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as agents run for longer and with more context, there's a lot of tricky things you have to consider for deployment! super excited to dive in…

applicationsharrison-chase--x

as agents run for longer and with more context, there's a lot of tricky things you have to consider for deployment! super excited to dive into deploying Deep Agents for this Boston tech week meetup! .

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Research

As always, 'hermes update'

DGX agent

Nous Research announced an update to their Hermes model, likely detailing improvements, new features, or performance enhancements to their open-source language model. The post was shared on X (formerl

researchnous-research--x

20 May 2026

Industry

As the recently expanded partnership with @AnthropicAI demonstrates, @SpaceX is offering AI compute as a service at significant scale. We ar…

As the recently expanded partnership with @AnthropicAI demonstrates, @SpaceX is offering AI compute as a service at significant scale. We are in discussions with other companies to do the same. Over t

industryelon-musk--x

Atomistic Modeling of Chemical Disorder in Materials: Bridging Classical Methods and AI-Assisted Approaches

arXiv:2605.19124v1 Announce Type: cross Abstract: Chemical disorder, originating from the mixed occupation of crystallographic sites by multiple elements, is widespread in alloys, ceramics, and compos

Atoms of Thought: Universal EEG Representation Learning with Microstates

arXiv:2605.20182v1 Announce Type: cross Abstract: Learning universal representations from electroencephalogram (EEG) signals is a cutting-edge approach in the field of neuroinformatics and brain-compu

researcharxiv-cs-ai

Attention-Guided Reward for Reinforcement Learning-based Jailbreak against Large Reasoning Models

arXiv:2605.19485v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) have demonstrated remarkable capabilities in solving complex problems by generating structured, step-by-step reasoning con

Auditing Privacy in Multi-Tenant RAG under Account Collusion

arXiv:2605.19847v1 Announce Type: cross Abstract: Multi-tenant retrieval-augmented generation (RAG) services advertise per-account differential privacy as the operative leakage boundary: each account'

researcharxiv-cs-lg

Auditing Reasoning-Trace Memorization Claims after Unlearning with Head-Conditioned Canaries

arXiv:2605.18891v1 Announce Type: cross Abstract: Evaluations of unlearning on reasoning models sometimes show a bypass pattern. The answer side looks unlearned, but the model's own thinking trace kee

Tutorials

Australian teens who lost access to social media because of age verification read less news

tutorialsjeremy-howard--x

Australian teenagers who were unable to access social media due to age verification requirements implemented under new legislation showed reduced news consumption compared to their peers. The finding

Automated Big Data Quality Assessment using Knowledge Graph Embeddings

arXiv:2605.18833v1 Announce Type: cross Abstract: Automated data quality assessment is crucial for managing big data, but existing solutions face challenges in achieving accurate context-aware assessm

applicationsarxiv-cs-ai

Automated Grading of Handwritten Mathematics Using Vision-Capable LLMs

arXiv:2605.19043v1 Announce Type: cross Abstract: Automated grading systems have enabled scalable assessment for many response types, but handwritten mathematics remains a barrier due to the complexit

researcharxiv-cs-ai

Automatically Improving Simulation Physics for Articulated Objects

arXiv:2605.19136v1 Announce Type: new Abstract: Simulation is a central tool for scalable robot learning, but its effectiveness depends on the quality of object assets. While modern 3D datasets provid

safetyarxiv-cs-ro

Agents

Automating what already exists isn’t enough — agents demand a fundamental rethink of the enterprise

Enterprises have figured out how to stand up AI agents, but agent management is another problem entirely. The agentic moment is forcing organizations to interrogate everything, including the operating

agentssiliconangle

AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration

arXiv:2605.20025v1 Announce Type: new Abstract: Automating scientific discovery requires more than generating papers from ideas. Real research is iterative: hypotheses are challenged from multiple per

