Search Results for author: Shasha Li

Found 33 papers, 9 papers with code

Disentangling Instructive Information from Ranked Multiple Candidates for Multi-Document Scientific Summarization

1 code implementation16 Apr 2024 Pancheng Wang, Shasha Li, Dong Li, Kehan Long, Jintao Tang, Ting Wang

Our insights are twofold: Firstly, summary candidates can provide instructive information from both positive and negative perspectives, and secondly, selecting higher-quality candidates from multiple options contributes to producing better summaries.


DWE+: Dual-Way Matching Enhanced Framework for Multimodal Entity Linking

2 code implementations7 Apr 2024 Shezheng Song, Shasha Li, Shan Zhao, Xiaopeng Li, Chengyu Wang, Jie Yu, Jun Ma, Tianwei Yan, Bin Ji, Xiaoguang Mao

Multimodal entity linking (MEL) aims to utilize multimodal information (usually textual and visual information) to link ambiguous mentions to unambiguous entities in knowledge base.

Contrastive Learning Entity Linking

Recommending Missed Citations Identified by Reviewers: A New Task, Dataset and Baselines

1 code implementation4 Mar 2024 Kehan Long, Shasha Li, Pancheng Wang, Chenlong Bao, Jintao Tang, Ting Wang

To help improve citations of full papers, we first define a novel task of Recommending Missed Citations Identified by Reviewers (RMC) and construct a corresponding expert-labeled dataset called CitationR.

Citation Recommendation Recommendation Systems

SWEA: Updating Factual Knowledge in Large Language Models via Subject Word Embedding Altering

no code implementations31 Jan 2024 Xiaopeng Li, Shasha Li, Shezheng Song, Huijun Liu, Bin Ji, Xi Wang, Jun Ma, Jie Yu, Xiaodong Liu, Jing Wang, Weimin Zhang

In particular, local editing methods, which directly update model parameters, are more suitable for updating a small amount of knowledge.

Model Editing Word Embeddings

A Dual-way Enhanced Framework from Text Matching Point of View for Multimodal Entity Linking

1 code implementation19 Dec 2023 Shezheng Song, Shan Zhao, Chengyu Wang, Tianwei Yan, Shasha Li, Xiaoguang Mao, Meng Wang

Multimodal Entity Linking (MEL) aims at linking ambiguous mentions with multimodal information to entity in Knowledge Graph (KG) such as Wikipedia, which plays a key role in many applications.

Entity Linking Text Matching

How to Bridge the Gap between Modalities: A Comprehensive Survey on Multimodal Large Language Model

no code implementations10 Nov 2023 Shezheng Song, Xiaopeng Li, Shasha Li, Shan Zhao, Jie Yu, Jun Ma, Xiaoguang Mao, Weimin Zhang

The study surveys existing modal alignment methods in MLLMs into four groups: (1) Multimodal Converters that change data into something LLMs can understand; (2) Multimodal Perceivers to improve how LLMs perceive different types of data; (3) Tools Assistance for changing data into one common format, usually text; and (4) Data-Driven methods that teach LLMs to understand specific types of data in a dataset.

Language Modelling Large Language Model

PMET: Precise Model Editing in a Transformer

1 code implementation17 Aug 2023 Xiaopeng Li, Shasha Li, Shezheng Song, Jing Yang, Jun Ma, Jie Yu

To achieve more precise model editing, we analyze hidden states of MHSA and FFN, finding that MHSA encodes certain general knowledge extraction patterns.

General Knowledge Model Editing

Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with Sample-aware Prompting and Dynamic Revision Chain

no code implementations11 Jul 2023 Chunxi Guo, Zhiliang Tian, Jintao Tang, Shasha Li, Zhihua Wen, Kaixuan Wang, Ting Wang

Prompt learning with large language models (LLMs) has emerged as a recent approach, which designs prompts to lead LLMs to understand the input question and generate the corresponding SQL.

Retrieval Text-To-SQL

Address Matching Based On Hierarchical Information

no code implementations10 May 2023 Chengxian Zhang, Jintao Tang, Ting Wang, Shasha Li

There is evidence that address matching plays a crucial role in many areas such as express delivery, online shopping and so on.

Dynamic Multi-View Fusion Mechanism For Chinese Relation Extraction

no code implementations9 Mar 2023 Jing Yang, Bin Ji, Shasha Li, Jun Ma, Long Peng, Jie Yu

Recently, many studies incorporate external knowledge into character-level feature based models to improve the performance of Chinese relation extraction.

Relation Relation Extraction

Span-based joint entity and relation extraction augmented with sequence tagging mechanism

no code implementations23 Oct 2022 Bin Ji, Shasha Li, Hao Xu, Jie Yu, Jun Ma, Huijun Liu, Jing Yang

On the one hand, the core architecture enables our model to learn token-level label information via the sequence tagging mechanism and then uses the information in the span-based joint extraction; on the other hand, it establishes a bi-directional information interaction between NER and RE.

Joint Entity and Relation Extraction named-entity-recognition +3

Leveraging Local Patch Differences in Multi-Object Scenes for Generative Adversarial Attacks

no code implementations20 Sep 2022 Abhishek Aich, Shasha Li, Chengyu Song, M. Salman Asif, Srikanth V. Krishnamurthy, Amit K. Roy-Chowdhury

Our goal is to design an attack strategy that can learn from such natural scenes by leveraging the local patch differences that occur inherently in such images (e. g. difference between the local patch on the object `person' and the object `bike' in a traffic scene).


