All entries

SafeHarbor: Hierarchical Memory-Augmented Guardrail for LLM Agent Safety

arXiv:2605.05704v2 Announce Type: replace-cross Abstract: Recent advances in foundation models have transformed LLMs from passive conversational systems into autonomous agents capable of reasoning and

safetyarxiv-cs-ai

Same Model, Different Weakness: How Language and Modality Reshape the Jailbreak Attack Surface in Frontier MLLMs

DGX agent

arXiv:2605.23157v1 Announce Type: new Abstract: The attack surface of a multimodal large language model (MLLM) is language-dependent in ways that reveal the mechanistic structure of alignment failures

model-releasesarxiv-cs-cl

25 May 2026

Sample-wise Targeted Adversarial Attacks on Test-time Adaptation

arXiv:2605.23411v1 Announce Type: cross Abstract: Test-time adaptation (TTA) effectively counters distribution shifts but exposes models to adversarial manipulation via the unlabeled test stream. Exis

safetyarxiv-cs-cv

Scalable Heterogeneous Graph Foundation Models for Data-Driven Optimal Power Flow in Smart Grids

arXiv:2605.23194v1 Announce Type: cross Abstract: Fast and reliable optimal power flow (OPF) approximation is essential for reliable smart-grid operation, yet many learning-based surrogates either fla

Scaling-Aware Adapter for Structure-Grounded LLM Reasoning

arXiv:2602.02780v3 Announce Type: replace Abstract: Large language models (LLMs) are enabling reasoning over 2D and 3D structures, yet existing methods remain modality-specific and typically compress

Agents

Scene Reconstruction as Mapping Priors for 3D Detection

arXiv:2605.22997v1 Announce Type: new Abstract: In autonomous driving, mapping is critical for motion planning but remains an under-utilized resource for perception tasks such as 3D object detection.

agentsarxiv-cs-cv

SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research

arXiv:2605.22878v1 Announce Type: new Abstract: The exponential growth of global academic output has confronted researchers and AI agents with an unprecedented ``information explosion,'' where fragmen

SciHorizon-GENE: Benchmarking LLM for Life Sciences Inference from Gene Knowledge to Functional Understanding

arXiv:2601.12805v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown growing promise in biomedical research, particularly for knowledge-driven interpretation tasks. Howeve

SciNet: Evaluating AI Agents in Relation-Aware Scientific Literature Retrieval

arXiv:2601.03260v2 Announce Type: replace-cross Abstract: AI agents have seen widespread adoption in information retrieval for scientific research, giving rise to tools such as Deep Research. However,

researcharxiv-cs-cl

Local Ai

SCOPE: Simulating Cross-game Operations in Playable Environments for FPS World Models

arXiv:2605.23345v1 Announce Type: new Abstract: Interactive world models for first-person shooter (FPS) games must resolve high-frequency overlapping control signals at every frame without disrupting

local-aiarxiv-cs-cv

Score-Based One-step MeanFlow Policy Optimization

arXiv:2605.23365v1 Announce Type: cross Abstract: Diffusion and flow matching have emerged as expressive policy classes in reinforcement learning, but their reliance on multi-step denoising imposes su

safetyarxiv-cs-ai

SCRIPT: Scalable Diffusion Policy with Multi-stage Training for Language-driven Physics-Based Humanoid Control

arXiv:2605.22894v1 Announce Type: cross Abstract: Controlling physics-based humanoids from natural-language instructions is a critical step toward general-purpose embodied agents. However, existing me

safetyarxiv-cs-lg

Searching X in Grok Build is really fast and useful for research/docs/real-time info, video is not sped up

Searching X in Grok Build is really fast and useful for research/docs/real-time info, video is not sped up Media I've been using Grok Build some time now, and it has genuinely surprised me. It is uniq

industryelon-musk--x

Security of LLM-generated Code: A Comparative Analysis

arXiv:2605.23091v1 Announce Type: cross Abstract: The majority of software developers use or are planning to use Artificial Intelligence (AI) tools in their development processes. Their top reasons in

applicationsarxiv-cs-ai

SeedER: Seed-and-Expand Retrieval from Knowledge Graphs

arXiv:2605.23753v1 Announce Type: new Abstract: Knowledge graphs (KGs) offer a rich representation for relational knowledge, but their irregular structure makes retrieval challenging: ego-graph expans

safetyarxiv-cs-lg

Seeing without Looking: Do Vision-Language Benchmarks Really Test Vision?

arXiv:2605.22903v1 Announce Type: cross Abstract: Benchmark accuracy is often implicitly assumed to reflect grounded visual understanding in vision-language models (VLMs), yet it remains unclear to wh