Awakening the Hydra: Stabilizing Multi-Concept Backdoor Injection in Text-to-Image Diffusion Models

arXiv:2605.19698v1 Announce Type: cross Abstract: Text-to-image diffusion models are increasingly developed through open-source reuse and repeated downstream fine-tuning, where reused checkpoints are

researcharxiv-cs-lg

B-cos GNNs: Faithful Explanations through Dynamic Linearity

arXiv:2605.19778v1 Announce Type: new Abstract: We introduce B-cos GNNs, an inherently explainable class of graph neural networks whose predictions decompose exactly into per-node, per-feature contrib

b9239

Build b9239 is a llama.cpp release that includes a fix for the --fit verbosity flag when used with --verbosity 4 . The release provides compiled binaries for multiple platforms including macOS (Apple

b9240

b9240 is a release of llama.cpp that includes a fix for the --help option related to the --verbosity flag . The release provides prebuilt binaries across multiple platforms including macOS (Apple Sili

b9244

b9244 is an intermediate build release of llama.cpp, a C/C++ implementation framework for running large language models with GGUF format support. The release includes pre-compiled binaries for multipl

b9245

llama.cpp release b9245, published on May 20, 2026, includes a CUDA optimization for RDNA3 Q6_K MMVQ performance tuning. The release provides pre-built binaries for multiple platforms including macOS,

b9251

B9251 is a build identifier for a release in the llama.cpp project, which enables LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware - locally and in the clo

b9253

b9253 is the latest version of llama.cpp, released on May 20, 2026. Llama.cpp is a project for LLM inference in C/C++. This build includes bug fixes, performance improvements, and features for running

BabyMamba-HAR: Lightweight Selective State Space Models for Efficient Human Activity Recognition on Resource Constrained Devices

arXiv:2602.09872v2 Announce Type: replace Abstract: Human activity recognition (HAR) on resource constrained devices requires high accuracy across diverse sensor setups. Selective state space models (

local-aiarxiv-cs-cv

Backdooring Masked Diffusion Language Models

model-releasesarxiv-cs-lg

arXiv:2605.19262v1 Announce Type: new Abstract: Masked diffusion language models (MDLMs) are emerging as a compelling new paradigm for text generation, but their training-time security remains largely

Backtracking When It Strays: Mitigating Dual Exposure Biases in LLM Reasoning Distillation

arXiv:2605.19433v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable success in complex reasoning tasks via long chain-of-thought (CoT), yet their immense computatio

BalanceRAG: Joint Risk Calibration for Cascaded Retrieval-Augmented Generation

arXiv:2605.20084v1 Announce Type: cross Abstract: Large language models (LLMs) can enhance factuality via retrieval-augmented generation (RAG), but applying RAG to every query is unnecessary when the

researcharxiv-cs-ai

Hardware

Banger take

Banger take Gavin Baker: 'I've been optimistic that the fundamental shortage of wafers, which is really controlled by Taiwan Semi, will prevent a bubble.' 'If Taiwan Semi did what Jensen wanted, Nvidi

hardwaredylan-patel--x

Base Models Look Human To AI Detectors

arXiv:2605.19516v1 Announce Type: cross Abstract: As AI-generated text enters the real-world at scale, institutions increasingly use commercial AI-text detectors, especially in education and academic-

Bayesian Joint Model of Multi-Sensor and Failure Event Data for Multi-Mode Failure Prediction

arXiv:2506.17036v2 Announce Type: replace-cross Abstract: Modern industrial systems are often subject to multiple failure modes, and their conditions are monitored by multiple sensors, generating mult

researcharxiv-cs-lg

Bayesian Latent Space Models for Graphs Are Misspecified: Toward Robust Inference via Generalized Posteriors

arXiv:2605.18927v1 Announce Type: cross Abstract: Bayesian latent space models offer a principled approach to network representation, but rely on correct specification of both geometry and link functi

applicationsarxiv-cs-lg

Tutorials

Bayesian Symbolic Regression for Missing Physics

arXiv:2603.14918v2 Announce Type: replace-cross Abstract: Model-based approaches for (bio)process systems often suffer from incomplete knowledge of the underlying physical, chemical, or biological law

tutorialsarxiv-cs-lg

Tutorials

BCI-sift: An automated feature selection toolbox for Brain Computer Interface applications

arXiv:2605.19646v1 Announce Type: cross Abstract: Advancements in clinical Brain-Computer Interfaces (BCIs) depend on precise and reliable signal interpretation. However, the high-dimensional and nois

tutorialsarxiv-cs-lg

Be Kind, Rewrite: Benign Projections via Rewriting Defend Against LLM Data Poisoning Attacks

arXiv:2605.19147v1 Announce Type: cross Abstract: Large language models (LLMs) are highly susceptible to backdoor attacks (BAs), wherein training samples are poisoned using trigger-based harmful conte

Agents

behaviors are small reactive units > state changes, behaviors react, behaviors emit more state changes no central orchestrator

