My research focuses on NLP, data mining, and AI for science and healthcare, including weakly supervised language understanding, reasoning and planning with language model agents, and interpretable multi-modal foundation models for text, omics, and brain data.
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Natural Language Understanding with Limited Supervision:
- Information extraction, knowledge graph construction, text classification, …
- Weakly-supervised/few-shot/zero-shot learning
Complex Reasoning and Planning with Language Model Agents:
- Complex reasoning with large language models (multi-hop, long-context, …)
- Multi-agent large language models for reasoning and planning
- Efficient small language models for reasoning and planning
Multi-Modal Science Foundation Models (FMs):
- Systematic integration of multi-modal FMs
- Interpretability, explainability, and causal inference of science FMs
- Text data, multi-omics data, brain signal data, …
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