Search: “models”

GPC: Large-Scale Generative Pretraining for Transferable Motor Control

arXiv:2606.29148v1 Announce Type: cross Abstract: Developing controllers capable of completing a wide range of tasks in a natural and life-like manner is a key challenge in enabling practical applicat

Granular-ball computing: an efficient, robust, and interpretable adaptive multi-granularity representation and computation method

DGX agent

arXiv:2304.11171v5 Announce Type: replace-cross Abstract: To overcome the limitations of point-based inputs, overly fine computation and limited adaptability in existing artificial intelligence method

researcharxiv-cs-ai

30 Jun 2026

Ground Truths in Suicide Research: The Current State of AI-Based Suicide Detection in Social Media

arXiv:2606.28334v1 Announce Type: cross Abstract: Recent advances in artificial intelligence (AI) and social media data have led to growing optimism about the ability to detect suicide risk at scale.

HKVLM: Faithful Reasoning Grounding by Binding Language Queries to a Frozen Detector

arXiv:2606.28862v1 Announce Type: new Abstract: Many visual requests -- ``the object to open this bottle'', ``the person not wearing a helmet'' -- require reasoning, not just category matching. Pure o

HTC-SGA Former: A Hybrid Transformer-CNN Network with Self-Guided Attention and a New Boundary-Weighted Adaptive Loss for Coronary DSA Vessel Segmentation

arXiv:2606.29744v1 Announce Type: new Abstract: Accurate coronary Digital Subtraction Angiography (DSA) vessel segmentation is essential for computer-aided diagnosis and treatment planning of coronary

Tutorials

Implementing resilience patterns with Amazon Bedrock and LLM gateway

In this post, you will learn five practical patterns for building resilient generative AI applications on AWS, progressing from native Amazon Bedrock features to multi-model orchestration using an LLM

tutorialsaws-ml-blog

Improving Large-Scale Weakly Supervised ASR by Filtering and Selection

arXiv:2606.28728v1 Announce Type: cross Abstract: Leveraging large-scale weakly supervised datasets is crucial to train robust end-to-end automatic speech recognition (ASR) models. However, such datas

researcharxiv-cs-cl

InsertAnywhere: Geometrically Grounded and Optics-Aware Video Object Insertion

arXiv:2512.17504v2 Announce Type: replace-cross Abstract: Recent advances in diffusion models have enabled impressive video editing capabilities, yet production-grade Video Object Insertion (VOI) rema

Is Muon as good as they say? We looked beyond training speed and found a hidden cost: Muon loses the simplicity bias of older optimizers lik…

Muon optimizer shows faster training speeds compared to traditional optimizers, but analysis reveals it sacrifices the simplicity bias that older optimizers maintain, potentially impacting model gener

safetyjeremy-howard--x

JoyAI-Sim: A Simulation-Enabled Interconversion Toolchain for the Embodied Data Pyramid

arXiv:2606.16776v2 Announce Type: replace Abstract: Generalist robot policies require trustworthy evaluation and robot-usable training data, but both are difficult to scale with physical robots alone.

researcharxiv-cs-ro

Knowing Bias, Doing Better: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement

arXiv:2601.21864v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit social biases that reinforce harmful stereotypes, limiting their safe deployment. Most existing debiasing metho

L2D2-GS: Learning to Densify for Feedforward Dynamic Gaussian Scene Reconstruction

arXiv:2606.29374v1 Announce Type: new Abstract: High-fidelity reconstruction of dynamic urban environments is a cornerstone of autonomous driving simulation and large-scale world modeling. While 3D Ga

safetyarxiv-cs-cv

Latent Actions from Factorized Transition Effects under Agent Ambiguity

arXiv:2606.30544v1 Announce Type: new Abstract: Latent Action Models (LAMs) learn action-like proxies from observation transitions. However, in multi-object or distractor-rich scenes, these visual eff

Tutorials

Learning How to Use Tools, Not Just When: Pattern-Aware Tool-Integrated Reasoning

arXiv:2509.23292v4 Announce Type: replace Abstract: Tool-integrated reasoning (TIR) has become a key approach for improving large reasoning models (LRMs) on complex problems. Prior work has mainly stu

tutorialsarxiv-cs-ai

Learning to Adaptively Allocate Gaussians for Arbitrary-Scale Image Super-Resolution

arXiv:2606.29400v1 Announce Type: cross Abstract: In computer graphics, visual content is continuously warped, zoomed and resampled. This occurs when engines upscale frames, users zoom into 3D scenes,

