3 papers
cs.AI2026
PRO-LONG: Programmatic Memory Enables Long-Horizon Reasoning
Alexis Fox, Junlin Wang, Paul Rosu +1
Long-horizon tasks require sustained perception, reasoning, and exploration, and are a persistent challenge for large language model (LLM) agents. This gap is reflected in their li…
cs.LG2026
Interpretable-by-Design Transformers via Architectural Stream Independence
Clayton Kerce, Alexis Fox
While transformers achieve strong performance, their internal decision-making processes remain opaque. We investigate whether architectural constraints can enforce interpretability…
cs.CL2026
The Dual-Stream Transformer: Channelized Architecture for Interpretable Language Modeling
J. Clayton Kerce, Alexis Fox
Standard transformers entangle all computation in a single residual stream, obscuring which components perform which functions. We introduce the Dual-Stream Transformer, which deco…