collaborators

8 papers

cs.CV2026

ChinaHeritaQA: A Culturally-Grounded Visual Question Answering Dataset for World Heritage Sites in China

Yi Zhang, Bolei Ma, Yong Cao +3

We introduce ChinaHeritaQA, a multimodal benchmark dataset for evaluating the cultural reasoning abilities of vision-language models (VLMs) on UNESCO World Heritage sites in China.…

cs.CL2026

FAITH: Factuality Alignment through Integrating Trustworthiness and Honestness

Xiaoning Dong, Chengyan Wu, Yajie Wen +5

Large Language Models (LLMs) can generate factually inaccurate content even if they have corresponding knowledge, which critically undermines their reliability. Existing approaches…

cs.CL2026

MSMO-ABSA: Multi-Scale and Multi-Objective Optimization for Cross-Lingual Aspect-Based Sentiment Analysis

Chengyan Wu, Bolei Ma, Ningyuan Deng +3

Aspect-based sentiment analysis (ABSA) garnered growing research interest in multilingual contexts in the past. However, the majority of the studies lack more robust feature alignm…

cs.CL2026

SURE: Synergistic Uncertainty-aware Reasoning for Multimodal Emotion Recognition in Conversations

Yiqiang Cai, Chengyan Wu, Bolei Ma +4

Multimodal emotion recognition in conversations (MERC) requires integrating multimodal signals while being robust to noise and modeling contextual reasoning. Existing approaches of…

cs.CL2025

From Detection to Mitigation: Addressing Gender Bias in Chinese Texts via Efficient Tuning and Voting-Based Rebalancing

Chengyan Wu, Yiqiang Cai, Yufei Cheng +1

This paper presents our team's solution to Shared Task 7 of NLPCC-2025, which focuses on sentence-level gender bias detection and mitigation in Chinese. The task aims to promote fa…

cs.CL2025

Multimodal Emotion Recognition in Conversations: A Survey of Methods, Trends, Challenges and Prospects

Chengyan Wu, Yiqiang Cai, Yang Liu +5

While text-based emotion recognition methods have achieved notable success, real-world dialogue systems often demand a more nuanced emotional understanding than any single modality…