Search: “papers”

Diffusion Models for Smarter UAVs: Decision-Making and Modeling

arXiv:2501.05819v2 Announce Type: replace-cross Abstract: Uncrewed Aerial Vehicles (UAVs) are increasingly used in modern communication networks. However, challenges in decision-making and digital mod

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Do Large Language Models Play Six Degrees of Separation? Measuring Topological Compression in Long-Context Manifolds

DGX agent

arXiv:2608.17950v1 Announce Type: new Abstract: Large Language Models (LLMs) demonstrate remarkable multi-hop reasoning capabilities over long contexts, yet the internal mechanisms enabling these dist

researcharxiv-cs-cl

19 Aug 2026

Evaluating the Diversity of AI-Generated Content with Diversity Profiles

model-releasesarxiv-cs-ai

arXiv:2608.17731v1 Announce Type: new Abstract: Diversity is a fundamental criterion for evaluating generative artificial intelligence (AI) systems, yet its measurement remains inherently ambiguous. E

Exact Reformulation and Optimization for Direct Metric Optimization in Binary Imbalanced Classification

arXiv:2507.15240v2 Announce Type: replace Abstract: For classification with imbalanced class frequencies, i.e., imbalanced classification (IC), standard accuracy is known to be misleading as a perform

From Global Benchmarks to Local Evaluations: Benchmarking LLMs for the German Public Sector

arXiv:2608.17827v1 Announce Type: new Abstract: Public institutions face a persistent challenge in selecting LLMs suited to their specific context. Existing benchmarks, however, are of limited use as

researcharxiv-cs-cl

From Student Risk Prediction to SC2R: Semantics-Constrained Counterfactual Recourse for Educational Decision Support

arXiv:2608.17618v1 Announce Type: cross Abstract: Learning analytics models can identify students at risk of poor performance, but they do not directly indicate which interventions are feasible, actio

applicationsarxiv-cs-ai

Future-Back Threat Modeling: A Foresight-Driven Security Framework

arXiv:2511.16088v3 Announce Type: replace-cross Abstract: Traditional threat modeling remains reactive-focused on known TTPs and past incident data, while threat prediction and forecasting frameworks

GADR: Gathering Architecture Decision Records from Meeting Transcriptions

arXiv:2608.17694v1 Announce Type: cross Abstract: Existing LLM-based approaches to Architecture Decision Record (ADR) generation share a critical and largely unexamined assumption: that input is alrea

General Semantic Knowledge Infusion for Spatio-Temporal Traffic Forecasting

arXiv:2608.17440v1 Announce Type: new Abstract: Although Graph Neural Networks (GNNs) have made significant advances in spatio-temporal traffic forecasting, their performance is limited when they rely

tutorialsarxiv-cs-lg

Global Convergence of Gradient EM for Over-Parameterized Gaussian Mixtures

arXiv:2506.06584v2 Announce Type: replace Abstract: Learning Gaussian Mixture Models (GMMs) is a fundamental problem in statistics and machine learning, with the Expectation-Maximization (EM) algorith

researcharxiv-cs-lg

GSToken: Geometry-Structured Gaussian Tokens for Compact 3D Medical Image Representation

model-releasesarxiv-cs-cv

arXiv:2608.17425v1 Announce Type: new Abstract: Effective segmentation of multi-modal MRI is central to improving neural network accuracy in brain tumor recognition. Existing methods typically compres

How much of the weight-space perception gap is actually symmetry? Evidence from ~1.8M fitted SIRENs [R]

model-releasesr-machinelearning

I’ve been looking at a fairly basic question in weight-space learning that I don’t think gets separated cleanly enough: Why does reading semantics directly from neural network weights work pretty well

Information fusion and machine learning for sensitivity analysis using physics knowledge and experimental data

arXiv:2608.17248v1 Announce Type: cross Abstract: When computational models (either physics-based or data-driven) are used for the sensitivity analysis of engineering systems, the sensitivity estimate

applicationsarxiv-cs-lg

Integrating Novelty and Surprise for Experience Prioritization and Exploration in Image-Based Reinforcement Learning

arXiv:2608.17373v1 Announce Type: cross Abstract: Sample efficiency is a central challenge in reinforcement learning (RL), particularly in image-based domains where agents must learn from high-dimensi

Intent-Driven Dynamic Chunking: Segmenting Documents to Reflect Predicted Information Needs

arXiv:2602.14784v1 Announce Type: cross Abstract: Breaking long documents into smaller segments is a fundamental challenge in information retrieval. Whether for search engines, question-answering syst

tutorialsarxiv-cs-ai

KernelArc: A Multi-Agent Framework for GPU Kernel Optimization

model-releasesarxiv-cs-ai

arXiv:2608.17071v1 Announce Type: new Abstract: We present KernelArc, a multi-agent framework for autonomous GPU kernel optimization across heterogeneous workloads. Strategy-specialized agents run in

