Search Results for author: Aixin Sun

Found 63 papers, 23 papers with code

MS-DETR: Natural Language Video Localization with Sampling Moment-Moment Interaction

1 code implementation30 May 2023 Jing Wang, Aixin Sun, Hao Zhang, XiaoLi Li

Given a query, the task of Natural Language Video Localization (NLVL) is to localize a temporal moment in an untrimmed video that semantically matches the query.

LogicLLM: Exploring Self-supervised Logic-enhanced Training for Large Language Models

no code implementations23 May 2023 Fangkai Jiao, Zhiyang Teng, Shafiq Joty, Bosheng Ding, Aixin Sun, Zhengyuan Liu, Nancy F. Chen

Existing efforts to improve logical reasoning ability of language models have predominantly relied on supervised fine-tuning, hindering generalization to new domains and/or tasks.

Logical Reasoning

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

1 code implementation18 May 2023 Xinze Li, Yixin Cao, Muhao Chen, Aixin Sun

Goal-oriented Script Generation is a new task of generating a list of steps that can fulfill the given goal.

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

no code implementations7 May 2023 Kuicai Dong, Aixin Sun, Jung-jae Kim, XiaoLi Li

We formally define the research problem of tuple-level speculation detection and conduct a detailed data analysis on the LSOIE dataset which contains labels for speculative tuples.

Open Information Extraction Speculation Detection

Open Information Extraction via Chunks

no code implementations5 May 2023 Kuicai Dong, Aixin Sun, Jung-jae Kim, XiaoLi Li

Accordingly, we propose a simple BERT-based model for sentence chunking, and propose Chunk-OIE for tuple extraction on top of SaC.

Chunking Open Information Extraction

Retraining A Graph-based Recommender with Interests Disentanglement

no code implementations5 May 2023 Yitong Ji, Aixin Sun, Jie Zhang

Then we blend the historical and new preferences in the form of node embeddings in the new graph, through a Disentanglement Module.

Disentanglement Incremental Learning +2

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

1 code implementation3 May 2023 Yubo Ma, Zehao Wang, Yixin Cao, Aixin Sun

Few-shot event detection (ED) has been widely studied, while this brings noticeable discrepancies, e. g., various motivations, tasks, and experimental settings, that hinder the understanding of models for future progress. This paper presents a thorough empirical study, a unified view of ED models, and a better unified baseline.

Event Detection

FreeLM: Fine-Tuning-Free Language Model

no code implementations2 May 2023 Xiang Li, Xin Jiang, Xuying Meng, Aixin Sun, Yequan Wang

FreeLM outperforms large models e. g., GPT-3 and InstructGPT, on a range of language understanding tasks in experiments.

Language Modelling

DiffuRec: A Diffusion Model for Sequential Recommendation

no code implementations3 Apr 2023 Zihao Li, Aixin Sun, Chenliang Li

Mainstream solutions to Sequential Recommendation (SR) represent items with fixed vectors.

Sequential Recommendation

GCRE-GPT: A Generative Model for Comparative Relation Extraction

no code implementations15 Mar 2023 Yequan Wang, Hengran Zhang, Aixin Sun, Xuying Meng

Given comparative text, comparative relation extraction aims to extract two targets (\eg two cameras) in comparison and the aspect they are compared for (\eg image quality).

Relation Extraction

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

no code implementations6 Dec 2022 Mengying Yu, Aixin Sun

The differences in these datasets can be attributed to the different information needs of the specific research tasks.

Image Captioning Information Retrieval +2

Syntactic Multi-view Learning for Open Information Extraction

1 code implementation5 Dec 2022 Kuicai Dong, Aixin Sun, Jung-jae Kim, XiaoLi Li

In this paper, we model both constituency and dependency trees into word-level graphs, and enable neural OpenIE to learn from the syntactic structures.

MULTI-VIEW LEARNING Open Information Extraction

Perplexity from PLM Is Unreliable for Evaluating Text Quality

no code implementations12 Oct 2022 Yequan Wang, Jiawen Deng, Aixin Sun, Xuying Meng

Recently, amounts of works utilize perplexity~(PPL) to evaluate the quality of the generated text.

