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Raphael Satter / Reuters: Letter: US Central Command says it received “threat reports concerning adversary exploitation of commercial location data” to target US personnel in war zones — U.S. forces d

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Tools

Leveling up Weaviate Cloud security: Expanding role-based access control for Cloud console

Weaviate has expanded its role-based access control (RBAC) capabilities for the Weaviate Cloud console, enabling more granular permission management and user access control. This enhancement allows ad

toolsweaviate

Local MDI+: Local Feature Importances for Tree-Based Models

model-releasesarxiv-cs-lg

arXiv:2506.08928v2 Announce Type: replace Abstract: Tree-based ensembles such as random forests remain the go-to for tabular data over deep learning models due to their prediction performance and comp

Modeling Vehicle-Type-Specific Pedestrian Crash Avoidance Behavior in Safety-Critical Interactions Using Smooth-Mamba Deep Reinforcement Learning

arXiv:2605.28552v1 Announce Type: new Abstract: As automated vehicles (AVs) increasingly share roadways with human-driven vehicles (HDVs), understanding how pedestrians respond to different vehicle ty

models being conscious would be harmful for humanity. it would encroach on our status and dignity. it would limit the type of things we can …

applicationsethan-mollick--x

models being conscious would be harmful for humanity. it would encroach on our status and dignity. it would limit the type of things we can do with them and use them for. it would vastly accelerate hu

Nano Banana 2 and Nano Banana Pro are generally available, and already powering creative workflows

model-releasesgoogle-cloud-ai

Organizations are unlocking entirely new ways to use image generation and editing across their industries. To drive next-generation experiences, businesses are embedding AI directly into creative, age

OccuReward: LLM-Guided Occupant-Centric Reward Shaping for Demographic Equity in Grid-Interactive Buildings

arXiv:2605.28168v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated promising capability in generating reward functions for deep reinforcement learning (DRL)-based building

Ocean4Rec: Offline LLM-Derived OCEAN Profiles for Request-Time VOD Reranking

arXiv:2605.27429v1 Announce Type: cross Abstract: Industrial video-on-demand (VOD) recommenders need richer content understanding, but LLM-as-reranker designs repeat prompt construction, token generat

researcharxiv-cs-ai

Hardware

Official @NVIDIAAI GLM5.1-NVFP4 spotted on @huggingface 🤩 https://huggingface.co/nvidia/GLM-5.1-NVFP4

NVIDIA has released GLM-5.1-NVFP4, a quantized version of the GLM-5.1 model, now available on Hugging Face. The model appears to use NVFP4 (NVIDIA's floating-point 4-bit) quantization format, designed

hardwareclem-delangue--x

{Omega}-QVLA: Robust Quantization for Vision-Language-Action Models via Composite Rotation and Per-step Scaling

arXiv:2605.28803v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models unify perception, reasoning, and control within a single policy, yet their multi-billion-parameter backbones and dif

OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibration

arXiv:2605.28805v1 Announce Type: cross Abstract: Visual outcomes are increasingly central to multimodal large language models, making reliable and fine-grained verification essential for scaling gene

Online Irregular Multivariate Time Series Forecasting via Uncertainty-Driven Dual-Expert Calibration

arXiv:2605.28603v1 Announce Type: cross Abstract: Irregular multivariate time series forecasting is critical in many real-world applications, where time series are irregularly sampled and exhibit dyna

applicationsarxiv-cs-ai

Industry

OpenCode Now Supports DigitalOcean Inference Router for Intelligent Model Routing

OpenCode now integrates with DigitalOcean's Inference Router, enabling intelligent routing of AI model requests across distributed infrastructure. This integration allows developers to optimize model

industrydigitalocean

Tools

Opus 4.8 on AI Gateway

Vercel announced support for Claude Opus 4.8 on its AI Gateway, enabling developers to integrate Anthropic's latest large language model through Vercel's unified API platform. This update allows seaml

toolsvercel-blog

Patched-DeltaNet: Token-Level Event-Driven Memory for Linear-Time Anomaly Detection

model-releasesarxiv-cs-lg

arXiv:2605.27992v1 Announce Type: new Abstract: Time series anomaly detection is critical for maintaining the reliability of mission-critical systems. While Transformer-based models like PatchTST have

Pattern Recognition Tasks with Personalized Federated Learning

arXiv:2605.27816v1 Announce Type: new Abstract: Personalized Federated Learning (PFL) constitutes a novel paradigm that tailors Machine Learning (ML) models to individual clients, thereby furnishing p

researcharxiv-cs-cv

PetroBench: A Benchmark for Large Language Models in Petroleum Engineering

arXiv:2605.28032v1 Announce Type: new Abstract: Large Language Models are increasingly applied in the petroleum industry, highlighting the need for a domain-specific evaluation framework. This study d

