Search: “framework”

Explainable graph attention network for stress recognition (StressGAT) via differential action units

arXiv:2607.20819v1 Announce Type: new Abstract: Stress is a dynamic process characterized by significant individual variability in facial expression. Traditional architectures, such as Recurrent Neura

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Research

External Clustering Validation by the Homogeneity-Parsimony Trade-off

DGX agent

arXiv:2607.20799v1 Announce Type: new Abstract: Scalar metrics are often used to evaluate clusterings against known classes, but they can obscure a fundamental trade-off: clusterings should be informa

researcharxiv-cs-lg

24 Jul 2026

FORGE-plus: Force-Budgeted Recovery for Contact-Rich Assembly with a Frozen LLM Supervisor

arXiv:2607.21227v1 Announce Type: new Abstract: Force-conditioned reinforcement learning (RL) enables tight-clearance assembly under a commanded force ceiling, but practical deployment requires determ

safetyarxiv-cs-ro

From Atoms to Entropy: Optimal Noise Allocation for Diffusion Training in the Convex Regime

arXiv:2607.20540v1 Announce Type: cross Abstract: How should a diffusion model decide which noise levels to train on, and how much? Despite the importance of this choice, current noise schedules are b

Local Ai

From Dependency to Compositionality: A Neurosymbolic Lifting of LLM Outputs via Combinatory Categorial Grammar

arXiv:2607.18961v2 Announce Type: replace Abstract: Large language models (LLMs) generate fluent text by incrementally predicting the next token from a prefix. Critics in the generative tradition argu

local-aiarxiv-cs-ai

GPE: Evaluating Robust Evidence Aggregation for Fact Verification under Controllable GEO-Style Poisoning

arXiv:2607.20730v1 Announce Type: cross Abstract: Large language models increasingly use search tools to retrieve up-to-date information, introducing a new attack surface in which retrieved documents

GroupVideo: Multi-Identity Customized Text-to-Video Generation

arXiv:2607.21027v1 Announce Type: new Abstract: Current identity customized video generation methodologies are predominantly limited to single-identity scenarios, as the lack of explicit identity sepa

Is Deep Research Reliable? Misleading Knowledge Induces False Conclusions

arXiv:2607.20891v1 Announce Type: new Abstract: Deep Research agents extend LLM-based assistants into long-horizon workflows involving planning, retrieval, evidence synthesis, and report generation, y

Multimodal Learning for Arcing Detection in Pantograph-Catenary Systems

arXiv:2602.08792v2 Announce Type: replace-cross Abstract: The pantograph-catenary interface is essential for ensuring uninterrupted and reliable power delivery in electrified rail systems. However, el

OpenForgeRL: Train Harness-native Agents in Any Environment

arXiv:2607.21557v1 Announce Type: new Abstract: Modern AI agents rely on elaborate inference harnesses such as Claude Code, Codex, and OpenClaw to drive multi-turn reasoning, tool use, and access to e

Agents

OPTScientist: Multi-Agent Discovery of Typed Optimizer Programs for Transformer Pretraining

arXiv:2607.20486v1 Announce Type: new Abstract: Designing optimizers for modern deep learning remains a challenging scientific problem, requiring the joint consideration of optimization geometry, stat

agentsarxiv-cs-ai

PILD: Physics-Informed Learning via Diffusion

arXiv:2601.21284v2 Announce Type: replace-cross Abstract: Diffusion models have emerged as powerful generative tools for modeling complex data distributions, yet their purely data-driven nature limits

RE-AD: Real-Time Requirement Adherence for Data Labeling

arXiv:2607.20455v1 Announce Type: cross Abstract: Human-annotated data remains fundamental to training frontier Large Language Models (LLMs). However, crowd-sourced annotations often suffer from quali

Reliability-Aware LLM Alignment from Inconsistent Human Feedback

arXiv:2607.20515v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) is critical for aligning Large Language Models (LLMs) with human preferences. However, its efficacy is

Robust Critics: Defending LLMs Against Multi-Turn Attacks

arXiv:2607.20472v1 Announce Type: new Abstract: When a user asks a language model something harmful, is it a genuine attack or a misunderstood but well-meaning question? This ambiguity is one of the c

Safe and Scalable Multi-Drone Payload Transport via CBF-based Reinforcement Learning with Zero-Shot Sim-to-Real Transfer

arXiv:2607.20665v1 Announce Type: new Abstract: Multi-drone payload transportation has emerged as a promising research paradigm with potential applications in construction, logistics, and disaster res

safetyarxiv-cs-ro

Agents

Scalable Low-Cost Laboratory Automation: A Digital Twin-Integrated Robotic Platform for Autonomous Liquid Handling (RAINBOTTM)

arXiv:2607.20662v1 Announce Type: new Abstract: Laboratory automation accelerates discovery, yet its adoption is constrained by the high cost, proprietary design, and limited remote supervisability of

agentsarxiv-cs-ro

Scale Up Strategically: Learning Compositional Generalization via Bias-Aware Evaluation and Data Collection for Robotic Manipulation

arXiv:2607.21582v1 Announce Type: cross Abstract: Compositional generalization is essential for robot to follow diverse instructions. However, pretrained policies are known to take shortcuts, deferrin

