Search: “models”

Automating Cause-Effect Specification with Knowledge Graphs and Large Language Models

arXiv:2606.31614v1 Announce Type: cross Abstract: Engineering specifications such as interlocks, alarm rationalization tables, and cause-and-effect (C&E) matrices remain central to process control and

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CHERRY: Compressed Hierarchical Experts with Recurrent Representational Yield

DGX agent

arXiv:2606.31796v1 Announce Type: cross Abstract: We study three complementary techniques for training compute-efficient language models. (1) Selective supervision and per-token efficiency. Selective

model-releasesarxiv-cs-ai

1 Jul 2026

CLOUDADV: Decision-Aligned Instance Sizing with Zero-Shot Foundation Models under Drift

arXiv:2606.31470v1 Announce Type: new Abstract: Cloud virtual machines are often overprovisioned, creating avoidable cost and operational inefficiency. We present CLOUDADV, an interactive engineer-fac

Dataset Construction for Training LLM to Learn Analog Circuit Knowledge

arXiv:2508.10409v3 Announce Type: replace-cross Abstract: This paper constructs a textual dataset for training large language models (LLMs) to learn analog circuit knowledge and customizes LLM trainin

Hybrid Unet-Transformer Model for Generating Stress and Strain Fields from Composite Geometrics

arXiv:2606.31068v1 Announce Type: new Abstract: Accurate prediction of stress and strain fields in hierarchical composite microstructures is critical for physics-informed material design, yet conventi

LOPA: Enhancing Spoken Language Assessment via Latent Ordinal Prototype Alignment

arXiv:2606.31310v1 Announce Type: new Abstract: Fueled by increasing model scale and multimodal inputs, Multimodal Large Language Models (MLLMs) have emerged as a promising paradigm for Spoken Languag

Moral Safety in LLMs: Exposing Performative Compliance with Puzzled Cues

arXiv:2606.31644v1 Announce Type: new Abstract: As large language models take on morally consequential roles in healthcare, legal, and hiring contexts, we need to examine whether their ethical behavio

Multilingual Polarization Detection Using Transformer-Based Models with Class Weighting and Threshold Tuning

arXiv:2606.30857v1 Announce Type: new Abstract: This paper describes our submission to SemEval-2026 Task 9 on detecting multilingual, multicultural, and multievent online polarization. We address all

researcharxiv-cs-cl

SAMBA: A Scatter-Guided Masked Bidirectional Mamba Foundation Model for SAR Target Recognition

arXiv:2606.31668v1 Announce Type: new Abstract: Synthetic aperture radar automatic target recognition (SAR ATR) is critical for Earth observation and defense, but its practical deployment is constrain

Scaling LLM Inference: Multi-Node KV Cache Offloading with GKE & Managed Lustre

model-releasesgoogle-cloud-ai

Significant contributors to this article include Sneha Aradhey, Software Engineer, Google Kubernetes Engine, and Michael MacDonald, Sr Software Engineer, Google Cloud Managed Lustre. Enterprise produc

Tutorials

ViTL: Temporal Logic-Guided Zero-Shot Natural Language Navigation via Vision-Language Models

arXiv:2606.30696v1 Announce Type: cross Abstract: Enabling robots to follow natural language commands to complete zero-shot long-horizon tasks remains challenging. It requires extracting implicit temp

tutorialsarxiv-cs-cl

A Bayesian latent Gaussian process framework for aerodynamic uncertainty quantification

model-releasesarxiv-cs-lg

arXiv:2606.28871v1 Announce Type: cross Abstract: Predicting the aerodynamic performance (e.g. lift, drag, and moment coefficients) of an aircraft is challenging -- computational models are biased and

Beyond Point Estimates for Glaucoma Visual Field Forecasting with Diffusion Models

arXiv:2606.30417v1 Announce Type: cross Abstract: Forecasting visual fields (VFs) is critical for personalized monitoring and treatment planning in glaucoma. This is inherently uncertain due to hetero

researcharxiv-cs-ai

Beyond Trajectory Matching: Reflow with Marginal Distribution Alignment

model-releasesarxiv-cs-cv

arXiv:2606.29287v1 Announce Type: cross Abstract: Diffusion and continuous-flow generative models achieve high-quality generation, and their deterministic sampling can be formulated as solving learned

Blackknife: Hard-Label Query-Limited Black-Box Attacks on Heterogeneous Graph Neural Networks

model-releasesarxiv-cs-lg

arXiv:2606.29240v1 Announce Type: new Abstract: Heterogeneous graph neural networks (HGNNs) have achieved strong performance in modeling complex graph-structured data with multiple node and relation t

