Search: “models”

Towards Geometry-Grounded Dense Semantic Matching with VGGT Priors

arXiv:2509.21263v2 Announce Type: replace Abstract: Semantic matching aims to establish pixel-level correspondences between instances of the same category and represents a fundamental task in computer

researcharxiv-cs-cv

12 Aug 2026

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TrAC: Trace-Conditioned Answer Consistency for Efficient Uncertainty Quantification in LLMs

DGX agent

arXiv:2608.00422v2 Announce Type: replace Abstract: Large language models (LLMs) can generate fluent reasoning traces that nevertheless lead to incorrect answers, making response-level uncertainty est

researcharxiv-cs-ai

12 Aug 2026

Tutorials

Transformer Geometry Observatory TGO-IV: Developmental Topology Observatory

arXiv:2608.09997v1 Announce Type: cross Abstract: Transformers have had a profound impact on the world of language processing and computer vision. As efforts to answer the million-dollar question of `

tutorialsarxiv-cs-cv

12 Aug 2026

Two-stage Odd Residual Flows for Mean-Preserving Probabilistic Time Series Forecasting

arXiv:2608.11114v1 Announce Type: cross Abstract: Probabilistic forecasting plays an essential role in risk-sensitive decision-making, particularly in long-horizon settings. However, existing approach

12 Aug 2026

A Hybrid Nested Harness for Decoupling Structure and Parameters in LLM-Driven Optimization

arXiv:2608.08156v1 Announce Type: new Abstract: In evolutionary algorithms powered by language models, the LLM acts as a single operator that simultaneously updates structural components (like control

A Probabilistic Circuit-Induced Pseudo-Metric for Out-of-Distribution Detection

arXiv:2608.09117v1 Announce Type: new Abstract: Probabilistic Circuits (PCs) are tractable generative models whose internal nodes encode a hierarchy of probabilistic sum- maries over different variabl

Tutorials

Adaptive Symmetry Discovery for Dynamical System Identification

arXiv:2608.08091v1 Announce Type: cross Abstract: Dynamical systems model trajectory data generated by fixed underlying dynamics, with applications ranging from biology to physics. Especially in scien

tutorialsarxiv-cs-ai

Agentic AI-driven Immersive Simulation: A Knowledge-Aware Virtual Training Platform forHigh Dose Rate (HDR) Brachytherapy

arXiv:2608.08163v1 Announce Type: new Abstract: The convergence of the Metaverse and Large Language Model (LLM)-based AI agent is catalyzing a shift toward autonomous, immersive, and personalized peda

local-aiarxiv-cs-ai

Agentic Harnesses: LLM-Driven Verification Layers for Robot Autonomy

arXiv:2608.09857v1 Announce Type: cross Abstract: Advances in advanced artificial intelligence tools have sparked research in robot autonomy, but the development of such systems has largely focused on

An AI Scientist that Doesn't Drift: Taste, Structure, and Falsifiable Findings in a Quadruped Navigation Research Loop

arXiv:2608.07542v1 Announce Type: new Abstract: Autonomous research loops driven by large language models can run machine-learning experiments at scale but tend to drift toward local refinements of wh

local-aiarxiv-cs-ai

BRUCE: Benchmarking Robustness Under Corruption Escalation for Scientific Vision-Language Reasoning

arXiv:2608.07742v1 Announce Type: new Abstract: Visual-language models (VLMs) frequently struggle with robustness issues in real-world situations due to low- or varying-quality input images. In this p

applicationsarxiv-cs-cv

CEAA: A Cognitive Embodied Agents Architecture for Interactive Computing Systems

arXiv:2608.09848v1 Announce Type: new Abstract: The development of embodied Intelligent Virtual Agents (IVAs) that have cognitive capabilities in real-time interactive virtual environments remains a c

agentsarxiv-cs-ai

CIFA: Contextual-Intersectional Fairness Auditing for Hidden Subgroup Discovery in Face Analysis

arXiv:2608.09669v1 Announce Type: new Abstract: Fairness evaluation in computer vision commonly relies on aggregate accuracy and demographic subgroup analysis. However, visual models are also sensitiv

safetyarxiv-cs-cv

Conditional Diffusion for Nonparametric Instrumental Variable Quantile Regression

arXiv:2608.08204v1 Announce Type: cross Abstract: This work proposes deep nonparametric Instrumental variable quantile regression (IVQR), a two-stage estimator that combines conditional diffusion mode

Consilience for Verifier-Free Test-Time Scaling

arXiv:2608.09898v1 Announce Type: new Abstract: Test-time scaling often uses an external verifier, such as compilers and test cases in coding or trained value functions in robotics applications, to ob

applicationsarxiv-cs-cl

Control-Oriented Scenario Tree Construction through Reinforcement Learning

arXiv:2608.09335v1 Announce Type: new Abstract: Multistage stochastic model predictive control (MPC) handles uncertainty by optimizing over a scenario tree, a finite branching approximation of future

