Search: “models”

Agents in the Large: Perception-Centered Architecture for Persistent Agents

arXiv:2608.30478v1 Announce Type: new Abstract: Cognitive language agents have achieved substantial progress by equipping language models with memory, tools, and decision-making procedures, enabling a

agentsarxiv-cs-cl

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AQ3D: Adaptive Query Transformer for 3D Instance Segmentation

DGX agent

arXiv:2608.30618v1 Announce Type: new Abstract: Transformer-based decoders for 3D instance segmentation typically commit to a fixed number of queries and positional modeling calibrated on the training

researcharxiv-cs-cv

1 Sept 2026

AssetOpsBench: Benchmarking AI Agents for Task Automation in Industrial Asset Operations and Maintenance

arXiv:2506.03828v4 Announce Type: replace Abstract: AI for Industrial Asset Lifecycle Management aims to automate complex operational workflows, such as condition monitoring and maintenance scheduling

agentsarxiv-cs-ai

Augmenting Interviewer Judgments of Patient Experience with Automatic Language Analysis

arXiv:2608.31007v1 Announce Type: cross Abstract: Understanding how psychiatric patients subjectively experienced a clinical conversation is important for feedback and alliance-related process monitor

researcharxiv-cs-cl

Beyond Ranking Accuracy: Evaluating LLM-Cited Feature Rationales for Next Basket Repurchase Recommendation

arXiv:2608.30333v1 Announce Type: cross Abstract: Next-basket repurchase recommendation is commonly formulated as a ranking task: given a customer's purchase history, the system ranks previously purch

applicationsarxiv-cs-ai

Beyond Visual Boundaries: Rethinking Scene Segmentation for Movie RAG

arXiv:2608.28699v1 Announce Type: new Abstract: Understanding long-form video remains a fundamental challenge for multimodal large language models (MLLMs). Sparse frame sampling fails to capture fine-

Breaking Darknet CAPTCHAs with general purpose LLM

arXiv:2608.28794v1 Announce Type: cross Abstract: Our work evaluates the effectiveness of automated methods for solving CAPTCHA challenges commonly encountered in darknet environments. These CAPTCHAs

safetyarxiv-cs-cv

Bridging Semantics and Physics with Constrained LLMs for Safe and Trustworthy Robotic Manipulation

arXiv:2608.29379v1 Announce Type: new Abstract: A language-guided robot operating in a real kitchen must do more than produce a plan that appears correct. It must also execute that plan safely in clut

safetyarxiv-cs-ro

Can escalation channels redirect reward hacking toward defect disclosure?

arXiv:2608.29460v1 Announce Type: new Abstract: When coding agents encounter defective test infrastructure they may reward-hack: hardcoding outputs or editing test files to pass tests they cannot legi

CARE: Privacy-Compliant Agentic Reasoning with Evidence Discordance

arXiv:2604.01113v2 Announce Type: replace Abstract: Large language model (LLM) systems are increasingly used to support high-stakes decision-making, but they typically perform worse when the available

local-aiarxiv-cs-cl

CateKV: On Sequential Consistency for Long-Context LLM Inference Acceleration

arXiv:2608.30295v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated strong capabilities in handling long-context tasks, but processing such long contexts remains challengi

Co-Annotator: Expert-Distilled ViT and VLM for Visual and Documentation Guidance in Age-Related Macular Degeneration

arXiv:2608.30352v1 Announce Type: new Abstract: Clinical AI often optimizes predictive performance without engaging how clinicians decide where to look and what to write. We present Co-Annotator, whic

applicationsarxiv-cs-ai

Coding What Matters: A Semantic-Aware Memory Interface for Energy-Efficient Perception in Autonomous Vehicles

arXiv:2608.29000v1 Announce Type: new Abstract: Autonomous vehicles stream high-resolution surround-camera frames into memory before perception runs. This sensor-to-memory path consumes energy when ce

safetyarxiv-cs-ro

CoJEPA: Combining Contrastive Learning and JEPA for Global-Local Music Representations

arXiv:2608.30974v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architecture (JEPA) has shown strong performance in learning rich representations through self-supervised prediction in lat

Collapsibility of Performance Metrics in Clinical Predictive AI

arXiv:2608.30568v1 Announce Type: cross Abstract: Background: Population level assessments of predictive artificial intelligence (AI) can conceal performance disparities across subgroups. Fairness eva

Cost-Effective Repository Exploration for Agentic Issue Localization

arXiv:2608.29675v1 Announce Type: cross Abstract: Repository exploration is a distinct and costly stage of coding-agent pipelines: before generating a patch, an agent must identify which repository fi