T-STAR: A Large-Scale Benchmark for Spatio-Temporal Panoptic Scene Graph Generation in Satellite Video

model-releasesarxiv-cs-cv

arXiv:2607.21228v1 Announce Type: new Abstract: Structured understanding of satellite video is essential for advancing dynamic geospatial scene analysis from low-level perception to high-level cogniti

Applications

TableVerse: A Large-scale Tabletop Dataset with Real-world Grounded Layouts for Generalizable Manipulation

arXiv:2607.21017v1 Announce Type: new Abstract: The development of generalizable robotic manipulation policies is inherently bounded by the availability of large-scale, high-fidelity scene data. While

applicationsarxiv-cs-ro

The Hidden Footprint: Making Storage a First-Class Metric for LLM Agent Evaluation

arXiv:2607.11149v3 Announce Type: replace Abstract: LLM agent benchmarks measure task completion, reliability, and inference cost, but not the persistent data an agent run leaves on disk, including lo

Local Ai

Toward Continuous Assurance for the Democratization of AI Agent Creation in Industry

arXiv:2607.21495v1 Announce Type: new Abstract: AI agents are increasingly created inside organizations by non-engineering users through low-code, no-code, and conversational development environments.

local-aiarxiv-cs-ai

Towards a Certifying Grounder

arXiv:2607.21199v1 Announce Type: cross Abstract: Grounding, the translation of high-level theories into equivalent quantifier-free formulas, is a crucial step in declarative solving, yet it has so fa

Towards Robust Iris Recognition Through Occlusion Identification and Conditional Diffusion-Based Reconstruction

arXiv:2607.21545v1 Announce Type: new Abstract: Iris recognition is a reliable biometric approach that identifies individuals using the distinctive and stable texture of the iris. However, recognition

Unsupervised Metal Artifact Reduction in Dental CBCT using Fine-tuned Cycle-Consistent Adversarial Networks

arXiv:2607.20977v1 Announce Type: new Abstract: Metal artifacts generated by dental implants significantly degrade cone-beam computed tomography (CBCT) volumes, obscuring critical anatomical structure

Wireless TokenCom: RL-Based Tokenizer Agreement for Multi-User Wireless Token Communications

arXiv:2602.12338v2 Announce Type: replace Abstract: Token Communications (TokenCom) has recently emerged as an effective new paradigm, where tokens are the unified units of multimodal communications a

safetyarxiv-cs-lg

Adaptive Visual Autoregressive Acceleration via Dual-Linkage Entropy Analysis

arXiv:2602.01345v2 Announce Type: replace Abstract: Visual AutoRegressive modeling (VAR) suffers from substantial computational cost due to the massive token count involved. Failing to account for the

Agentic Real2Sim: Physics-based World Modeling with Vision-Language Agents

arXiv:2607.19190v2 Announce Type: replace-cross Abstract: Real-to-sim conversion for robotic interaction with objects remains labor-intensive because it requires more than visual reconstruction: a str

Tutorials

Auditing Retrieval-Augmented LLM Hypotheses for Longitudinal Cell Painting Morphology

arXiv:2607.19415v1 Announce Type: cross Abstract: High-content morphological profiling (Cell Painting) yields sensitive, high-dimensional signatures of cellular state, but translating longitudinal mor

tutorialsarxiv-cs-ai

AuditVotes: Elevating Provable Defense for GNNs with Efficient Augmentation and Conditional Smoothing

arXiv:2503.22998v3 Announce Type: replace-cross Abstract: Despite advancements in Graph Neural Networks (GNNs), adaptive attacks continue to challenge their robustness. Certified robustness via random

Causal dictionary learning reveals and validates transcription-factor binding features in genomic language models

arXiv:2607.19618v1 Announce Type: cross Abstract: Genomic language models achieve strong performance across regulatory-genomics tasks, yet what these models internally represent remains opaque, and th

Applications

Challenges of Explainability in Continual Learning for Time Series Forecasting

arXiv:2607.19382v1 Announce Type: cross Abstract: Deep learning models have shown strong potential for time series forecasting, yet their deployment in real-world environmental monitoring remains chal

applicationsarxiv-cs-ai

Confidence-Gated Vision-Only Heading Alignment for UAV-UGV Cooperative Systems

arXiv:2607.18713v1 Announce Type: cross Abstract: Vision-based heading prediction is useful for UAV--UGV cooperation, but accurate prediction alone does not guarantee that every predicted heading shou

