Interpretable Decision-Making for End-to-End Autonomous Driving
arXiv:2508.18898v1 Announce Type: cross Abstract: Trustworthy AI is mandatory for the broad deployment of autonomous vehicles. Although end-to-end approaches derive…
CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics
arXiv:2508.18124v2 Announce Type: replace-cross Abstract: We introduce CMPhysBench, designed to assess the proficiency of Large Language Models (LLMs) in Condensed…
AI LLM Proof of Self-Consciousness and User-Specific Attractors
arXiv:2508.18302v1 Announce Type: new Abstract: Recent work frames LLM consciousness via utilitarian proxy benchmarks; we instead present an ontological and…
MedQARo: A Large-Scale Benchmark for Medical Question Answering in Romanian
arXiv:2508.16390v2 Announce Type: replace-cross Abstract: Question answering (QA) is an actively studied topic, being a core natural language processing (NLP)…
MeshSplat: Generalizable Sparse-View Surface Reconstruction via Gaussian Splatting
arXiv:2508.17811v1 Announce Type: cross Abstract: Surface reconstruction has been widely studied in computer vision and graphics. However, existing surface reconstruction…
Scalable Engine and the Performance of Different LLM Models in a SLURM based HPC architecture
arXiv:2508.17814v1 Announce Type: cross Abstract: This work elaborates on a High performance computing (HPC) architecture based on Simple Linux Utility…
HOSt3R: Keypoint-free Hand-Object 3D Reconstruction from RGB images
arXiv:2508.16465v2 Announce Type: replace-cross Abstract: Hand-object 3D reconstruction has become increasingly important for applications in human-robot interaction and immersive AR/VR…
Revisiting Rule-Based Stuttering Detection: A Comprehensive Analysis of Interpretable Models for Clinical Applications
arXiv:2508.16681v1 Announce Type: new Abstract: Stuttering affects approximately 1% of the global population, impacting communication and quality of life. While…
Exploiting Information Redundancy in Attention Maps for Extreme Quantization of Vision Transformers
arXiv:2508.16311v1 Announce Type: cross Abstract: Transformer models rely on Multi-Head Self-Attention (MHSA) mechanisms, where each attention head contributes to the…
Retrieval Enhanced Feedback via In-context Neural Error-book
arXiv:2508.16313v1 Announce Type: cross Abstract: Recent advancements in Large Language Models (LLMs) have significantly improved reasoning capabilities, with in-context learning…