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arXiv:2607.05465v1 Announce Type: cross Abstract: Complex image creation and editing often require more than a single generation or editing model. A user request may involve synthesizing images, local

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CHARLIE: An On-Premise Multi-Agent Retrieval-Augmented Generation System for Evidential Reasoning in Forensic Science

DGX agent

arXiv:2607.05428v1 Announce Type: cross Abstract: We present Charlie, an on-premise multi-agent Retrieval-Augmented Generation (RAG) system for structured evidential processing in digital forensic env

local-aiarxiv-cs-ai

8 Jul 2026

Hardware

Clustering-Embedded Model Predictive Path Integral Control: Avoiding Averaging-Induced Failure and Enabling Efficient Cluster Selection for Dynamic Obstacles

arXiv:2607.06499v1 Announce Type: new Abstract: With the widespread availability of parallel computing hardware, sampling-based motion planning methods such as Model Predictive Path Integral (MPPI) co

hardwarearxiv-cs-ro

CMDR: Contextual Multimodal Document Retrieval

arXiv:2607.05927v1 Announce Type: cross Abstract: Multimodal document retrieval aims to retrieve relevant pages while preserving both textual and visual content from the original document. However, ex

Agents

Danus: Orchestrating Mathematical Reasoning Agents with Fact-Graph Memory

arXiv:2607.06447v1 Announce Type: new Abstract: Recent LLM-based mathematical reasoning agents have begun to tackle research-level problems and, in several cases, have contributed to the resolution of

agentsarxiv-cs-ai

Data-dependent Evaluations for Budgeted Submodular Maximization

arXiv:2607.05759v1 Announce Type: cross Abstract: Submodular maximization is an important building block for developing algorithms in many areas such as machine learning and data mining. Due to the NP

applicationsarxiv-cs-ai

Diffusion Language Model Parallel Decoding via Product-of-Experts Bridge

arXiv:2606.08048v1 Announce Type: cross Abstract: Diffusion language models (DLMs) offer substantial speed advantages through parallel decoding, but the lack of token dependencies limits generation qu

researcharxiv-cs-lg

Do It Right! A Methodology for Successful NLP System Development

arXiv:2607.05644v1 Announce Type: cross Abstract: Natural language processing (NLP) is a common method for supplying data to clinical research and decision making by extracting information from electr

Dynamic Evaluation of Classical and Control-Aware Optimal Trajectory Planning in Robot Manipulators

arXiv:2607.05544v1 Announce Type: new Abstract: Trajectory planning strongly influences tracking accuracy, actuator demand, and overall execution behavior in robotic manipulators. Classical planners s

researcharxiv-cs-ro

EeveeDark: A Binary Neural Framework for Low-Light Video Enhancement via Event-Guided Sensor-Level Fusion

arXiv:2607.06217v1 Announce Type: new Abstract: Enhancing videos under extreme low-light conditions remains challenging due to the difficulty of balancing restoration quality and computational efficie

Empirical Minimal-Realisation Compression of Deep Neural Networks via Controllability-Observability Tests

arXiv:2607.05457v1 Announce Type: cross Abstract: Deep neural networks often contain substantial hidden-state redundancy, but most compression methods operate directly on weights, neurons, or quantise

ExplAIner: A Declarative Query Language for Explaining Classification Models

arXiv:2607.06407v1 Announce Type: new Abstract: The XAI community has studied a wide range of queries and scores for explaining predictions of ML models. From a data management perspective, this proli

FedDAF: Federated Domain Adaptation Using Model Functional Distance

arXiv:2509.11819v2 Announce Type: replace-cross Abstract: Federated Domain Adaptation (FDA) is a federated learning (FL) approach that improves model performance at the target client by collaborating

Federated Physics-Grounded Reinforcement Learning for Distributed Stability Control in Smart Grids

model-releasesarxiv-cs-lg

arXiv:2607.05553v1 Announce Type: new Abstract: Transient stability control in smart grids requires rapid post-fault damping of generator frequency and rotor angle deviations to prevent cascading fail

Few-Medoids: An Embarrassingly Simple Coreset Selection Method for Few-Shot Knowledge Distillation

arXiv:2607.05891v1 Announce Type: cross Abstract: Coreset selection aims to identify a small and highly representative subset of a massive dataset for efficient model training. The problem remains cha

Local Ai

Freqformer: Image-Demoireing Transformer via Effective Frequency Decomposition

arXiv:2505.19120v2 Announce Type: replace Abstract: Image demoireing remains a challenging task due to the complex interplay between texture corruption and color distortions caused by moire patterns.

local-aiarxiv-cs-cv

From Application-Layer Simulation to Native Meta-Architecture: Structural Tension as an Endogenous Driver for Heterogeneous AI Evolution

arXiv:2607.06269v1 Announce Type: new Abstract: Current large language models (LLMs) are fundamentally stateless: their behavior is fully determined by input at inference time, and any higher-order co

