The Workshop on LLM for Scientific Discovery
Welcome to the LLM for Scientific Discovery: Reasoning, Assistance, and Collaboration (LM4Sci), a forum for researchers, practitioners, and stakeholders working at the intersection of artificial intelligence and scientific discovery.
About the Workshop
Significant advancements in Large Language Models (LLMs) have spurred interest in using these frontier AI models to assist researchers in various scientific tasks, such as:
- Idea generation and brainstorming
- Experiment execution and automated ML engineering
- Searching and synthesizing literature reviews
- Literature-based question-answering
- Data analysis and data-driven discovery
- End-to-end research pipeline including paper generation
Many of these AI systems are shown to be helpful tools for human researchers to accelerate the scientific discovery process. For example, systems like Scideator provide assistance such as key facet extraction from papers and automated novelty assessment with explanations to facilitate ideation. Beyond these simple collaboration modes, there is still a huge under-explored space for building helpful AI tools for accelerating scientific research and fostering more effective human-AI collaboration in science.
The focus of our workshop is on developing LLMs and AI systems that can accelerate scientific research in various scientific domains and assist human researchers. We aim to bring together researchers from different communities, including ML, NLP, Human-Computer Interaction, and various scientific disciplines such as biology and chemistry, to work together on the design, development, and evaluation of various forms of scientific LLMs and systems.