Know3D: Prompting 3D Generation with Knowledge from Vision-Language Models

arXiv:2603.22782v2 Announce Type: replace Abstract: Recent advances in 3D generation have improved the fidelity and geometric details of synthesized 3D assets. However, due to the inherent ambiguity o

researcharxiv-cs-cv

Language Has Two Parameters: Narrative-Induced Semantic Plasticity and Phase-Sensitive Interpretation

model-releasesarxiv-cs-cl

arXiv:2608.18041v1 Announce Type: new Abstract: Language has two parameters. Count how often words occur together and you estimate amplitude, the strength of association. Word embeddings and attention

LLM Enhancement with Domain Expert Mental Model to Reduce LLM Hallucination with Causal Prompt Engineering

arXiv:2509.10818v2 Announce Type: replace Abstract: When consequential decisions depend on knowledge that exists nowhere in writing, LLMs hallucinate not from retrieval failure but from model absence.

LLM-Only PDDL Domain Repair with Open-Weight Models

arXiv:2608.17341v1 Announce Type: new Abstract: AI planning is concerned with finding a sequence of actions that achieves a specified goal. It relies on explicit models of the world, commonly represen

Looking Beyond the Scale: Do Surgical Skill Models Learn Transferable Representations Across Assessment Rubrics?

arXiv:2608.17519v1 Announce Type: new Abstract: Vision-based surgical skill assessment has shown strong in-domain results, yet a fundamental question remains unasked: do these models learn transferabl

tutorialsarxiv-cs-cv

LSem2Vec: A Simple yet Effective Two-Stage Approach for Source Code Embedding

arXiv:2409.14644v4 Announce Type: replace-cross Abstract: The advent of large language models (LLMs) has significantly advanced artificial intelligence in software engineering, with source code embedd

MagViT: Interpretable Multi-Magnification Transformers with Patient-Level Model Selection for Breast Histopathology

arXiv:2608.16959v1 Announce Type: cross Abstract: Breast cancer is one of the most common types of cancer among women around the world. Rapid detection and early treatment can hinder its progress to m

researcharxiv-cs-cv

Local Ai

Mixture-of-Expert Blocks Contain Strong Hallucination Detection Signals

arXiv:2608.17687v1 Announce Type: new Abstract: Despite their widespread use, Large Language Models (LLMs) remain limited by a fundamental problem: the generation of plausible but false content, known

local-aiarxiv-cs-ai

Multi-Observer Vehicle Localization Case Study with Roadside Radar and Connected Vehicle Sensing

arXiv:2608.16966v1 Announce Type: new Abstract: In modern intelligent transportation systems, it is essential to accurately estimate vehicle positions, especially in mixed traffic conditions where bot

applicationsarxiv-cs-cv

Hardware

Multi-Scale Spectral Attention Module-based Hyperspectral Segmentation in Autonomous Driving Scenarios

arXiv:2506.18682v3 Announce Type: replace-cross Abstract: Recent advances in autonomous driving (AD) have highlighted the potential of hyperspectral imaging (HSI) for enhanced environmental perception

hardwarearxiv-cs-ai

N-gram-like Language Models Predict Naturalistic Reading Time Best

arXiv:2603.09872v2 Announce Type: replace Abstract: Recent work has found that contemporary language models such as transformers can become so good at next-word prediction that the probabilities they

researcharxiv-cs-cl

NeuroAbs: A Neuro-Symbolic RTL Abstraction Framework for Property Checking Acceleration

arXiv:2608.17304v1 Announce Type: cross Abstract: Formal verification is a crucial technique for ensuring the functional correctness of hardware designs. In the context of property checking, a key cha

tutorialsarxiv-cs-ai

New open-source agent harness just landed! I got early access to TrueForge by TrueFoundry and have been running it locally for the past few …

New open-source agent harness just landed! I got early access to TrueForge by TrueFoundry and have been running it locally for the past few days. The harness layer deserves as much attention as the mo

model-releasesdair-ai--x

NGS-Marker: Robust Native Watermarking for 3D Gaussian Splatting

arXiv:2608.17447v1 Announce Type: new Abstract: With the rapid development and adoption of 3D Gaussian Splatting (3DGS), the need for effective copyright protection has become increasingly critical. E

applicationsarxiv-cs-cv

Nonlocal Transition Kernel for Efficient Learning of Restricted Boltzmann Machines

arXiv:2608.17450v1 Announce Type: cross Abstract: Learning restricted Boltzmann machines (RBMs) is computationally challenging because it requires expectations whose exact evaluation is generally intr

researcharxiv-cs-lg

Online Generalized Sparse Regression: How Does Overparametrization Help?

arXiv:2608.17466v1 Announce Type: cross Abstract: Regularized sparse regression has been extensively studied in the offline setting, but online formulation remains relatively under-explored. This gap

