From the 2 of 9 linked papers with an AI index.
9 papers
Memory Efficient Tabular Foundation Models
Shuting Luo, Monika Mikhail Kanaan, Cameron Gordon +2
The paper studies how to reduce the memory footprint of tabular foundation models like TabPFN using compression techniques, achieving up to 7.6× memory savings with little performa…
Beyond Generalist LLMs: Specialist Agentic Systems for Structured Code Workflow Execution
Harris Borman, Herman Wandabwa, Fusun Yu +4
The paper evaluates specialist AI agents designed to convert BPMN business process diagrams into deterministic, executable workflows, showing they outperform general-purpose LLM ag…
EmbGen: Teaching with Reassembled Corpora
Arun K Lenin, Kai Rouse, Andrea Nicastro +1
Adapting small instruction-tuned models to specialized domains often relies on supervised fine-tuning (SFT) on curated instruction-response examples, which is expensive to collect…
Prompt Segmentation and Annotation Optimisation: Controlling LLM Behaviour via Optimised Segment-Level Annotations
Devika Prasad, Luke Gerschwitz, Tong Li +5
Prompt engineering is crucial for effective interaction with generative artificial intelligence systems, yet existing optimisation methods often operate over an unstructured and va…
Learning Adapter Rank via Symmetry Breaking
Cooper Doyle, Andy Hu, Rebecca Chan +1
Low-rank adaptation is effective partly because downstream updates lie in a low-dimensional subspace, but the latent rank coordinates of LoRA are not identifiable: any invertible r…
BOND: License to Train with Black-Box Functions
Andrew Clark, Jack Moursounidis, Osmaan Rasouli +3
We introduce Bounded Numerical Differentiation (BOND), a perturbative method for estimating the gradients of black-box functions. BOND is distinguished by its formulation, which ad…