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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

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LingDT-VL-OCR: Structure-Aware Document-Level Parsing with Fine-Grained Visual Reference

DGX agent

arXiv:2603.11044v2 Announce Type: replace Abstract: In this paper, we propose LingDT-VL-OCR, a document parsing system tailored to financial-domain documents, transforming ultra-long financial PDFs in

model-releasesarxiv-cs-cv

8 Jul 2026

Lingering Authority: Revocable Resource-and-Effect Capabilities for Coding Agents

arXiv:2606.22504v1 Announce Type: cross Abstract: Coding agents often receive broad tool access for an entire task, even when a resource is needed only for one subgoal. We call this gap lingering auth

safetyarxiv-cs-ai

Linking Hadith Narrator Identities Across Heterogeneous Arabic Biographical Databases: A Multi-Signal Entity Resolution Pipeline

model-releasesarxiv-cs-cl

arXiv:2607.05424v1 Announce Type: cross Abstract: The transmission chains (sanad) of Islamic Hadith literature encode relationships among tens of thousands of historical narrators whose biographical r

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

LLM-Driven Neural Network Generation with Same-Family Architecture Guidance: Disentangling Transfer and Adaptation

arXiv:2607.05704v1 Announce Type: cross Abstract: Large language models (LLMs) can generate neural-network modifications, but unrestricted generation is often invalid or harmful. This paper studies a

Local Ai

LLM-Guided Measurement Credibility Correction for Trustworthy Industrial Process Inference

arXiv:2607.06111v1 Announce Type: cross Abstract: Industrial prediction and soft sensing depend on credible input measurements. In field deployment, a predictor may receive biased, delayed, stale, or

local-aiarxiv-cs-ai

LongCrafter: Towards Diverse Long-Context Understanding via Evidence-Graph-Guided Instruction Synthesis

arXiv:2607.06160v1 Announce Type: cross Abstract: Synthesizing long-context supervised fine-tuning (SFT) data is a scalable way to enhance the long-context understanding of large language models (LLMs

Low-Overhead Error-Corrected QCNNs Using Bivariate Bicycle Codes

arXiv:2607.05724v1 Announce Type: new Abstract: Quantum convolutional neural networks (QCNNs) combine the power of quantum computing and classical CNN for computational speedup in classification tasks

researcharxiv-cs-lg

MAC-XA: Multi-view Anatomy-Correspondence Fusion for Coronary Stenosis Reporting from X-ray Angiography

arXiv:2607.06268v1 Announce Type: new Abstract: Multi-view reasoning in coronary X-ray angiography is inherently a cross-projection geometric problem, yet automated report generation in this setting r

safetyarxiv-cs-cv

MAME: Multidimensional Adaptive Metamer Exploration with Human Perceptual Feedback

arXiv:2503.13212v3 Announce Type: replace Abstract: Alignment between human brain networks and artificial models has become an active research area in vision science and machine learning. A widely ado

safetyarxiv-cs-lg

MASCA: LLM based-Multi Agents System for Credit Assessment

arXiv:2507.22758v2 Announce Type: replace Abstract: Recent advancements in financial problem-solving have leveraged LLMs and agent-based systems, with a primary focus on trading and financial modeling

safetyarxiv-cs-cl

mathbf{lambda}-VAE: Variance Equalization for Posterior Collapse

arXiv:2607.05531v1 Announce Type: cross Abstract: Variational Autoencoders (VAEs) frequently suffer from posterior collapse, a failure mode in which the approximate posterior converges to the prior, r

researcharxiv-cs-cv

MCP-Enabled Agentic AI for Autonomous IPoDWDM Network Lifecycle Automation

arXiv:2607.05975v1 Announce Type: cross Abstract: This demo presents an MCP-enabled agentic AI architecture for autonomous control of vendor-agnostic IPoDWDM networks. We demonstrate live end-to-end l

agentsarxiv-cs-ai

Local Ai

Measuring the practice of shared-decision making (OPTION12): An Investigation into Open-sourced Smaller LLMs (OS-sLLMs) for Better Privacy and Sustainability

arXiv:2607.06127v1 Announce Type: new Abstract: We present LLM4SDM, the first study of open-source smaller language models (OS-sLLMs) for automated assessment of shared decision making (SDM) using the

local-aiarxiv-cs-cl

Medix: Out-of-Distribution Detection from Unlabeled Wild Data via Robust Gradient Statistics

arXiv:2510.06505v2 Announce Type: replace-cross Abstract: Out-of-distribution (OOD) detection plays a crucial role in ensuring the robustness of machine learning systems deployed in real-world applica

applicationsarxiv-cs-ai

MemDefrag: Latent Memory Defragmentation for Large Language Models

arXiv:2607.05969v1 Announce Type: new Abstract: Latent memory, which stores past knowledge fragments as per-layer hidden states, has emerged as a promising paradigm (e.g., MemoryLLM and M+) for long-t

researcharxiv-cs-cl

Memory in the Loop: In-Process Retrieval as ExtendedWorking Memory for Language Agents

arXiv:2607.05690v1 Announce Type: new Abstract: Language agents run a loop - observe, reason, act - but the memory they reason over sits outside it: a store queried at most once per turn. We study the

