Agentic multi-agent LLM system for controllable text clustering outperforms fixed-pipeline baselines by up to 32% ARI on seven public benchmarks.
Agent-centric personalized mul- tiple clustering with multi-modal llms.arXiv preprint arXiv:2503.22241, 2025
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A hybrid LLM agent framework performs universal image clustering by generating guideline-aware embeddings via concept proxies and using MST-based LLM traversal for automatic discovery.
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Agentic Clustering: Controllable Text Taxonomies via Multi-Agent Refinement
Agentic multi-agent LLM system for controllable text clustering outperforms fixed-pipeline baselines by up to 32% ARI on seven public benchmarks.
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Universal Guideline-Driven Image Clustering via a Hybrid LLM Agent
A hybrid LLM agent framework performs universal image clustering by generating guideline-aware embeddings via concept proxies and using MST-based LLM traversal for automatic discovery.