Protocol Radar — Week 2026-W06

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Research

• Representation Learning Enhanced Deep Reinforcement Learning for Optimal Operation of Hydrogen-based Multi-Energy Systems
  arXiv cs.LG (new submissions) · 2026-02-03
  arXiv:2602.00027v1 Announce Type: new Abstract: Hydrogen-based multi-energy systems (HMES) have emerged as a promising low-carbon and energy-efficient solution, as it can enable the coordinated operation of electricity, heating and cooling supply and demand to
• Measurement for Opaque Systems: Multi-source Triangulation with Interpretable Machine Learning
  arXiv cs.LG (new submissions) · 2026-02-03
  arXiv:2602.00022v1 Announce Type: new Abstract: We propose a measurement framework for difficult-to-access contexts that uses indirect data traces, interpretable machine-learning models, and theory-guided triangulation to fill inaccessible measurement spaces.
• OGD4All: A Framework for Accessible Interaction with Geospatial Open Government Data Based on Large Language Models
  arXiv cs.LG (new submissions) · 2026-02-03
  arXiv:2602.00012v1 Announce Type: new Abstract: We present OGD4All, a transparent, auditable, and reproducible framework based on Large Language Models (LLMs) to enhance citizens' interaction with geospatial Open Government Data (OGD).
• G-MemLLM: Gated Latent Memory Augmentation for Long-Context Reasoning in Large Language Models
  arXiv cs.CL (new submissions) · 2026-02-03
  arXiv:2602.00015v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in natural language understanding, yet they remain constrained by the finite capacity of their context windows and the inherent difficulty of
• Unlocking Electronic Health Records: A Hybrid Graph RAG Approach to Safe Clinical AI for Patient QA
  arXiv cs.CL (new submissions) · 2026-02-03
  arXiv:2602.00009v1 Announce Type: new Abstract: Electronic health record (EHR) systems present clinicians with vast repositories of clinical information, creating a significant cognitive burden where critical details are easily overlooked.
• PPoGA: Predictive Plan-on-Graph with Action for Knowledge Graph Question Answering
  arXiv cs.CL (new submissions) · 2026-02-03
  arXiv:2602.00007v1 Announce Type: new Abstract: Large Language Models (LLMs) augmented with Knowledge Graphs (KGs) have advanced complex question answering, yet they often remain susceptible to failure when their initial high-level reasoning plan is flawed.
• From Gameplay Traces to Game Mechanics: Causal Induction with Large Language Models
  arXiv cs.AI (new submissions) · 2026-02-03
  arXiv:2602.00190v1 Announce Type: new Abstract: Deep learning agents can achieve high performance in complex game domains without often understanding the underlying causal game mechanics.
• Learning to Price: Interpretable Attribute-Level Models for Dynamic Markets
  arXiv cs.AI (new submissions) · 2026-02-03
  arXiv:2602.00188v1 Announce Type: new Abstract: Dynamic pricing in high-dimensional markets poses fundamental challenges of scalability, uncertainty, and interpretability.
• Scalable and Secure AI Inference in Healthcare: A Comparative Benchmarking of FastAPI and Triton Inference Server on Kubernetes
  arXiv cs.AI (new submissions) · 2026-02-03
  arXiv:2602.00053v1 Announce Type: new Abstract: Efficient and scalable deployment of machine learning (ML) models is a prerequisite for modern production environments, particularly within regulated domains such as healthcare and pharmaceuticals.

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• 2026-W06 · 9 items · 2026-01-26 → 2026-02-03