Contrastive On-Policy Distillation

arXiv:2607.19046v1 Announce Type: new Abstract: On-policy Distillation (OPD) supervises a student model on trajectories sampled from its own policy by minimizing the divergence between the output dist

Coordinating from Memory: Graph-Structured Experience Reuse for Multi-Agent Adaptation in Dynamic Manufacturing

arXiv:2607.19985v1 Announce Type: new Abstract: Dynamic manufacturing environments require multi-agent systems to coordinate effectively under frequent operational disturbances such as machine failure

Cross-Subject Semantic Decoding with Shared-Space Alignment for Generalized Neural Representation Learning

arXiv:2607.19394v1 Announce Type: cross Abstract: Generalizing across subjects remains challenging in invasive neural recordings because electrode configurations, anatomical structures, and neural sig

Detect Early, Escalate Rarely: Anytime Detection of AI-Generated Video from the Compressed Bitstream

arXiv:2607.19476v1 Announce Type: new Abstract: Detectors for AI-generated video are evaluated offline. A clip is decoded to pixels and scored once, increasingly by a large vision-language model. Dete

Distributed Motion Planning with Safety Guarantees for Self-Reconfiguring Robotic Boats

arXiv:2607.20352v1 Announce Type: new Abstract: Aquatic self-reconfigurable robots must assemble into desired shapes while ensuring safe interactions among multiple agents. This paper proposes a hybri

safetyarxiv-cs-ro

DQAOA-GPT: AI-Accelerated Distributed Quantum Optimization for Combinatorial Problems

arXiv:2607.20225v1 Announce Type: cross Abstract: While combinatorial optimization problems are central to many scientific and engineering applications, their solution remains challenging due to expon

Dual Adversarial Fine-tuning for Enhancing Robustness of Large Vision Language Model

arXiv:2607.18958v1 Announce Type: new Abstract: While Large Vision-Language Models (LVLMs), represented by LLaVA and GPT-4V, have demonstrated remarkable capabilities, their visual inputs remain vulne

ETPDesigner: Multi-Agent Orchestration for Interactive Multimodal Electronic Theater Program

model-releasesarxiv-cs-cv

arXiv:2607.19947v1 Announce Type: new Abstract: Electronic Theater Programs (ETPs) serve as critical promotional media in the performing arts, comprising a multi-page collection of heterogeneous visua

Applications

FE-MCFormer: a novel time-frequency interpretable architecture for machinery fault diagnosis under strong noise environments

arXiv:2505.06285v3 Announce Type: replace-cross Abstract: Interpretable fault diagnosis (FD) plays a critical role in industrial manufacturing, as it improves human-machine understanding and operation

applicationsarxiv-cs-cv

FormulaSPIN: Self-Play Fine-Tuning for Natural Language to Spreadsheet Formula Generation

arXiv:2607.19354v1 Announce Type: new Abstract: Spreadsheet applications are used by hundreds of millions worldwide, yet writing formulas remains a significant barrier. Existing approaches rely on sta

Hardware

From Pixel to Prognosis: Convolutional and GLCM Feature Fusion for Automated Four-Class Cataract Severity Classification

arXiv:2607.18349v1 Announce Type: new Abstract: Objective: To develop a low-cost automated cataract severity classification system operating on standard consumer-grade colour photographs of the eye, w

hardwarearxiv-cs-cv

Interactive Medical-SAM2 GUI: A Napari-based semi-automatic annotation tool for medical images

model-releasesarxiv-cs-cv

arXiv:2602.22649v2 Announce Type: replace Abstract: Interactive Medical-SAM2 GUI is an open-source desktop application for semi-automatic annotation of 2D and 3D medical images. Built on the Napari mu

Tutorials

Interval and fuzzy physics-augmented neural networks (iPANN and fPANN) for uncertainty quantification and propagation in constitutive modeling

arXiv:2607.20339v1 Announce Type: new Abstract: Constitutive modeling under uncertainty remains a central challenge for reliable mechanics simulations, particularly when the available stress-deformati

tutorialsarxiv-cs-lg

LAARA: Layer-Aware Adaptive Rank Allocation for Parameter-Efficient Fine-Tuning

arXiv:2607.19391v1 Announce Type: cross Abstract: Low-Rank Adaptation is widely used for parameter-efficient fine-tuning, yet existing methods typically assign the same adapter rank to every transform

Meta-Learning Preferences for Multilingual LLM Alignment

arXiv:2607.13315v2 Announce Type: replace Abstract: Unequal availability of human preference data across languages poses a significant challenge for aligning large language models in multilingual sett

safetyarxiv-cs-cl