3 papers
cs.LG2026
At the Edge of Understanding: Sparse Autoencoders Trace The Limits of Transformer Generalization
Praneet Suresh, Jack Stanley, Sonia Joseph +2
Pre-trained transformers have demonstrated remarkable generalization abilities, at times extending beyond the scope of their training data. Yet, real-world deployments often face u…
cs.LG2026
Quantifying LLM Attention-Head Stability: Implications for Circuit Universality
Karan Bali, Jack Stanley, Praneet Suresh +1
In mechanistic interpretability, recent work scrutinizes transformer "circuits" - sparse, mono or multi layer sub computations, that may reflect human understandable functions. Yet…
cs.LG2025
From Noise to Narrative: Tracing the Origins of Hallucinations in Transformers
Praneet Suresh, Jack Stanley, Sonia Joseph +2
As generative AI systems become competent and democratized in science, business, and government, deeper insight into their failure modes now poses an acute need. The occasional vol…