Deep Learning based Detection of Fishing Vessels and Fishing Monitoring using Nightlight Images

arXiv:2608.09360v1 Announce Type: cross Abstract: The demand for maritime surveillance has given rise to the need for monitoring fishing vessel activities, particularly in addressing the challenge of

Defending Retrieval-Augmented Intrusion Detection Against Knowledge Poisoning and Prompt Injection

arXiv:2608.08100v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enables large language models to classify network flows and generate human-readable incident reports by retrievin

agentsarxiv-cs-ai

DistMoE: Private-data Rehearsal-free Routing in Mixture-of-Experts for Distributed Instruction Tuning

arXiv:2608.09907v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown strong multimodal instruction-following ability, but adapting them to diverse visual-language domain

local-aiarxiv-cs-cv

Diversity Matters: Distributional Feature Coverage Sample Selection for Data-Efficient Backdoor Attacks

arXiv:2608.09047v1 Announce Type: cross Abstract: Backdoor attacks compromise training data so that a model retains clean accuracy but predicts an attacker-chosen target on triggered inputs. At very l

researcharxiv-cs-cv

Do Evaluation Metrics Detect Errors in Classical Chinese to English Translations?

arXiv:2608.08283v1 Announce Type: cross Abstract: Although large language models can translate some historical languages surprisingly well, their usefulness in digital humanities workflows is limited

DUET: A Diversity-Quality Duet of Distillation Experts for Two-Step Video Generation

arXiv:2608.09637v1 Announce Type: cross Abstract: Diffusion models have enabled high-quality video generation in recent years, but the high cost of iterative sampling hinders their practical deploymen

Efficient identification of critical regions via Flow Matching-based Monte Carlo initialization

arXiv:2508.15318v5 Announce Type: replace-cross Abstract: Markov chain Monte Carlo (MCMC) is a standard tool for studying many-body systems, but its practical cost can become substantial, especially w

EHR-MPC: Inference-Time Control for Sepsis Treatment with Generative Patient Digital Twins

arXiv:2607.08793v4 Announce Type: replace-cross Abstract: Sepsis is a leading cause of mortality, yet optimal treatment policies remain contested. Existing reinforcement learning (RL) approaches learn

EMMR: Emotion-Mediated Multimodal Reasoning for Personality Assessment in Asynchronous Video Interviews

arXiv:2608.07512v1 Announce Type: cross Abstract: Asynchronous Video Interviews (AVIs) have become increasingly popular for personality assessment. Recent large language models (LLMs) have shown poten

Evaluation of Motivational Interviewing Counsellors with Task-Aware Multi-Stage LLM-Based Simulated Clients

arXiv:2608.07499v1 Announce Type: cross Abstract: The development and benchmarking of Large Language Model (LLM)-based Motivational Interviewing (MI) counsellors now often rely on LLM-based simulated

Evidence-RL: Towards Evidence-intensive Visual Reasoning

arXiv:2608.08021v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) should answer from concrete image evidence rather than language priors, dataset shortcuts, or irrelevant visual context.

local-aiarxiv-cs-ai

Exact Network Surgery: Functional Invariance and Gradient Plasticity in Reactive Computational Graphs

arXiv:2607.16568v2 Announce Type: replace Abstract: Function-preserving network growth techniques such as Net2Net and progressive stacking expand a model's capacity without destroying its learned func

Tutorials

Experience-Sensitive Game Learning: A Behavioral Study of Humans and Language Agents

arXiv:2608.07490v1 Announce Type: cross Abstract: Large language model agents are increasingly evaluated through games, but most benchmarks emphasize final outcomes rather than how players learn from

tutorialsarxiv-cs-ai

Explainable Machine Learning in Healthcare: Methods, Interpretation, and Applications for Clinical Research

arXiv:2608.07522v1 Announce Type: cross Abstract: We present a structured review of commonly used Explainable machine learning (XML) methodologies, including global and local interpretability tools su

local-aiarxiv-cs-lg

Explore, Map, Remember, Decide: Are Embodied VLMs Ready for Safety-Critical Scenarios?

arXiv:2608.08077v1 Announce Type: new Abstract: Theory of Space framework (ToS) assesses the spatial understanding of curiosity-driven Vision-Language Models (VLMs) under partial observability. As AI

