Ollivier-Ricci Curvature of Riemannian Manifolds and Directed Graphs with Applications to Graph Neural Networks

Local Linearity of LLMs Enables Activation Steering via Model-Based Linear Optimal Control

arXiv:2604.19018v1 Announce Type: cross Abstract: Inference-time LLM alignment methods, particularly activation steering, offer an alternative to fine-tuning by directly modifying activations during generation. Existing methods,

Choose Your Own Adventure: Non-Linear AI-Assisted Programming with EvoGraph

arXiv:2604.18883v1 Announce Type: cross Abstract: Current AI-assisted programming tools are predominantly linear and chat-based, which deviates from the iterative and branching nature of programming itself.

Assessing Capabilities of Large Language Models in Social Media Analytics: A Multi-task Quest

arXiv:2604.18955v1 Announce Type: cross Abstract: In this study, we present the first comprehensive evaluation of modern LLMs – including GPT-4, GPT-4o, GPT-3.5-Turbo, Gemini 1.5 Pro,

Cyber Defense Benchmark: Agentic Threat Hunting Evaluation for LLMs in SecOps

arXiv:2604.19533v1 Announce Type: cross Abstract: We introduce the Cyber Defense Benchmark, a benchmark for measuring how well large language model (LLM) agents perform the core

Semantic Needles in Document Haystacks: Sensitivity Testing of LLM-as-a-Judge Similarity Scoring

arXiv:2604.18835v1 Announce Type: cross Abstract: We propose a scalable, multifactorial experimental framework that systematically probes LLM sensitivity to subtle semantic changes in pairwise document comparison.