Search: “models”

Predictive Maps of Multi-Agent Reasoning: A Successor-Representation Spectrum for LLM Communication Topologies

arXiv:2605.11453v1 Announce Type: cross Abstract: Practitioners deploying multi-agent large language model (LLM) systems must currently choose between communication topologies such as chain, star, mes

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Research

Principle-Guided Supervision for Interpretable Uncertainty in Medical Image Segmentation

DGX agent

arXiv:2605.10984v1 Announce Type: new Abstract: Uncertainty quantification complements model predictions by characterizing their reliability, which is essential for high-stakes decision making such as

researcharxiv-cs-cv

13 May 2026

RACC: Representation-Aware Coverage Criteria for LLM Safety Testing

arXiv:2602.02280v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) face severe safety risks from jailbreak attacks, yet current safety testing largely relies on static datasets and

Robust Biomedical Publication Type and Study Design Classification with Knowledge-Guided Perturbations

arXiv:2605.11502v1 Announce Type: new Abstract: Accurately and consistently indexing biomedical literature by publication type and study design is essential for supporting evidence synthesis and knowl

researcharxiv-cs-cl

SI-Diff: A Framework for Learning Search and High-Precision Insertion with a Force-Domain Diffusion Policy

arXiv:2605.12247v1 Announce Type: new Abstract: Contact-rich assembly is fundamental in robotics but poses significant challenges due to uncertainties in relative poses, such as misalignments and smal

safetyarxiv-cs-ro

SkillGraph: Skill-Augmented Reinforcement Learning for Agents via Evolving Skill Graphs

arXiv:2605.12039v1 Announce Type: new Abstract: Skill libraries enable large language model agents to reuse experience from past interactions, but most existing libraries store skills as isolated entr

Smart moves: Building resilient transportation systems with Google AI

What does transportation mean to you? For some, it’s making sure the train is on schedule so they can get to work on time. Maybe it’s making sure you have time connecting between flights. Maybe it’s a

safetygoogle-cloud-ai

Sobolev Regularized MMD Gradient Flow

arXiv:2605.11884v1 Announce Type: new Abstract: We propose Sobolev-regularized Maximum Mean Discrepancy (SrMMD) gradient flow, a regularized variant of maximum mean discrepancy (MMD) gradient flow bas

SRG: Score-based Relaxation-guided Generation for Mixed Integer Linear Programming

arXiv:2603.24033v2 Announce Type: replace Abstract: We propose Score-based Relaxation-guided Generation (SRG), a generative framework based on an approximate formulation of relaxation-guided stochasti

Tackling Fake Forgetting through Uncertainty Quantification

arXiv:2501.19403v3 Announce Type: replace Abstract: Machine unlearning seeks to remove the influence of specified data from a trained model. While the unlearning accuracy provides a widely used metric

Taming Extreme Tokens: Covariance-Aware GRPO with Gaussian-Kernel Advantage Reweighting

arXiv:2605.11538v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has emerged as a promising approach for improving the reasoning capabilities of large language models. However

Taming Score-Based Denoisers in ADMM: A Convergent Plug-and-Play Framework

arXiv:2603.10281v3 Announce Type: replace-cross Abstract: While score-based generative models have emerged as powerful priors for solving inverse problems, directly integrating them into optimization

The Algorithmic Caricature: Auditing LLM-Generated Political Discourse Across Crisis Events

arXiv:2605.12452v1 Announce Type: new Abstract: Large Language Models (LLMs) can generate fluent political text at scale, raising concerns about synthetic discourse during crises and social conflict.

researcharxiv-cs-cl

The tractability landscape of diffusion alignment: regularization, rewards, and computational primitives

arXiv:2605.11361v1 Announce Type: new Abstract: Inference-time reward alignment asks how to turn a pre-trained diffusion model with base law p into a sampler that favors a reward r while remaining clo

Toxicity Detection Should Measure Contextual Harm, Not Text-Intrinsic Badness

arXiv:2503.16072v4 Announce Type: replace-cross Abstract: Toxicity detection has become core safety infrastructure for online moderation, dataset filtering, and deployed language-model systems. Yet mo