Bricker to BRACE: A Bracket Exposure RAW Dataset and Restoration Model for Flicker-Banding

arXiv:2606.29845v1 Announce Type: new Abstract: Flicker-banding (FB), arises from temporal aliasing between a camera's rolling shutter and a display's brightness modulation, degrading screen-captured

Can LLMs Hire Fairly? Racial Bias in Resume Screening

arXiv:2606.28978v1 Announce Type: new Abstract: We audit fourteen mainstream large language models (LLMs) for hiring discrimination using the paired-resume methodology of Kline, Rose, and Walters (202

Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark Framework

arXiv:2406.08311v3 Announce Type: replace-cross Abstract: Existing evaluations of tabular synthesis models rely primarily on low-order statistics and downstream task performance, leaving multivariate

DrivenMorph: Bridging Attention Mechanism and Variational Image Registration via Difference Modeling

arXiv:2606.30183v1 Announce Type: new Abstract: Medical image registration benefits significantly from deep learning, yet existing approaches often lack physical explainability and fine-grained deform

safetyarxiv-cs-cv

Efficient Spatio-Temporal Grounding with Multimodal Large Models via Second-Level Tracking and RL Verification

arXiv:2606.29023v1 Announce Type: cross Abstract: Spatio-temporal grounding in long videos requires precise temporal localization and robust object tracking conditioned on natural-language queries. Wh

Exploration and Online Transfer with Behavioral Foundation Models

arXiv:2606.29980v1 Announce Type: new Abstract: Zero-shot Transfer in Reinforcement Learning (RL) aims to train an agent that can generate optimal policies for any reward function, without additional

Fast Equivariant Imaging: Accelerating Unsupervised Learning and Model Adaptation via Inexact Splitting

arXiv:2507.06764v5 Announce Type: replace-cross Abstract: In this work, we propose Fast Equivariant Imaging (FEI), a novel unsupervised learning framework to rapidly and efficiently train deep imaging

How LLMs See Creativity: Zero-Shot Scoring of Visual Creativity with Interpretable Reasoning

arXiv:2606.29672v1 Announce Type: new Abstract: Evaluating the originality of visual images poses enduring challenges for creativity assessment. Automated scoring using AI models has proven effective

HSD: Training-Free Acceleration for Document Parsing Vision-Language Models with Hierarchical Speculative Decoding

arXiv:2602.12957v3 Announce Type: replace Abstract: Document parsing is a fundamental task in multimodal understanding, supporting a wide range of downstream applications such as information extractio

KernelSight-LM: A Kernel-Level LLM Inference Simulator

arXiv:2606.28565v1 Announce Type: cross Abstract: As large language models (LLMs) move into production serving, practitioners must rapidly evaluate inference performance across diverse hardware, model

LETT-NeXt: A Lightweight RECIST-Guided Model for 3D CT Lesion Segmentation

arXiv:2606.30108v1 Announce Type: new Abstract: RECIST diameter measurements are widely used for tumor response assessment, but they provide only a limited 2D description of lesion extent. We present

Multimodal Large Language Model driven Radiology Report Generation with Clinical Knowledge Enhancement

arXiv:2403.06728v2 Announce Type: replace Abstract: Radiology report generation (RRG) has attracted significant attention due to its potential to reduce the workload of radiologists. The performance o

safetyarxiv-cs-cv

Pessimism's Paradox: Conservative Offline Training Amplifies Reward Hacking During Online Adaptation in Reasoning Models

arXiv:2606.30627v1 Announce Type: cross Abstract: Conservative offline training is widely advocated as a safe foundation for subsequent online adaptation: if a policy stays close to well-supported beh

RADIANT-PET: Reasoning-Augmented PET/CT Lesion Segmentation with Large Language Models and Reinforcement Learning

arXiv:2606.28392v1 Announce Type: cross Abstract: Accurate lesion segmentation in PET/CT is critical for oncology, yet remains challenging because physiologic tracer uptake and artifacts can mimic mal

SA-VLA: State-aware tokenizer for improving Vision-Language-Action Models' performance

arXiv:2606.30113v1 Announce Type: cross Abstract: Discrete action tokenization provides a compact interface for autoregressive VLA policies, but accurately recovering continuous robot actions from dis

Scaling the Horizon, Not the Parameters: Reaching Trillion-Parameter Performance with a 35B Agent

arXiv:2606.30616v1 Announce Type: new Abstract: We introduce Agents-A1, a 35B Mixture-of-Experts Agentic Model that reaches trillion-parameter-level performance by scaling the agent horizon. We invest

