Ziyang Luo
Ziyang Luo has 3 papers in our library, in 2023–2026, most of them on Language models & pretraining, Sentiment & emotion, Vision & language; often with Jing Ma, Hongzhan Lin, Can Xu.
OpenAlex · ORCID · h-index 12 · 23 works · 999 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 31 times in our library · ⭐ Paper Stars ranking: #7684
Affiliations
Fields, topics and concepts
📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 3 worksArtificial Intelligence · 3 worksComputer Vision and Pattern Recognition · 2 worksArts and Humanities · 2 worksLanguage and Linguistics · 2 works
🧭 Topics 3Research subjects and languages the work is about.Language models & pretraining · 1 workSentiment & emotion · 1 workVision & language · 1 work
Works by year
2020s
Papers
- Augmented Large Language Models with Parametric Knowledge Guiding (2023 · 32 citations)
Commercial LLMs that are reachable only through APIs often perform poorly on tasks that need specialised domain knowledge. - CofiPara: A Coarse-to-fine Paradigm for Multimodal Sarcasm Target Identification with Large Multimodal Models (2024 · 20 citations)
The paper tackles Multimodal Sarcasm Target Identification (MSTI), which means locating the mocked entity in a social-media post as both a text span and an image bounding box. - From Storage to Experience: A Survey on the Evolution of LLM Agent Memory Mechanisms (2026 · 3 citations)
LLM-based agents are stateless by default. They struggle to stay coherent across long multi-step tasks and cannot learn from earlier interactions. Work on agent memory is split between an engineering camp that borrows operating-system ideas and a camp that imitates human cognition. Earlier surveys mostly catalogue…
Co-authors here
- Jing Ma ×3
- Hongzhan Lin ×2
- Can Xu
- Chongyang Tao
- Daxin Jiang
- Kaixin Li
- Pu Zhao
- Qingwei Lin
- Xiubo Geng
- Zixin Chen
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2024
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
Cited by
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