FactorDrive: Adaptive Multi-Step Reasoning Driven by Planning-Critical Factors for End-to-End Autonomous Driving

arXiv:2608.09591v1 Announce Type: cross Abstract: Vision-language models (VLMs) have advanced scene understanding and enabled explicit reasoning in end-to-end autonomous driving. However, existing met

safetyarxiv-cs-cv

From Sweep to Seam: Interleaved Cross-Block Post-Training Quantization

arXiv:2608.09595v1 Announce Type: new Abstract: Compressing large language models to two bits or fewer is increasingly feasible through block-wise post-training quantization; cross-block variants reco

Gated Spatial Redundancy Projection for Pathology Transformer Attentions

arXiv:2608.08374v1 Announce Type: new Abstract: Transformer models are increasingly used for whole-slide image analysis in computational pathology. Yet, WSIs differ fundamentally from natural images:

researcharxiv-cs-cv

Guixu: Valuation-Driven Data Discovery for Autonomous AI Agents with On-Chain Attestation

arXiv:2608.07949v1 Announce Type: new Abstract: Autonomous agents increasingly rely on external data to complete downstream tasks such as model training and decision support. However, existing data di

agentsarxiv-cs-ai

Hierarchical Multi-Task Federated Learning in VANETs

arXiv:2608.08111v1 Announce Type: cross Abstract: Vehicular Ad hoc Networks (VANETs) increasingly rely on federated learning (FL) to enable collaborative intelligence without sharing raw sensory data.

How Can Rhetoric Reward-Hack AI Reviewers? Dissecting Rhetorical Sensitivity in AI-Based Peer Review

arXiv:2608.08975v1 Announce Type: cross Abstract: As large language models increasingly participate in scientific evaluation, we investigate a potential form of reward hacking: how rhetorical choices

Human-Guided Causal Knowledge Injection for Virtual Cells

arXiv:2608.08430v1 Announce Type: cross Abstract: Virtual cells employ machine learning models to simulate and predict cellular behaviors, serving as a critical computational framework for investigati

applicationsarxiv-cs-ai

In-Context Density Estimation for Tabular Data

arXiv:2608.09348v1 Announce Type: new Abstract: Density estimation underlies many unsupervised tasks on tabular data such as anomaly detection, out-of-distribution detection, and data augmentation. Al

KGCache: Amortized Subgraph Retrieval for KG Reasoning with LLMs

arXiv:2608.07954v1 Announce Type: new Abstract: Large language models can answer knowledge-intensive questions more reliably when they are grounded with knowledge graphs, but systems such as Think-on-

KumbhDoot: A Scale-Ready, LLM-Bounded Architecture for Mass-Gathering Public-Service Assistants

arXiv:2608.07520v1 Announce Type: cross Abstract: Mass religious gatherings such as the Kumbh Mela concentrate tens of millions of people into a single region over a few weeks, producing intense, repe

LAVE: Latent Visual Evidence-Enhanced Planning for Video Tool-use Agents

arXiv:2608.07585v1 Announce Type: new Abstract: Long-video understanding requires models to efficiently acquire and reuse sparse visual evidence from long and redundant video streams. Recent video too

agentsarxiv-cs-cv

Linguistically-Aligned and Visually-Grounded Preference Optimization for Clinically-Augmented Medical Report Generation

arXiv:2608.08494v1 Announce Type: new Abstract: Despite significant advances in Medical Report Generation (MRG), the reliability remains constrained by the prevalence of factual errors. While Direct P

safetyarxiv-cs-cv

LLM-Based Embeddings for Program Analysis and Optimization

arXiv:2608.07894v1 Announce Type: new Abstract: Recent advances have highlighted the potential of machine learning, particularly Large Language Models (LLMs), for analyzing and optimizing programs. We

LLM Reasoning for Subjective Tasks: Failure Modes, Mitigation, and Dynamic Reasoning Routing

arXiv:2608.08889v1 Announce Type: new Abstract: Recommendation systems thrive on personalization, where ''correctness'' is rarely a binary truth but a matter of subjective human preference. As Large L

Measuring and Reducing WebGPU Dispatch Overhead for LLM Inference

arXiv:2608.08730v1 Announce Type: new Abstract: Large Language Models are deployed to multiple types of environments, from internet browsers to edge devices, and WebGPU serves as a modern cross-platfo

Motion-Aware Animatable Gaussian Avatars Deblurring

arXiv:2411.16758v4 Announce Type: replace Abstract: The creation of 3D human avatars from multi-view videos is a significant yet challenging task in computer vision. However, existing techniques rely

applicationsarxiv-cs-cv

MPPI Planning with Gaussian Based Human Cost Function for Social Navigation

arXiv:2608.08323v1 Announce Type: new Abstract: Safe robot navigation in crowded spaces requires planning that accounts for where people will be, not only where they are now. Model Predictive Path Int

researcharxiv-cs-ro