Jul 28, 2026
DSCH-Loss: A Dynamic Semantic Channel Objective for Deep Semantic Hashing
Deep learning-based semantic hashing is a powerful technique for organizing high-dimensional data into short binary codes, enabling fast and efficient search...
Jul 28, 2026
TRACE-CTI: Auditable Post-Extraction Governance of TTP Claims with Knowledge Graphs
TRACE-CTI: Auditable Post-Extraction Governance of TTP Claims with Knowledge Graphs Security Operations Centers (SOCs) frequently use automated tools to map...
Jul 27, 2026
Do Agent Benchmarks Measure Capability? Protocol Validity in the Age of Agentic AI
This paper investigates whether current AI agent benchmarks actually measure the capabilities they claim to test.
Jul 24, 2026
Regulating autonomous and agentic AI
Regulating autonomous and agentic AI The paper "Regulating autonomous and agentic AI" examines the growing disconnect between traditional regulatory framewor...
Jul 24, 2026
Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems
Agentic Context Management: Solving Agent Memory and Cost by Treating Them as Lifecycle and Architecture Problems proposes a shift in how AI agents handle in...
Jul 22, 2026
Graph-Based Agentic AI with LangGraph: Workflow Pathways for Long-Running Stateful Business Processes
Graph-Based Agentic AI with LangGraph: Workflow Pathways for Long-Running Stateful Business Processes provides a practical guide for developers building comp...
Jul 22, 2026
Comparative Study of Multi-Agent Actor-Critic Algorithms in Parameterized Action Reinforcement Learning
Comparative Study of Multi-Agent Actor-Critic Algorithms in Parameterized Action Reinforcement Learning This research explores how to scale reinforcement lea...
Jul 21, 2026
The Shared Discovery Paradox: How a One-Answer Rule Turns Better Information into Worse Search
The Shared Discovery Paradox: How a One-Answer Rule Turns Better Information into Worse Search This paper investigates a common organizational failure: when...
Jul 17, 2026
Long-Context Fine-Tuning with Limited VRAM
Long-Context Fine-Tuning with Limited VRAM Training large language models on long sequences is typically limited by the massive amount of memory required to...
Jul 17, 2026
Explaining Process Control Optimisation Recommendations via GradientSHAP and Implicit Differentiation
Explaining Process Control Optimisation Recommendations via GradientSHAP and Implicit Differentiation Modern industrial processes rely on automated optimisat...