Common Sense Reasoning

Take a Fresh Look at Recommender Systems from an Evaluation Standpoint

no code implementations9 Oct 2022 Aixin Sun

We then move on to explore the two implications of neglecting a global timeline during evaluation: data leakage and oversimplification of user preference modeling.

Information Retrieval Recommendation Systems +1

CofeNet: Context and Former-Label Enhanced Net for Complicated Quotation Extraction

1 code implementation COLING 2022 Yequan Wang, Xiang Li, Aixin Sun, Xuying Meng, Huaming Liao, Jiafeng Guo

CofeNet is able to extract complicated quotations with components of variable lengths and complicated structures.

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

no code implementations28 May 2022 Xinyu Zou, Zhi Hu, Yiming Zhao, Xuchu Ding, Zhongyi Liu, Chenliang Li, Aixin Sun

At each multi-scenario/multi-task layer, a novel expert selection algorithm is proposed to automatically identify scenario-/task-specific and shared experts for each input.

Multi-Task Learning

Do Loyal Users Enjoy Better Recommendations? Understanding Recommender Accuracy from a Time Perspective

1 code implementation12 Apr 2022 Yitong Ji, Aixin Sun, Jie Zhang, Chenliang Li

Our study offers a different perspective to understand recommender accuracy, and our findings could trigger a revisit of recommender model design.

Recommendation Systems

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

no code implementations23 Mar 2022 Yequan Wang, Xuying Meng, Yiyi Liu, Aixin Sun, Yao Wang, Yinhe Zheng, Minlie Huang

These models hence are not optimized for dialog-level emotion detection, i. e. to predict the emotion category of a dialog as a whole.

Emotion Recognition

Temporal Sentence Grounding in Videos: A Survey and Future Directions

no code implementations20 Jan 2022 Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou

Temporal sentence grounding in videos (TSGV), \aka natural language video localization (NLVL) or video moment retrieval (VMR), aims to retrieve a temporal moment that semantically corresponds to a language query from an untrimmed video.

Moment Retrieval Retrieval

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

no code implementations14 Jan 2022 Grace E. Lee, Aixin Sun

This practice, known as screening prioritization (ie., document ranking approach), speeds up the process of conducting a SR as the documents labelled as relevant can move to the next tasks earlier.

Document Ranking

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

no code implementations28 Dec 2021 Grace E. Lee, Aixin Sun

Alternatively, we formulate the SDR task as finding similar documents to a query document and produce rankings based on similarity scores.

Document Ranking Retrieval

Towards Debiasing Temporal Sentence Grounding in Video

no code implementations8 Nov 2021 Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou

In this paper, we propose two debiasing strategies, data debiasing and model debiasing, to "force" a TSGV model to capture cross-modal interactions.

SelfCF: A Simple Framework for Self-supervised Collaborative Filtering

2 code implementations7 Jul 2021 Xin Zhou, Aixin Sun, Yong liu, Jie Zhang, Chunyan Miao

Collaborative filtering (CF) is widely used to learn informative latent representations of users and items from observed interactions.

Collaborative Filtering Self-Supervised Learning

Parallel Attention Network with Sequence Matching for Video Grounding

no code implementations Findings (ACL) 2021 Hao Zhang, Aixin Sun, Wei Jing, Liangli Zhen, Joey Tianyi Zhou, Rick Siow Mong Goh

In this work, we propose a Parallel Attention Network with Sequence matching (SeqPAN) to address the challenges in this task: multi-modal representation learning, and target moment boundary prediction.

Representation Learning Video Grounding

Video Corpus Moment Retrieval with Contrastive Learning

1 code implementation13 May 2021 Hao Zhang, Aixin Sun, Wei Jing, Guoshun Nan, Liangli Zhen, Joey Tianyi Zhou, Rick Siow Mong Goh

We adopt the first approach and introduce two contrastive learning objectives to refine video encoder and text encoder to learn video and text representations separately but with better alignment for VCMR.

