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🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with …

model-releasesdeepseek--x

🚀 Introducing DeepSeek-V4.1-Flash: smarter, faster, more efficient. 🔹 Introducing the smallest model in our new architecture family, with native visual understanding. 🔹 Designed for greater capability

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Model Releases

Introducing Gen-1 Slides: an open model that matches Claude Opus 5 on slide generation, at ~1/17 of its input-token price. @genspark_ai post…

DGX agent

Introducing Gen-1 Slides: an open model that matches Claude Opus 5 on slide generation, at ~1/17 of its input-token price. @genspark_ai post-trained it from a @MiniMax_AI M3 base with Fireworks Lab us

model-releasesfireworks-ai--x

10 Sept 2026

Hardware

introducing preemptible compute for together gpu clusters same nvidia gpu infrastructure, 50% of the on-demand price built for evals, fine-t…

introducing preemptible compute for together gpu clusters same nvidia gpu infrastructure, 50% of the on-demand price built for evals, fine-tuning, batch inference + short experiments, with up to 5 min

hardwaretogether-ai--x

Introducing the Google Cloud Developer Plugin for AI Coding Agents

model-releasesgoogle-cloud-ai

Agent skills fit well alongside documentation and remote MCP servers as ways of enabling the success of your AI workflows. They reduce context window usage for certain use cases, and they're straightf

Isotropic Embedding Perturbations for Robust Vision Language Encoders

arXiv:2609.10292v1 Announce Type: new Abstract: Data augmentation is fundamental to training modern deep vision and multimodal models. While individual methods, such as RandAug, CutMix, Mixup, RandEra

safetyarxiv-cs-cv

Applications

It Is Not My Code Anymore

arXiv:2609.09022v1 Announce Type: cross Abstract: AI-assisted programming raises distinct questions about who produces code, who feels ownership of it, and who is responsible when it fails. This resea

applicationsarxiv-cs-ai

Agents

It is Not Yet Another Tool: Creating and Deploying an Agentic AI Companion in a Security Operations Center

arXiv:2609.06250v1 Announce Type: cross Abstract: Security Operations Centers (SOCs) process large amounts of tickets, most of which are low-interest events not worthy of further investigation. The re

agentsarxiv-cs-ai

It's All in the Way You Say It: The Role of Information Representation in LLM-Based Glycemic-Event Prediction

arXiv:2609.08772v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly being investigated for physiological time-series prediction, yet their effectiveness may depend not only o

It's time to call these end-of-the-world anti-AI messaging groups exactly what they are: Terror cells - They funnel and wash money from a fe…

It's time to call these end-of-the-world anti-AI messaging groups exactly what they are: Terror cells - They funnel and wash money from a few donors to smaller groups to obscure origin - insert sleepe

safetyyann-lecun--x

Jacob was a senior researcher who joined Anthropic in May. My Anthropic colleagues and I had been trying to recruit him for ~2 years, becaus…

Jacob was a senior researcher who joined Anthropic in May. My Anthropic colleagues and I had been trying to recruit him for ~2 years, because we knew he was a strong researcher at OpenAI. Before he le

safetygary-marcus--x

JEPA Policy: Diffusion-Free Imitation Learning via Paired Action and Future Representation Prediction

arXiv:2609.09630v1 Announce Type: new Abstract: Standard behavior cloning supervises actions without explicitly constraining the future representation paired with each demonstrated action chunk. We in

safetyarxiv-cs-ro

Agents

JumpCloud extends Agentic IAM with new controls for autonomous AI agents

Identity and access management company JumpCloud Inc. today extended its Agentic IAM service to give information technology teams direct control over the autonomous artificial intelligence agents runn

agentssiliconangle

Kernel-Complexity Edge Sanitization for Training-Free Defense against Structural Graph Attacks

arXiv:2609.09698v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have achieved remarkable success across diverse applications, yet they remain highly vulnerable to adversarial attacks that

researcharxiv-cs-lg

Kernel-Managed Shared Memory for System-Wide Personalization

model-releasesarxiv-cs-lg

arXiv:2609.10144v1 Announce Type: cross Abstract: AI systems become more useful when they can adapt to the people using them, but in multi-agent systems, useful context learned by one agent often rema

Key Path Identification for Resolving Knowledge Conflicts via SAE-based Steering

arXiv:2609.08173v1 Announce Type: new Abstract: Sparse autoencoder (SAE)-based steering has been widely used to address knowledge conflicts by guiding LLMs to be more faithful to the contextual knowle

Kino-PAX^+: Near-Optimal Massively Parallel Kinodynamic Sampling-based Motion Planner

arXiv:2602.02846v2 Announce Type: replace Abstract: Sampling-based motion planners (SBMPs) are widely used for robot motion planning with complex kinodynamic constraints in high-dimensional spaces, ye

researcharxiv-cs-ro

Knowing Your Uncertainty -- On the application of LLM in social sciences

arXiv:2512.05461v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are rapidly being integrated into computational social science research, yet their blackboxed training and design

