Search: “framework”

DocOps: A Verifiable Benchmark for Autonomous Agents in Complex Document Operations

model-releasesarxiv-cs-ai

arXiv:2607.19865v1 Announce Type: new Abstract: As autonomous agents rapidly evolve, their ability to reliably manipulate ubiquitous digital documents has become critical for enabling general-purpose

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Safety

Drift-Aware RL-based Wavelet Denoising for Network-Traffic Anomaly Detection

DGX agent

arXiv:2607.20011v1 Announce Type: cross Abstract: Traffic-utilisation measurements for network monitoring are corrupted by additive noise and statistical drift: time-dependent change in the signal's m

safetyarxiv-cs-ai

23 Jul 2026

EA-Nav: Learning Safe Visual Navigation Policies with Embodiment Awareness

arXiv:2607.19880v1 Announce Type: new Abstract: Cross-embodiment navigation is a key challenge in embodied intelligence. Due to differences in embodiment, the same visual observation may imply differe

applicationsarxiv-cs-ro

ECoNGS: Efficient Compressive Neural Gaussian Splats for Volume Visualization

arXiv:2607.18466v1 Announce Type: new Abstract: Recent advances in differentiable Gaussian splatting have highlighted the potential of primitive-based approaches as alternative scene representations f

Efficient Chain-of-Modality Reasoning via Progressive Compression for Spoken Language Models

arXiv:2607.19932v1 Announce Type: new Abstract: Spoken language models (SLMs) enable natural human-computer interaction, but their reasoning ability still lags behind that of text-based large language

researcharxiv-cs-cl

EgoRecovery: Acquiring Failure Recovery Ability Through Human Recovery Demonstration

arXiv:2607.19745v1 Announce Type: new Abstract: Robust embodied robots should be able to recover from failures and retry tasks in order to operate reliably in unstructured and noisy real-world environ

applicationsarxiv-cs-ro

ELSAA: Efficient Low-Rank and Sparse Attention Approximation for Training Transformers

arXiv:2607.20214v1 Announce Type: cross Abstract: The quadratic Nimes N attention score matrix remains a central obstacle to extending Transformers to longer input lengths. Existing efficient attentio

End-to-End Differential Privacy in Training Deep Neural Network Classifiers

arXiv:2607.19580v1 Announce Type: new Abstract: Differentially private machine learning enables model training on sensitive data while ensuring that individual data is unlikely to be recoverable from

researcharxiv-cs-lg

Euclean: Automated Geometry Problem Formalization with Unified Verification in Lean

arXiv:2607.19374v1 Announce Type: new Abstract: Recent formal reasoning systems have reached IMO-level performance, yet they leave a fragmented landscape: algebra and number theory are handled in Lean

Evaluating and Mitigating Gender Bias in Pre-trained Embeddings for ML-based Recruitment

arXiv:2607.20073v1 Announce Type: new Abstract: AI-based recruitment systems that rely on machine learning models trained on historical CV data, risk perpetuating and amplifying social biases. A key c

safetyarxiv-cs-lg

Evolving Cache Schedules for Fast Diffusion Policy Inference

arXiv:2607.20293v1 Announce Type: new Abstract: Diffusion policies achieve strong visuomotor control by iteratively denoising action chunks, but repeated denoising makes real-time deployment computati

safetyarxiv-cs-cv

EvoThink: Evolving Thinking in Large Reasoning Models via Self-Pruning and Aha-Moment Preference Optimization

arXiv:2607.19962v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) often suffer from overthinking due to redundant verification steps. Existing approaches for mitigating overthinking, such

Tutorials

Expert-Guided Forecast Editing for Time-Series Foundation Models

arXiv:2607.19659v1 Announce Type: new Abstract: Time-series foundation models can forecast across heterogeneous domains without task-specific training, but their forecasts are fixed once produced and

tutorialsarxiv-cs-lg

Extreme-RGMT: Continual Learning of Highly Dynamic Skills for Robust Generalist Humanoid Control

arXiv:2607.20110v1 Announce Type: new Abstract: Humans can progressively acquire highly dynamic motor skills while preserving reliable everyday motor abilities. In contrast, existing humanoid controll

safetyarxiv-cs-ro

Factor-Informed Uncertainty Distillation for Gaze Estimation

arXiv:2607.20072v1 Announce Type: new Abstract: Deep gaze estimation works well in controlled capture but degrades in unconstrained settings, where systems must reject unreliable predictions. Single-p

FilmWorld: Agentic Novel-to-Film Generation through Dynamic Cinematic World Modeling

arXiv:2607.19038v1 Announce Type: new Abstract: Translating novels into films poses a grand challenge for generative artificial intelligence, requiring conversion of abstract literary prose into long-

