Search: “framework”

arXiv:2608.15869v1 Announce Type: cross Abstract: Multimodal large language models increasingly use visual chain-of-thought (Visual CoT) to reason about spatial, temporal, and embodied environments. B

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Bias-Corrected Ceilings of Emotion Predictability from Human Label Variation Based on Instance-Level Fano Bounds

DGX agent

arXiv:2608.15619v1 Announce Type: new Abstract: Emotion recognition from text keeps improving on benchmarks, yet whether an accuracy ceiling has been reached is seldom asked with discipline. Our aim i

safetyarxiv-cs-ai

18 Aug 2026

Bitstream Action Recognition is Byte Modeling

arXiv:2608.15695v1 Announce Type: new Abstract: Conventional action recognition typically relies on successful pixel decoding of the bitstream. However, bitstream corruption during storage or transmis

BRA-Audit: Budgeted Runtime Auditing for LLM Multi-Agent Systems via Cumulative-Exposure Audit-Point Placement

arXiv:2608.14668v1 Announce Type: cross Abstract: LLM-based multi-agent systems (LLM-MAS) solve complex tasks through specialized collaboration, but inter-agent dependencies can propagate hallucinated

agentsarxiv-cs-ai

Hardware

BrainLinear: A Linear Model for Brain Network Analysis in Sparse Tangent Subspaces

arXiv:2608.15266v1 Announce Type: cross Abstract: Functional connectome analysis examines brain-region interactions to understand and identify disorders such as autism spectrum disorder and Alzheimer'

hardwarearxiv-cs-lg

Breaking and Defending LLM-Powered Social Media Bot Detection Systems

arXiv:2608.15893v1 Announce Type: new Abstract: The rise of social media bots poses a persistent threat, enabling misinformation, opinion manipulation, and the erosion of trust in online platforms. To

Bringing Generative Learning to Representation Learning: Self-Supervised Transfer Learning as Distribution Matching

arXiv:2502.14424v3 Announce Type: replace-cross Abstract: Most self-supervised learning objectives defend against collapse but leave the target representation law unspecified. We formulate representat

Budget-Aware Tool Use Enables Effective Agent Scaling

arXiv:2511.17006v2 Announce Type: replace Abstract: Scaling test-time computation has been extended from language model reasoning to tool-augmented agents, where scaling involves not only thinking in

agentsarxiv-cs-ai

Building cost-effective, high-throughput gen AI workflows in Google Dataflow

model-releasesgoogle-cloud-ai

Real-time streaming pipelines are the operational backbone of modern enterprises, continuously processing everything from customer support interactions to transaction logs. Traditionally, streaming DA

Building operational resilience with agentic AI in financial services

model-releasesgoogle-cloud-ai

For financial institutions, operational resilience has long been embedded in regulatory and supervisory expectations — to say nothing of the high expectations of consumers. With the implementation of

CACSurv: Concordance-Aligned Comparative Learning with Large Language Models for Cancer Survival Prediction

arXiv:2608.16594v1 Announce Type: new Abstract: Cancer survival prediction supports treatment planning, risk stratification, and follow-up management. Existing methods use structured clinical variable

Camera-Agnostic Pruning of 3D Gaussian Splats via Descriptor-Based Beta Evidence

arXiv:2603.21933v2 Announce Type: replace-cross Abstract: The pruning of 3D Gaussian splats is essential for reducing their complexity to enable efficient storage, transmission, and downstream process

Can Attribution Predict Risk? From Multi-View Attribution to Planning Risk Signals in End-to-End Autonomous Driving

arXiv:2605.06264v2 Announce Type: replace Abstract: End-to-end autonomous driving models generate future trajectories from multi-view inputs, improving system integration but introducing opaque decisi

agentsarxiv-cs-lg

Can LLMs Reason Like Automated Theorem Provers for Rust Verification? VCoT-Bench: Evaluating via Verification Chain of Thought

arXiv:2603.18334v2 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) increasingly assist secure software development, their ability to meet the rigorous demands of Rust program ve

Can Neural Networks Learn by Experimenting on Themselves? Self-Interventional Learning from Functional Consequences to Predictive Self-Knowledge

arXiv:2608.14894v1 Announce Type: new Abstract: Machine-learning systems usually model external data, while their internal functional organization is analyzed by external observers. This work introduc

safetyarxiv-cs-lg

CardiacMamba: Fair and Robust RGB-RF Fusion for Remote Heart Rate Estimation via State Space Modeling

arXiv:2608.15831v1 Announce Type: cross Abstract: Remote photoplethysmography (rPPG) enables non-contact heart rate (HR) monitoring from facial videos, but RGB-only methods are vulnerable to illuminat

