Falsifying Causal Graphs With Outlier Events
arXiv:2607.12145v1 Announce Type: new Abstract: True causal relationships are rarely known, and inferring causal graphs from data is hard. A fundamental challenge is how to assess…
Papers 5622 stories
When Does Personality Composition Matter for Multi-Agent LLM Teams?
arXiv:2606.27443v2 Announce Type: replace Abstract: Personality prompting shapes how large language models communicate, yet whether these behavioral shifts affect objective task outcomes remains under-explored. Prior work…
Connected by Construction: Learning Tractable Near-Tour Marginals for Traveling Salesman Problems
arXiv:2607.12127v1 Announce Type: new Abstract: Learning-based methods for the traveling salesman problem (TSP) are often evaluated through the tours produced after decoding or search, but the…
Graph-Based Detection of Disinformation Narrative Diffusion between Russian and Ukrainian Telegram Channels
arXiv:2607.11894v1 Announce Type: new Abstract: Detecting disinformation narratives on social media is challenging due to the scale of amplification, rapid evolution, and linguistic variability of online…
Do You Remember? Toward Memory-Centric Multimodal AI
arXiv:2607.11919v1 Announce Type: cross Abstract: Human memory is reconstructive, not a faithful recording. Current multimodal LLMs (MLLMs) lack this capability: they process images through a frozen…
ViCo3D: Empowering LiDAR-based Collaborative 3D Object Detection with Vision Foundation Models
arXiv:2607.12959v1 Announce Type: new Abstract: LiDAR-based collaborative 3D perception in Vehicle-to-Everything (V2X) systems typically relies on fusing bird's-eye-view (BEV) features across agents. However, current BEV representations,…
Generalized Distribution-Free Semi-Supervised Learning with Risk Rewrite
arXiv:2607.11947v1 Announce Type: new Abstract: Typical semi-supervised learning (SSL) methods rely on distributional assumptions, and their performance degrades when these are violated. While PNU learning, a…
Structured Fluctuations and the Information Dynamics of Self-Maintenance in Growing Neural Cellular Automata
arXiv:2607.12403v1 Announce Type: new Abstract: Growing Neural Cellular Automata (GNCA) are capable of robust self-maintenance and self-repair, yet the internal dynamical mechanisms that support these capabilities…
Dynamic Online Processor-Native Inference for State Estimation
arXiv:2607.12095v1 Announce Type: new Abstract: Sensor-rich data-driven applications increasingly use Bayesian approaches to infer latent states of dynamic systems from noisy sensor measurements and physical models.…
Toward Metaphor-Fluid Conversation Design for Voice User Interfaces
arXiv:2502.11554v3 Announce Type: replace-cross Abstract: Metaphors play a critical role in shaping user experiences with Voice User Interfaces (VUIs), yet existing designs often rely on static,…
Mistake gating leads to energy and memory efficient continual learning
arXiv:2604.14336v2 Announce Type: replace Abstract: Synaptic plasticity is metabolically expensive, yet animals continuously update their internal models without exhausting energy reserves. However, when artificial neural networks…
I'm Sorry, but I Can't Help with Braille: Revealing Accessibility Failures in State-of-the-Art LLMs
arXiv:2607.11893v1 Announce Type: new Abstract: Large Language Models (LLMs) perform strongly on many language tasks, but their capability in structurally constrained, accessibility-critical modalities such as Braille…
CreatiParser: Generative Image Parsing of Raster Graphic Designs into Editable Layers
arXiv:2604.19632v2 Announce Type: replace Abstract: Graphic design images consist of multiple editable layers, such as text, background, and decorative elements, while most generative models produce rasterized…
ACZ-GSeg: Adaptive Concentric Zone-based Two-stage Ground Segmentation for LiDAR Point Clouds
arXiv:2607.12110v1 Announce Type: new Abstract: Ground segmentation is a fundamental prerequisite for autonomous navigation, environmental perception, and object detection in ground mobile platforms. To address the…
Deep4ge: DNN Training Trajectories for Fault Detection and Diagnosis
arXiv:2607.12868v1 Announce Type: cross Abstract: Deep learning systems often fail due to subtle implementation faults that alter training behavior. Recent work has studied how to detect…
QDEvo: A Multi-Objective Quality-Diversity Framework for Automated Heuristic Design
arXiv:2607.11916v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) with evolutionary computation has emerged as a powerful paradigm for automated heuristic design in…
Quantification of Credal Uncertainty: A Distance-Based Approach
arXiv:2603.27270v2 Announce Type: replace-cross Abstract: Credal sets, i.e., closed convex sets of probability measures, provide a natural framework to represent aleatoric and epistemic uncertainty in machine…
The One-Word Census: Answer-Choice Conformity Across 44 Language Models
arXiv:2607.12796v1 Announce Type: cross Abstract: When a language model must pick one answer from a large space of equally valid options, which does it pick --…
The Emerging Paradigm of Geospatial Foundation Models: From Pre-Training to Agentic Reasoning
arXiv:2607.12177v1 Announce Type: new Abstract: The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models. This paper describes…
G-SHARE: A Guideline-Based Structured Reasoning Framework for Human-Factor Event Diagnosis
arXiv:2607.11892v1 Announce Type: new Abstract: Human-factor event diagnosis is essential for learning from operational events in nuclear power plants, yet its quality depends strongly on expert…
MoHallBench: A Benchmark for Motion Hallucination in Video Large Language Models
arXiv:2607.01117v2 Announce Type: replace Abstract: Video Large Language Models (VideoLLMs) have shown strong progress in video understanding, yet they still suffer from hallucinations that are inconsistent…
Continual Learning with Elastic Regularization and Synthetic Replay for Federated MLLM Fine-Tuning
arXiv:2607.12112v1 Announce Type: cross Abstract: Federated fine-tuning of Multimodal Large Language Models (MLLMs) across distributed networks enables privacy-sensitive adaptation to evolving data streams, yet a fundamental…
Scale-Aware Attention for Scarce Neural Data: An RG-Flow Transformer on Sleep-EDF EEG
arXiv:2607.11950v1 Announce Type: new Abstract: Brain field potentials are scale-free: their power spectra follow a $1/f^{beta}$ law whose aperiodic exponent $beta$ tracks cortical state, and sleep…
Burst Spiking Neural Networks
arXiv:2607.11914v1 Announce Type: new Abstract: A central goal of current Spiking Neural Network (SNN) research is to improve their accuracy toward becoming low-power alternatives to Artificial…