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Jianhan Wu

2 accepted papers

2026

MITA: A HIERARCHICAL MULTI-AGENT COLLABORATION FRAMEWORK WITH MEMORY-INTEGRATED AND TASK ALLOCATION

ICASSP 2026poster

Recent advances in large language models (LLMs) have substantially accelerated the development of embodied agents. LLM-based multi-agent systems mitigate the inefficiency of single agents in complex tasks. However, they still suffer from issues such as memory inconsistency and agent behavioral confl…

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2025

Federated Domain Generalization with Domain-specific Soft Prompts Generation

ICCV 2025poster

Prompt learning has become an efficient paradigm for adapting CLIP to downstream tasks. Compared with traditional fine-tuning, prompt learning optimizes a few parameters yet yields highly competitive results, especially appealing in federated learning for computational efficiency. engendering domain…

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