b'Aixin Sun'

research

∙ 09/13/2023

An Image Dataset for Benchmarking Recommender Systems with Raw Pixels

Recommender systems (RS) have achieved significant success by leveraging...

0 Yu Cheng, et al. ∙

research

∙ 07/19/2023

Our Model Achieves Excellent Performance on MovieLens: What Does it Mean?

A typical benchmark dataset for recommender system (RecSys) evaluation c...

0 Yu-chen Fan, et al. ∙

research

∙ 07/13/2023

Research Explosion: More Effort to Climb onto Shoulders of the Giant

Fast-growing scientific publications present challenges to the scientifi...

0 Guoxiu He, et al. ∙

research

∙ 05/18/2023

Take a Break in the Middle: Investigating Subgoals towards Hierarchical Script Generation

Goal-oriented Script Generation is a new task of generating a list of st...

0 Xinze Li, et al. ∙

research

∙ 05/07/2023

Shall We Trust All Relational Tuples by Open Information Extraction? A Study on Speculation Detection

Open Information Extraction (OIE) aims to extract factual relational tup...

0 Kuicai Dong, et al. ∙

research

∙ 05/05/2023

Retraining A Graph-based Recommender with Interests Disentanglement

In a practical recommender system, new interactions are continuously obs...

0 Yitong Ji, et al. ∙

research

∙ 05/05/2023

Open Information Extraction via Chunks

Open Information Extraction (OIE) aims to extract relational tuples from...

0 Kuicai Dong, et al. ∙

research

∙ 05/03/2023

Few-shot Event Detection: An Empirical Study and a Unified View

Few-shot event detection (ED) has been widely studied, while this brings...

0 Yubo Ma, et al. ∙

research

∙ 04/03/2023

DiffuRec: A Diffusion Model for Sequential Recommendation

Mainstream solutions to Sequential Recommendation (SR) represent items w...

0 Zihao Li, et al. ∙

research

∙ 03/15/2023

GCRE-GPT: A Generative Model for Comparative Relation Extraction

Given comparative text, comparative relation extraction aims to extract ...

0 Yequan Wang, et al. ∙

research

∙ 03/15/2023

Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!

Large Language Models (LLMs) have made remarkable strides in various tas...

0 Yubo Ma, et al. ∙

research

∙ 12/06/2022

Dataset vs Reality: Understanding Model Performance from the Perspective of Information Need

Deep learning technologies have brought us many models that outperform h...

0 Mengying Yu, et al. ∙

research

∙ 12/05/2022

Syntactic Multi-view Learning for Open Information Extraction

Open Information Extraction (OpenIE) aims to extract relational tuples f...

0 Kuicai Dong, et al. ∙

research

∙ 10/12/2022

Perplexity from PLM Is Unreliable for Evaluating Text Quality

Recently, amounts of works utilize perplexity (PPL) to evaluate the qual...

0 Yequan Wang, et al. ∙

research

∙ 10/09/2022

From Counter-intuitive Observations to a Fresh Look at Recommender System

Recently, a few papers report counter-intuitive observations made from e...

0 Aixin Sun, et al. ∙

research

∙ 05/28/2022

Automatic Expert Selection for Multi-Scenario and Multi-Task Search

Multi-scenario learning (MSL) enables a service provider to cater for us...

0 Xinyu Zou, et al. ∙

research

∙ 05/24/2022

A Survey on Neural Open Information Extraction: Current Status and Future Directions

Open Information Extraction (OpenIE) facilitates domain-independent disc...

0 Shaowen Zhou, et al. ∙

research

∙ 04/12/2022

Recommender May Not Favor Loyal Users

In academic research, recommender systems are often evaluated on benchma...

0 Yitong Ji, et al. ∙

research

∙ 03/23/2022

Chat-Capsule: A Hierarchical Capsule for Dialog-level Emotion Analysis

Many studies on dialog emotion analysis focus on utterance-level emotion...

0 Yequan Wang, et al. ∙

research

∙ 02/05/2022

Aspect-based Sentiment Analysis through EDU-level Attentions

A sentence may express sentiments on multiple aspects. When these aspect...

0 Ting Lin, et al. ∙

research

∙ 01/14/2022

Towards Reducing Manual Workload in Technology-Assisted Reviews: Estimating Ranking Performance

Conducting a systematic review (SR) is comprised of multiple tasks: (i) ...

