Minimal Decision Dynamics and Contextual Probability: A Quantum Tug-of-War Model
arXiv:2601.10034v2 Announce Type: cross Abstract: Decision making often exhibits context dependence that challenges classical probability theory. This paper develops a…
Evaluating Retrieval-Augmented Generation vs. Long-Context Input for Clinical Reasoning over EHRs
arXiv:2508.14817v2 Announce Type: replace-cross Abstract: Objective: To evaluate whether retrieval-augmented generation (RAG) can serve as an efficient alternative to long-context…
Riemannian Geometry for Pre-trained Language Model Embeddings
arXiv:2607.07047v2 Announce Type: replace-cross Abstract: Understanding the geometric structure of pre-trained language model embeddings matters for interpretability and safety. We…
Diversifying to Verify: When Task-Equivalent Programs Differ in Verifiability
arXiv:2607.09366v1 Announce Type: cross Abstract: Program verification is crucial for software correctness, but producing fully verified programs remains difficult in…
Search Beyond What Can Be Taught: Evolving the Knowledge Boundary in Agentic Visual Generation
arXiv:2607.05382v3 Announce Type: replace-cross Abstract: Visual generators excel at rendering, but they confidently fabricate what they do not know. User…
On the Role of Conversational Timing in Synthetic Training Data for ASR
arXiv:2607.08371v1 Announce Type: cross Abstract: Synthetic multi-speaker conversations are widely used to train conversational automatic speech recognition (ASR) systems, but…
Self-Adaptive Anomaly Detection with Reinforcement Learning and Human Feedback in Connected Vehicles
arXiv:2607.08373v1 Announce Type: cross Abstract: Connected vehicles are autonomous cyber-physical systems whose behavior must be continuously monitored during operation to…
Behavior Foundations for Quadruped Robots: ABot-C0 Technical Report
arXiv:2607.07370v2 Announce Type: replace-cross Abstract: The motion controller is one of the most fundamental modules in embodied intelligence systems. Driven…
Context Graphs for Proactive Enterprise Agents
arXiv:2607.07721v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) and agentic frameworks have advanced enterprise AI considerably, yet agents remain fundamentally…