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

applicationsarxiv-cs-cv

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

Mitigating Factual Hallucination in Large Reasoning Models via Mixed-Mode Advantage Regularization

arXiv:2607.05861v1 Announce Type: new Abstract: Large reasoning models (LRMs) improve language model capabilities by generating explicit thinking traces before final answers. In factuality-oriented qu

researcharxiv-cs-cl

Local Ai

MLLM-LLaVA-FL: Multimodal Large Language Model Assisted Federated Learning

arXiv:2409.06067v3 Announce Type: replace Abstract: Previous studies on federated learning (FL) often encounter performance degradation due to data heterogeneity among different clients. In light of t

local-aiarxiv-cs-ai

MobileWan: Closing the Quality Gap for Mobile Video Diffusion

arXiv:2607.06173v1 Announce Type: new Abstract: Recent advances in video diffusion have been driven by scaling transformer-based architectures to billions of parameters, substantially improving visual

Modality Relevance is not Modality Utility: Post-hoc Selective Modality Escalation for Cost-Aware Multimodal RAG

arXiv:2607.05438v1 Announce Type: cross Abstract: Multimodal retrieval-augmented generation (RAG) grounds a generator in evidence drawn from heterogeneous modalities -- text, tables, and images. The d

researcharxiv-cs-ai

Modeling Normal Is All You Need: Joint Latent Clustering for Anomaly Detection in Multimodal Cyber-Physical Systems

arXiv:2607.06094v1 Announce Type: new Abstract: Faults on a cyber-physical system (CPS) are too rare and unrepresentative to characterise, or even to select a model on, so detection must instead model

researcharxiv-cs-lg

MonoIR-RS: Infrared Remote Sensing Vision-Language Learning with CLIP and VLM Adaptation

arXiv:2607.06552v1 Announce Type: new Abstract: Infrared remote-sensing imagery captures intensity structure, object-background contrast, and illumination-invariant cues often invisible in RGB imagery

More Convincing, Not More Correct: Self-Play Reward Hacking of Reference-Free LLM Judges

model-releasesarxiv-cs-lg

arXiv:2607.05904v1 Announce Type: new Abstract: Training a language model against its own reference-free judgments (the premise of self-rewarding, self-play, and LLM-as-a-judge pipelines) assumes a mo

MorphGS: Morphology-Adaptive Articulated 3D Motion Transfer from Videos

arXiv:2601.02716v3 Announce Type: replace Abstract: Transferring articulated motion from monocular videos to rigged 3D characters is challenging due to pose ambiguity in 2D observations and morphologi

applicationsarxiv-cs-cv

Most LLM Conformity Needs No Speaker: Measuring the Speaker-Free Floor in Peer-Pressure Benchmarks

arXiv:2607.05545v1 Announce Type: cross Abstract: LLM conformity is often used to describe cases where a model changes a correct answer toward a peer or group response. We show that most of this appar

researcharxiv-cs-ai

MoWorld: A Flash World Model

arXiv:2607.06216v1 Announce Type: new Abstract: The future of World Models depends not only on scaling model capability, but also on scaling practicality and inference efficiency. High-frame-rate infe

agentsarxiv-cs-cv

MP-MPPI: A Motion Primitive Guided Sampling-Based Optimizer for Model Predictive Control

arXiv:2607.06123v1 Announce Type: new Abstract: This paper proposes a novel method that extends the Model Predictive Path Integral (MPPI) method with motion primitives for additional structured sampli

researcharxiv-cs-ro

MSA-DCNN: A Data-Efficient Multi-Scale Deformable CNN for Medical Image Classification

arXiv:2607.06083v1 Announce Type: new Abstract: Existing deep learning methods perform well in medical image classification but struggle with multi-scale morphology and limited annotations due to fixe

researcharxiv-cs-cv

Multi-Agent Deep Reinforcement Learning for Multi Objective Battery Management in Dairy Farms

arXiv:2607.06489v1 Announce Type: new Abstract: The dairy industry in Ireland has a large potential for the integration of renewable energy and the reduction of carbon emissions. However, researchers

agentsarxiv-cs-ai

Multi-Channel Spread-Spectrum Code Watermarking

model-releasesarxiv-cs-lg

arXiv:2607.06009v1 Announce Type: cross Abstract: Attributing code to the large language model that produced it is essential for provenance, licensing, and misuse accountability, yet no deployed water