Position: Retire the 'Positive Backdoor' Label -- Secret Alignment Requires Strict and Systematic Evaluation

arXiv:2605.28597v1 Announce Type: cross Abstract: This position paper argues that the AI/ML community should stop overclaiming and retire the label 'positive backdoor,' and instead treat trigger-activ

Prompt Codebooks: Discrete Compositional Optimization for Language Model Instruction Refinement

arXiv:2605.28360v1 Announce Type: new Abstract: Automatic prompt optimization (APO) has driven significant gains in LLM-based agentic workflows. However, existing methods treat each task's prompt as a

Prompting Is All You Need: Multi-view Prompting Large Language Models for Aspect-Based Sentiment Analysis

model-releasesarxiv-cs-cl

arXiv:2605.28058v1 Announce Type: new Abstract: Recent work explored the capabilities of Large Language Models (LLMs) in Aspect-Based Sentiment Analysis (ABSA) through few-shot prompting, requiring su

PrunePath: Towards Highly Structured Sparse Language Models

arXiv:2605.28283v1 Announce Type: cross Abstract: Feed-forward networks (FFNs) dominate the parameter count and computation of modern language models, yet existing pruning methods often struggle to co

Pruning and Distilling Mixture-of-Experts into Dense Language Models

arXiv:2605.28207v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) is now the dominant architecture for frontier language models, yet it requires all expert parameters to be loaded in memory,

Relational Semantic Reasoning on 3D Scene Graphs for Open World Interactive Object Search

arXiv:2603.05642v2 Announce Type: replace-cross Abstract: Open-world interactive object search in household environments requires understanding semantic relationships between objects and their surroun

Resource-Constrained Affect Modelling via Variance Regularisation Pruning

arXiv:2605.27479v1 Announce Type: cross Abstract: Affective computing systems are increasingly embedded in pervasive and interactive environments, such as adaptive games, assistive technologies, and r

Robo-Blocks: Generative Scaffolding in End-User Design and Programming of Social Robots

arXiv:2605.28154v1 Announce Type: cross Abstract: Programming social robots is challenging for novice robot programmers due to required expertise in planning, interaction design, and programming. Whil

researcharxiv-cs-ro

Safe In-Context Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2509.25582v3 Announce Type: replace Abstract: In-context reinforcement learning (ICRL) is an emerging RL paradigm where an agent, after pretraining, can adapt to out-of-distribution test tasks w

Self-Supervised Online Robot-Agnostic Traversability Estimation for Open-World Environments

arXiv:2605.28442v1 Announce Type: cross Abstract: Self-supervised online traversability estimation enables robots to continuously learn from unlabeled open-world experiences and adapt their navigation

Semantic Flow Regularization: Teaching LLMs to Generate Diverse Yet Coherent Responses

arXiv:2605.27971v1 Announce Type: cross Abstract: When large language models are fine-tuned to generate persona- or tone-conditioned responses, their output diversity is severely limited--a failure we

researcharxiv-cs-ai

STARS: Spike Tail-Aware Relational Synthesis for ANN-to-SNN Data-Free Knowledge Distillation

arXiv:2605.27409v1 Announce Type: cross Abstract: SNNs promise energy-efficient and low-latency inference, but their performance still trails that of ANNs. ANN-to-SNN knowledge distillation helps narr

Super-Resolved Canopy Height Mapping from Sentinel-2 Time Series Using Airborne LiDAR HD Reference Data across Metropolitan France

arXiv:2512.11524v3 Announce Type: replace Abstract: Fine-scale forest monitoring is essential for understanding canopy structure and its dynamics, which are key indicators of carbon stocks, biodiversi

researcharxiv-cs-cv

The Alignment Floor: When Persona Customization Is Safe

arXiv:2605.27382v1 Announce Type: cross Abstract: A key promise of pluralistic AI is behavioral adaptation: persona prompts like 'be creative' or 'be thorough' let systems respect diverse user values

The Energy Blind Spot: NVIDIA's Flagship Edge AI Hardware Cannot Support Process-Level Energy Attribution

arXiv:2605.27599v1 Announce Type: cross Abstract: Agentic AI workloads - where a single user goal triggers multi-step orchestration, tool calls, retries, and failure recovery - are being targeted for