Cost-efficient Active Learning for Referring Image Segmentation and Grounding

arXiv:2608.30621v1 Announce Type: cross Abstract: Collecting natural-language referring expressions along with region annotations, such as masks or boxes, is a major bottleneck in visual grounding (VG

Data-to-Energy Stochastic Dynamics

arXiv:2509.26364v3 Announce Type: replace Abstract: The Schrodinger bridge problem is concerned with finding a stochastic dynamical system bridging two marginal distributions that minimises a certain

safetyarxiv-cs-lg

Delegating Before Learning: Where Generative AI Sits in Students' Professional Communication

arXiv:2608.28837v1 Announce Type: cross Abstract: We conducted an interview study with twelve students on their use of generative AI in academic communication. Students delegated professional messages

Designing an Auditable LLM-Supported Workflow for Qualitative Thematic Analysis

arXiv:2608.30543v1 Announce Type: new Abstract: Large Language Models (LLMs) offer new possibilities for scaling qualitative analysis, but existing applications often provide limited methodological tr

Detect Before You Attribute: Cascade Failure Attribution for Multi-Agent Systems

arXiv:2608.29646v1 Announce Type: new Abstract: Large language model (LLM)-based agents have shown strong potential in solving complex tasks through multi-step reasoning, yet they remain vulnerable to

agentsarxiv-cs-ai

Diagnose, Then Refine: A Closed-Loop TTS System with AudioLLM-Guided Correction

arXiv:2608.28970v1 Announce Type: cross Abstract: Current TTS systems typically rely on open-loop, single-pass generation and can produce sporadic local prosodic defects, such as misplaced stress, unn

DiffInf: Influence-Guided Diffusion for Supervision Alignment in Facial Attribute Learning

arXiv:2603.06399v2 Announce Type: replace Abstract: Facial attribute classification relies on large-scale annotated datasets in which many traits, such as age and expression, are inherently ambiguous

safetyarxiv-cs-cv

Tutorials

DiffSAC: Diffusion-guided Sampling for Consensus-based Robust Estimation

arXiv:2608.30603v1 Announce Type: cross Abstract: Robust estimation is a core computer vision task frequently tackled using sample consensus. However, traditional methods suffer from inefficient sampl

tutorialsarxiv-cs-ai

Equivariant Sheaf Neural Networks: Learning Geometric Transport on Graphs

arXiv:2608.28853v1 Announce Type: cross Abstract: Equivariant graph neural networks provide a principled way to model geometric systems, but efficient first-order architectures remain limited in how v

Evaluating the Capabilities of LLMs for Persuasive Dialogue

arXiv:2608.29738v1 Announce Type: new Abstract: Large language models (LLMs) can generate apparently highly persuasive text, but does sounding persuasive mean arguing well? We introduce extsc{Persuasi

agentsarxiv-cs-cl

Event-triggered Control and Online Learning for Networked Systems under Computational Delays

arXiv:2608.29576v1 Announce Type: new Abstract: Online learning-based control is a promising approach to control uncertain systems, where unknown components are identified during operation to improve

Tutorials

Expected flow networks in stochastic environments and two-player zero-sum games

arXiv:2310.02779v3 Announce Type: replace Abstract: Generative flow networks (GFlowNets) are sequential sampling models trained to match a given distribution. GFlowNets have been successfully applied

tutorialsarxiv-cs-lg

Explainable Machine Learning for Broadband Adoption Disparities: Tract-Level Prediction and SHAP-Based Factor Profiling

arXiv:2608.29110v1 Announce Type: new Abstract: The United States has allocated approximately $65 billion through the Infrastructure Investment and Jobs Act for broadband expansion, yet evidence-based

applicationsarxiv-cs-lg

Explanations, Prompts, and Formalizations: Arguments for New Norms in LLM-Enabled Mathematical Research

arXiv:2608.29401v1 Announce Type: cross Abstract: As several mathematical conjectures have recently been settled using large language models (LLMs), the mathematical community has formulated norms and

FairReL: Deepfake Detection using Fairness-Aware Representation Learning

arXiv:2608.28777v1 Announce Type: new Abstract: Although recent deepfake detectors achieve high overall accuracy, their errors remain unevenly distributed across demographic subgroups, with real faces

local-aiarxiv-cs-cv

FiLM-GPNet: Geometry-Aware Pseudo-Supervised Phase Restoration with Zero-Shot Generalization for Large Temporal InSAR Stacks

arXiv:2608.29384v1 Announce Type: new Abstract: The growing availability of dense commercial Synthetic Aperture Radar (SAR) time series enables temporal Interferometric SAR (InSAR) analysis, but fixed