SEG-JPEG: Simple Visual Semantic Communications for Remote Operation of Automated Vehicles over Unreliable Wireless Networks

arXiv:2602.15258v2 Announce Type: replace Abstract: Remote Operation is touted as being key to the rapid deployment of automated vehicles. Streaming imagery to control connected vehicles remotely curr

applicationsarxiv-cs-ro

Selective Ambulance Dispatch Under Contextual Travel-Time Uncertainty

arXiv:2605.23378v1 Announce Type: cross Abstract: Ambulance response is time-critical in out-of-hospital cardiac arrest (OHCA), where dispatchers must balance timely arrivals with limited fleet capaci

Self-Improving In-Context Learning

arXiv:2605.23180v1 Announce Type: new Abstract: We propose to improve in-context learning (ICL) by optimizing the continuous embeddings of a fixed few-shot prompt at test time. The key observation is

researcharxiv-cs-cl

Self-supervised Adversarial Purification for Graph Neural Networks

arXiv:2605.23239v1 Announce Type: new Abstract: Defending Graph Neural Networks (GNNs) against adversarial attacks requires balancing accuracy and robustness, a trade-off often mishandled by tradition

Semantic-Aware Guided Drone Exploration for Language-Conditioned 3D Indoor Mapping

arXiv:2605.23160v1 Announce Type: cross Abstract: We present Semantic-Aware Guided Exploration, SAGE, a system for open-vocabulary exploration in unknown 3D indoor environments that preserves coverage

applicationsarxiv-cs-cv

Semantically Structured Mixture-of-Experts for Compositional Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2605.23477v1 Announce Type: new Abstract: Diffusion-based policies have established a new standard for precise robotic manipulation but face a critical scalability bottleneck: high-performance m

SemEval-2026 Task 6: CLARITY -- Unmasking Political Question Evasions

model-releasesarxiv-cs-cl

arXiv:2603.14027v2 Announce Type: replace Abstract: Political speakers often avoid answering questions directly while maintaining the appearance of responsiveness. Despite its importance for public di

Agents

SFG-ROS: A Resource-Aware Framework for Dense Multi-Agent Perception

arXiv:2605.23832v1 Announce Type: new Abstract: Deploying heterogeneous multi-agent robot fleets for collaborative perception requires robust data exchange and scalable software architectures. However

agentsarxiv-cs-ro

Signal Temporal Logic Motion Planning via Graphs of Convex Sets

arXiv:2605.23240v1 Announce Type: new Abstract: This paper investigates continuous-time motion planning under Signal Temporal Logic (STL) specifications. The goal is to generate smooth robot trajector

researcharxiv-cs-ro

SimInsert: Seamless Video Object Insertion via Regional Sparse Attention Fusion

arXiv:2605.23245v1 Announce Type: cross Abstract: Video object insertion requires ensuring spatio-temporal coherence and interactive realism, extending far beyond simple content placement. However, cu

SkillOpt: Executive Strategy for Self-Evolving Agent Skills

arXiv:2605.23904v1 Announce Type: new Abstract: Agent skills today are hand-crafted, generated one-shot, or evolved through loosely controlled self-revision, none of which behaves like a deep-learning

SLIP-RS: Structured-Attribute Language-Image Pre-Training for Remote Sensing Object Detection

arXiv:2605.23144v1 Announce Type: new Abstract: Existing language-image pre-training for remote sensing object detection is constrained by Monolithic Label Learning, which relies on exhaustively enume

researcharxiv-cs-cv

Smart-Insertion-V: Photorealistic Video Insertion via a Closed-Loop Feedback Dual-Stream Framework

arXiv:2605.23891v1 Announce Type: new Abstract: Mask-free video object insertion has emerged as a challenging task, requiring harmonious integration of reference objects into source videos. However, e

researcharxiv-cs-cv

smdh

smdh Chamath Lays Out the Case for SpaceX at $2 Trillion – Starlink: the most important internet infra project since the internet itself – Rockets: underlying platform that allows everything else to h

safetygary-marcus--x

Smoothed Elicitation Complexity for Approximate Gamma-calibration of Discrete Classification Tasks

arXiv:2605.23017v1 Announce Type: new Abstract: One prominent method of evaluating machine learning model trustworthiness is the notion of calibration. In the binary outcome setting, a probabilistic p

Agents

Socially fluent AI decouples conversational signals from source identity in online interaction

arXiv:2605.23426v1 Announce Type: cross Abstract: Socially fluent agentic AI can now participate in online interaction in ways that resemble ordinary human conversation, potentially weakening people's

agentsarxiv-cs-ai

SoftBank stock jumped 4.6% to a record high on Monday, spurred by hopes of big returns from the company's stakes in OpenAI and SB Energy Corp if they go public (Bloomberg)

