Arjun Subramonian

Citation errors stemming from name changes can lead to significant mental health challenges for researchers, but inclusive policies can drastically reduce these issues.

Automated identification of individual animals can only be effective if it aligns with ecological questions and data practices, not just algorithmic accuracy.

Don't count on unembedding matrix geometry to predict language model performance—it's more a reflection of training hyperparameters than inherent capabilities.

Despite growing interest, queer NLP research remains largely reactive, highlighting biases instead of building proactive solutions, leaving significant opportunities for stakeholder-driven and intersectional approaches.