From Graphs to Gradients: Physics-Inspired Structural Attribution for Cyber-Physical IoT Systems and Beyond

arXiv:2607.05563v1 Announce Type: new Abstract: Interpretable explanation methods in Artificial Intelligence aim to uncover the underlying causes and their effects, enabling a deeper understanding of

From Passive Observer to Active Critic: Reinforcement Learning Elicits Process Reasoning for Robotic Manipulation

arXiv:2603.15600v2 Announce Type: replace-cross Abstract: Accurate process supervision remains a critical challenge for long-horizon robotic manipulation. A primary bottleneck is that current video ML

GaussFusion: Towards Multimodal 3D Gaussian Pretraining

arXiv:2607.05906v1 Announce Type: new Abstract: 3D Gaussian Splatting provides an explicit representation that jointly models geometry and appearance, serving as a scalable foundation for 3D represent

safetyarxiv-cs-cv

Ground3D-LMM: Fine-Grained 3D Point Grounding and Spatial Reasoning with LMM

arXiv:2607.05493v1 Announce Type: new Abstract: Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to

Hierarchical Acoustic-Semantic Modeling: Modality Separation and Semantic Coherence for Full-Duplex SLMs

model-releasesarxiv-cs-cl

arXiv:2607.06540v1 Announce Type: new Abstract: Developing seamless, high-performance, native intelligent full-duplex Spoken Language Models (SLMs) remains a critical challenge and long-standing goal

Hilti-Trimble-Oxford Dataset: 360 Visual-Inertial Benchmark with Floor Plan Priors for SLAM and Localization

model-releasesarxiv-cs-ro

arXiv:2607.06464v1 Announce Type: new Abstract: Automated progress monitoring on construction sites is an active area of research and development. Robot and human-carried mapping systems have been dev

Tutorials

How Can Mamba Learn In Context with Outliers and Generalize Provably?

arXiv:2510.00399v2 Announce Type: replace Abstract: The Mamba model has gained significant attention for its computational advantages over Transformer-based models, while achieving comparable performa

tutorialsarxiv-cs-lg

Information Gain-based Rollout Policy Optimization: An Adaptive Tree-Structured Rollout Approach for Multi-Turn LLM Agents

arXiv:2607.06223v1 Announce Type: new Abstract: Reinforcement learning has become a promising paradigm for improving large language model (LLM) agents on long-horizon search tasks, where the agent mus

Integrating knowledge graphs and multilingual scholarly corpora for domain-adaptive LLMs in SSH

arXiv:2607.05956v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into scientific research workflows, particularly for bibliographic discovery and literature synthesis, r

applicationsarxiv-cs-ai

InvWeaver: Deductive Feedback for Invariant Synthesis in Interacting-Loop Programs

model-releasesarxiv-cs-lg

arXiv:2607.05478v1 Announce Type: new Abstract: Loop invariant inference is a fundamental yet challenging problem in program verification. Recent LLM-aided guess-and-check techniques have shown strong

K-ABENA: K-Adaptive Backpropagation with Error-based N-exclusion Algorithm : (Compensated Loss-Based Sample Exclusion with Unbiased Gradient Estimation)

arXiv:2607.05903v1 Announce Type: cross Abstract: We present K-ABENA (K-Adaptive Backpropagation with Error-based N-exclusion Algorithm), a selective gradient computation framework that reduces per-it

KernelEvolve: Scaling Agentic Kernel Coding for Heterogeneous AI Accelerators at Meta

arXiv:2512.23236v4 Announce Type: replace-cross Abstract: Making deep learning recommendation model (DLRM) training and inference fast and efficient is important. However, this presents three key syst

Label Hierarchy Transition: Delving into Class Hierarchies to Enhance Deep Classifiers

model-releasesarxiv-cs-cv

arXiv:2112.02353v3 Announce Type: replace Abstract: Hierarchical classification aims to sort the object into a hierarchical structure of categories. For example, a bird can be categorized according to

Learnable Weighting of Intra-Attribute Distances for Categorical Data Clustering with Nominal and Ordinal Attributes

arXiv:2607.05464v1 Announce Type: cross Abstract: The success of categorical data clustering generally much relies on the distance metric that measures the dissimilarity degree between two objects. Ho

