Titlebook: Web and Big Data; 8th International Jo Wenjie Zhang,Anthony Tung,Hongjie Guo Conference proceedings 2024 The Editor(s) (if applicable) and

膝蓋

CGSL: Collaborative Graph and?Segment Learning Based Aspect-Level Sentiment Analysis Modelsentiment analysis focuses on mining the grammatical and semantic relationship between aspects and isolated sentences. However, the relationship between words and multiple sentence contexts in the whole corpus and the sentiment attributes of different segments are ignored. We propose a collaborative

hypertension

不出名

SE-GCN: A Syntactic Information Enhanced Model for Aspect-Based Sentiment Analysisnt years is mainly based on graph convolutional networks, and although much progress has been made, the existing methods focus on utilizing sequence information or syntactic dependency constraints within the text, but without fully utilizing the type of dependency relationships between the aspect te

Fibrin

Answering Spatial Commonsense Questions Based on?Chain-of-Thought Reasoning with?Adaptive ComplexityCurrent mainstream methods are based on the large language model (.) which uses the chain-of-thought (.) to support reasoning. However, these methods neglect to consider the differences in reasoning complexity of the questions when designing the . prompts, resulting in poor performance. Spatial ques

庇護

Shuttle

LLM-Based Empathetic Response Through Psychologist-Agent Debate in generating empathetic responses. But currently, many research only use a single LLM to generate responses. For empathetic responses, the approach of using a single LLM with single-turn has a problem, which is the lack of utilizing the capability of multiple LLMs for debate. Just like humans, the

褲子

男學(xué)院

UFI4ER: An Utterance-Level Feature Dynamic Interaction Model for?Cognition-Enhanced Empathetic Respotead, they naturally engage in dynamic interactions throughout the conversation, facilitating the emergence and development of empathy. However, existing works primarily focus on capturing dialogue-level features, disregarding the sequential structure of dialogues and failing to perceive the dynamic

Jacket

LLM-Based Empathetic Response Through Psychologist-Agent Debate in generating empathetic responses. But currently, many research only use a single LLM to generate responses. For empathetic responses, the approach of using a single LLM with single-turn has a problem, which is the lack of utilizing the capability of multiple LLMs for debate. Just like humans, the

真實的人

UFI4ER: An Utterance-Level Feature Dynamic Interaction Model for?Cognition-Enhanced Empathetic Respotead, they naturally engage in dynamic interactions throughout the conversation, facilitating the emergence and development of empathy. However, existing works primarily focus on capturing dialogue-level features, disregarding the sequential structure of dialogues and failing to perceive the dynamic