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Found 14 papers, 9 papers with code
FedCQA: Answering Complex Queries on Multi-Source Knowledge Graphs via Federated Learning
An entity can be involved in various knowledge graphs and reasoning on multiple KGs and answering complex queries on multi-source KGs is important in discovering knowledge cross graphs.
CANDLE: Iterative Conceptualization and Instantiation Distillation from Large Language Models for Commonsense Reasoning
The sequential process of conceptualization and instantiation is essential to generalizable commonsense reasoning as it allows the application of existing knowledge to unfamiliar scenarios.
Advancing Abductive Reasoning in Knowledge Graphs through Complex Logical Hypothesis Generation
Although many applications require the use of knowledge for explanations, the utilization of abductive reasoning in conjunction with structured knowledge, such as a knowledge graph, remains largely unexplored.
Privacy-Preserved Neural Graph Databases
Neural graph databases (NGDBs) have emerged as a powerful paradigm that combines the strengths of graph databases (GDBs) and neural networks to enable efficient storage, retrieval, and analysis of graph-structured data which can be adaptively trained with LLMs.
Understanding Inter-Session Intentions via Complex Logical Reasoning
In this paper, we introduce the task of logical session complex query answering, where sessions are treated as hyperedges of items, and we formulate the problem of complex intention understanding as a task of logical session complex queries answering (LS-CQA) on an aggregated hypergraph of sessions, items, and attributes.
Knowledge Graph Reasoning over Entities and Numerical Values
To address the difference between entities and numerical values, we also propose the framework of Number Reasoning Network (NRN) for alternatively encoding entities and numerical values into separate encoding structures.
Complex Query Answering on Eventuality Knowledge Graph with Implicit Logical Constraints
Traditional neural complex query answering (CQA) approaches mostly work on entity-centric KGs.
Sequential Query Encoding For Complex Query Answering on Knowledge Graphs
Instead of parameterizing and executing the computational graph, SQE first uses a search-based algorithm to linearize the computational graph to a sequence of tokens and then uses a sequence encoder to compute its vector representation.
FolkScope: Intention Knowledge Graph Construction for E-commerce Commonsense Discovery
Understanding users' intentions in e-commerce platforms requires commonsense knowledge.
Query2Particles: Knowledge Graph Reasoning with Particle Embeddings
The query embedding method is proposed to answer these queries by jointly encoding queries and entities to the same embedding space.
Multi-Relational Graph based Heterogeneous Multi-Task Learning in Community Question Answering
To tackle this challenge, we develop a multi-relational graph based MTL model called Heterogeneous Multi-Task Graph Isomorphism Network (HMTGIN) which efficiently solves heterogeneous CQA tasks.
Joint Coreference Resolution and Character Linking for Multiparty Conversation
Character linking, the task of linking mentioned people in conversations to the real world, is crucial for understanding the conversations.
Multiplex Word Embeddings for Selectional Preference Acquisition
Therefore, in this paper, we propose a multiplex word embedding model, which can be easily extended according to various relations among words.
ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
Moreover, it is shown that reasonable performance can be obtained when ZEN is trained on a small corpus, which is important for applying pre-training techniques to scenarios with limited data.
Ranked #1 on
Chinese Part-of-Speech Tagging
on CTB5 Dev
Chinese Named Entity Recognition
Chinese Word Segmentation
+5