Multi-Task Instruction Tuning via Data Scheduling for Low-Resource Arabic SpeechLLMs

arXiv:2601.12494v3 Announce Type: replace-cross Abstract: Audio large language models (LLMs) enable unified speech understanding and generation, but adapting them to linguistically complex and dialect

Multi-Teacher Contrastive Distillation for Edge-Efficient Pathology Foundation Models

arXiv:2607.05533v1 Announce Type: new Abstract: Computational pathology foundation models (PFMs) have advanced whole-slide image analysis. However, their size and inference cost hinder local deploymen

Multimodal Analytics of Cybersecurity Crisis Preparation Exercises: What Predicts Success?

arXiv:2603.28553v2 Announce Type: replace-cross Abstract: Instructional alignment, the match between intended cognition and enacted activity, is central to effective instruction but hard to operationa

safetyarxiv-cs-lg

Multimodal Molecular Representation Learning with Graph Neural Networks, Deep & Cross Networks, and SMILES Embeddings

model-releasesarxiv-cs-lg

arXiv:2607.05736v1 Announce Type: new Abstract: Molecular property prediction often relies on isolated data modalities, where continuous 3D graph neural networks (GNNs) struggle to efficiently capture

NAMD: Virtual Follow-up Computed Tomography Synthesis via Nodule-Aligned Multimodal Diffusion Models for Early Lung Cancer Diagnosis

arXiv:2603.15932v2 Announce Type: replace Abstract: Lung cancer remains the leading cause of cancer-related mortality worldwide, with survival outcomes critically dependent on early and accurate detec

researcharxiv-cs-cv

Narrative-Centered Emotional Reflection: An Early Prototype for AI-Supported Emotional Self-Reflection

arXiv:2504.20342v2 Announce Type: replace-cross Abstract: Reflexion is an AI-powered prototype designed to explore structured emotional self-reflection. By integrating emotion detection, layered refle

agentsarxiv-cs-ai

Narrative World Model: Narratology-Grounded Writer Memory for Long-Form Fiction

arXiv:2607.05577v1 Announce Type: new Abstract: Long-form fiction writers need memory that answers multi-hop questions about evolving story state: who knows a secret and when they learned it, whether

NAVER LABS System Re-implementation for the IWSLT 2026 Instruction-Following Task

model-releasesarxiv-cs-cl

arXiv:2607.05623v1 Announce Type: new Abstract: We re-implement the NAVER LABS IWSLT 2025 instruction-following pipeline for the IWSLT 2026 Shared Task (constrained condition, short audio track), adap

NegROI: Click-Centric Uncertainty-Guided Refinement with Scene-Conditioned Negative Prompts for Robust Interactive 3D Segmentation

arXiv:2607.05955v1 Announce Type: cross Abstract: Interactive 3D segmentation aims to extract object masks in point clouds with minimal user clicks. Despite recent progress, most existing approaches s

Nemotron-Labs-Diffusion: A Tri-Mode Language Model Unifying Autoregressive, Diffusion, and Self-Speculation Decoding

model-releasesarxiv-cs-cl

arXiv:2607.05722v1 Announce Type: new Abstract: We introduce Nemotron-Labs-Diffusion, a tri-mode language model (LM) that unifies AR, diffusion, and self-speculation decoding within a single architect

Nested Episodic State Topology (NEST): A Graph-Theoretic Architecture of Cognitive States

arXiv:2607.06055v1 Announce Type: cross Abstract: We present NEST (Nested Episodic State Topology), a foundational graph-theoretic representational ontology for modeling cognition as structured state

researcharxiv-cs-cl

Neural-ESO: A Dual-Pathway Architecture for Provably Robust Learning-Based Control

arXiv:2607.06535v1 Announce Type: new Abstract: A learning-enabled disturbance-rejection framework based on a Neural Extended State Observer (Neural-ESO) is presented in this letter. Unlike existing l

researcharxiv-cs-ro

No-Regret Gaussian Process Optimization of Time-Varying Functions

arXiv:2512.00517v3 Announce Type: replace-cross Abstract: Sequential optimization of black-box functions from noisy evaluations has been widely studied, with Gaussian Process bandit algorithms such as

researcharxiv-cs-lg