Search: “models”

ReCrit: Transition-Aware Reinforcement Learning for Scientific Critic Reasoning

arXiv:2605.18799v1 Announce Type: cross Abstract: Large language models can fail in critic interaction not only by answering incorrectly, but also by abandoning an initially correct scientific solutio

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Agents

Robust Checkpoint Selection for Multimodal LLMs via Agentic Evaluation and Stability-Aware Ranking

DGX agent

arXiv:2605.18852v1 Announce Type: cross Abstract: Checkpoint selection for multimodal large language models (MLLMs) presents significant challenges when performance differentials are marginal and eval

agentsarxiv-cs-ai

20 May 2026

SafeAlign-VLA: A Negative-Enhanced Safe Alignment Framework for Risk-Aware Autonomous Driving

arXiv:2605.19524v1 Announce Type: cross Abstract: End-to-end autonomous driving systems excel in common scenarios but struggle with safety-critical long-tail cases. Vision-Language-Action (VLA) models

safetyarxiv-cs-cv

Self-Creative Text-to-Object Generation using Semantic-Aware Spatial Weighting

arXiv:2605.19554v1 Announce Type: new Abstract: Instilling creativity in text-to-image (T2I) generation presents a significant challenge, as it requires synthesized images to exhibit not only visual n

safetyarxiv-cs-cv

Slot-MLLM: Object-Centric Visual Tokenization for Multimodal LLM

arXiv:2505.17726v3 Announce Type: replace-cross Abstract: Recently, multimodal large language models (MLLMs) have emerged as a key approach in achieving artificial general intelligence. In particular,

Stage-adaptive Token Selection for Efficient Omni-modal LLMs

arXiv:2605.20035v1 Announce Type: new Abstract: Omni-modal large language models (om-LLMs) achieve unified audio-visual understanding by encoding video and audio into temporally aligned token sequence

STRIDE: Learnable Stepwise Language Feedback for LLM Reasoning

arXiv:2605.18851v1 Announce Type: new Abstract: Recent advances in Reinforcement Learning (RL) have underscored its potential for incentivizing reasoning capabilities of Large Language Models (LLMs).

local-aiarxiv-cs-lg

Structural Energy Guidance for View-Consistent Text-to-3D Generation

arXiv:2605.19876v1 Announce Type: new Abstract: Text-to-3D generation based on diffusion models often suffers from the Janus problem, leading to inconsistent geometry across viewpoints. This work iden

safetyarxiv-cs-cv

The Insurability Frontier of AI Risk: Mapping Threats to Affirmative Coverage, Silent Exposures, and Exclusions

arXiv:2605.18784v1 Announce Type: cross Abstract: The rapid diffusion of agentic AI has created a new coverage problem for commercial insurance: some AI-mediated losses are now affirmatively insured,

TORQ: Two-Level Orthogonal Rotation for MXFP4 Quantization

arXiv:2605.19561v1 Announce Type: cross Abstract: As Large Language Models (LLMs) advance toward practical deployment, the Microscaling FP4 (MXFP4) format has emerged as a cornerstone for next-generat

Toward Training Superintelligent Software Agents through Self-Play SWE-RL

arXiv:2512.18552v2 Announce Type: replace-cross Abstract: While current software agents powered by large language models (LLMs) and agentic reinforcement learning (RL) can boost programmer productivit

Towards LLM-Assisted Architecture Recovery for Real-World ROS~2 Systems: An Agent-Based Multi-Level Approach to Hierarchical Structural Architecture Reconstruction

arXiv:2605.20055v1 Announce Type: cross Abstract: Explicit software architecture models are essential artifacts for communicating, analyzing, and evolving complex software-intensive systems. In ROS~2-

Trust It or Not: Evidential Uncertainty for Feed-Forward 3D Reconstruction with Trust3R

arXiv:2605.19539v1 Announce Type: new Abstract: Geometric foundation models hold promise for unconstrained dense geometry prediction from uncalibrated images. However, in current feed-forward designs,

Trustworthy Agent Network: Trust in Agent Networks Must Be Baked In, Not Bolted On

arXiv:2605.19035v1 Announce Type: new Abstract: The rapid advancement of Large Language Models has given rise to autonomous LLM-based agents capable of complex reasoning and execution. As these agents

TSR: Trajectory-Search Rollouts for Multi-Turn RL of LLM Agents

arXiv:2602.11767v3 Announce Type: replace Abstract: Advances in large language models (LLMs) are driving a shift toward using reinforcement learning (RL) to train agents from iterative, multi-turn int

