancient Chinese has been the key to comprehending vast Chin...

0 Geyang Guo, et al. ∙

research

∙ 07/21/2023

Alleviating the Long-Tail Problem in Conversational Recommender Systems

Conversational recommender systems (CRS) aim to provide the recommendati...

0 Zhipeng Zhao, 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

∙ 06/19/2023

JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solving

Although pre-trained language models (PLMs) have recently advanced the r...

0 Wayne Xin Zhao, et al. ∙

research

∙ 06/05/2023

Improving Conversational Recommendation Systems via Counterfactual Data Simulation

Conversational recommender systems (CRSs) aim to provide recommendation ...

0 Xiaolei Wang, et al. ∙

research

∙ 06/04/2023

Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning

Chain-of-thought prompting (CoT) and tool augmentation have been validat...

0 Beichen Zhang, et al. ∙

research

∙ 05/26/2023

Zero-shot Visual Question Answering with Language Model Feedback

In this paper, we propose a novel language model guided captioning appro...

0 Yifan Du, et al. ∙

research

∙ 05/26/2023

Learning to Imagine: Visually-Augmented Natural Language Generation

People often imagine relevant scenes to aid in the writing process. In t...

0 Tianyi Tang, et al. ∙

research

∙ 05/24/2023

Not All Metrics Are Guilty: Improving NLG Evaluation with LLM Paraphrasing

Most research about natural language generation (NLG) relies on evaluati...

0 Tianyi Tang, et al. ∙

research

∙ 05/23/2023

ChatCoT: Tool-Augmented Chain-of-Thought Reasoning on Chat-based Large Language Models

Although large language models (LLMs) have achieved excellent performanc...

0 Zhipeng Chen, et al. ∙

research

∙ 05/22/2023

Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models

The recent success of large language models (LLMs) has shown great poten...

0 Xiaolei Wang, et al. ∙

research

∙ 05/19/2023

HaluEval: A Large-Scale Hallucination Evaluation Benchmark for Large Language Models

Large language models (LLMs), such as ChatGPT, are prone to generate hal...

0 Junyi Li, et al. ∙

research

∙ 05/18/2023

The Web Can Be Your Oyster for Improving Large Language Models

Large language models (LLMs) encode a large amount of world knowledge. H...

0 Junyi Li, et al. ∙

research

∙ 05/17/2023

Evaluating Object Hallucination in Large Vision-Language Models

Inspired by the superior language abilities of large language models (LL...

0 Yifan Li, et al. ∙

research

∙ 05/16/2023

StructGPT: A General Framework for Large Language Model to Reason over Structured Data

In this paper, we study how to improve the zero-shot reasoning ability o...

0 Jinhao Jiang, et al. ∙

research

∙ 05/15/2023

Large Language Models are Zero-Shot Rankers for Recommender Systems

Recently, large language models (LLMs) (e.g. GPT-4) have demonstrated im...

0 Yupeng Hou, et al. ∙

research

∙ 05/11/2023

Not All Languages Are Created Equal in LLMs: Improving Multilingual Capability by Cross-Lingual-Thought Prompting

Large language models (LLMs) demonstrate impressive multilingual capabil...

0 Haoyang Huang, et al. ∙

research

∙ 05/11/2023

Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach

In the past decades, recommender systems have attracted much attention i...

0 Junjie Zhang, et al. ∙

research

∙ 05/06/2023

Diffusion-NAT: Self-Prompting Discrete Diffusion for Non-Autoregressive Text Generation

Recently, continuous diffusion models (CDM) have been introduced into no...

0 Kun Zhou, et al. ∙

research

∙ 04/27/2023

Towards Efficient and Comprehensive Urban Spatial-Temporal Prediction: A Unified Library and Performance Benchmark

As deep learning technology advances and more urban spatial-temporal dat...

0 Jingyuan Wang, et al. ∙

research

∙ 04/25/2023

RenderDiffusion: Text Generation as Image Generation

Diffusion models have become a new generative paradigm for text generati...

0 Junyi Li, et al. ∙

research

∙ 04/21/2023

EulerNet: Adaptive Feature Interaction Learning via Euler's Formula for CTR Prediction

Learning effective high-order feature interactions is very crucial in th...

0 Zhen Tian, et al. ∙

research

∙ 03/27/2023

Scaling Pre-trained Language Models to Deeper via Parameter-efficient Architecture

In this paper, we propose a highly parameter-efficient approach to scali...

0 Peiyu Liu, et al. ∙

research

∙ 03/12/2023

Diffusion Models for Non-autoregressive Text Generation: A Survey

Non-autoregressive (NAR) text generation has attracted much attention in...

0 Yifan Li, et al. ∙

research

∙ 02/28/2023

A Survey on Long Text Modeling with Transformers

Modeling long texts has been an essential technique in the field of natu...