0 Grace E. Lee, et al. ∙

research

∙ 12/28/2021

Mirror Matching: Document Matching Approach in Seed-driven Document Ranking for Medical Systematic Reviews

When medical researchers conduct a systematic review (SR), screening stu...

0 Grace E. Lee, et al. ∙

research

∙ 09/08/2021

A Dual-Channel Framework for Sarcasm Recognition by Detecting Sentiment Conflict

Sarcasm employs ambivalence, where one says something positive but actua...

0 Yiyi Liu, et al. ∙

research

∙ 07/07/2021

SelfCF: A Simple Framework for Self-supervised Collaborative Filtering

Collaborative filtering (CF) is widely used to learn an informative late...

15 Xin Zhou, et al. ∙

research

∙ 05/10/2021

DocOIE: A Document-level Context-Aware Dataset for OpenIE

Open Information Extraction (OpenIE) aims to extract structured relation...

0 Kuicai Dong, et al. ∙

research

∙ 05/03/2021

Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference

Recent advances in reinforcement learning have inspired increasing inter...

0 Xiaocong Chen, et al. ∙

research

∙ 11/04/2020

Generative Inverse Deep Reinforcement Learning for Online Recommendation

Deep reinforcement learning enables an agent to capture user's interest ...

0 Xiaocong Chen, et al. ∙

research

∙ 10/21/2020

On Offline Evaluation of Recommender Systems

In academic research, recommender models are often evaluated offline on ...

0 Yitong Ji, et al. ∙

research

∙ 05/28/2020

A Re-visit of the Popularity Baseline in Recommender Systems

Popularity is often included in experimental evaluation to provide a ref...

0 Yitong Ji, et al. ∙

research

∙ 05/21/2020

CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network

In a large recommender system, the products (or items) could be in many ...

0 Cheng Zhao, et al. ∙

research

∙ 03/02/2020

UFTR: A Unified Framework for Ticket Routing

Corporations today face increasing demands for the timely and effective ...

0 Jianglei Han, et al. ∙

research

∙ 12/31/2019

CASE: Context-Aware Semantic Expansion

In this paper, we define and study a new task called Context-Aware Seman...

0 Jialong Han, et al. ∙

research

∙ 07/23/2019

Efficient Approximation Algorithms for Adaptive Seed Minimization

As a dual problem of influence maximization, the seed minimization probl...

0 Jing Tang, et al. ∙

research

∙ 06/04/2019

ChID: A Large-scale Chinese IDiom Dataset for Cloze Test

Cloze-style reading comprehension in Chinese is still limited due to the...

0 Chujie Zheng, et al. ∙

research

∙ 05/25/2019

DeepRec: An Open-source Toolkit for Deep Learning based Recommendation

Deep learning based recommender systems have been extensively explored i...

0 Shuai Zhang, et al. ∙

research

∙ 05/09/2019

Targeted Sentiment Analysis: A Data-Driven Categorization

Targeted sentiment analysis (TSA), also known as aspect based sentiment ...

0 Jiaxin Pei, et al. ∙

research

∙ 04/21/2019

A Study on Agreement in PICO Span Annotations

In evidence-based medicine, relevance of medical literature is determine...

0 Grace E. Lee, et al. ∙

research

∙ 04/21/2019

Understanding Stability of Medical Concept Embeddings: Analysis and Prediction

In biomedical area, medical concepts linked to external knowledge bases ...

0 Grace E. Lee, et al. ∙

research

∙ 12/22/2018

A Survey on Deep Learning for Named Entity Recognition

Named entity recognition (NER) is the task to identify text spans that m...

0 Jing Li, et al. ∙

research

∙ 08/20/2018

Next Item Recommendation with Self-Attention

In this paper, we propose a novel sequence-aware recommendation model. O...

0 Shuai Zhang, et al. ∙

research

∙ 08/20/2018

Dynamic Intention-Aware Recommendation with Self-Attention

Predicting the missing values given the observed interaction matrix is a...

0 Shuai Zhang, et al. ∙

research

∙ 05/08/2018

NeuRec: On Nonlinear Transformation for Personalized Ranking

Modelling user-item interaction patterns is an important task for person...

0 Shuai Zhang, et al. ∙

research

∙ 02/04/2018

Pair-Linking for Collective Entity Disambiguation: Two Could Be Better Than All

Collective entity disambiguation, or collective entity linking aims to j...

0 Minh C. Phan, et al. ∙

Aixin Sun

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