WBCAtt+: Fine-Grained Pixel-Level Morphological Annotations for White Blood Cell Images

arXiv:2605.19692v1 Announce Type: new Abstract: The microscopic examination of white blood cells (WBCs) plays a fundamental role in pathology and is essential for diagnosing blood disorders such as le

What Really Improves Mathematical Reasoning: Structured Reasoning Signals Beyond Pure Code

arXiv:2605.19762v1 Announce Type: new Abstract: Code has become a standard component of modern foundation language model (LM) training, yet its role beyond programming remains unclear. We revisit the

When to Stop Reusing: Dynamic Gradient Gating for Sample-Efficient RLVR

arXiv:2605.19425v1 Announce Type: cross Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become the dominant paradigm for advanced reasoning in Large Language Models (LLMs), but rol

A neurosymbolic Approach with Epistemic Deep Learning for Hierarchical Image Classification

arXiv:2605.16383v1 Announce Type: cross Abstract: Deep neural networks achieve high accuracy on image classification tasks. Yet, they often produce overconfident predictions as which fail to express e

Accelerating AI-Powered Research: The PuppyChatter Framework for Usable and Flexible Tooling

arXiv:2605.17809v1 Announce Type: new Abstract: This research addresses the challenges inherent in developing Artificial Intelligence (AI) applications, particularly those leveraging Large Language Mo

Activation Steering with a Feedback Controller

arXiv:2510.04309v3 Announce Type: replace Abstract: Controlling the behaviors of large language models (LLM) is fundamental to their safety alignment and reliable deployment. However, existing steerin

safetyarxiv-cs-lg

Agentic Pipeline for Self-Synchronized Multiview Joint Angle Monitoring in Uncalibrated Environments

arXiv:2605.16419v1 Announce Type: cross Abstract: Kinematic monitoring plays a critical role in long-term rehabilitation for patients with spinal cord injury (SCI), where multi-view markerless motion

ALIGN: A Vision-Language Framework for High-Accuracy Accident Location Inference through Geo-Spatial Neural Reasoning

arXiv:2511.06316v3 Announce Type: replace Abstract: In low- and middle-income countries, public safety and urban planning initiatives frequently face a critical shortage of accurate, location-specific

AMATA: Adaptive Multi-Agent Trajectory Alignment for Knowledge-Intensive Question Answering

arXiv:2605.17352v1 Announce Type: new Abstract: Despite substantial advances in large language models (LLMs), generating factually consistent responses for knowledge-intensive question answering remai

safetyarxiv-cs-cl

AMR-SD: Asymmetric Meta-Reflective Self-Distillation for Token-Level Credit Assignment

arXiv:2605.18529v1 Announce Type: new Abstract: The alignment of Large Language Models (LLMs) for complex reasoning heavily relies on Reinforcement Learning with Verifiable Rewards (RLVR). However, st

An AI system to help scientists write expert-level empirical software

arXiv:2509.06503v2 Announce Type: replace Abstract: The cycle of scientific discovery is frequently bottlenecked by the slow, manual creation of software to support computational experimentsite{hannay

Applications

An Analytical Multiple Criteria Framework for Temporal and Dynamic Business-to-Business Customer Segmentation in Manufacturing

arXiv:2605.17151v1 Announce Type: new Abstract: In sales and marketing, customer segmentation is an important tool for formulating strategies for customer treatment and supply chain management. Most s

applicationsarxiv-cs-lg

AnchorDiff: Topology-Aware Masked Diffusion with Confidence-based Rewriting for Radiology Report Generation

arXiv:2605.17071v1 Announce Type: new Abstract: Radiology report generation (RRG) aims to automatically produce clinically accurate textual reports from medical images. Existing methods predominantly

Are Sparse Autoencoder Benchmarks Reliable?

arXiv:2605.18229v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) are a core interpretability tool for large language models, and progress on SAE architectures depends on benchmarks that re

Artificial Intelligence can Recognize Whether a Job Applicant is Selling and/or Lying According to Facial Expressions and Head Movements Much More Correctly Than Human Interviewers

arXiv:2605.17461v1 Announce Type: cross Abstract: Whether an interviewee's honest and deceptive responses can be detected by facial expression signals in videos has been debated and requires further r