This post discusses a reactive programming or state management architecture where individual behaviors function as small, independent units that respond to state changes and generate new state changes

agentsyohei-nakajima--x

Behind the scenes with Sundar Pichai and Demis Hassabis, two of the most important people in AI We covered timelines to curing every disease…

applicationsrowan-cheung--x

Behind the scenes with Sundar Pichai and Demis Hassabis, two of the most important people in AI We covered timelines to curing every disease, AGI bottlenecks, democratizing AI healthcare, and the futu

Benchmark and optimize LLMs on-device with AI Edge Portal

model-releasesgoogle-cloud-ai

LLMs have become more powerful at smaller sizes, but deploying them to edge devices like smartphones remains a massive challenge. Today, developers have to optimize across a sprawling combination of a

Benchmarking and Evolving Reason-Reflect-Rectify for Reflective Visual Generation

model-releasesarxiv-cs-cv

arXiv:2605.19639v1 Announce Type: new Abstract: Text-to-Image (T2I) models and Unified Multimodal Models (UMMs) have achieved remarkable progress in visual generation. However, their reliance on a sin

Benchmarking Commercial ASR Systems on Code-Switching Speech: Arabic, Persian, and German

arXiv:2605.19069v1 Announce Type: cross Abstract: Code-switching -- the natural alternation between two languages within a single utterance -- represents one of the most challenging and under-studied

BERTO: Intent-Driven Network Time Series Forecasting via Natural Language Operator Preferences

arXiv:2512.05721v2 Announce Type: replace Abstract: Traditional cellular traffic forecasting models are optimized for minimizing symmetric errors, leaving them indifferent to shifting operational prio

Beyond Action Residuals: Real-World Robot Policy Steering via Bottleneck Latent Reinforcement Learning

arXiv:2605.19919v1 Announce Type: new Abstract: Pretrained imitation policies have become a strong foundation for robot manipulation, but they often require online improvement to overcome execution er

safetyarxiv-cs-ro

Beyond Binary Success: A Diagnostic Meta-Evaluation Framework for Fine-Grained Manipulation

model-releasesarxiv-cs-cv

arXiv:2605.19986v1 Announce Type: cross Abstract: Fine-grained manipulation marks a regime where global scene context no longer suffices, and success hinges on the tight coupling of local attribute gr

Beyond Extrapolation: Knowledge Utilization Paradigm with Bidirectional Inspiration for Time Series Forecasting

arXiv:2605.19249v1 Announce Type: new Abstract: Time-series forecasting is critical in various scenarios, such as energy, transportation, and public health. However, most existing forecasters rely pri

Beyond Imitation: Learning Safe End-to-End Autonomous Driving from Hard Negatives

model-releasesarxiv-cs-cv

arXiv:2605.19771v1 Announce Type: cross Abstract: Existing imitation learning methods for end-to-end autonomous driving predominantly learn from successful demonstrations by minimizing geometric devia

Beyond Isotropy in JEPAs: Hamiltonian Geometry and Symplectic Prediction

arXiv:2605.20107v1 Announce Type: cross Abstract: JEPAs often regularize one-view embeddings toward an isotropic Gaussian, implicitly baking Euclidean symmetry into the representation. We show that th

Beyond Leakage and Complexity: Towards Realistic and Efficient Information Cascade Prediction

arXiv:2510.25348v2 Announce Type: replace Abstract: Information cascade popularity prediction is a key problem in analyzing content diffusion in social networks. However, current related works suffer

applicationsarxiv-cs-lg

Agents

Beyond Majority Voting: LLM Aggregation by Leveraging Higher-Order Information

arXiv:2510.01499v2 Announce Type: replace-cross Abstract: With the rapid progress of multi-agent large language model (LLM) reasoning, how to effectively aggregate answers from multiple LLMs has emerg

agentsarxiv-cs-ai

Beyond Mode Collapse: Distribution Matching for Diverse Reasoning

arXiv:2605.19461v1 Announce Type: new Abstract: On-policy reinforcement learning methods like GRPO suffer from mode collapse: they exhibit reduced solution diversity, concentrating probability mass on

Beyond Prediction Accuracy: Target-Space Recovery Profiles for Evaluating Model-Brain Alignment

arXiv:2605.20127v1 Announce Type: cross Abstract: Artificial vision models are often evaluated against the human visual cortex by measuring how accurately their internal representations predict brain