CEDAR-GRPO: Process-Aware Reinforcement Learning for General Abductive Reasoning in LLMs

arXiv:2608.14791v1 Announce Type: new Abstract: Abductive reasoning, often characterized as inference to the best explanation, is central to explanation under uncertainty, from everyday sense-making a

CETalk: Continuous Valence-Arousal Control for Audio-Driven 3D Talking Head Generation

arXiv:2608.15110v1 Announce Type: cross Abstract: Emotional 3D talking head generation aims to synthesize expressive facial animations with accurate lip synchronization. However, existing methods ofte

CG-GLORE: A Conjugate Gradient-Based Global-Local Regularization Network for Sparse-View CT Reconstruction

arXiv:2608.15246v1 Announce Type: cross Abstract: Sparse-view computed tomography (CT) reduces radiation dose by acquiring fewer projection views, but the resulting inverse problem is highly ill-posed

ChainSpace: A Chained-Reasoning Paradigm for Spatial Intelligence

arXiv:2608.15788v1 Announce Type: new Abstract: Spatial intelligence requires foundation models to maintain coherent spatial state across interactions with the physical world. However, existing data-c

Characterization of Thermal Systems from Noisy and Low-resolution Measurements Using Dynamic Mode Decomposition

arXiv:2608.14581v1 Announce Type: cross Abstract: Thermal monitoring in practical applications is often constrained by sparse sensing, measurement noise, and limited spatial resolution, which hinder t

CLARA: Clip-Level Multimodal Alignment with VLM-Derived Rationales for Hateful Video Detection

arXiv:2608.15905v1 Announce Type: new Abstract: Hateful video detection has become increasingly important with the rapid growth of video-centric social media platforms, given the serious risks that ha

Coarse-to-Fine Multi-Resolution Diffusion Models for Trajectory Generation in Urban Systems

arXiv:2608.14570v1 Announce Type: new Abstract: Understanding human mobility is critical for a wide range of urban applications, including traffic management, epidemic control, and urban planning. How

researcharxiv-cs-lg

CompoSkill: Compositional Skill Chain Attacks from Individually Scanner-Passing LLM Agent Skills

arXiv:2608.16246v1 Announce Type: cross Abstract: Autonomous AI agents tackling Long Horizon Tasks depend on marketplace skills that are certified one at a time: a scanner returns a safety verdict for

Local Ai

ConceptFormer: Learning Adaptive Latent Concepts for Query-Document Alignment in Visual Document Retrieval

arXiv:2608.15698v1 Announce Type: new Abstract: Visual document retrieval is a critical component of multimodal retrieval-augmented generation, aiming to identify query-relevant pages from document co

local-aiarxiv-cs-cv

Convolution Smoothed Quantile Regression for XGBoost

arXiv:2608.15290v1 Announce Type: cross Abstract: The increasing availability of large and complex datasets across many scientific disciplines has led to widespread adoption of machine learning (ML) f

Cross-Modal Ultrasound-MRI Learning for Fetal Brain Ventricular Volumetry and Abnormality Screening

arXiv:2608.14763v1 Announce Type: cross Abstract: Assessment of ventriculomegaly (VM) on fetal brain ultrasound relies primarily on measuring lateral ventricular atrial width on standard planes, which

safetyarxiv-cs-ai

Crystal-structure design by agentic AI in a language of motifs

arXiv:2608.15900v1 Announce Type: cross Abstract: Data-driven materials discovery interpolates more reliably than it extrapolates and seldom reaches new structure types. We present MatEvolve, an agent

CUBICS: Situation-aware performance estimation for safety-relevant ML components

arXiv:2608.16564v1 Announce Type: new Abstract: Machine learning (ML) is a key technology driving innovation today, but ensuring ML safety remains a major challenge for safety-related applications. A

safetyarxiv-cs-ai

Cyclops: LiDAR as a Camera That Dreams in Color

arXiv:2608.16264v1 Announce Type: new Abstract: Conventionally, robotic perception relies heavily on cameras due to the rich semantic texture they provide. However, their performance degrades signific

safetyarxiv-cs-ro

D2-ScaleAgent: Dual-Dimensional Scaling for Long Document Understanding

arXiv:2608.16417v1 Announce Type: new Abstract: Multi-modal retrieval-augmented generation (RAG) is a key technique for visually rich long document understanding. Existing multi-modal RAG methods are

agentsarxiv-cs-cl

Tutorials

Data-Driven Reconstruction of Spatially Resolved Electron and Ion Energy Distributions from Macroscopic Plasma Quantities with Deep Neural Networks

arXiv:2608.16519v1 Announce Type: cross Abstract: Spatially resolved EEDFs/IEDFs provide essential kinetic information about low-temperature plasmas (LTPs) and play a central role in determining trans

tutorialsarxiv-cs-lg

Local Ai

DCA-MoE: Spatially Adaptive Cross-Layer Fusion and Density-Routed Experts for Crowd Counting