Learning Where and When: Patch-Based Spatiotemporal Localization in Weakly Supervised Video Anomaly Detection

arXiv:2606.29498v1 Announce Type: new Abstract: Weakly supervised video anomaly detection (WSVAD) has predominantly focused on temporal localization, identifying when anomalies occur while largely neg

Linguistic Firewall: Geometry as Defense in Multi-Agent Systems Routing

arXiv:2606.30555v1 Announce Type: new Abstract: The rapid integration of Large Language Models (LLMs) has driven the evolution of Multi-Agent Systems (MAS), where specialized agents collaborate to exe

LLM agents security duality: a comprehensive survey of self-security and empowered cybersecurity

arXiv:2606.28450v1 Announce Type: cross Abstract: Large language model (LLM) agents are rapidly being integrated into real-world systems. Their autonomy and tool-use capabilities generate substantial

LogiCo: A Unified Framework for Logical and Structural Anomaly Detection

arXiv:2606.28688v1 Announce Type: new Abstract: Current anomaly detection methods primarily focus on structural anomalies, while paying insufficient attention to anomalies that violate logical constra

MALOQ: Massively Accelerated Learning of Operators for Quantum Transport

arXiv:2606.28911v1 Announce Type: new Abstract: Machine-learned (ML) operator models can be trained to predict density functional theory (DFT) Hamiltonian/density matrices at significantly reduced com

researcharxiv-cs-lg

Masked Diffusion Decoding as x-Prediction Flow

arXiv:2606.29066v1 Announce Type: new Abstract: Masked diffusion language models (MDLMs) generate text by iteratively unmasking tokens, but their standard decoder reduces each step to a binary action:

safetyarxiv-cs-cl

MeEvo: Metacognitive Evolution Combined with Natural Evolution for Automatic Heuristic Design

arXiv:2606.14202v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have advanced Automatic Heuristic Design (AHD) by enabling heuristic generation through reasoning and code synthe

Memory as an Attack Surface in LLM Agents: A Study on Multiple-Choice Question Answering

arXiv:2606.29030v1 Announce Type: new Abstract: AI agents extend conventional large language model (LLM) applications by integrating language understanding with task execution, external tool use, and

Metric Aggregation Divergence: A Hidden Validity Threat in Agent-Based Policy Optimization and a Contractual Remedy

arXiv:2606.29038v1 Announce Type: cross Abstract: Metric aggregation divergence (MAD) is the silent inconsistency that arises when distinct pipeline stages in an agent-based model coupled with a multi

MIRROR: Aligning Semantic Relations from Language to Image via Gromov--Wasserstein

arXiv:2606.29462v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) inherit rich relational priors from their language backbones, yet often fail when asked to apply these relation

safetyarxiv-cs-cv

Miti360: A Comprehensive Dataset for Improved Reforestation Monitoring

arXiv:2606.29447v1 Announce Type: new Abstract: Over the past decade, interest in applying machine learning (ML) to automate forest monitoring has grown significantly. However, existing training datas

Mixture of Debaters: Learn to Debate at Architectural Level in Multi-Agent Reasoning

arXiv:2606.29425v1 Announce Type: new Abstract: Existing multi-agent debate frameworks suffer from two critical limitations: they rely on static architectures where agent roles and coordination patter

local-aiarxiv-cs-ai

NaLA: A 3D Native LLM Layout Agent for High-quality 3D Scene Generation

arXiv:2606.29395v1 Announce Type: new Abstract: Recently, Large Language Models (LLMs) have emerged as promising layout agents for 3D scene generation. Existing layout agents still suffer from implaus

agentsarxiv-cs-cv

PHF: Privileged Hidden Flow for On-Policy Self-Distillation

arXiv:2606.29340v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) trains a reasoning model on rollouts sampled from its own policy by matching a privileged teacher that also sees veri

Preserving Fairness and Safety in Quantized LLMs Through Critical Weight Protection

arXiv:2601.12033v2 Announce Type: replace Abstract: Quantization is widely adopted to reduce the computational cost of large language models (LLMs); however, its implications for fairness and safety,

safetyarxiv-cs-cl

Preventing Error Propagation in Multi-Agent AI through Runtime Monitoring

arXiv:2606.29026v1 Announce Type: new Abstract: Multi-agent AI systems can improve answer selection by allowing different language models to exchange reasoning traces, revise initial predictions, and

Projection-based coupling of infrared thermography and stereocorrelation-based digital image correlation

arXiv:2606.28905v1 Announce Type: new Abstract: Full-field measurement techniques such as digital image correlation and infrared thermography are prevalent in experimental solid mechanics. Digital ima

