Topic
agentic framework
Agentic Framework Achieves 91% Numerical Equivalence in PyTorch-to-JAX Migration via In-Context Learning
Researchers propose an autonomous system that combines in-context learning (ICL) with oracle-driven self-debugging to translate deep learning models from PyTorch to JAX. The lightweight pipeline achieves 91% numerical equivalence, far outperforming baseline methods (9%) and instruction-plus-self-debugging (27%). Validated on models including SAM, T5, and Code Whisper.
New Agentic LLM Framework Improves HTS Tariff Code Classification for Maritime Logistics
Researchers have developed a consensus-based agentic large language model framework for Harmonized Tariff Schedule (HTS) code classification, addressing challenges in maritime logistics. The framework integrates multi-agent retrieval, evidence-grounded reasoning, and human-in-the-loop escalation, outperforming single-step LLM predictions on a private dataset of 3,300 product records.