Agents

KVShareArena: KV-Cache Reuse Across Contexts and Model Checkpoints

arXiv:2609.10266v1 Announce Type: new Abstract: LLM serving systems already reuse KV caches, but only when the reused text sits at the very start of the prompt. Two growing workloads break this condit

agentsarxiv-cs-cl

LANTERN: Language Model Assessment on Noisy and Transformed Tasks for Understanding Error and Robustness Nuances

arXiv:2609.07309v1 Announce Type: cross Abstract: Robustness evaluation of large language models (LLMs) remains a critical challenge, particularly in assessing their sensitivity to perturbations in in

Large Language Models Transform Organic Synthesis From Reaction Prediction to Automation

arXiv:2508.05427v2 Announce Type: replace Abstract: Large language models (LLMs) are beginning to reshape how organic-synthesis workflows are represented, queried, planned, and connected to experiment

safetyarxiv-cs-ai

Applications

Large-Scale User Behavior Analysis in Multimodal AI-Assisted Manual Task Execution

arXiv:2609.07594v1 Announce Type: cross Abstract: Conversational Task Assistants (CTAs) are multimodal dialogue systems that support users in complex real-world tasks such as cooking and DIY through v

applicationsarxiv-cs-ai

LatentDx: Latent Multi-Agent Communication for Cross-Hospital Rare-Disease Diagnosis

model-releasesarxiv-cs-cl

arXiv:2606.13945v2 Announce Type: replace Abstract: Rare diseases affect over 300 million patients across more than 7{,}000 conditions, yet no single hospital encounters enough cases of any one condit

Layerwise Tunable Lifting Scheme for the Convolutional Neural Network

model-releasesarxiv-cs-cv

arXiv:2609.09827v1 Announce Type: new Abstract: This work introduces a family of tunable lifting schemes for biorthogonal wavelet filter banks. We propose three lifting strategies: low-pass tuning (LS

Tutorials

Learning Counterfactual World Models for Embodied Reasoning under Partial Observability

arXiv:2609.05834v1 Announce Type: new Abstract: World models promise a general route to embodied intelligence: learn predictive dynamics once, then reason, plan, and act with them. Increasingly, the r

tutorialsarxiv-cs-ai

Learning Global Camera Poses from Noisy View-Graphs for Structure from Motion

arXiv:2609.09491v1 Announce Type: new Abstract: Camera pose estimation is a key step in 3D reconstruction and view-synthesis pipelines. We present a deep, global Structure-from-Motion framework based

researcharxiv-cs-cv

Learning Terrain-Adaptive Humanoid Locomotion on Granular Terrain

arXiv:2609.10286v1 Announce Type: new Abstract: Humanoid locomotion on granular terrain remains a significant challenge due to its complex foot-terrain interaction dynamics that are difficult to model

safetyarxiv-cs-ro

Learning to Adapt and Calibrate: Score Distribution Alignment for Few-Shot Uncertainty Prediction in Medical VLMs

arXiv:2609.10333v1 Announce Type: new Abstract: Uncertainty estimation for medical vision--language models (VLMs) using conformal prediction has gained increasing attention due to its distribution-fre

safetyarxiv-cs-cv

Learning to Fly: Stable Vision-Guided UAV Servoing with Compact Target-Centric Cues and Reinforcement Learning

arXiv:2609.09234v1 Announce Type: cross Abstract: Vision-guided reinforcement learning for Unmanned Aerial Vehicles (UAVs) remains challenging due to unstable policy optimisation, aggressive explorati

safetyarxiv-cs-lg

Learning transferable human physiology from two million hours of sleep with SleepFM-2

arXiv:2609.06849v1 Announce Type: new Abstract: Sleep provides a nightly window into health by capturing coordinated activity across the brain, heart, muscles and respiratory system. We introduce Slee

Tutorials

Learning with Covariance Matrices: Principal Component Analysis Meets Learning with Graphs

arXiv:2609.10490v1 Announce Type: new Abstract: This feature article provides an overview of the theoretical foundations for coVariance neural networks (VNNs), i.e., graph neural networks (GNNs) opera

tutorialsarxiv-cs-lg

Learning with Synthetic Data via SGD in High-Dimensional Linear Regression

arXiv:2609.09572v1 Announce Type: cross Abstract: Synthetic data has become a promising way to scale model training beyond limited human-generated data but it may also induce strong model collapse (Do

safetyarxiv-cs-lg

LEBGen: An LLM-Enhanced Bayesian Network Framework for Few-Shot Travel Survey Data Generation

arXiv:2609.08288v1 Announce Type: new Abstract: Travel survey data are essential for transportation planning and travel behavior analysis, yet collecting large-scale representative samples is costly a