Contrastive Learning Moment Retrieval +2

Generative Adversarial Reward Learning for Generalized Behavior Tendency Inference

no code implementations3 May 2021 Xiaocong Chen, Lina Yao, Xianzhi Wang, Aixin Sun, Wenjie Zhang, Quan Z. Sheng

Recent advances in reinforcement learning have inspired increasing interest in learning user modeling adaptively through dynamic interactions, e. g., in reinforcement learning based recommender systems.

Recommendation Systems reinforcement-learning +2

An Embarrassingly Simple Model for Dialogue Relation Extraction

1 code implementation27 Dec 2020 Fuzhao Xue, Aixin Sun, Hao Zhang, Jinjie Ni, Eng Siong Chng

Dialogue relation extraction (RE) is to predict the relation type of two entities mentioned in a dialogue.

Dialog Relation Extraction

GDPNet: Refining Latent Multi-View Graph for Relation Extraction

1 code implementation12 Dec 2020 Fuzhao Xue, Aixin Sun, Hao Zhang, Eng Siong Chng

Recent advances on RE task are from BERT-based sequence modeling and graph-based modeling of relationships among the tokens in the sequence.

Ranked #4 on Dialog Relation Extraction on DialogRE (F1c (v1) metric)

Dialog Relation Extraction Dynamic Time Warping

A Critical Study on Data Leakage in Recommender System Offline Evaluation

1 code implementation21 Oct 2020 Yitong Ji, Aixin Sun, Jie Zhang, Chenliang Li

To evaluate recommendation systems in a realistic manner in offline setting, we propose a timeline scheme, which calls for a revisit of the recommendation model design.

Collaborative Filtering Recommendation Systems

A Re-visit of the Popularity Baseline in Recommender Systems

1 code implementation28 May 2020 Yitong Ji, Aixin Sun, Jie Zhang, Chenliang Li

On the widely used MovieLens dataset, we show that the performance of popularity could be significantly improved by 70% or more, if we consider the popular items at the time point when a user interacts with the system.

Recommendation Systems

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

1 code implementation21 May 2020 Cheng Zhao, Chenliang Li, Rong Xiao, Hongbo Deng, Aixin Sun

Given two relevant domains (e. g., Book and Movie), users may have interactions with items in one domain but not in the other domain.

Recommendation Systems

Span-based Localizing Network for Natural Language Video Localization

1 code implementation ACL 2020 Hao Zhang, Aixin Sun, Wei Jing, Joey Tianyi Zhou

Given an untrimmed video and a text query, natural language video localization (NLVL) is to locate a matching span from the video that semantically corresponds to the query.

Efficient Approximation Algorithms for Adaptive Influence Maximization

2 code implementations14 Apr 2020 Keke Huang, Jing Tang, Kai Han, Xiaokui Xiao, Wei Chen, Aixin Sun, Xueyan Tang, Andrew Lim

In this paper, we propose the first practical algorithm for the adaptive IM problem that could provide the worst-case approximation guarantee of $1-\mathrm{e}^{\rho_b(\varepsilon-1)}$, where $\rho_b=1-(1-1/b)^b$ and $\varepsilon \in (0, 1)$ is a user-specified parameter.

Social and Information Networks

UFTR: A Unified Framework for Ticket Routing

no code implementations2 Mar 2020 Jianglei Han, Jing Li, Aixin Sun

In short, our results demonstrate that the UFTR is a superior solution to the ticket routing problem because it takes into account previously unexploited interrelationships between the group assignment and group transfer problems.

CASE: Context-Aware Semantic Expansion

no code implementations31 Dec 2019 Jialong Han, Aixin Sun, Haisong Zhang, Chenliang Li, Shuming Shi

In this study, we demonstrate that annotations for this task can be harvested at scale from existing corpora, in a fully automatic manner.

Word Sense Disambiguation

Subtopic-driven Multi-Document Summarization

no code implementations IJCNLP 2019 Xin Zheng, Aixin Sun, Jing Li, Karthik Muthuswamy

In multi-document summarization, a set of documents to be summarized is assumed to be on the same topic, known as the underlying topic in this paper.