Solver-Verified Formulation Generation and Selection for Multi-Warehouse Inventory Allocation Using Large Language Models

arXiv:2606.29366v1 Announce Type: cross Abstract: Balance-oriented multi-warehouse inventory allocation is a recurring decision problem in large-scale e-commerce supply chains, in which a fixed replen

applicationsarxiv-cs-ai

SUMO: Segment and Track Any Motion with Nonlinear State Space Models

arXiv:2606.29861v1 Announce Type: cross Abstract: Visual Object Tracking (VOT) and Moving Object Segmentation (MOS) are two fundamental tasks in computer vision that involve both spatial and temporal

applicationsarxiv-cs-ai

The Complexity Ceiling Benchmark: A Multi-Domain Evaluation of Sequential Reasoning Under Depth Scaling

arXiv:2606.29278v1 Announce Type: new Abstract: We introduce the Complexity Ceiling Benchmark (CCB), a controlled evaluation of how language-model reasoning decays as the number of required sequential

Agents

The Emergence of Autonomous Penetration Capabilities in Large Language Model-Powered AI Systems

arXiv:2606.13079v2 Announce Type: replace-cross Abstract: Nowadays, the autonomous execution of cyberattacks capable of causing substantial real-world harm is widely regarded as one of the critical re

agentsarxiv-cs-ai

Unified Complex-valued Neural Network: A Magnitude-Phase Computational Model for Event-Driven Neuromorphic Learning

arXiv:2606.29099v1 Announce Type: cross Abstract: Artificial neural networks (ANN) provide accurate continuous-valued representation, whereas spiking neural networks (SNN) offer event-driven temporal

EchoSonar-R: A Multi-View Reasoning-Enabled Model for Disease Classification and Report Generation in Echocardiography

arXiv:2606.28164v1 Announce Type: new Abstract: Echocardiography is the most widely used non-invasive cardiac imaging modality, providing essential information for cardiovascular diagnosis. Interpreti

safetyarxiv-cs-cv

HumanMoveVQA: Can Video MLLMs reason about human movement in videos?

model-releasesarxiv-cs-cv

arXiv:2606.27999v1 Announce Type: new Abstract: Despite the rapid advance of Multimodal Large Language Models (MLLMs) in high-level video understanding, a fundamental bottleneck remains: these models

Learning Complementary Action Modeling from Automotive Maintenance Instructions

arXiv:2606.27808v1 Announce Type: new Abstract: A minute lexical variation can reverse the procedural meaning of an instruction even when the rest of the sentence remains unchanged. In automotive main

researcharxiv-cs-cl

Non-Linear Model-Based Sequential Decision-Making in Agriculture

arXiv:2509.01924v4 Announce Type: replace-cross Abstract: Agricultural decision-making faces a dual challenge: sustaining high yields to meet global food security needs while reducing the environmenta

applicationsarxiv-cs-lg

On the Inseparability of Instructions and Data in Shared-Embedding Sequence Models

arXiv:2606.27567v1 Announce Type: cross Abstract: Prompt injection is the top security risk for LLM-integrated applications, yet every defense proposed so far has been broken. We prove this is not a c

A Pipeline for Generating Longitudinal Synthetic Clinical Notes Using Large Language Models

arXiv:2606.26879v1 Announce Type: new Abstract: Synthetic data is increasingly used to enable the development and evaluation of AI systems in domains where access to real-world data is restricted. In

applicationsarxiv-cs-ai

Automating Potential-based Reward Shaping with Vision Language Model Guidance

arXiv:2606.27180v1 Announce Type: cross Abstract: Sparse rewards are inherently challenging for reinforcement learning agents as they lack intermediate feedback to guide exploration and to correctly a

Charting the Growth of Social-Physical HRI (spHRI): A Systematic Review Pipeline Augmented by Small Language Models

arXiv:2606.26382v1 Announce Type: cross Abstract: Social-physical human-robot interaction (spHRI) has grown rapidly across robotics, human-computer interaction, human-robot interaction, and haptics. Y

researcharxiv-cs-ai

Embarrassingly Simple Self-Distillation Improves Code Generation

arXiv:2604.01193v2 Announce Type: replace Abstract: Can a large language model (LLM) improve at code generation using only its own raw outputs, without a verifier, a teacher model, or reinforcement le

LLM-based Models for Detecting Emerging Topics in Service Feedback

arXiv:2606.26595v1 Announce Type: new Abstract: Enhancing the analysis of service feedback is essential for public sector organizations, particularly tax administrations, where trust and compliance de

NebulaExp-8B: An Empirical Post-Training Pipeline via Full-Scale Ablation Research

arXiv:2606.26671v1 Announce Type: new Abstract: Post-training alignment determines the reasoning and human preference following capabilities of large language models, yet most existing works withhold

OpenAI unveils GPT-5.6 amid US AI regulatory drama

model-releasesthe-verge-ai

Less than 24 hours after news broke that OpenAI would stagger its next model release at the request of the Trump administration, that model, GPT-5.6, is here. On Friday, the company unveiled the limit