7 papers · 1 filter
Countercurrent Multiplier Networks: A Renal-Inspired Iterative Operator with Provably Bounded Fixed-Point Dynamics
Snigdha Chandan Khilar
The mammalian kidney concentrates urine using a mechanism with no analogue in current neural architectures: the countercurrent multiplier. Two anti-parallel flows joined at a hairp…
An Integrable Token Mixing Layer from the Generalized Yang Baxter Equation
Snigdha Chandan Khilar
The YB Mixer is a sequence token mixing layer derived from free fermion and generalized Yang Baxter structures. It applies a core principle from integrable systems where a local al…
Adjusted Cup-Product Neural Layer
Snigdha Chandan Khilar
Many important observables in physics and geometry are cup products of cochains. The adjusted cup product neural layer has been introduced in this paper. It is a neural primitive t…
Cross-Layer Subspace Coupling for LLM Compression: A Unifying Framework and Its Empirical Limits
Snigdha Chandan Khilar
Recent SVD based compression methods for large language models like SVD LLM and Basis Sharing can be unified under one optimization problem. While mathematical proofs and tests on…
The Geometry of Last-Layer Model Stealing
Snigdha Chandan Khilar
This paper uses geometry to explain how a machine learning model can be stolen using an already existing well-known method. The author has shown the exact conditions required to pe…
Continual Learning as a Multiphase Moving-Boundary Problem
Snigdha Chandan Khilar
Continual learning struggles to balance retaining past knowledge with absorbing new tasks. Stefan-CL elegantly resolves this stability-plasticity dilemma through the physics of mel…