The Harder Text Embedding Benchmark (HTEB): Beyond One-dimensional Static Robustness

model-releasesarxiv-cs-cl

arXiv:2605.28190v1 Announce Type: new Abstract: Embedding benchmarks like MTEB report a single score per model, implicitly treating robustness as a static, scalar property. We argue that embedding rob

The Shape of Overthinking: Backtracking Bursts in Long Reasoning Traces

arXiv:2605.27965v1 Announce Type: new Abstract: Reasoning models often generate long traces in which useful self-correction and unproductive revision are hard to distinguish. We study this distinction

Unified Multi-Domain Graph Pre-training for Homogeneous and Heterogeneous Graphs via Domain-Specific Expert Encoding

arXiv:2602.13075v2 Announce Type: replace Abstract: Graph pre-training has achieved remarkable success in recent years, delivering transferable representations for downstream adaptation. However, most

applicationsarxiv-cs-lg

Verified Misguidance: Measuring Structural Citation Failures in Search-Augmented LLMs

arXiv:2605.28565v1 Announce Type: cross Abstract: Users of search-augmented LLMs rely on citations as evidence that responses are grounded in real sources, and rarely verify the cited pages themselves

VidPrism: Heterogeneous Mixture of Experts for Image-to-Video Transfer

arXiv:2605.28229v1 Announce Type: cross Abstract: With the rapid development of pre-training technologies, adapting large-scale Vision-Language Models (VLMs) for video understanding ie image-to-video

researcharxiv-cs-ai

VLA-Hijack: A Transferable Patch Attack against Vision-Language-Action Models via Visual Proprioception Hijacking

arXiv:2605.28083v1 Announce Type: new Abstract: While Vision-Language-Action (VLA) models have emerged as powerful generalist policies, their severe vulnerability to adversarial patches significantly

safetyarxiv-cs-cv

What Are We Measuring in NLG? A Meta-Analysis of Evaluation Trends 2020-2025

arXiv:2601.07648v2 Announce Type: replace Abstract: As Natural Language Generation (NLG) dominates modern NLP, scalable evaluation remains a critical bottleneck. Consequently, LLM-as-a-judge (LaaJ) ad

safetyarxiv-cs-cl

Agents

When Does Memory Help Multi-Trajectory Inference for Tool-Use LLM Agents?

arXiv:2605.28224v1 Announce Type: new Abstract: Multi-trajectory inference for tool-use LLM agents - generating multiple reasoning attempts and selecting among them - benefits from transferring knowle

agentsarxiv-cs-ai

XTransfer: Modality-Agnostic Few-Shot Model Transfer for Human Sensing at the Edge

arXiv:2506.22726v4 Announce Type: replace Abstract: Deep learning for human sensing on edge systems presents significant potential for smart applications. However, its training and development are hin

You Are in Control of Your State: Why Human Outcomes Are Controllable Through Causal State Intervention

arXiv:2605.27580v1 Announce Type: new Abstract: A central puzzle for the behavioural sciences and for human-facing artificial intelligence is the persistence of within-person variability. The same ind

applicationsarxiv-cs-ai

A Hybrid Vision-Language Architecture for Automated Defect Reasoning and Report Generation in Industrial Inspection

arXiv:2605.26533v1 Announce Type: cross Abstract: Automated industrial inspection requires both precise defect localization and structured maintenance report generation; in current practice these task

a16z waking up and realizing we are nowhere near the singularity 🤣

a16z waking up and realizing we are nowhere near the singularity 🤣 OpenAI and Anthropic are effectively telling the market they can't solve every problem with a generic AI coworker. You don't pour bil

safetygary-marcus--x

AdaSD: Adaptive Speculative Decoding for Efficient Language Model Inference

model-releasesarxiv-cs-cl

arXiv:2512.11280v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved remarkable performance across a wide range of tasks, but their increasing parameter sizes significantly s

Tools

[AINews] New AI Infra decacorns: Fireworks, Baseten (with OpenRouter on the way)

Latent Space reports on emerging AI infrastructure companies achieving unicorn status, specifically highlighting Fireworks and Baseten as new decacorns (companies valued at $10+ billion), with OpenRou

toolslatent-space

BatteryMFormer: Multi-level Learning for Battery Degradation Trajectory Forecasting

arXiv:2605.27044v1 Announce Type: new Abstract: Early battery degradation trajectory forecasting (BDTF), which predicts the full-life state-of-health trajectory from early operational data, is critica

Benchmarking Convolutional, Transformer, Hybrid, and Vision Language Models for Multi Disease Retinal Screening

arXiv:2605.26283v1 Announce Type: new Abstract: Modern deep learning offers powerful tools for automated retinal screening, but it remains unclear how different visual model families compare in realis