FIS-OT: Feature-Induced Optimal Transport for Unsupervised Action Segmentation

arXiv:2608.29980v1 Announce Type: new Abstract: Unsupervised action segmentation is a challenging task. It involves finding action categories and boundaries in videos without labels. Existing Optimal

safetyarxiv-cs-cv

Forget or Fine-tune? A Comparative Study of Machine Unlearning Strategies for Noisy Label Correction

arXiv:2608.30046v1 Announce Type: cross Abstract: Noisy labels remain a critical challenge for training deep neural networks, since memorizing incorrect labels degrades generalization. Once noisy samp

applicationsarxiv-cs-ai

FRAMEWORKERS: A Dynamic Multi-Agent Framework for AI-Generated Video Production

arXiv:2608.29814v1 Announce Type: new Abstract: Modern video generators excel at synthesizing individual clips, but complete video production requires coordinating a long sequence of interdependent cr

FreeFuse: Multi-Subject LoRA Fusion via Adaptive Token-Level Routing at Test Time

arXiv:2510.23515v3 Announce Type: replace Abstract: This paper proposes FreeFuse, a training-free framework for multi-subject text-to-image generation through automatic fusion of multiple subject LoRA

local-aiarxiv-cs-cv

Generation of High-Level Concepts in 3D Scene Graphs via Autoregressive Diffusion

arXiv:2608.28733v1 Announce Type: cross Abstract: Indoor 3D Scene Graphs (3DSGs) represent environments as multi-layer hierarchies that connect observed geometric primitives (e.g., planes) to higher-l

GMTS: Gradient Magnitude-based Token Selection Improves RLVR Training for LLM Reasoning

arXiv:2608.30632v1 Announce Type: cross Abstract: Reinforcement learning (RL), particularly RL with Verifiable Rewards (RLVR), has recently emerged as a central paradigm for enhancing large language m

Ground-to-Satellite Localization in Unconstrained Image Collections for 3D Scene Reconstruction

arXiv:2608.29211v1 Announce Type: new Abstract: Ground image localization with respect to satellite imagery is a key enabler for metrically-accurate, geo-localized 3D scene reconstruction from unconst

local-aiarxiv-cs-cv

Higher-Dimensional Rotary Position Embedding

arXiv:2608.29715v1 Announce Type: cross Abstract: Transformers rely on position embedding mechanisms in long context modeling in most cases. Rotary Position Embedding (RoPE) embeds positional informat

How You Ask Shapes What You Get: A Theory-Seeded Measurement of Articulation in Advice-Seeking LLM Conversations

arXiv:2608.29591v1 Announce Type: new Abstract: Users articulate the same advice-seeking request in different ways: some specify detailed constraints, others gesture at a vague need. Prior work treats

researcharxiv-cs-cl

Hybrid Offline-Online Multi-Agent Decision Transformers for Wireless Resource Management

arXiv:2608.28878v1 Announce Type: cross Abstract: This paper develops a hybrid offline-online multi-agent reinforcement learning framework based on decision transformers. The policy is first pretraine

Integrating Triaxial IMU Sensors and Ensemble Learning for Effective Parkinson Disease Severity Classification

arXiv:2608.28602v1 Announce Type: new Abstract: Parkinson disease PD is a progressive neurodegenerative disease that can have a significant impact on motor performance resulting in the appearance of s

Kronecker Factorization Improves Efficiency and Interpretability of Sparse Autoencoders

arXiv:2505.22255v4 Announce Type: replace-cross Abstract: Sparse Autoencoders (SAEs) decompose language-model activations into sparse, interpretable features, but standard encoders usually treat the l

researcharxiv-cs-cl

Learning Representations through Token Prediction: Geometry, Approximation, and Downstream Guarantees

arXiv:2608.30072v1 Announce Type: cross Abstract: Token prediction is a central pre-training objective for modern language models. Despite its empirical success, why token prediction learns broadly us

Least but not Last: Fine-tuning Intermediate Principal Components for Better Performance-Forgetting Trade-Offs

arXiv:2602.03493v2 Announce Type: replace Abstract: Low-Rank Adaptation (LoRA) methods have emerged as crucial techniques for adapting large pre-trained models to downstream tasks under computational

LightFuse: Relightable Interactive Gaussian Scene Reconstruction via Multi-Scan Fusion and 2D Gaussian Ray Tracing

arXiv:2608.29269v1 Announce Type: new Abstract: Relightable interactive scene reconstruction aims to build an editable 3D model from scans of different object arrangements and render new layouts under

Mapping-Based Image Diffusion

arXiv:2608.29164v1 Announce Type: new Abstract: In this work, we introduce a novel tensor-based functional for targeted image enhancement and denoising. Via explicit regularization, our formulation in