Proactive Road Safety Intervention in Australia: Predicting Risky Driving Hotspots from Connected Vehicle Data

arXiv:2608.16913v1 Announce Type: new Abstract: Road safety monitoring has historically been reactive, relying on crash-record analysis after fatalities and injuries have already occurred. Proactive i

safetyarxiv-cs-lg

Reflex-Guard: A Low-Latency Guardrail for LLM Prompt Safety Using Dense Semantic Embeddings

model-releasesarxiv-cs-cl

arXiv:2608.17556v1 Announce Type: cross Abstract: Large Language Models (LLMs) in real-world applications often face the risks of specially crafted prompts designed to bypass the safety controls. Exis

Reinforcement Learning as (Discrete) Potential Theory

arXiv:2608.17181v1 Announce Type: new Abstract: Reinforcement learning (RL) theory fundamentally depends on probability theory through the Markov chain. There is a deep connection between probability

safetyarxiv-cs-lg

Revisiting WEASEL 2.0: Reproduction, Sensitivity, and an Adaptive Ensemble-Size Rule

arXiv:2608.18021v1 Announce Type: new Abstract: WEASEL 2.0 is a dictionary-based time series classifier that combines dilated sliding windows with a randomised hyperparameter ensemble and a fixed-size

researcharxiv-cs-lg

RoBell-RVFL: A Robust Generalized Bell Random Vector Functional Link Network

arXiv:2608.16965v1 Announce Type: new Abstract: The dominance of majority classes in real-world datasets poses a fundamental challenge to randomized neural networks, often biasing decision boundaries

S^3AM: A Single-Stream SAM with Reliability-Calibrated Frequency Adapter for Multi-modal Salient Object Detection

model-releasesarxiv-cs-cv

arXiv:2608.17475v1 Announce Type: new Abstract: Vision foundation models have recently advanced multi-modal salient object detection (MSOD) through parameter-efficient tuning and prompt learning. Howe

Scalix: Uncertainty-Aware Scale-Consistent Monocular SLAM

arXiv:2608.17553v1 Announce Type: new Abstract: Cameras are ubiquitous sensors in robotics due to their compact form factor and the perceptual richness captured through visual information. Monocular S

researcharxiv-cs-ro

SCRIBES: Web-Scale Script-Based Semi-Structured Data Extraction with Reinforcement Learning

arXiv:2510.01832v2 Announce Type: replace Abstract: Semi-structured content in HTML tables, lists, and infoboxes accounts for a substantial share of factual data on the web, yet the formatting complic

researcharxiv-cs-cl

SFMformer: A Spatial-Frequency Modulation Transformer for Lightweight Image Super-Resolution

model-releasesarxiv-cs-cv

arXiv:2608.17966v1 Announce Type: new Abstract: Sparse attention mechanisms, which score all token pairs but propagate only the strongest, now underpin the most efficient Transformers for lightweight

Speak in Context: Multilingual ASR with Speech Context Alignment via Contrastive Learning

arXiv:2603.06505v2 Announce Type: replace Abstract: Automatic speech recognition (ASR) has benefited from advances in pretrained speech and language models, yet most systems remain constrained to mono

safetyarxiv-cs-cl

SPVC: Structured and Panoptic Video Fixing for Cross-Dataset Driving Scene Rendering

arXiv:2608.17420v1 Announce Type: new Abstract: Driving scene reconstruction and rendering, especially with 3D Gaussian Splatting, has become an important component of autonomous driving simulation. H

agentsarxiv-cs-cv

Structural Plan-to-Model Conversion with Deterministic Geometry and Guarded Agentic Vision-Language Refinement

model-releasesarxiv-cs-ai

arXiv:2608.17237v1 Announce Type: cross Abstract: Converting structural framing plans into editable finite-element model drafts remains labor-intensive and prone to transcription error. Existing drawi

SW-ProxyCE: Zero-Query Adversarial Transfer from Public EEG Encoders to Private Downstream Models

arXiv:2608.16931v1 Announce Type: new Abstract: Electroencephalography (EEG) foundation models have recently emerged as a promising paradigm for EEG decoding by learning reusable representations from

Task-Aware Harness Provisioning for LLM Agents in Mission-Critical Infrastructure Operations

arXiv:2608.17433v1 Announce Type: new Abstract: LLM agents have been widely adopted to operate mission-critical infrastructure (MCI). These agents normally rely on a harness that determines what infor

The Curious Case of Exploding DecPOMDPs: Containing the Fire through Policy Counting

arXiv:2608.17749v1 Announce Type: new Abstract: Decentralised partially observable Markov decision processes (DecPOMDPs) provide a general framework for modelling multi-agent decision making under unc

safetyarxiv-cs-ai

The Model's Tell: Measuring Context-Leakage Attack Signals with Behavior Gauges

arXiv:2608.17829v1 Announce Type: cross Abstract: LLMs increasingly rely on external contexts, such as pre-defined system prompts or retrieved documents, to improve generation quality. However, proces