Improving large language models in event relation logical prediction
Event relations are crucial for narrative understanding and reasoning. Governed by nuanced
logic, event relation extraction (ERE) is a challenging task that demands thorough semantic …
logic, event relation extraction (ERE) is a challenging task that demands thorough semantic …
A graph propagation model with rich event structures for joint event relation extraction
The task of event relation extraction (ERE) aims to organize multiple events and their
relations as a directed graph. However, existing ERE methods exhibit two limitations:(1) …
relations as a directed graph. However, existing ERE methods exhibit two limitations:(1) …
Learning to teach large language models logical reasoning
Large language models (LLMs) have gained enormous attention from both academia and
industry, due to their exceptional ability in language generation and extremely powerful …
industry, due to their exceptional ability in language generation and extremely powerful …
Mastering context-to-label representation transformation for event causality identification with diffusion models
To understand event structures of documents, event causality identification (ECI) emerges
as a crucial task, aiming to discern causal relationships among event mentions. The latest …
as a crucial task, aiming to discern causal relationships among event mentions. The latest …
CHEER: Centrality-aware high-order event reasoning network for document-level event causality identification
Abstract Document-level Event Causality Identification (DECI) aims to recognize causal
relations between events within a document. Recent studies focus on building a document …
relations between events within a document. Recent studies focus on building a document …
Document-level causal relation extraction with knowledge-guided binary question answering
As an essential task in information extraction (IE), Event-Event Causal Relation Extraction
(ECRE) aims to identify and classify the causal relationships between event mentions in …
(ECRE) aims to identify and classify the causal relationships between event mentions in …
Zero-shot cross-lingual document-level event causality identification with heterogeneous graph contrastive transfer learning
Event Causality Identification (ECI) refers to the detection of causal relations between events
in texts. However, most existing studies focus on sentence-level ECI with high-resource …
in texts. However, most existing studies focus on sentence-level ECI with high-resource …
CELLO: Causal Evaluation of Large Vision-Language Models
Causal reasoning is fundamental to human intelligence and crucial for effective decision-
making in real-world environments. Despite recent advancements in large vision-language …
making in real-world environments. Despite recent advancements in large vision-language …
Discriminative reasoning with sparse event representation for document-level event-event relation extraction
Abstract Document-level Event-Event Relation Extraction (DERE) aims to extract relations
between events in a document. It challenges conventional sentence-level task (SERE) with …
between events in a document. It challenges conventional sentence-level task (SERE) with …
Prompt-based event relation identification with Constrained Prefix ATTention mechanism
H Zhang, W Ke, J Zhang, Z Luo, H Ma, Z Luan… - Knowledge-Based …, 2023 - Elsevier
Abstract Event Relation Identification (ERI) aims at mining the inter-event dependencies
expressed in event-mentioned sentences. The main challenge of this task lies in recognizing …
expressed in event-mentioned sentences. The main challenge of this task lies in recognizing …