Attend Locally, Remember Linearly: Linear Attention as Cross-Frame Memory for Autoregressive Video Diffusion

arXiv:2605.16579v1 Announce Type: new Abstract: Autoregressive (AR) video diffusion is a powerful paradigm for streaming and interactive video generation. However, its reliance on softmax self-attenti

local-aiarxiv-cs-cv

Beyond Scaling: Agents Are Heading to the Edge

arXiv:2605.18535v1 Announce Type: new Abstract: The bottleneck of useful agentic intelligence has shifted from compressing world knowledge into a single model to executing a coordinated system. This p

safetyarxiv-cs-lg

Beyond Square Roots: Explicit Memory-Efficient Factorization for Multi-Epoch Private Learning

arXiv:2605.18379v1 Announce Type: new Abstract: Correlated-noise mechanisms are among the most promising approaches for improving the utility of differentially private model training, but rigorous gua

Beyond the Cartesian Illusion: Testing Two-Stage Multi-Modal Theory of Mind under Perceptual Bottlenecks

arXiv:2605.18194v1 Announce Type: new Abstract: While Multi-Modal Large Language Models (MLLMs) demonstrate impressive capabilities in general reasoning, their embodied spatial intelligence remains ha

Bi-Level Chaotic Fusion Based Graph Convolutional Network for Stock Market Prediction Interval

arXiv:2605.16324v1 Announce Type: new Abstract: Financial market forecasting is inherently uncertain, yet most deep learning approaches rely on point predictions that provide only single-value estimat

Body-Grounded Perspective Formation and Conative Attunement in Artificial Agents

arXiv:2605.16728v1 Announce Type: new Abstract: This paper proposes a minimal architecture for body-grounded perspective formation in artificial agents. Extending prior work, the model introduces an i

Byzantine-Resilient Federated Learning via QUBO-Based Client Selection on Quantum Annealers

arXiv:2605.16438v1 Announce Type: cross Abstract: Federated Learning (FL) trains a global model across decentralized clients while preserving data privacy, but at scale it is vulnerable to malicious u

Capturing LLM Capabilities via Evidence-Calibrated Query Clustering

arXiv:2605.17110v1 Announce Type: new Abstract: Query clustering organizes queries into groups that reflect shared latent capability demands, enabling capability-aware LLM evaluation. Existing cluster

CheckSupport: A Local LLM-Powered Tool for Automated Manuscript Submission Checklist Selection and Completion

arXiv:2605.16377v1 Announce Type: cross Abstract: Transparent and standardized reporting is essential for reproducible scientific research, yet adherence to reporting guidelines remains inconsistent b

CodeBind: Decoupled Representation Learning for Multimodal Alignment with Unified Compositional Codebook

arXiv:2605.18257v1 Announce Type: cross Abstract: Multimodal representation alignment is pivotal for large language models and robotics. Traditional methods are often hindered by cross-modal informati

Computational Challenges in Token Economics: Bridging Economic Theory and AI System Design

arXiv:2605.17410v1 Announce Type: new Abstract: Token economics has emerged as a useful lens for understanding resource allocation, value creation, and pricing in large language model systems. While r

CORAL: Towards Autonomous Multi-Agent Evolution for Open-Ended Discovery

arXiv:2604.01658v2 Announce Type: replace Abstract: Large language model (LLM)-based evolution is a promising approach for open-ended discovery, where progress requires sustained search and knowledge

Corruptions of Supervised Learning Problems: Typology and Mitigations

arXiv:2307.08643v4 Announce Type: replace Abstract: Corruption is notoriously widespread in data collection. Despite extensive research, the existing literature predominantly focuses on specific setti

Counterfactual Explanations Under Concept Drift

arXiv:2605.17651v1 Announce Type: new Abstract: Counterfactual explanations (CFEs) provide actionable recourse, but most methods assume a static framework with fixed data and a trained classifier. Thi

Hardware

DashAttention: Differentiable and Adaptive Sparse Hierarchical Attention

arXiv:2605.18753v1 Announce Type: cross Abstract: Current hierarchical attention methods, such as NSA and InfLLMv2, select the top-k relevant key-value (KV) blocks based on coarse attention scores and

hardwarearxiv-cs-ai

Decoupling Motion and Geometry in 4D Gaussian Splatting

arXiv:2603.00952v2 Announce Type: replace Abstract: High-fidelity reconstruction of dynamic scenes is an important yet challenging problem. While recent 4D Gaussian Splatting (4DGS) has demonstrated t

Dexora: Open-source VLA for High-DoF Bimanual Dexterity

arXiv:2605.18722v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently become a central direction in embodied AI, but current systems are restricted to either dual-gripper c

safetyarxiv-cs-ro

Domain Incremental Learning for Pandemic-Resilient Chest X-Ray Analysis

arXiv:2605.17729v1 Announce Type: cross Abstract: Deep learning models achieved high accuracy in pneumonia detection from chest X-rays. However, their generalization across clinical domains remains li