Humans ask follow-up questions driven by curiosity, which reflects a cre...
Event forecasting has been a demanding and challenging task throughout t...
Video Semantic Role Labeling (VidSRL) aims to detect the salient events ...
Sparse knowledge graph (KG) scenarios pose a challenge for previous Know...
Existing research on multimodal relation extraction (MRE) faces two
co-e...
Large Language Models (LLMs) have demonstrated human-like intelligence a...
Goal-oriented Script Generation is a new task of generating a list of st...
Few-shot event detection (ED) has been widely studied, while this brings...
Large Language Models (LLMs) have made remarkable strides in various tas...
In an attempt to understanding the complexity of the independent set pro...
Document-level natural language inference (DOCNLI) is a new challenging ...
Given sufficient training data on the source domain, cross-domain few-sh...
Knowledge Graphs (KGs) are becoming increasingly essential infrastructur...
Document-level Event Causality Identification (DECI) aims to identify ca...
In this paper, we propose an effective yet efficient model PAIE for both...
We present a 9^k· n^O(1)-time algorithm for the proper circular-arc
vert...
Future Event Generation aims to generate fluent and reasonable future ev...
Self-supervised entity alignment (EA) aims to link equivalent entities a...
We present TFGM (Training Free Graph Matching), a framework to boost the...
We present InferWiki, a Knowledge Graph Completion (KGC) dataset that
im...
Knowledge Graph (KG) and attention mechanism have been demonstrated effe...
Few-shot Named Entity Recognition (NER) exploits only a handful of
annot...
Inspired by applications of perfect graphs in combinatorial optimization...
In an edge modification problem, we are asked to modify at most k edges ...
Multi-hop reasoning has been widely studied in recent years to obtain mo...
Relation Extraction (RE) is a vital step to complete Knowledge Graph (KG...
Corneil, Olariu, and Stewart [SODA 1998; SIAM Journal on Discrete Mathem...
Entity alignment (EA) aims at building a unified Knowledge Graph (KG) of...
The rapid growth of user-generated videos on the Internet has intensifie...
The curse of knowledge can impede communication between experts and laym...
Given a graph G, the maximal induced subgraphs problem asks to enumerate...
Let H be a fixed graph. Given a graph G and an integer k, the H-free
edg...
Properly handling missing data is a fundamental challenge in recommendat...
In a paired threshold graph, each vertex has a weight, and two vertices ...
Entity alignment typically suffers from the issues of structural
heterog...
Name tagging in low-resource languages or domains suffers from inadequat...
Fashion knowledge helps people to dress properly and addresses not only
...
Relation extraction (RE) aims at extracting the relation between two ent...
Graph search, the process of visiting vertices in a graph in a specific
...
To provide more accurate, diverse, and explainable recommendation, it is...
Incorporating knowledge graph (KG) into recommender system is promising ...
Joint representation learning of words and entities benefits many NLP ta...
Entity Linking aims to link entity mentions in texts to knowledge bases,...
Incorporating knowledge graph into recommender systems has attracted
inc...
A k-coloring of a graph is an assignment of integers between 1 and k to
...
The P_2-packing problem asks for whether a graph contains k
vertex-disjo...
An H-free editing problem asks whether we can edit at most k edges to
ma...
Images account for a significant part of user decisions in many applicat...
We study the multiterminal cut problem, which, given an n-vertex
graph w...