LeCor: Learning to Be Corrected by Meta-Learned Test-Time Training for Interactive 3D Lung-Tumour Segmentation

arXiv:2609.09477v1 Announce Type: new Abstract: Delineating lung tumours on computed tomography (CT) takes a considerable share of the time spent on radiotherapy planning, and a contour proposed by a

researcharxiv-cs-cv

Lensless Gaze Is Not Private by Default: Auditing Identity Leakage Across Disclosure Surfaces

model-releasesarxiv-cs-cv

arXiv:2609.09188v1 Announce Type: new Abstract: Lensless near-eye sensing is often described as privacy-friendly because its coded measurements are visually unintelligible. Yet visual unintelligibilit

Less Is Personal: Learning Minimal Sufficient User Profiles for Personalized Language Models

arXiv:2609.08180v1 Announce Type: new Abstract: Retrieval-augmented personalization enables large language models to produce more accurate and preference-aligned outputs using relevant records retriev

Industry

Letter: the Senate disaster management subcommittee, led by Sen. Josh Hawley, is probing OpenAI's handling of the Hugging Face breach, calling it 'reckless' (Axios)

Axios: Letter: the Senate disaster management subcommittee, led by Sen. Josh Hawley, is probing OpenAI's handling of the Hugging Face breach, calling it “reckless” — A Republican-led Senate subcommitt

industrytechmeme

Leveraging Fine-grained Error Correction in Korean Speech Recognition for Consultation Services

model-releasesarxiv-cs-cl

arXiv:2609.09889v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) technology is fundamental to customer service automation and large-scale transcription. However, even advanced ASR mo

LightMedSeg-ISLES: Stroke Lesion Segmentation with 81x Fewer Parameters than nnU-Net

model-releasesarxiv-cs-cv

arXiv:2609.09634v1 Announce Type: new Abstract: Large networks and ensembles often lead medical image segmentation challenges, but their storage and inference demands complicate deployment. We present

Likelihood-free inference with nuisance parameters through normalizing flows

model-releasesarxiv-cs-lg

arXiv:2609.10534v1 Announce Type: cross Abstract: We present a simple decomposition of a neural-network-based normalizing flow that naturally uncovers a pivotal statistic (or something close) in the p

Limits of Reliability and Scaling in Language Models

arXiv:2607.14112v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are trained and evaluated as though perfect reliability is achievable for any task given sufficient scale. We sho

LinearMask-GS: Stable-Mask Importance Pruning for Compact 3D Gaussian Splatting

arXiv:2609.10095v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables real-time novel view synthesis but produces millions of primitives through adaptive densification, leading to signi

researcharxiv-cs-cv

LiteRAG: Cost-Efficient Graph-Based Retrieval-Augmented Generation

model-releasesarxiv-cs-cl

arXiv:2609.10239v1 Announce Type: cross Abstract: Graph-based retrieval can improve multi-hop question answering, but existing approaches often incur high query-time costs and produce diffuse, oversiz

Literati: Towards Anytime Optimal Shape Generalized Trees via AO*

arXiv:2609.09299v1 Announce Type: new Abstract: Decision trees are prized for their interpretability and strong performance on tabular data, but popular greedy top-down induction algorithms can yield

safetyarxiv-cs-lg

LLM-Generated or Human-Written? Comparing Review and Non-Review Papers on ArXiv

arXiv:2601.17036v2 Announce Type: replace-cross Abstract: ArXiv recently prohibited the upload of unpublished review papers to its servers in the Computer Science domain, citing a high prevalence of L

safetyarxiv-cs-cl

LLMs for Social Network Modeling: From Network Generation to Dynamic Processes

arXiv:2609.08049v1 Announce Type: cross Abstract: Large language models (LLMs) are rapidly emerging as a new paradigm for modeling social networks by representing users and their relationships and int

LOBERT: Generative AI Foundation Model for Limit Order Book Messages

arXiv:2511.12563v2 Announce Type: replace Abstract: Modeling the dynamics of financial Limit Order Books (LOB) at the message level is challenging due to irregular event timing, rapid regime shifts, a

Local LLM / Qwen 3.8 win

model-releasesr-localllama

I’ve been working on perfecting my setup ever since 3.8 hit, but no longer pay for subscriptions. I had a coding interview today and setup openrouter ahead of time as another option. I figured I could

Local Ai

Localizing and Correcting Errors for LLM-based Planners

arXiv:2602.00276v3 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated strong reasoning capabilities on math and coding, but frequently fail on symbolic classical planning

local-aiarxiv-cs-ai