FlexiAvatar: Unified 3D Gaussian Human Avatars Under Arbitrary Body Visibility

arXiv:2607.19100v1 Announce Type: new Abstract: Reconstructing animatable 3D human avatars from monocular video is a fundamental problem in computer vision with broad applications in AR/VR and digital

Fluid-SDF: Ultra-Lightweight and Editable Implicit Shape Representation via Differentiable Primitives

arXiv:2607.18646v1 Announce Type: new Abstract: Implicit Neural Representations (INRs) have become the standard for continuous 2D shape modeling, but they suffer from black-box uneditability, vulnerab

FMRP-LEAN: A HIPAA-Compliant AI-Augmented LIMS Architecture for End-to-End Clinical Assay Workflow Optimization

arXiv:2607.20382v1 Announce Type: cross Abstract: Clinical biomarker workflows in translational research settings often rely on spreadsheet-driven tracking, manual quality control (QC) reconciliation,

applicationsarxiv-cs-ai

FORCE-Bench: A Benchmark, Dataset, and Evaluation Harness for Agentic AI in Enterprise Finance

model-releasesarxiv-cs-ai

arXiv:2607.19409v1 Announce Type: new Abstract: Recent advances in large language models have accelerated deployment of agentic systems in operational finance. Existing benchmarks emphasize measuring

Forecasting the Number of Harvest-ready Fruits of Sweet Peppers Using Multimodal Time-Series Data

arXiv:2607.19975v1 Announce Type: new Abstract: Accurate yield forecasting at the individual-plant level is critical for precision agriculture and supply-chain planning, yet public datasets capturing

applicationsarxiv-cs-cv

Frequency-Hierarchical Active k-Space Sampling for Diagnostic MRI

arXiv:2607.19779v1 Announce Type: new Abstract: Active sampling for accelerated MRI must distribute a tight sampling budget across spatial frequencies that carry very different kinds of information. L

FreyaTTS: A Compact Tokenizer-Free Flow-Matching Transformer for Turkish-First Speech Synthesis

model-releasesarxiv-cs-cl

arXiv:2607.09530v2 Announce Type: replace Abstract: We introduce Freya-TTS, a compact, tokenizer-free, Turkish-first text-to-speech model designed for highly reliable and efficient conversational synt

From Trajectories to Prefixes: Reusing Teacher Trajectories via Replayed Prefixes and Online Continuation

arXiv:2607.19395v1 Announce Type: cross Abstract: Small language models are attractive backbones for interactive agents, but direct distillation from strong teacher trajectories often turns rich multi

FSDBN: Foreground-Aware EEG-Visual Alignment via Dynamic Brain Networks

arXiv:2607.18344v2 Announce Type: replace-cross Abstract: EEG-based visual decoding provides a non-invasive pathway for interpreting visual semantics. However, existing methods often overlook the perc

Agents

GaussianSeed: Hierarchical Gaussian Seeding for High-Resolution 3D Occupancy Prediction

arXiv:2607.20071v1 Announce Type: new Abstract: Vision-centric 3D occupancy prediction provides dense scene representations essential for autonomous driving and robotic navigation, yet existing method

agentsarxiv-cs-cv

Local Ai

Generalized Least Squares Kernelized Tensor Factorization

arXiv:2412.07041v4 Announce Type: replace-cross Abstract: Recovering incomplete multidimensional tensor-structured data is a fundamental task in many real-world applications. Smoothness-constrained lo

local-aiarxiv-cs-cv

Generative AI-enhanced Probabilistic Multi-Fidelity Surrogate Modeling Via Transfer Learning

model-releasesarxiv-cs-lg

arXiv:2602.00072v2 Announce Type: replace Abstract: The performance of machine learning surrogates is critically dependent on data quality and quantity. This presents a major challenge, as high-fideli

Geometry-Guided Generative Representation for Functional Brain Graphs

arXiv:2511.04539v2 Announce Type: replace-cross Abstract: In network neuroscience, functional brain systems are often characterized using separate yet related graph-theoretic or spectral descriptors,

safetyarxiv-cs-lg

Local Ai

GeoTrace: Geometry-Aware Trajectory Token Compression for Video Large Language Models

arXiv:2607.09080v2 Announce Type: replace Abstract: Although Video Large Language Models (Video LLMs) have shown strong performance in video understanding, their efficiency is still limited by the lar

local-aiarxiv-cs-cv

GH-ESD: Grounded Hypothesis-Driven Error Slice Discovery for Instance-Level Vision Tasks

arXiv:2512.24592v3 Announce Type: replace Abstract: Systematic failures of vision models on semantically coherent subsets, known as error slices, reveal limitations in robustness and evaluation. Exist

