37 citations · 73 across the 29 of their papers we have counts for
31 papers
PAT: A Personality-Driven Augmentation and Transfer Learning Framework for Depression Detection on Social Media
Shengwu Zheng, Yuzhe Ding, Xiaohui Liang +3
Depression is a prevalent mental disorder that affects millions worldwide, with early detection crucial for effective intervention. While exist?ing methods have achieved promising…
ReCite: Agentic Reasoning for Faithful Citation
Yuyang Huang, Bobo Li, Jiajia Song +4
Accurate citations are the foundation of academic writing, tracing intellectual origins and substantiating core claims. However, manually navigating the growing volume of scientifi…
MMDS-Bench: Benchmarking Multimodal Large Language Models on Dynamic Stance in Social Media Interactions
Yuzhe Ding, Kang He, Li Zheng +5
Dynamic stance classification models how a reply responds to its direct parent message, rather than how a post relates to a fixed topic. Existing work has mainly studied this probl…
Are Emotion and Rhetoric Neurons in LLM? Neuron Recognition and Adaptive Masking for Emotion-Rhetoric Prediction Steering
Li Zheng, Xin Zhang, Shuyi He +5
Accurate comprehension and controllable generation of emotion and rhetoric are pivotal for enhancing the reasoning capabilities of large language models (LLMs). Existing studies mo…
Enhance-then-Balance Modality Collaboration for Robust Multimodal Sentiment Analysis
Kang He, Yuzhe Ding, Xinrong Wang +3
Multimodal sentiment analysis (MSA) integrates heterogeneous text, audio, and visual signals to infer human emotions. While recent approaches leverage cross-modal complementarity,…
Dynamic Emotion and Personality Profiling for Multimodal Deception Detection
Li Zheng, Yanyi Luo, Hao Fei +5
Deception detection is of great significance for ensuring information security and conducting public opinion analysis, with personality factors and emotion cues playing a critical…
Code-MIE: A Code-style Model for Multimodal Information Extraction with Scene Graph and Entity Attribute Knowledge Enhancement
Jiang Liu, Ge Qiu, Hao Fei +5
With the rapid development of large language models (LLMs), more and more researchers have paid attention to information extraction based on LLMs. However, there are still some spa…
PaSE: Prototype-aligned Calibration and Shapley-based Equilibrium for Multimodal Sentiment Analysis
Kang He, Boyu Chen, Yuzhe Ding +3
Multimodal Sentiment Analysis (MSA) seeks to understand human emotions by integrating textual, acoustic, and visual signals. Although multimodal fusion is designed to leverage cros…
DALR: Dual-level Alignment Learning for Multimodal Sentence Representation Learning
Kang He, Yuzhe Ding, Haining Wang +3
Previous multimodal sentence representation learning methods have achieved impressive performance. However, most approaches focus on aligning images and text at a coarse level, fac…
Zero-Shot Conversational Stance Detection: Dataset and Approaches
Yuzhe Ding, Kang He, Bobo Li +5
Stance detection, which aims to identify public opinion towards specific targets using social media data, is an important yet challenging task. With the increasing number of online…
Enhancing Hyperbole and Metaphor Detection with Their Bidirectional Dynamic Interaction and Emotion Knowledge
Li Zheng, Sihang Wang, Hao Fei +5
Text-based hyperbole and metaphor detection are of great significance for natural language processing (NLP) tasks. However, due to their semantic obscurity and expressive diversity…
DiscoSG: Towards Discourse-Level Text Scene Graph Parsing through Iterative Graph Refinement
Shaoqing Lin, Chong Teng, Fei Li +3
Vision-Language Models (VLMs) generate discourse-level, multi-sentence visual descriptions, challenging text scene graph parsers built for single-sentence caption-to-graph mapping.…
TRIDENT: Enhancing Large Language Model Safety with Tri-Dimensional Diversified Red-Teaming Data Synthesis
Xiaorui Wu, Xiaofeng Mao, Fei Li +5
Large Language Models (LLMs) excel in various natural language processing tasks but remain vulnerable to generating harmful content or being exploited for malicious purposes. Altho…
EVOREFUSE: Evolutionary Prompt Optimization for Evaluation and Mitigation of LLM Over-Refusal to Pseudo-Malicious Instructions
Xiaorui Wu, Fei Li, Xiaofeng Mao +6
Large language models (LLMs) frequently refuse to respond to pseudo-malicious instructions: semantically harmless input queries triggering unnecessary LLM refusals due to conservat…
Cross-Document Cross-Lingual NLI via RST-Enhanced Graph Fusion and Interpretability Prediction
Mengying Yuan, Wenhao Wang, Zixuan Wang +5
Natural Language Inference (NLI) is a fundamental task in natural language processing. While NLI has developed many sub-directions such as sentence-level NLI, document-level NLI an…
Multi-Granular Multimodal Clue Fusion for Meme Understanding
Li Zheng, Hao Fei, Ting Dai +5
With the continuous emergence of various social media platforms frequently used in daily life, the multimodal meme understanding (MMU) task has been garnering increasing attention.…
Revisiting Structured Sentiment Analysis as Latent Dependency Graph Parsing
Chengjie Zhou, Bobo Li, Hao Fei +3
Structured Sentiment Analysis (SSA) was cast as a problem of bi-lexical dependency graph parsing by prior studies. Multiple formulations have been proposed to construct the graph,…
Harvesting Events from Multiple Sources: Towards a Cross-Document Event Extraction Paradigm
Qiang Gao, Zixiang Meng, Bobo Li +4
Document-level event extraction aims to extract structured event information from unstructured text. However, a single document often contains limited event information and the rol…
Enhancing Cross-Document Event Coreference Resolution by Discourse Structure and Semantic Information
Qiang Gao, Bobo Li, Zixiang Meng +5
Existing cross-document event coreference resolution models, which either compute mention similarity directly or enhance mention representation by extracting event arguments (such…
Modeling Unified Semantic Discourse Structure for High-quality Headline Generation
Minghui Xu, Hao Fei, Fei Li +4
Headline generation aims to summarize a long document with a short, catchy title that reflects the main idea. This requires accurately capturing the core document semantics, which…
CMNER: A Chinese Multimodal NER Dataset based on Social Media
Yuanze Ji, Bobo Li, Jun Zhou +3
Multimodal Named Entity Recognition (MNER) is a pivotal task designed to extract named entities from text with the support of pertinent images. Nonetheless, a notable paucity of da…
Reverse Multi-Choice Dialogue Commonsense Inference with Graph-of-Thought
Li Zheng, Hao Fei, Fei Li +4
With the proliferation of dialogic data across the Internet, the Dialogue Commonsense Multi-choice Question Answering (DC-MCQ) task has emerged as a response to the challenge of co…
Compositional Generalization for Multi-label Text Classification: A Data-Augmentation Approach
Yuyang Chai, Zhuang Li, Jiahui Liu +4
Despite significant advancements in multi-label text classification, the ability of existing models to generalize to novel and seldom-encountered complex concepts, which are compos…
Revisiting Disentanglement and Fusion on Modality and Context in Conversational Multimodal Emotion Recognition
Bobo Li, Hao Fei, Lizi Liao +5
It has been a hot research topic to enable machines to understand human emotions in multimodal contexts under dialogue scenarios, which is tasked with multimodal emotion analysis i…