arXiv Computer Science @arxiv_cs@qoto.org

Vanishing Depth: A Depth Adapter with Positional Depth Encoding for Generalized Image Encoders https://arxiv.org/abs/2503.19947 #cs.CV #cs.AI

Bernstein-Vazirani Algorithm with A CCNOT-Based Oracle https://arxiv.org/abs/2503.18951 #quant-ph #cs.DS

Reclaiming the Future: American Information Technology Leadership in an Era of Global Competition https://arxiv.org/abs/2503.18952 #cs.CY

Is there a future for AI without representation? https://arxiv.org/abs/2503.18955 #cs.AI #cs.CV

International Agreements on AI Safety: Review and Recommendations for a Conditional AI Safety Treaty https://arxiv.org/abs/2503.18956 #cs.CY #cs.AI

A Real-Time Human Action Recognition Model for Assisted Living https://arxiv.org/abs/2503.18957 #cs.CV

Advancing Deep Learning through Probability Engineering: A Pragmatic Paradigm for Modern AI https://arxiv.org/abs/2503.18958 #math.PR #stat.ML #cs.AI

An Approach to Analyze Niche Evolution in XCS Models https://arxiv.org/abs/2503.18961 #cs.NE #cs.LG

Representative Ranking for Deliberation in the Public Sphere https://arxiv.org/abs/2503.18962 #cs.SI #cs.LG

Unifying EEG and Speech for Emotion Recognition: A Two-Step Joint Learning Framework for Handling Missing EEG Data During Inference https://arxiv.org/abs/2503.18964 #cs.SD #cs.AI

MedAgent-Pro: Towards Multi-modal Evidence-based Medical Diagnosis via Reasoning Agentic Workflow https://arxiv.org/abs/2503.18968 #cs.AI

How Effective Is Constitutional AI in Small LLMs? A Study on DeepSeek-R1 and Its Peers https://arxiv.org/abs/2503.17365 #cs.LG #cs.AI #cs.CY

Duality between Lines and Points https://arxiv.org/abs/2503.17372 #cs.CG #cs.DS

Intanify AI Platform: Embedded AI for Automated IP Audit and Due Diligence https://arxiv.org/abs/2503.17374 #cs.CY #cs.CE #cs.HC

Large language model-powered AI systems achieve self-replication with no human intervention https://arxiv.org/abs/2503.17378 #cs.AI #cs.CR #cs.CY #cs.ET #cs.MA

State Fourier Diffusion Language Model (SFDLM): A Scalable, Novel Iterative Approach to Language Modeling https://arxiv.org/abs/2503.17382 #cs.LG #cs.CL

Uncertainty Quantification for Data-Driven Machine Learning Models in Nuclear Engineering Applications: Where We Are and What Do We Need? https://arxiv.org/abs/2503.17385 #eess.SY #stat.ML #cs.LG #cs.SY

A new graph-based surrogate model for rapid prediction of crashworthiness performance of vehicle panel components https://arxiv.org/abs/2503.17386 #eess.SY #cs.LG #cs.SY

AI Companies Should Report Pre- and Post-Mitigation Safety Evaluations https://arxiv.org/abs/2503.17388 #cs.CY #cs.AI #cs.LG

AI-driven Automation of End-to-end Assessment of Suturing Expertise https://arxiv.org/abs/2503.17391 #cs.CV #cs.AI #cs.LG