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Hongzhan Lin

Hong Kong Baptist University, Hong Kong

22 papers at tracked venues · 17 at CORE A* · active 20242026

Venues

Frequent coauthors

Papers

  1. Dialectical Structured Reasoning for Explainable Multimodal Fake News Detection
  2. DiffCoT: Diffusion-styled Chain-of-Thought Reasoning in LLMs
  3. From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms
  4. REFLEX: Self-Refining Explainable Fact-Checking via Verdict-Anchored Style Control
  5. AdamMeme: Adaptively Probe the Reasoning Capacity of Multimodal Large Language Models on Harmfulness
  6. Codec Does Matter: Exploring the Semantic Shortcoming of Codec for Audio Language Model
  7. FACT-AUDIT: An Adaptive Multi-Agent Framework for Dynamic Fact-Checking Evaluation of Large Language Models
    ACL 2025 · Hongzhan Lin
  8. Knowledge-Augmented Multimodal Clinical Rationale Generation for Disease Diagnosis with Small Language Models
  9. MM-CRITIC: A Holistic Evaluation of Large Multimodal Models as Multimodal Critique
  10. Meme Trojan: Backdoor Attacks Against Hateful Meme Detection via Cross-Modal Triggers
  11. MemeArena: Automating Context-Aware Unbiased Evaluation of Harmfulness Understanding for Multimodal Large Language Models
  12. ProMedTS: A Self-Supervised, Prompt-Guided Multimodal Approach for Integrating Medical Text and Time Series
  13. SHARP: Unlocking Interactive Hallucination via Stance Transfer in Role-Playing LLMs
  14. ScratchEval: Are GPT-4o Smarter than My Child? Evaluating Large Multimodal Models with Visual Programming Challenges
  15. ScreenSpot-Pro: GUI Grounding for Professional High-Resolution Computer Use
  16. Tree-of-Evolution: Tree-Structured Instruction Evolution for Code Generation in Large Language Models
  17. AMR-Evol: Adaptive Modular Response Evolution Elicits Better Knowledge Distillation for Large Language Models in Code Generation
  18. CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models
  19. Explainable Fake News Detection with Large Language Model via Defense Among Competing Wisdom
  20. Reinforcement Tuning for Detecting Stances and Debunking Rumors Jointly with Large Language Models
  21. Towards Explainable Harmful Meme Detection through Multimodal Debate between Large Language Models
    WWW 2024 · Hongzhan Lin
  22. Towards Low-Resource Harmful Meme Detection with LMM Agents