Search: “papers”

Parallel Causal Associative Fields: Gated Sparse Memory for Long-Context Language Modeling

model-releasesarxiv-cs-cl

arXiv:2606.10435v1 Announce Type: cross Abstract: Transformers achieve strong language modeling performance by providing direct token-to-token communication paths, but causal self-attention scales qua

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Parametric Knowledge is Not All You Need: Toward Honest Large Language Models via Retrieval of Pretraining Data

DGX agent

arXiv:2601.21218v2 Announce Type: replace Abstract: Large language models (LLMs) are highly capable of answering questions, but they are often unaware of their own knowledge boundary, i.e., knowing wh

model-releasesarxiv-cs-cl

10 Jun 2026

Planar-Sector LOS Guidance for Interception of Agile Targets with Lifting-Wing Quadcopters

arXiv:2606.10639v1 Announce Type: new Abstract: Autonomous visual interception of agile aerial targets is challenging due to unpredictable target motion, limited sensing, and the strong coupling betwe

Population-Aware Physics-Informed Neural Particle Flow for Bayesian Update

arXiv:2606.10959v1 Announce Type: new Abstract: Physics-informed neural particle flow (PINPF) learns a deterministic transport field that moves particles from a prior distribution toward a Bayesian po

Position: The ML Community Must Build an AI-Augmented Peer-Review Ecosystem

arXiv:2506.08134v4 Announce Type: replace Abstract: Peer review, the bedrock of scientific advancement in machine learning (ML), is strained by a crisis of scale. Exponential growth in manuscript subm

Local Ai

Post-Quantum Secure Federated DeFi for Inclusive Banking

arXiv:2606.10658v1 Announce Type: cross Abstract: Recent advances in error-corrected qubits have accelerated the timeline for practical quantum computing. It poses a threat to cryptographic primitives

local-aiarxiv-cs-ai

Predictive Assistance and the Temporal Dynamics of Exploratory Compression

arXiv:2606.10094v1 Announce Type: new Abstract: Classical theories of cognition describe problem solving as exploratory search through structured problem spaces in which repeated interaction gradually

Pushing the Performance Limits in Autonomous Racing: Continuous Stability-Aware Adaptive Velocity Planning in Formula Student Driverless

arXiv:2606.10733v1 Announce Type: new Abstract: In autonomous racing, especially in competitions such as Formula Student Driverless, precise planning of the target velocity of a race car is crucial fo

QSplitFL: Capability Aware Deep Q-Learning for Optimal Split Point Selection in Split Federated Learning

arXiv:2606.09869v1 Announce Type: cross Abstract: Federated Learning (FL) combined with Split Learning (SL) is a privacy preserving paradigm that enables training deep neural networks (DNNs) on resour

Quantifying Uncertainty in AI Visibility: A Statistical Framework for Generative Search Measurement

arXiv:2603.08924v2 Announce Type: replace-cross Abstract: AI-powered answer engines are inherently non-deterministic: identical queries submitted at different times can produce different responses and

Reasoning or Memorization? Direction-Aware Diversity Exploration in LLM Reinforcement Learning

arXiv:2606.10346v1 Announce Type: new Abstract: Reinforcement learning has become a key paradigm for eliciting reasoning abilities in large language models, where exploration is crucial for discoverin

Recovering the Zipfian Distribution in Unsupervised Term Discovery

arXiv:2606.10781v1 Announce Type: cross Abstract: Unsupervised term discovery involves segmenting unlabelled speech into word- or syllable-like units and clustering these into a lexicon of candidate t

safetyarxiv-cs-cl

Resilient Navigation for Autonomous Farm Robots by Leveraging Jerk-Augmented Models with IMU-Only Disturbance Rejection

arXiv:2606.10971v1 Announce Type: new Abstract: Precise state estimation for navigation of autonomous agricultural robots is often compromised by sensor outages (GNSS/LiDAR/Visual) and high-frequency

RobotEQ: Transitioning from Passive Intelligence to Active Intelligence in Embodied AI

model-releasesarxiv-cs-ro

arXiv:2605.06234v2 Announce Type: replace Abstract: Embodied AI is a prominent research topic in both academia and industry. Current research centers on completing tasks based on explicit user instruc

Role-Agent: Bootstrapping LLM Agents via Dual-Role Evolution

arXiv:2606.10917v1 Announce Type: new Abstract: Although Large Language Model (LLM) agents have demonstrated strong performance on complex tasks, their learning is often limited by inefficient interac

Secure Aggregation with Top-K Sparsification in Decentralized Federated Learning

arXiv:2606.10780v1 Announce Type: cross Abstract: Secure aggregation is a vital component for mitigating gradient leakage in federated learning, but its communication cost conventionally scales with t