Tutorials

UniCustom: Unified Visual Conditioning for Multi-Reference Image Generation

arXiv:2605.12088v1 Announce Type: new Abstract: Multi-reference image generation aims to synthesize images from textual instructions while faithfully preserving subject identities from multiple refere

tutorialsarxiv-cs-cv

UniFixer: A Universal Reference-Guided Fixer for Diffusion-Based View Synthesis

arXiv:2605.12169v1 Announce Type: new Abstract: With the recent surge of generative models, diffusion-based approaches have become mainstream for view synthesis tasks, either in an explicit depth-warp

safetyarxiv-cs-cv

Unlearning with Asymmetric Sources: Improved Unlearning-Utility Trade-off with Public Data

arXiv:2605.11170v1 Announce Type: new Abstract: Noise-based certified machine unlearning currently faces a hard ceiling: the noise magnitude required to certify unlearning typically destroys model uti

Unlocking Compositional Generalization in Continual Few-Shot Learning

arXiv:2605.11710v1 Announce Type: cross Abstract: Object-centric representations promise a key property for few-shot learning: Rather than treating a scene as a single unit, a model can decompose it i

Applications

X-Imitator: Spatial-Aware Imitation Learning via Bidirectional Action-Pose Interaction

arXiv:2605.12162v1 Announce Type: new Abstract: Effectively handling the interplay between spatial perception and action generation remains a critical bottleneck in robotic manipulation. Existing meth

applicationsarxiv-cs-ro

Zero-shot Human Pose Estimation using Diffusion-based Inverse solvers

arXiv:2510.02043v2 Announce Type: replace Abstract: Pose estimation refers to tracking a human's full body posture, including their head, torso, arms, and legs. The problem is challenging in practical

Applications

A Comparative Study of Machine Learning and Deep Learning for Out-of-Distribution Detection

arXiv:2605.10181v1 Announce Type: cross Abstract: Out-of-distribution (OOD) detection is essential for building reliable AI systems, as models that produce outputs for invalid inputs cannot be trusted

applicationsarxiv-cs-ai

A Unified Pair-GRPO Family: From Implicit to Explicit Preference Constraints for Stable and General RL Alignment

arXiv:2605.06375v1 Announce Type: cross Abstract: Large language model (LLM) alignment via reinforcement learning from human preferences (RLHF) suffers from unstable policy updates, ambiguous gradient

local-aiarxiv-cs-ai

Accurate Trajectory Tracking with MPCC for Flapping-Wing MAVs

arXiv:2605.06042v2 Announce Type: replace Abstract: Flapping-wing micro aerial vehicles offer quieter and safer operation than rotary-wing drones, yet achieving precise autonomous control of bird-scal

agentsarxiv-cs-ro

Ace-Skill: Bootstrapping Multimodal Agents with Prioritized and Clustered Evolution

arXiv:2605.08887v1 Announce Type: new Abstract: Self-evolving agents present a promising path toward continual adaptation by distilling task interactions into reusable knowledge artifacts. In practice

agentsarxiv-cs-ai

AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning

arXiv:2410.13181v2 Announce Type: replace Abstract: Recent advancements in large language models (LLMs) have been remarkable. Users face a choice between using cloud-based LLMs for generation quality

local-aiarxiv-cs-cl

Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery

arXiv:2605.08956v1 Announce Type: new Abstract: A growing body of work pursues AI scientists capable of end-to-end autonomous scientific discovery. This position paper argues that although they alread

agentsarxiv-cs-ai

AgentSlimming: Towards Efficient and Cost-Aware Multi-Agent Systems

arXiv:2605.08813v1 Announce Type: new Abstract: Large Language Model-based Multi-Agent Systems (MAS) have demonstrated remarkable capabilities in complex tasks. However, manually designing optimal com

agentsarxiv-cs-lg

Industry

AI security startup Grego AI debuts, claims record $250,000 bounty for AI-found exploit

Artificial intelligence cybersecurity startup Grego AI formally launched today with a claimed method of using existing AI models to find critical software vulnerabilities that human auditors and other

industrysiliconangle

Alignment as Jurisprudence

arXiv:2605.08416v1 Announce Type: new Abstract: Jurisprudence, the study of how judges should properly decide cases, and alignment, the science of getting AI models to conform to human values, share a

safetyarxiv-cs-ai

An Empirical Analysis of Calibration and Selective Prediction in Multimodal Clinical Condition Classification

arXiv:2603.02719v2 Announce Type: replace Abstract: As artificial intelligence systems move toward clinical deployment, ensuring reliable prediction behavior is fundamental for safety-critical decisio

