How is OR Related to NLP Systems?

The relationship is tenuous at first glance but it exists. My goal is to design algorithms to optimize NLP systems so that they are seamless in their interactions with us. For me, this looks like formalizating methods for reasoning-intensive problems both mathematically and empirically.

This research area involves developing novel algorithms that can handle the unique challenges of language models, such as:

• Optimizing retrieval mechanisms for knowledge-intensive tasks.
• Creating mathematical formalisms that can prove properties about language model reasoning.
• Building optimization frameworks that balance model performance with computational efficiency.

For the last bullet, traditionally, OR techniques have been used to optimize computational resources of which LLMs are an example! Just take a look this Online Scheduling for LLM Inference with KV Cache Constraints paper written by operations research, reseachers. While not exactly aligned with my interest, it is quite telling: research at this intersection can help develop more efficient, reliable, and theoretically grounded language technologies.

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