Propagation of~Interval Belief Structures and~Imprecise Copulas for~Neural Network Verification

arXiv:2606.30105v1 Announce Type: new Abstract: Quantitative verification of neural networks requires reasoning about probabilities under substantial uncertainty in both input distributions and their

ProSpec RL: Plan Ahead, then Execute

arXiv:2407.21359v2 Announce Type: replace-cross Abstract: Imagining potential outcomes of actions before execution helps agents make more informed decisions, a prospective thinking ability fundamental

PS-MOT: Cultivating Instance Awareness from Point Seeds for Multi-Object Tracking

arXiv:2606.30476v1 Announce Type: new Abstract: We introduce Point-supervised Multi-Object Tracking (PS-MOT) as a cost-effective alternative to traditional bounding box supervision, shifting the focus

PS-PPO: Prefix-Sampling PPO for Critic-Free RLHF

arXiv:2606.29758v1 Announce Type: cross Abstract: Reinforcement Learning from Human Feedback (RLHF) for Large Language Models increasingly relies on critic-free methods as a practical alternative to a

RainODE: Continuous-Time Precipitation Forecasting with Latent Neural ODEs

arXiv:2606.29855v1 Announce Type: new Abstract: In precipitation forecasting, not only accuracy but also temporal resolution is critical. However, increasing temporal resolution is constrained by obse

ReactiveBFM: Reactive Closed-Loop Motion Planning Towards Universal Humanoid Whole-Body Control

arXiv:2606.30362v1 Announce Type: cross Abstract: While current Behavior Foundation Models (BFMs) provide robust control priors for humanoids, they only execute pre-defined reference motions. As a res

Applications

RefGlass-GS: A UAV-Enabled Fusion Framework for Photorealistic, Semantic and Interactive Digitization of Reflective Glass Facades via Gaussian Splatting

arXiv:2606.28826v1 Announce Type: new Abstract: Existing digitization of buildings with reflective glass facades suffers from geometric reconstruction distortion, unrealistic view-dependent texture re

applicationsarxiv-cs-cv

Reproducing FACTER: Fairness via Conformal Thresholding and Prompt Repair

arXiv:2606.28620v1 Announce Type: cross Abstract: Fayyazi et al. (2025) recently proposed FACTER, a model-agnostic framework designed to jointly enforce fairness and statistical coverage in LLM-based

safetyarxiv-cs-lg

Robust Zero-shot Anomaly Detection under Limited Auxiliary Anomaly Priors

arXiv:2606.29428v1 Announce Type: new Abstract: Zero-shot anomaly detection aims to identify defects in arbitrary novel domains; however, existing models assume that the auxiliary data contains a rich

safetyarxiv-cs-cv

SA-VIS: Sparse frame Annotations for training Video Instance Segmentation

arXiv:2606.20140v2 Announce Type: replace Abstract: Recent online video instance segmentation (VIS) methods have achieved impressive results, thus becoming the preferred approach to segment instances

Same Concept, Different Directions: Cross-Modal Feature Heterogeneity in Sparse Autoencoders

arXiv:2606.29888v1 Announce Type: cross Abstract: Vision-language models map images and text into a joint embedding space. However, these embeddings often entangle multiple semantic features, which li

Sample-Efficient Learning of Probabilistic Causes for Reachability in Markov Decision Processes with Probabilistic Guarantees

arXiv:2606.29681v1 Announce Type: new Abstract: Probabilistic model checking for Markov decision processes (MDPs) provides quantitative guarantees, but often offers limited insight into why undesired

SARLO-80: Worldwide Slant SAR Language Optic Dataset 80cm

arXiv:2606.20523v2 Announce Type: replace-cross Abstract: Multimodal foundation models have advanced rapidly thanks to large optical benchmarks, but comparable resources for synthetic aperture radar (

Tutorials

ScaleErasure: Inference-Time Minimal Intervention for Precise Concept Erasure in Next-Scale Autoregressive Image Generation

arXiv:2606.29282v1 Announce Type: new Abstract: Concept erasure aims to prevent image generative models from producing unsafe content while preserving their general generative capability. Meanwhile, n

tutorialsarxiv-cs-cv

Applications

Schema-First Retrieval: Embedding Catalogs for Natural Language Analytics

arXiv:2606.28387v1 Announce Type: cross Abstract: Enterprise text-to-SQL systems often fail before SQL is generated: the model receives the wrong schema context. Modern warehouses contain thousands of

applicationsarxiv-cs-ai

See Only When Needed: Context-Aware Attention Intervention for Mitigating Hallucinations in LVLMs

arXiv:2606.29847v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) excel at multimodal tasks but remain prone to object hallucinations. Prior training-free remedies often uniformly s