Hongzhan Lin

According to our database, Hongzhan Lin authored at least 40 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

AmbiGraph-Eval: Can LLMs Effectively Handle Ambiguous Graph Queries?

Yuchen Tian, Kaixin Li, Hao Chen, Ziyang Luo, Hongzhan Lin, Sebastian Schelter, Lun Du, Jing Ma

CoRR, August, 2025

LLM-Enhanced Multiple Instance Learning for Joint Rumor and Stance Detection with Social Context Information.

Ruichao Yang, Jing Ma, Wei Gao, Hongzhan Lin

ACM Trans. Intell. Syst. Technol., June, 2025

Exploring the Impact of Personality Traits on Conversational Recommender Systems: A Simulation with Large Language Models.

Xiaoyan Zhao, Yang Deng, Wenjie Wang, Hongzhan Lin, Hong Cheng, Rui Zhang, See-Kiong Ng, Tat-Seng Chua

CoRR, April, 2025

ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use.

Kaixin Li, Ziyang Meng, Hongzhan Lin, Ziyang Luo, Yuchen Tian, Jing Ma, Zhiyong Huang, Tat-Seng Chua

CoRR, April, 2025

Unlocking Multimodal Integration in EHRs: A Prompt Learning Framework for Language and Time Series Fusion.

Shuai Niu, Jing Ma, Hongzhan Lin, Liang Bai, Zhihua Wang, Wei Bi, Yida Xu, Guo Li, Xian Yang

CoRR, February, 2025

Llasa: Scaling Train-Time and Inference-Time Compute for Llama-based Speech Synthesis.

Zhen Ye, Xinfa Zhu, Chi-Min Chan, Xinsheng Wang, Xu Tan, Jiahe Lei, Yi Peng, Haohe Liu, Yizhu Jin, Zheqi Dai, Hongzhan Lin, Jianyi Chen, Xingjian Du, Liumeng Xue, Yunlin Chen, Zhifei Li, Lei Xie, Qiuqiang Kong, Yike Guo, Wei Xue

CoRR, February, 2025

ScratchEval: Are GPT-4o Smarter than My Child? Evaluating Large Multimodal Models with Visual Programming Challenges.

Rao Fu, Ziyang Luo, Hongzhan Lin, Zhen Ye, Jing Ma

Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies, 2025

CodeJudge-Eval: Can Large Language Models be Good Judges in Code Understanding?

Yuwei Zhao, Ziyang Luo, Yuchen Tian, Hongzhan Lin, Weixiang Yan, Annan Li, Jing Ma

Proceedings of the 31st International Conference on Computational Linguistics, 2025

Knowledge-Augmented Multimodal Clinical Rationale Generation for Disease Diagnosis with Small Language Models.

Shuai Niu, Jing Ma, Hongzhan Lin, Liang Bai, Zhihua Wang, Richard Yi Da Xu, Yunya Song, Xian Yang

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

ProMedTS: A Self-Supervised, Prompt-Guided Multimodal Approach for Integrating Medical Text and Time Series.

Shuai Niu, Jing Ma, Hongzhan Lin, Liang Bai, Zhihua Wang, Wei Bi, Richard Yi Da Xu, Guo Li, Xian Yang

Proceedings of the Findings of the Association for Computational Linguistics, 2025

Tree-of-Evolution: Tree-Structured Instruction Evolution for Code Generation in Large Language Models.

Ziyang Luo, Kaixin Li, Hongzhan Lin, Yuchen Tian, Mohan S. Kankanhalli, Jing Ma

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

SHARP: Unlocking Interactive Hallucination via Stance Transfer in Role-Playing LLMs.

Chuyi Kong, Ziyang Luo, Hongzhan Lin, Zhiyuan Fan, Yaxin Fan, Yuxi Sun, Jing Ma

Proceedings of the Findings of the Association for Computational Linguistics, 2025

AdamMeme: Adaptively Probe the Reasoning Capacity of Multimodal Large Language Models on Harmfulness.

Zixin Chen, Hongzhan Lin, Kaixin Li, Ziyang Luo, Zhen Ye, Guang Chen, Zhiyong Huang, Jing Ma

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

FACT-AUDIT: An Adaptive Multi-Agent Framework for Dynamic Fact-Checking Evaluation of Large Language Models.

Hongzhan Lin, Yang Deng, Yuxuan Gu, Wenxuan Zhang, Jing Ma, See-Kiong Ng, Tat-Seng Chua

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

Codec Does Matter: Exploring the Semantic Shortcoming of Codec for Audio Language Model.

Zhen Ye, Peiwen Sun, Jiahe Lei, Hongzhan Lin, Xu Tan, Zheqi Dai, Qiuqiang Kong, Jianyi Chen, Jiahao Pan, Qifeng Liu, Yike Guo, Wei Xue

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

Meme Trojan: Backdoor Attacks Against Hateful Meme Detection via Cross-Modal Triggers.

Ruofei Wang, Hongzhan Lin, Ziyuan Luo, Ka Chun Cheung, Simon See, Jing Ma, Renjie Wan

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Towards low-resource rumor detection: Unified contrastive transfer with propagation structure.