Learning Sparsest Linear Causal DAGs with Latent Confounders via Higher-Order Cumulants

arXiv:2607.05984v1 Announce Type: new Abstract: Recovering the exact directed acyclic graph (DAG) in linear non-Gaussian acyclic models with latent confounders (LvLiNGAM) remains a challenging problem

researcharxiv-cs-lg

Learning to Throw Objects Safely in Multi-Obstacle Environments

arXiv:2607.06388v1 Announce Type: cross Abstract: Robotic throwing enables fast and efficient object placement beyond the robot's immediate workspace, but reliable throwing in cluttered environments r

safetyarxiv-cs-cv

Leech Lattice Vector Quantization for Efficient LLM Compression

arXiv:2603.11021v2 Announce Type: replace Abstract: Scalar quantization of large language models (LLMs) is fundamentally limited by information-theoretic bounds. While vector quantization (VQ) overcom

researcharxiv-cs-lg

Hardware

Light-Omni: Reflex over Reasoning in Agentic Video Understanding with Long-Term Memory

arXiv:2607.05511v1 Announce Type: new Abstract: Agentic video understanding equips models with long-term memory to autonomously process and respond to continuous, long-horizon multimodal streams. Howe

hardwarearxiv-cs-cv

LIPP: Load-Aware Informative Path Planning with Physical Sampling

arXiv:2603.06924v2 Announce Type: replace Abstract: In classical Informative Path Planning (C-IPP), robots are typically modeled as mobile sensors that acquire digital measurements such as images or r

researcharxiv-cs-ro

LLM Agents for Deliberative Collaboration: A Study on Joint Decision Making Under Partial Observability

arXiv:2607.06157v1 Announce Type: cross Abstract: Deliberation plays a crucial role in collaboration; when humans work together, they naturally engage in communication to align information and reach a

Mitigating Domain Shift in Conditioned Floor Plan Generation: Synthetic Pre-training for Data-Efficient Adaptation

arXiv:2607.06483v1 Announce Type: new Abstract: Robustness to domain shift is a key requirement for floor plan generative models to be applicable beyond the single dataset they were trained on, as flo

Mitigating Errors in LLM-Generated Web API Invocations via Retrieval-Augmented Generation and Constrained Decoding

arXiv:2607.05936v1 Announce Type: cross Abstract: Integration of web APIs is a cornerstone of modern software systems, yet writing correct web API invocation code remains challenging due to complex an

applicationsarxiv-cs-lg

Local Ai

NumGrad-Pull: Numerical Gradient Guided Tri-plane Representation for Surface Reconstruction from Point Clouds

arXiv:2411.17392v3 Announce Type: replace Abstract: Reconstructing continuous surfaces from unoriented and unordered 3D points is a fundamental challenge in computer vision and graphics. Recent advanc

local-aiarxiv-cs-cv

Observation Quality Matters: Robust Multi-Fisheye Calibration via Failure-Oriented Analysis

arXiv:2607.05777v1 Announce Type: new Abstract: Reliable calibration of multi-fisheye camera systems remains challenging as rig size, camera arrangement diversity, and field of view increase. Existing

applicationsarxiv-cs-ro

Local Ai

Physics-Regularized Machine Learning for Proprioceptive Vehicle Localization Using Onboard Sensors

arXiv:2607.05663v1 Announce Type: cross Abstract: Accurate and robust localization is essential for autonomous mobility systems in real-world environments. While fusing Inertial Measurement Unit (IMU)

local-aiarxiv-cs-ai

PORTS: Preference-Optimized Retrievers for Tool Selection with Large Language Models

arXiv:2607.05441v1 Announce Type: cross Abstract: Integrating external tools with Large Language Models (LLMs) has emerged as a promising paradigm for accomplishing complex tasks. Since LLMs still str

Position: Preventing AI-Generated CSAM Necessitates New Approaches to AI Safety

arXiv:2607.05407v1 Announce Type: cross Abstract: Modern artificial intelligence (AI) systems present profound new risks to child safety. AI is increasingly being misused to create AI-generated child

Tutorials

Pro-Pose: Unpaired Full-Body Portrait Synthesis via Canonical UV Maps

arXiv:2512.17143v3 Announce Type: replace Abstract: Photographs of people taken by professional photographers typically present the person in beautiful lighting, with an interesting pose, and flatteri

tutorialsarxiv-cs-cv

Agents

Prompt Coach: An Empirical Evaluation of an Agentic Tutor for Learning Prompt Engineering in Software Development

arXiv:2607.06074v1 Announce Type: cross Abstract: Prompt engineering has emerged as a critical yet undertaught skill for software developers, one that traditional learning approaches are ill-equipped

agentsarxiv-cs-ai

PVCap: Towards Accurate 3D Dense Captioning via PseudoCap and VoxelCapNet

arXiv:2607.06097v1 Announce Type: cross Abstract: 3D dense captioning, an emerging vision-language task, aims to generate descriptive sentences for each object in the 3D scene. Despite the impressive

Realistic Compound-Lens Defocus Blur Synthesis

arXiv:2607.05837v1 Announce Type: new Abstract: Defocus blur degrades fine image structures and limits visual perception, which can adversely affect downstream vision tasks. Although recent deep learn

safetyarxiv-cs-cv