Segment and Select: Vision-Language Segmentation in 3D Scenarios

arXiv:2606.10594v1 Announce Type: new Abstract: 3D vision-language segmentation aims to segment target objects in 3D scenarios according to the linguistic instructions and visual observations. Prior a

researcharxiv-cs-cv

Applications

Segmentation-Driven Monocular Shape from Polarization based on Physical Model

arXiv:2601.04776v2 Announce Type: replace Abstract: Monocular shape-from-polarization (SfP) leverages the intrinsic relationship between light polarization properties and surface geometry to recover s

applicationsarxiv-cs-cv

Sketch-to-Layout: A Human-Centric Computational Agent for Constraint-Aware Synthesis of Modular Photobioreactors

arXiv:2606.09849v1 Announce Type: cross Abstract: Building-integrated photobioreactors (PBRs) offer a pathway for carbon-neutral architecture, yet deployment is hindered by configuration complexity an

safetyarxiv-cs-cv

Soul Computing: A Theoretical Framework and Technical Architecture for Intelligent Agents with Independent Consciousness

arXiv:2606.10413v1 Announce Type: new Abstract: Breakthroughs in large language models and multimodal generation technologies have propelled the digital reconstruction of human mental traits, emotiona

Local Ai

SPARX: Secure and Privacy-Aware Approximate CNN Acceleration with Edge RISC-V SoC

arXiv:2606.09946v1 Announce Type: cross Abstract: Edge-AI systems increasingly require real-time CNN inference under strict energy, performance, security, and privacy constraints. Approximate computin

local-aiarxiv-cs-cv

Tutorials

Spatiotemporal Graph Transformer for 3D Neighborhood Interaction and Quality Prediction in Metal Additive Manufacturing

arXiv:2606.10227v1 Announce Type: new Abstract: Metal additive manufacturing enables the fabrication of complex parts, but achieving consistent build quality remains challenging due to interactions in

tutorialsarxiv-cs-lg

Spiking Neural Network inference on FPGAs with hls4ml

arXiv:2606.10008v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) provide a naturally temporal machine-learning framework. Their neurons maintain an internal state and propagate informa

Standard Language Ideology in AI-Generated Language

arXiv:2406.08726v3 Announce Type: replace Abstract: Large language models (LLMs) generate text that reinforces standard language ideology: a bias towards certain language varieties that are granted mo

safetyarxiv-cs-cl

Support sufficiency as action-sufficient compression: a single-cycle rate-regret formulation

arXiv:2606.09858v1 Announce Type: cross Abstract: Robust decision-making requires compression. A system that forms a rich support state cannot usually preserve its full structure at the point of actio

Task Robustness via Re-Labelling Vision-Action Robot Data

arXiv:2606.10918v1 Announce Type: cross Abstract: The recent trend in scaling models for robot learning has resulted in impressive policies that can perform various manipulation tasks and generalize t

safetyarxiv-cs-lg

Temporal Context Conditioning for Seasonality-Aware Precipitation Nowcasting of High-Intensity Rainfall

arXiv:2606.09959v1 Announce Type: cross Abstract: Precipitation nowcasting is increasingly being approached with deep learning models that learn directly from recent radar observations. Although such

Test-Time Gradient Guidance of Flow Policies in Reinforcement Learning

arXiv:2606.11087v1 Announce Type: cross Abstract: Expressive continuous control policies, such as diffusion and flow models, form the backbone of recent advances in scaling imitation learning for simu

The Distributed Detectability Band Against Marginal-Preserving Attacks

arXiv:2606.10456v1 Announce Type: cross Abstract: AI-control monitors score individual agent actions to detect misbehavior, but real harm can be distributed across many benign-looking steps, each indi

Towards Autonomous Accelerator Design: FPGA Accelerator Generation with SECDA

arXiv:2606.11117v1 Announce Type: cross Abstract: Designing FPGA-based accelerators for modern artificial intelligence workloads requires exploring a large and complex hardware design space that invol

Trainable Smooth-Rotation Transforms with Learned Channel Scales for LLM Quantization

arXiv:2606.09927v1 Announce Type: cross Abstract: Post-training quantization (PTQ) is one of the most practical ways to reduce the serving cost of Large Language Models (LLMs), but activation quantiza