Hongzhan Lin, Jing Ma, Ruichao Yang, Zhiwei Yang, Mingfei Cheng

Neurocomputing, 2024

From General to Specific: Utilizing General Hallucination to Benchmark Specific Role-Playing Agents.

Chuyi Kong, Ziyang Luo, Hongzhan Lin, Zhiyuan Fan, Yaxin Fan, Yuxi Sun, Jing Ma

CoRR, 2024

MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language Models.

Shengkang Wang, Hongzhan Lin, Ziyang Luo, Zhen Ye, Guang Chen, Jing Ma

CoRR, 2024

GOAT-Bench: Safety Insights to Large Multimodal Models through Meme-Based Social Abuse.

Hongzhan Lin, Ziyang Luo, Bo Wang, Ruichao Yang, Jing Ma

CoRR, 2024

Explainable Fake News Detection with Large Language Model via Defense Among Competing Wisdom.

Bo Wang, Jing Ma, Hongzhan Lin, Zhiwei Yang, Ruichao Yang, Yuan Tian, Yi Chang

Proceedings of the ACM on Web Conference 2024, 2024

Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models.

Hongzhan Lin, Ziyang Luo, Wei Gao, Jing Ma, Bo Wang, Ruichao Yang

Proceedings of the ACM on Web Conference 2024, 2024

Unleashing Trigger-Free Event Detection: Revealing Event Correlations Via a Contrastive Derangement Framework.

Hongzhan Lin, Haiqin Yang, Ziyang Luo, Jing Ma

Proceedings of the IEEE International Conference on Acoustics, 2024

AMR-Evol: Adaptive Modular Response Evolution Elicits Better Knowledge Distillation for Large Language Models in Code Generation.

Ziyang Luo, Xin Li, Hongzhan Lin, Jing Ma, Lidong Bing

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Towards Low-Resource Harmful Meme Detection with LMM Agents.

Jianzhao Huang, Hongzhan Lin, Ziyan Liu, Ziyang Luo, Guang Chen, Jing Ma

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Reinforcement Tuning for Detecting Stances and Debunking Rumors Jointly with Large Language Models.

Ruichao Yang, Wei Gao, Jing Ma, Hongzhan Lin, Bo Wang

Proceedings of the Findings of the Association for Computational Linguistics, 2024

CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models.

Zixin Chen, Hongzhan Lin, Ziyang Luo, Mingfei Cheng, Jing Ma, Guang Chen

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

Semantic-consistent learning for one-shot joint entity and relation extraction.

Jinglei Li, Yajing Xu, Hongzhan Lin, Guang Chen, Bosen Zhang, Boya Ren

Appl. Intell., March, 2023

A Unified Contrastive Transfer Framework with Propagation Structure for Boosting Low-Resource Rumor Detection.

Hongzhan Lin, Jing Ma, Ruichao Yang, Zhiwei Yang, Mingfei Cheng

CoRR, 2023

WSDMS: Debunk Fake News via Weakly Supervised Detection of Misinforming Sentences with Contextualized Social Wisdom.

Ruichao Yang, Wei Gao, Jing Ma, Hongzhan Lin, Zhiwei Yang

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Beneath the Surface: Unveiling Harmful Memes with Multimodal Reasoning Distilled from Large Language Models.

Hongzhan Lin, Ziyang Luo, Jing Ma, Long Chen

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Dual-Scale Interest Extraction Framework with Self-Supervision for Sequential Recommendation.

Liangliang Chen, Hongzhan Lin, Jinshan Ma, Guang Chen

Proceedings of the ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland, 2023

Zero-Shot Rumor Detection with Propagation Structure via Prompt Learning.

Hongzhan Lin, Pengyao Yi, Jing Ma, Haiyun Jiang, Ziyang Luo, Shuming Shi, Ruifang Liu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

A Weakly Supervised Propagation Model for Rumor Verification and Stance Detection with Multiple Instance Learning.

Ruichao Yang, Jing Ma, Hongzhan Lin, Wei Gao

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

Detect Rumors in Microblog Posts for Low-Resource Domains via Adversarial Contrastive Learning.

Hongzhan Lin, Jing Ma, Liangliang Chen, Zhiwei Yang, Mingfei Cheng, Guang Chen

Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

AMIF: A Hybrid Model for Improving Fact Checking in Product Question Answering.

Hongzhan Lin, Liangliang Chen, Jing Ma, Zhiwei Yang, Guang Chen

Proceedings of the International Joint Conference on Neural Networks, 2022

A Coarse-to-fine Cascaded Evidence-Distillation Neural Network for Explainable Fake News Detection.

Zhiwei Yang, Jing Ma, Hechang Chen, Hongzhan Lin, Ziyang Luo, Yi Chang

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

TANTP: Conversational Emotion Recognition Using Tree-Based Attention Networks with Transformer Pre-training.

Haozhe Liu, Hongzhan Lin, Guang Chen

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

Boosting Low-Resource Intent Detection with in-Scope Prototypical Networks.

Hongzhan Lin, Yuanmeng Yan, Guang Chen

Proceedings of the IEEE International Conference on Acoustics, 2021

Rumor Detection on Twitter with Claim-Guided Hierarchical Graph Attention Networks.

Hongzhan Lin, Jing Ma, Mingfei Cheng, Zhiwei Yang, Liangliang Chen, Guang Chen

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021