Tutorials

GraphContainer: A Unified Platform for Comparing and Debugging Graph RAG Methods

arXiv:2607.19362v1 Announce Type: new Abstract: Graph RAG mitigates hallucinations and stale knowledge in LLMs, particularly for multi-hop question answering. However, existing approaches remain highl

tutorialsarxiv-cs-ai

Great X: A Unified Multi-Modal Simulator Bridging the Sim2Real Gap for 6G

arXiv:2507.08716v4 Announce Type: replace Abstract: Large-scale, precisely synchronized multi-modal datasets are critical for data-driven sixth-generation (6G) wireless research, yet real-world collec

safetyarxiv-cs-cv

Group-of-Latents: Perceptual Video Compression at Extreme Bitrates via Masked Latent Generative Modeling

arXiv:2607.19437v1 Announce Type: cross Abstract: Most existing video compression algorithms follow a paradigm of transformation and quantization, optimizing the trade-off between distortion and bitra

HeadCast: Casting Attention Heads for Efficient Autoregressive Video Generation

arXiv:2607.20125v1 Announce Type: cross Abstract: Autoregressive (AR) video diffusion models have become a promising paradigm for long and streaming video synthesis, but the continuously growing Key-V

researcharxiv-cs-lg

HijackKV: New Threat in Position-Independent KV Cache Reuse

arXiv:2607.19957v1 Announce Type: cross Abstract: Key-Value (KV) cache reduces inference latency in large language models (LLMs). Traditional prefix-based reuse has low cache hit rates across inferenc

HOMIE: Human-object Centric Video Personalization via Multimodal Intelligent Enhancement

arXiv:2607.18217v2 Announce Type: replace Abstract: Human-object centric video personalization (HOCVP) is a core task within subject-driven video generation. However, existing methods suffer from two

safetyarxiv-cs-cv

HyGRL: Adaptive Hybrid Graph Reasoning for Multi-Entity Questions

arXiv:2607.19398v1 Announce Type: new Abstract: Multi-entity compositional questions pose significant challenges to existing retrieval-augmented language models. Conventional methods fall into a dilem

IConE: Batch Independent Collapse Prevention for Self-Supervised Representation Learning

arXiv:2603.15263v2 Announce Type: replace-cross Abstract: Self-supervised learning (SSL) has revolutionized representation learning, with Joint-Embedding Architectures (JEAs) emerging as an effective

researcharxiv-cs-lg

Local Ai

In-the-Flow Agentic System Optimization for Effective Planning and Tool Use

arXiv:2510.05592v2 Announce Type: replace Abstract: Outcome-driven reinforcement learning has advanced reasoning in large language models (LLMs), but prevailing tool-augmented approaches train a singl

local-aiarxiv-cs-ai

Information Discernment in Large Language Models

model-releasesarxiv-cs-ai

arXiv:2607.19355v1 Announce Type: new Abstract: LLMs are increasingly used with external knowledge sources like the internet. Do they weigh information appropriately -- updating more for reliable sour

Hardware

InstantSfM: Towards GPU-Native SfM for the Deep Learning Era

arXiv:2510.13310v3 Announce Type: replace Abstract: Structure-from-Motion (SfM) is a fundamental technique for recovering camera poses and scene structure from multi-view imagery, serving as a critica

hardwarearxiv-cs-cv

JANUS: Foreseeing Latent Risk for Long-Horizon Agent Safety

arXiv:2607.19913v1 Announce Type: new Abstract: Agent safety is moving from content moderation toward preventing operational failures before tool-using agents act. We propose Janus, a foresight-orient

Juxtaposition of Shallow Reservoir-Triggered Seismicity and Deep Tectonic Locking in the Qiaojia-Dongchuan Seismic Gap

arXiv:2607.19606v1 Announce Type: cross Abstract: Identifying the critical state of mature seismic gaps is challenging, especially when anthropogenic stress perturbations, such as reservoir impoundmen

KineBench: Benchmarking Embodied World Models via IDM-Free Kinematic Grounding

model-releasesarxiv-cs-ro

arXiv:2607.19876v1 Announce Type: new Abstract: Evaluating the physical consistency of embodied world models(EWMs) is a critical open challenge. While closed-loop evaluation via simulator rollouts off

Agents

Know Your Agent: Reconnaissance-Driven Pentesting of AI Agents

arXiv:2607.19837v1 Announce Type: new Abstract: Traditional pentesting uses reconnaissance at each step to uncover unseen weaknesses, build stronger attacks, and advance the objective; we argue that A

agentsarxiv-cs-ai

LaCache: Exact Caching and Precision-Adaptive Inference for Diffusion Large Language Models

arXiv:2607.16339v2 Announce Type: replace Abstract: Diffusion-based Large Language Models(DLLMs) enable parallel generation via Semi-Autoregressive (SAR) decoding in text generation. However, current

Latent Riemannian Flow Matching for Geometry-Grounded 3D Foundation Models

arXiv:2607.19120v1 Announce Type: new Abstract: Geometric foundation models, such as the Visual Geometry Grounded Transformer (VGGT), provide strong 3D priors from unposed images. However, such models