Local Ai

Unleashing Correlation and Continuity for Hyperspectral Reconstruction from RGB Images

arXiv:2501.01481v2 Announce Type: replace-cross Abstract: Reconstructing Hyperspectral Images (HSI) from RGB images can yield high spatial resolution HSI at a lower cost, demonstrating significant app

local-aiarxiv-cs-cv

Upper Bounds for Local Learning Coefficients of Three-Layer Neural Networks

arXiv:2603.12785v2 Announce Type: replace Abstract: Three-layer neural networks are known to form singular learning models, and their Bayesian asymptotic behavior is governed by the learning coefficie

Validation-Stage Combinatorial Fusion Analysis for Imbalanced Credit-Card Fraud Detection

model-releasesarxiv-cs-lg

arXiv:2606.10393v1 Announce Type: new Abstract: Credit-card fraud detection is difficult because fraudulent transactions are rare, costly, and unevenly distributed. Strong gradient-boosted tree models

Vehicle Prediction Model for Enhanced MPC Path Tracking in Formula Student Driverless

arXiv:2606.10732v1 Announce Type: new Abstract: Autonomous race cars, such as in Formula Student Driverless, operate close to their physical handling limits. The resulting highly nonlinear vehicle beh

Tutorials

Vision-Assisted Foundation Model for Solving Multi-Task Vehicle Routing Problems

arXiv:2606.10431v1 Announce Type: cross Abstract: Multi-task vehicle routing problems play a critical role in enhancing efficiency across various industries and service sectors. These problems consist

tutorialsarxiv-cs-ai

What Matters in Orchestrating Robot Policies: A Systematic Study of Hierarchical VLA Agents

arXiv:2606.10267v1 Announce Type: cross Abstract: Hierarchical vision-language-action (Hi-VLA) systems have emerged as a promising paradigm for complex robot manipulation, by using high-level VLM plan

WorldKernel: A World Model is the Coupling Kernel of Admissible Possible Worlds

arXiv:2606.10934v1 Announce Type: new Abstract: A common assumption holds that enough observational and interventional data, given to a strong enough predictor, suffices. We report a failure mode that

3D Oral Modelling with Improved Vertex Distribution Using Matching-Based Learning

arXiv:2606.07907v1 Announce Type: cross Abstract: In our previous work, a deep learning-based framework for 3D intraoral reconstruction was proposed. The model directly predicts explicit 3D point clou

A Camera-Native Talking-Head Video Dataset for Various Computer Vision Tasks

arXiv:2603.26763v2 Announce Type: replace Abstract: Talking-head videos constitute a predominant content type in real-time communication, yet publicly available datasets for video processing research

researcharxiv-cs-cv

A Resilience-as-a-Service assessment framework for coordinated disruption response in interdependent urban transit systems

arXiv:2606.08849v1 Announce Type: new Abstract: Urban public transport disruptions require rapid response strategies, yet existing studies rarely provide a decision support framework to compare altern

A Robust widetilde{O}(1/sqrt{T}) Rate for Unprojected TD Learning with Linear Function Approximation

arXiv:2506.01052v3 Announce Type: replace Abstract: We investigate the finite-time convergence properties of Temporal Difference (TD) learning with linear function approximation, a cornerstone of rein

A Survey on Large Language Model-Based Game Agents

arXiv:2404.02039v5 Announce Type: replace Abstract: Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity. As such, game agents offer a valuable te

A Variability-Based Framework for Interpretable Naming in Formal and Relational Concept Analysis

arXiv:2606.08477v1 Announce Type: new Abstract: Knowledge extraction from symbolic data often produces abstractions that are formally defined but not immediately interpretable by users. Formal Concept

Activation Steering Induces Emergent Misalignment: A More Comprehensive Evaluation

arXiv:2606.08682v1 Announce Type: cross Abstract: Activation steering has emerged as a popular inference-time technique for modulating the behavior of large language models (LLMs). By constructing a s

Adversarial Instance Generation and Robust Training for Neural Combinatorial Optimization with Multiple Objectives

arXiv:2601.01665v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (DRL) has shown great promise in addressing multi-objective combinatorial optimization problems (MOCOPs). Neverthe

AeroSpectra Sentinel: An Auditable LLM Prompt-Chaining Decision-Support Workflow for Acute Asthma Risk Assessment from Respiratory Sounds and Clinical Signals

arXiv:2606.08247v1 Announce Type: cross Abstract: Acute asthma risk assessment requires rapid interpretation of respiratory sounds, oxygenation, airflow limitation, speech ability, work of breathing,

Agentic Neuro-Symbolic Planning and Commissioning for Human-in-the-Loop Industrial Robotics with Digital Twins

arXiv:2606.08214v1 Announce Type: new Abstract: Flexible robotic automation requires systems that interpret operator intent, verify physical feasibility, and recover from execution failures across bot