arXiv:2608.15213v1 Announce Type: new Abstract: Crowd counting must recover reliable local density under severe variations in perspective, head scale, occlusion, and background clutter. Although moder

local-aiarxiv-cs-cv

Dear Algo: A Precision-First Agentic Intent Layer for Unified Search and Recommendation

arXiv:2608.15877v1 Announce Type: new Abstract: Search and recommendation serve a shared discovery objective but encode intent differently. We study this boundary through Dear Algo on Threads, a deplo

agentsarxiv-cs-ai

Decision-Driven Regularization: A Blended Model for Learning and Optimization

arXiv:2608.15124v1 Announce Type: new Abstract: In contextual optimization, the decision-maker seeks optimal decisions to minimize a cost function, that varies based on observed features. This context

researcharxiv-cs-lg

Decomposing Whole Slide Image Report Generation with Graph-Constrained Multiple Instance Learning Workflows

arXiv:2608.15353v1 Announce Type: new Abstract: Whole-slide image (WSI) report generation requires recognizing spatially distributed pathological features and organizing them into a coherent diagnosti

researcharxiv-cs-cv

Decoupled Temporal Encoding for Generative Recommendation

arXiv:2608.16274v1 Announce Type: cross Abstract: Positional encoding is a fundamental component of Transformer-based generative recommendation models, where user histories are modeled as autoregressi

Local Ai

Deep Probabilistic Indoor Gas Source Localization via Physical Dependency-Guided Sequential Inference

arXiv:2608.16221v1 Announce Type: new Abstract: Reliable gas source localization (GSL) is critical to safety in industrial and urban environments, yet remains challenging indoors because walls and obs

local-aiarxiv-cs-ro

DeepOHeat-v2: Self-Improving Operator Learning for Fast and Trustworthy Thermal Optimization in 3D-IC Design

arXiv:2608.16080v1 Announce Type: new Abstract: Thermal-aware optimization of multi-die 3D integrated circuits evaluates many designs, each a costly heat-equation solve. Operator-learning surrogates r

Applications

Degradation-Aligned Self-Supervised Learning for State of Health Estimation of Lithium-Ion Batteries under Label Sparsity

arXiv:2608.16612v1 Announce Type: cross Abstract: An accurate estimation of the state of health (SOH) underpins a safe and optimized use of the battery system. Although compelling, data-driven SOH est

applicationsarxiv-cs-ai

DeMTS: Denoising Trajectories as Multivariate Time Series for Hallucination Detection in Diffusion Language Models

arXiv:2608.14632v1 Announce Type: cross Abstract: Diffusion large language models (D-LLMs) have emerged as a promising paradigm for text generation. However, similar to autoregressive LLMs, D-LLMs rem

DepthArb: Training-Free Depth-Arbitrated Generation for Occlusion-Robust Image Synthesis

arXiv:2603.23924v2 Announce Type: replace Abstract: Text-to-image models often struggle to synthesize correct occlusion relationships among multiple objects, especially in densely overlapping regions.

Design Optimization for Large High-Force Soft Robot Manipulators Under Gravitational Loads

arXiv:2608.16728v1 Announce Type: new Abstract: Designing large soft robots capable of generating high forces for physical human-robot interaction remains a significant challenge in soft robotics. Pri

researcharxiv-cs-ro

Detachable Wire Drive : Reconfigurable Robot Architecture with Shared Actuators

arXiv:2608.15461v1 Announce Type: new Abstract: Reconfigurable robots offer significant potential for adapting to diverse tasks; however, conventional centralized architectures often require dedicated

researcharxiv-cs-ro

Differentiable Thermodynamic Phase-Equilibria for Machine Learning

arXiv:2603.11249v4 Announce Type: replace Abstract: Accurate prediction of phase equilibria remains a central challenge in chemical engineering. Physics-consistent machine learning methods that incorp

researcharxiv-cs-lg

DirMixE: Harnessing Test Agnostic Long-tail Recognition with Hierarchical Label Variations

arXiv:2405.07780v3 Announce Type: replace-cross Abstract: This paper explores test-agnostic long-tail recognition, a challenging long-tail task where the test label distributions are unknown and arbit

Domain-Agnostic Neural Topic Modeling with Contextual Token-Level Semantic Graph Representation

model-releasesarxiv-cs-cl

arXiv:2608.16269v1 Announce Type: new Abstract: Recent advances in neural topic models with pre-trained language models (PLMs) have achieved strong performance by leveraging general-domain pre-trainin

Tutorials

Domain Agnostic Text Redaction from Natural Language Rules using Instruction Tuning

arXiv:2608.14693v1 Announce Type: cross Abstract: With the increasing digitization of personal and corporate communication, the automatic sanitization of textual data has become a crucial component of

tutorialsarxiv-cs-ai