ArchRAG: Attributed Community-based Hierarchical Retrieval-Augmented Generation

arXiv:2502.09891v4 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) has proven effective in integrating external knowledge into large language models (LLMs) for solving ques

Attention Sinks in Diffusion Transformers: A Causal Analysis

arXiv:2605.09313v1 Announce Type: new Abstract: Attention sinks -- tokens that receive disproportionate attention mass -- are assumed to be functionally important in autoregressive language models, bu

safetyarxiv-cs-cv

Attribution-based Explanations for Markov Decision Processes

arXiv:2605.09780v1 Announce Type: new Abstract: Attribution techniques explain the outcome of an AI model by assigning a numerical score to its inputs. So far, these techniques have mainly focused on

Augmented Equivariant Mesh Networks for Anatomical Segmentation

arXiv:2605.08172v1 Announce Type: new Abstract: Anatomical mesh segmentation requires models that operate directly on irregular surface geometry while remaining robust to arbitrary patient pose and me

AxiomOcean: Forecasting the Three-Dimensional Structure of the Upper Ocean

arXiv:2605.10455v1 Announce Type: new Abstract: Short-term ocean forecast skill depends strongly on the three-dimensional ocean structure of the upper ocean, which governs stratification, subsurface h

b9122

local-aillama-cpp-releases

Release b9122 of llama.cpp addresses precision issues for multimodal models through ggml-webgpu, including fixes for GELU functions, flash attention tile implementations, and type conflict resolution.

b9123

local-aillama-cpp-releases

b9123 is a release of llama.cpp created on May 12, 2026 . llama.cpp is an open source software library that performs inference on various large language models such as Llama , providing LLM inference

b9124

local-aillama-cpp-releases

B9124 is a build release from the llama.cpp project, created on May 12, 2026 . Llama.cpp is an open source software library that performs inference on various large language models such as Llama, deve

Benchmarking ResNet Backbones in RT-DETR: Impact of Depth and Regularization under environmental conditions

arXiv:2605.08136v1 Announce Type: cross Abstract: Visual perception plays a central role in competitive robotics, where environmental variations can directly affect real-time detection performance. Th

Beyond Autonomy: A Dynamic Tiered AgentRunner Framework for Governable and Resilient Enterprise AI Execution

arXiv:2605.10223v1 Announce Type: new Abstract: Current large language model agent frameworks prioritize autonomy but lack the governability mechanisms required for enterprise deployment. High-risk wr

safetyarxiv-cs-ai

Beyond Multiple Choice: Evaluating Steering Vectors for Summarization

arXiv:2505.24859v3 Announce Type: replace-cross Abstract: Steering vectors are a lightweight method for controlling text properties by adding a learned bias to language model activations at inference

Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration

arXiv:2605.10195v1 Announce Type: new Abstract: Tree-of-Thought (ToT) reasoning structures Large Language Model (LLM) inference as a tree-based search, demonstrating strong potential for solving compl

BRIDGE: Building Representations In Domain Guided Program Synthesis

arXiv:2511.21104v3 Announce Type: replace Abstract: Large language models can generate plausible code, but remain brittle for formal verification in proof assistants such as Lean. A central scalabilit

BubbleSpec: Turning Long-Tail Bubbles into Speculative Rollout Drafts for Synchronous Reinforcement Learning

arXiv:2605.08862v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has become a cornerstone for improving the performance of Large Language Models (LLMs). However, its rollout phase constit

Budget-Efficient Automatic Algorithm Design via Code Graph

arXiv:2605.10598v1 Announce Type: new Abstract: Large language models (LLMs) have emerged as powerful tools for automatic algorithm design (AAD). However, existing pipelines remain inefficient. They o

safetyarxiv-cs-ai

Can MLLMs Reason About Visual Persuasion? Evaluating the Efficacy and Faithfulness of Reasoning

arXiv:2605.08965v1 Announce Type: new Abstract: Despite strong performance of Multimodal Large Language Models (MLLMs) on multimodal tasks, predicting whether and why an image is persuasive remains ch

Applications

Can We Formally Verify Neural PDE Surrogates? SMT Compilation of Small Fourier Neural Operators

arXiv:2605.08938v1 Announce Type: new Abstract: Fourier Neural Operators (FNOs) can greatly accelerate PDE simulation, but they are often used without formal guarantees that they preserve basic physic

applicationsarxiv-cs-ai