0 Zican Dong, et al. ∙

research

∙ 01/19/2023

PDFormer: Propagation Delay-aware Dynamic Long-range Transformer for Traffic Flow Prediction

As a core technology of Intelligent Transportation System, traffic flow ...

0 Jiawei Jiang, et al. ∙

research

∙ 01/16/2023

Continuous Trajectory Generation Based on Two-Stage GAN

Simulating the human mobility and generating large-scale trajectories ar...

0 Wenjun Jiang, et al. ∙

research

∙ 12/26/2022

TextBox 2.0: A Text Generation Library with Pre-trained Language Models

To facilitate research on text generation, this paper presents a compreh...

0 Tianyi Tang, et al. ∙

research

∙ 12/15/2022

Visually-augmented pretrained language models for NLP tasks without images

Although pre-trained language models (PLMs) have shown impressive perfor...

0 Hangyu Guo, et al. ∙

research

∙ 12/15/2022

MASTER: Multi-task Pre-trained Bottlenecked Masked Autoencoders are Better Dense Retrievers

Dense retrieval aims to map queries and passages into low-dimensional ve...

0 Kun Zhou, et al. ∙

research

∙ 12/02/2022

UniKGQA: Unified Retrieval and Reasoning for Solving Multi-hop Question Answering Over Knowledge Graph

Multi-hop Question Answering over Knowledge Graph (KGQA) aims to find th...

0 Jinhao Jiang, et al. ∙

research

∙ 11/21/2022

Directed Acyclic Graph Factorization Machines for CTR Prediction via Knowledge Distillation

With the growth of high-dimensional sparse data in web-scale recommender...

0 Zhen Tian, et al. ∙

research

∙ 10/24/2022

ELMER: A Non-Autoregressive Pre-trained Language Model for Efficient and Effective Text Generation

We study the text generation task under the approach of pre-trained lang...

0 Junyi Li, et al. ∙

research

∙ 10/22/2022

Learning Vector-Quantized Item Representation for Transferable Sequential Recommenders

Recently, the generality of natural language text has been leveraged to ...

0 Yupeng Hou, et al. ∙

research

∙ 10/21/2022

SimANS: Simple Ambiguous Negatives Sampling for Dense Text Retrieval

Sampling proper negatives from a large document pool is vital to effecti...

0 Kun Zhou, 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

∙ 06/24/2022

MVP: Multi-task Supervised Pre-training for Natural Language Generation

Pre-trained language models (PLMs) have achieved notable success in natu...

6 Tianyi Tang, et al. ∙

research

∙ 06/19/2022

Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning

Conversational recommender systems (CRS) aim to proactively elicit user ...

0 Xiaolei Wang, et al. ∙

research

∙ 06/15/2022

RecBole 2.0: Towards a More Up-to-Date Recommendation Library

In order to support the study of recent advances in recommender systems,...

0 Wayne Xin Zhao, et al. ∙

research

∙ 06/13/2022

JiuZhang: A Chinese Pre-trained Language Model for Mathematical Problem Understanding

This paper aims to advance the mathematical intelligence of machines by ...

0 Wayne Xin Zhao, 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

∙ 06/10/2022

Feature-aware Diversified Re-ranking with Disentangled Representations for Relevant Recommendation

Relevant recommendation is a special recommendation scenario which provi...

0 Zihan Lin, 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

∙ 06/01/2022

Negative Sampling for Contrastive Representation Learning: A Review

The learn-to-compare paradigm of contrastive representation learning (CR...

0 Lanling Xu, et al. ∙

research

∙ 05/22/2022

Ada-Ranker: A Data Distribution Adaptive Ranking Paradigm for Sequential Recommendation

A large-scale recommender system usually consists of recall and ranking ...

0 Xinyan Fan, et al. ∙

research

∙ 05/04/2022

Great Truths are Always Simple: A Rather Simple Knowledge Encoder for Enhancing the Commonsense Reasoning Capacity of Pre-Trained Models

Commonsense reasoning in natural language is a desired ability of artifi...

0 Jinhao Jiang, et al. ∙

research

∙ 05/03/2022

Learning to Transfer Prompts for Text Generation

Pretrained language models (PLMs) have made remarkable progress in text ...

5 Junyi Li, et al. ∙

research

∙ 05/03/2022

ElitePLM: An Empirical Study on General Language Ability Evaluation of Pretrained Language Models

Nowadays, pretrained language models (PLMs) have dominated the majority ...

1 Junyi Li, et al. ∙

research

∙ 05/02/2022

Debiased Contrastive Learning of Unsupervised Sentence Representations

Recently, contrastive learning has been shown to be effective in improvi...

0 Kun Zhou, et al. ∙

Wayne Xin Zhao

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