Document Summarization Multi-Document Summarization

Robust Representation Learning of Biomedical Names

no code implementations ACL 2019 Minh C. Phan, Aixin Sun, Yi Tay

Moreover, our proposed method is also able to compute meaningful representations for unseen names, resulting in high practical utility in real-world applications.

Representation Learning Retrieval

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

4 code implementations25 May 2019 Shuai Zhang, Yi Tay, Lina Yao, Bin Wu, Aixin Sun

In this toolkit, we have implemented a number of deep learning based recommendation algorithms using Python and the widely used deep learning package - Tensorflow.

Sequential Recommendation

Targeted Sentiment Analysis: A Data-Driven Categorization

1 code implementation9 May 2019 Jiaxin Pei, Aixin Sun, Chenliang Li

Targeted sentiment analysis (TSA), also known as aspect based sentiment analysis (ABSA), aims at detecting fine-grained sentiment polarity towards targets in a given opinion document.

Aspect-Based Sentiment Analysis (ABSA)

Understanding the Stability of Medical Concept Embeddings

no code implementations21 Apr 2019 Grace E. Lee, Aixin Sun

In this work, we conduct a detailed analysis on the stability of concept embeddings in medical domain, particularly the relation with concept frequency.

Word Embeddings

A Study on Agreement in PICO Span Annotations

no code implementations21 Apr 2019 Grace E. Lee, Aixin Sun

Based on the analysis, we report two observations: (i) Boundaries of PICO span annotations by individual human annotators are very diverse.


Enhancing Topic Modeling for Short Texts with Auxiliary Word Embeddings

no code implementations22 Dec 2018 Chenliang Li, Yu Duan, Haoran Wang, Zhiqian Zhang, Aixin Sun, Zongyang Ma

Recent studies show that the Dirichlet Multinomial Mixture (DMM) model is effective for topic inference over short texts by assuming that each piece of short text is generated by a single topic.

text-classification Topic Models +1

Next Item Recommendation with Self-Attention

no code implementations20 Aug 2018 Shuai Zhang, Yi Tay, Lina Yao, Aixin Sun

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

Metric Learning

NeuRec: On Nonlinear Transformation for Personalized Ranking

no code implementations8 May 2018 Shuai Zhang, Lina Yao, Aixin Sun, Sen Wang, Guodong Long, Manqing Dong

Modeling user-item interaction patterns is an important task for personalized recommendations.

Recommendation Systems

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

no code implementations4 Feb 2018 Minh C. Phan, Aixin Sun, Yi Tay, Jialong Han, Chenliang Li

For the first time, we show that the semantic relationships between the mentioned entities are in fact less dense than expected.

Decision Making Entity Disambiguation

Deep Learning based Recommender System: A Survey and New Perspectives

10 code implementations24 Jul 2017 Shuai Zhang, Lina Yao, Aixin Sun, Yi Tay

This article aims to provide a comprehensive review of recent research efforts on deep learning based recommender systems.

Information Retrieval Recommendation Systems +1

A Survey of Location Prediction on Twitter

no code implementations9 May 2017 Xin Zheng, Jialong Han, Aixin Sun

Specifically, we concentrate on the prediction of user home locations, tweet locations, and mentioned locations.

point of interests

NEXT: A Neural Network Framework for Next POI Recommendation

no code implementations15 Apr 2017 Zhiqian Zhang, Chenliang Li, Zhiyong Wu, Aixin Sun, Dengpan Ye, Xiangyang Luo

Inspired by the recent success of neural networks in many areas, in this paper, we present a simple but effective neural network framework for next POI recommendation, named NEXT.

Representation Learning

Graph-based Point-of-interest Recommendation with Geographical and Temporal Influences

no code implementations1 Nov 2014 Quan Yuan, Gao Cong, Aixin Sun

In this paper, we focus on the problem of time-aware POI recommendation, which aims at recommending a list of POIs for a user to visit at a given time.

Recommendation Systems

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