Multi-Document Scientific Summarization from a Knowledge Graph-Centric View

1 code implementation COLING 2022 Pancheng Wang, Shasha Li, Kunyuan Pang, Liangliang He, Dong Li, Jintao Tang, Ting Wang

Multi-Document Scientific Summarization (MDSS) aims to produce coherent and concise summaries for clusters of topic-relevant scientific papers.

Decoder Descriptive +1

A Two-Phase Paradigm for Joint Entity-Relation Extraction

no code implementations18 Aug 2022 Bin Ji, Hao Xu, Jie Yu, Shasha Li, Jun Ma, Yuke Ji, Huijun Liu

An exhaustive study has been conducted to investigate span-based models for the joint entity and relation extraction task.

Joint Entity and Relation Extraction Relation +1

A Context-Aware Approach for Textual Adversarial Attack through Probability Difference Guided Beam Search

no code implementations17 Aug 2022 Huijun Liu, Jie Yu, Shasha Li, Jun Ma, Bin Ji

Textual adversarial attacks expose the vulnerabilities of text classifiers and can be used to improve their robustness.

Adversarial Attack

SummScore: A Comprehensive Evaluation Metric for Summary Quality Based on Cross-Encoder

no code implementations11 Jul 2022 Wuhang Lin, Shasha Li, Chen Zhang, Bin Ji, Jie Yu, Jun Ma, Zibo Yi

However, the existing evaluation metrics for summary text are only rough proxies for summary quality, suffering from low correlation with human scoring and inhibition of summary diversity.

Text Matching Text Summarization

Topic-Grained Text Representation-based Model for Document Retrieval

no code implementations11 Jul 2022 Mengxue Du, Shasha Li, Jie Yu, Jun Ma, Bin Ji, Huijun Liu, Wuhang Lin, Zibo Yi

Document retrieval enables users to find their required documents accurately and quickly.


Win-Win Cooperation: Bundling Sequence and Span Models for Named Entity Recognition

no code implementations7 Jul 2022 Bin Ji, Shasha Li, Jie Yu, Jun Ma, Huijun Liu

Previous research has demonstrated that the two paradigms have clear complementary advantages, but few models have attempted to leverage these advantages in a single NER model as far as we know.

named-entity-recognition Named Entity Recognition +2

ADC: Adversarial attacks against object Detection that evade Context consistency checks

no code implementations24 Oct 2021 Mingjun Yin, Shasha Li, Chengyu Song, M. Salman Asif, Amit K. Roy-Chowdhury, Srikanth V. Krishnamurthy

A very recent defense strategy for detecting adversarial examples, that has been shown to be robust to current attacks, is to check for intrinsic context consistencies in the input data, where context refers to various relationships (e. g., object-to-object co-occurrence relationships) in images.

Object object-detection +1

Boosting Span-based Joint Entity and Relation Extraction via Squence Tagging Mechanism

no code implementations21 May 2021 Bin Ji, Shasha Li, Jie Yu, Jun Ma, Huijun Liu

To solve this problem, we pro-pose Sequence Tagging enhanced Span-based Network (STSN), a span-based joint extrac-tion network that is enhanced by token BIO label information derived from sequence tag-ging based NER.

Joint Entity and Relation Extraction named-entity-recognition +4

The smallest number of vertices in a 2-arc-strong digraph which has no good pair

no code implementations7 Dec 2020 Ran Gu, Gregory Gutin, Shasha Li, Yongtang Shi, Zhenyu Taoqiu

They also proved that every digraph on at most 6 vertices and arc-connectivity at least 2 has a good pair and gave an example of a 2-arc-strong digraph $D$ on 10 vertices with independence number 4 that has no good pair.


Measurement-driven Security Analysis of Imperceptible Impersonation Attacks

no code implementations26 Aug 2020 Shasha Li, Karim Khalil, Rameswar Panda, Chengyu Song, Srikanth V. Krishnamurthy, Amit K. Roy-Chowdhury, Ananthram Swami

The emergence of Internet of Things (IoT) brings about new security challenges at the intersection of cyber and physical spaces.

Face Recognition

Connecting the Dots: Detecting Adversarial Perturbations Using Context Inconsistency

no code implementations ECCV 2020 Shasha Li, Shitong Zhu, Sudipta Paul, Amit Roy-Chowdhury, Chengyu Song, Srikanth Krishnamurthy, Ananthram Swami, Kevin S. Chan

There has been a recent surge in research on adversarial perturbations that defeat Deep Neural Networks (DNNs) in machine vision; most of these perturbation-based attacks target object classifiers.

A4 : Evading Learning-based Adblockers

no code implementations29 Jan 2020 Shitong Zhu, Zhongjie Wang, Xun Chen, Shasha Li, Umar Iqbal, Zhiyun Qian, Kevin S. Chan, Srikanth V. Krishnamurthy, Zubair Shafiq

Efforts by online ad publishers to circumvent traditional ad blockers towards regaining fiduciary benefits, have been demonstrably successful.


Adversarial Perturbations Against Real-Time Video Classification Systems

1 code implementation2 Jul 2018 Shasha Li, Ajaya Neupane, Sujoy Paul, Chengyu Song, Srikanth V. Krishnamurthy, Amit K. Roy Chowdhury, Ananthram Swami

We exploit recent advances in generative adversarial network (GAN) architectures to account for temporal correlations and generate adversarial samples that can cause misclassification rates of over 80% for targeted activities.

Classification General Classification +2

Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers

no code implementations9 May 2017 Zibo Yi, Shasha Li, Jie Yu, Qingbo Wu

The experiments show that our model classifies most of the drug pairs into correct DDI categories, which outperforms the existing NLP or deep learning methods.

Drug–drug Interaction Extraction Feature Engineering +2

Cannot find the paper you are looking for? You can Submit a new open access paper.