Bloomberg: SoftBank stock jumped 4.6% to a record high on Monday, spurred by hopes of big returns from the company's stakes in OpenAI and SB Energy Corp if they go public — SoftBank Group Corp. shares

industrytechmeme

Solving the Aircraft Disassembly Scheduling Problem

arXiv:2605.23592v1 Announce Type: new Abstract: Dismantling aircrafts reaching their end of life is a complex endeavour that is necessary in terms of sustainability but yields small income margins for

Hardware

Sources: Meta, Google, and Amazon execs met Vatican officials on April 29, as part of a quiet lobbying push ahead of Pope Leo XIV's first AI encyclical (Océane Herrero/Politico)

Océane Herrero / Politico: Sources: Meta, Google, and Amazon execs met Vatican officials on April 29, as part of a quiet lobbying push ahead of Pope Leo XIV's first AI encyclical — As Leo XIV prepares

hardwaretechmeme

Sources: Wix is expected to cut ~1,000 jobs in the coming months, or ~20% of its workforce, after weak Q1 earnings and a ~50% collapse of its stock in 2026 (Sophie Shulman/CTech)

Sophie Shulman / CTech: Sources: Wix is expected to cut ~1,000 jobs in the coming months, or ~20% of its workforce, after weak Q1 earnings and a ~50% collapse of its stock in 2026 — The company will r

industrytechmeme

SPACENUM: Revisiting Spatial Numerical Understanding in VLMs

arXiv:2605.23898v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are increasingly deployed in embodied environments, where they need produce numerical outputs such as action magnitudes an

SpaceX put 10 megawatts of solar power in space across 3000 gen1 Starlink satellites, then they put 100 megawatts in space with 7000 gen2. s…

SpaceX put 10 megawatts of solar power in space across 3000 gen1 Starlink satellites, then they put 100 megawatts in space with 7000 gen2. soon, they're doing 1000 megawatts with gen3. SpaceX is basic

industrydavid-holz--x

Sparse Autoencoders Map Brain-LLM Alignment onto Cortical Semantic Topography

arXiv:2605.23035v1 Announce Type: cross Abstract: Intermediate layers of large language models (LLMs) best predict human brain responses to language, one of the most robust findings in computational n

Sparse Compositional Flow Matching by geometric assembly from motion primitives

arXiv:2605.23341v1 Announce Type: cross Abstract: Embodied trajectories, such as the executable motion sequences of robotic manipulators, underwater vehicles, and mobile robots, are a fundamental outp

Sparse In-Network Learning via Shortest-Path Backpropagation and Finite-Rate Gating

arXiv:2605.23424v1 Announce Type: cross Abstract: In-network learning (INL) trains distributed neural modules by exchanging latent activations and backpropagated errors over a communication graph. Thi

Sparser Block-Sparse Attention via Token Permutation

arXiv:2510.21270v2 Announce Type: replace-cross Abstract: Scaling the context length of large language models (LLMs) offers significant benefits but is computationally expensive. This expense stems pr

applicationsarxiv-cs-ai

Spatio-Temporal Forecasting of Retaining Wall Deformation: Mitigating Error Accumulation via Multi-Resolution ConvLSTM Stacking Ensemble

arXiv:2603.10453v2 Announce Type: replace Abstract: This study proposes a multi-resolution Convolutional Long Short-Term Memory (ConvLSTM) ensemble framework that leverages diverse temporal input reso

Spatio-Temporal Similarity Volume Aggregation for Open-Vocabulary Action Recognition

arXiv:2605.23288v1 Announce Type: new Abstract: Recent Open-Vocabulary Action Recognition (OVAR) methods typically aggregate visual features into a global representation before computing text alignmen

safetyarxiv-cs-cv

Speak-to-Structure: Evaluating LLMs in Open-domain Natural Language-Driven Molecule Generation

model-releasesarxiv-cs-cl

arXiv:2412.14642v4 Announce Type: replace Abstract: Recently, Large Language Models (LLMs) have demonstrated great potential in natural language-driven molecule discovery. However, existing datasets a

Local Ai

Spectral-inspired Operator Learning with Limited Data and Unknown Physics

arXiv:2505.21573v3 Announce Type: replace-cross Abstract: Learning PDE dynamics from limited data with unknown physics is challenging. Existing neural PDE solvers either require large datasets or rely

local-aiarxiv-cs-ai

SpinFlow: A Physics-Informed Spin Field Framework for Traffic Phase Inference and Transition Detection

arXiv:2605.23306v1 Announce Type: cross Abstract: Active traffic management (ATM) is frequently hindered by traditional macroscopic models and rigid empirical thresholds that fail to capture metastabl

safetyarxiv-cs-lg

SSDAU: Structured Semantic Data Augmentation for Joint Entity and Relation Extraction

arXiv:2605.23440v1 Announce Type: cross Abstract: Joint Entity and Relation Extraction (JERE) is highly susceptible to weak generalization due to low-quality training data. Data augmentation is a comm