model releases

Have an LLM Write Your Anomaly Detector: Autonomous Discovery of Compact, Interpretable Detectors for Time Series

arXiv:2610.01223v1 Announce Type: cross Abstract: Time-series anomaly detection trades off predictive accuracy, computational efficiency, and interpretability. We use a large language model not as the

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Heteroskedastic Canonical Polyadic Tensor Decomposition

DGX agent

arXiv:2610.00498v1 Announce Type: cross Abstract: When minimizing the squared-error loss, the popular CP decomposition can be interpreted as parameter inference in a Gaussian model with a low-rank mea

model-releasesarxiv-cs-lg

2 Oct 2026

HHR: Hierarchical Hash Retrieval for Efficient LLM Generation

arXiv:2610.01230v1 Announce Type: new Abstract: Efficient long-context inference is essential for large language models (LLMs), yet it poses a severe computational bottleneck. Hash-based retrieval off

High-Value Synthetic Supervision for Parameter-Efficient Adaptation of a Compact Japanese Speech Model

arXiv:2610.00026v1 Announce Type: cross Abstract: Private domain speech is difficult to collect and redistribute, while compact models need task-specific supervision. We study an auditable synthetic p

Higher-Order Molecular Grammars for Generative and Foundation Models in Chemistry

arXiv:2610.02186v1 Announce Type: cross Abstract: Molecular learning models are strongly shaped by their underlying representations. Yet standard sequential and graph formalisms struggle to explicitly

HiPhy: Hierarchical Alignment for Physically-Plausible Multi-Principle Video Generation

model-releasesarxiv-cs-cv

arXiv:2610.02197v1 Announce Type: new Abstract: Video generation models have achieved remarkable visual fidelity and have strong potential to become general-purpose world simulators. Despite this prog

Hob-VL: A Benchmark for Visually Grounded Boolean Reasoning

arXiv:2610.01605v1 Announce Type: cross Abstract: Reliable visual reasoning requires composing multiple visual observations and returning consistent answers to logically equivalent questions. We intro

Homomorphic Advantage Operator: Stabilizing Reinforcement Learning Under Fully Homomorphic Encryption Constraints

arXiv:2610.02074v1 Announce Type: new Abstract: Privacy-preserving machine learning presents significant deployment challenges on the cloud for intelligent systems with confidential data. Fully Homomo

How Much Can Language Models Gain from Test-Time Computation?

arXiv:2610.01110v1 Announce Type: new Abstract: How much can test-time computation improve a language model, and at what cost? Test-time scaling is widely proposed as a substitute for larger models, b

How to implement long-term AI agent memory in AlloyDB and Memorystore for Valkey

model-releasesgoogle-cloud-ai

Enterprise AI agents need persistent memory to execute complex, multi-day workflows and long-horizon tasks. In this blog, we examine how a 2-tier memory architecture using Memorystore for Valkey for s

HumanoidToolBench: Benchmarking Humanoid Tool Use from Selection to Mobile Execution

arXiv:2610.02089v1 Announce Type: cross Abstract: As robotic hardware and learning methods advance, humanoids need tools to perform tasks beyond their inherent physical limits. Successful tool use req

HydroJEV: A one-second, training-free screen for cyber-attack and fault attribution in water distribution networks

arXiv:2610.02048v1 Announce Type: new Abstract: When a SCADA alarm is raised in a water distribution network, operators must decide quickly whether it reflects a cyberattack, a physical fault, a norma

I benchmarked Qwen 3.8 27B on my M4 Max — here's what I learned about local models, context, and coding performance

I've been experimenting with running larger models locally with Ollama, mainly because I'm interested in using them for agentic coding. I kept seeing benchmarks expressed as something like: 40 tokens/

model-releasesr-ollama

I made my iPhone a second GPU for my 24 GB MacBook: Qwen 3.8 27B prefills 29–44% faster & my holds part of the CTX window.

**DISCLAIMER** THE PREFILLING TPS SHOWN ON THE PHONE IS COMPUTED ONLY FOR THE LAYERS IT HOLDS. ALREADY FIXING IT TO SHOW END-TO-END PREFILL RATE. NUMBERS BELOW ARE ACCURATE FOR E2E PREFILL RATE. Every

I made my own cybersecurity benchmark and ran Qwen3.8 27B, here's how a local model actually does at hacking

Hey local AI community, I've been working on this for a while and finally feel ok sharing it. It's a cyber benchmark where the model gets a shell in an isolated docker box and has to find the exact fl

I spent 3 weeks testing local Qwen3.8 on the new low-latency SGLang/vLLM recipes: DFlash2 2.8x. Builds: RadixArk + Inferact 27B NVFP4, 27B BF16, orcarouter 27B Uncensored, Flash-Next NVFP4

Hey guys, Last time I tested Qwen3.8-Flash-Next on its own. This time I put three Qwen3.8 checkpoints through the same 10 tests on the same RTX PRO 6000: RadixArk/Qwen3.8-27B-NVFP4 (dense) orcarouter/

Improving scoring functions for protein-protein docking with LambdaLoss

arXiv:2610.00191v1 Announce Type: cross Abstract: Modeling protein-protein interactions requires accurate scoring functions that can rank potential poses (conformations) of a protein-protein complex t

Incident-Arena: Getting agents to the last nine of reliability

arXiv:2610.00648v1 Announce Type: new Abstract: AI coding agents are ubiquitous in engineering workflows amongst industry and academia. Yet, despite their use in app coding, relatively less attention

Increasing Width Allows Greedy Layer-wise Training to Rival End-to-End Backpropagation in Self-Supervised Learning

arXiv:2610.00753v1 Announce Type: cross Abstract: End-to-end backpropagation has been the dominant mode of training in deep learning, allowing for the coordination of parameter updates across layers o

INDEQS: Informed Neural controlled Differential EQuationS

arXiv:2606.19138v2 Announce Type: replace Abstract: Neural Controlled Differential Equations (NCDE) provide a powerful continuous-time framework for forecasting time series, but standard graph-based e

Inference Engineering for Dummies

Hi all! I am a former SWE who has recently transitioned into inference engineering. I launched a side hustle a few months back and I've just taken it full time due to excessive demand. Its been such a

Inside-Out AI: Rebuilding Airbnb Behind the Scenes and Across the Guest Experience

model-releaseslatent-space

Ahmad Al‑Dahle joined Airbnb as CTO in January 2026 after leading Meta’s Llama generative‑AI models (2023–2025). He is steering an “inside‑out AI” strategy that deploys internal AI tools—such as the c

Interpretable Synthetic Medical Tabular Data Generation for Clinical Decision Support Using Fuzzy Cognitive Maps

arXiv:2610.00391v1 Announce Type: cross Abstract: Synthetic medical tabular data generation has become essential for developing and validating computer-based medical systems (CBMSs) when real clinical

Interpreting Reasoning of Large Language Models via Partial Information Decomposition

arXiv:2610.00571v1 Announce Type: cross Abstract: Large reasoning models (LRMs) have achieved substantial improvements in solving complex mathematical problems, but often produce lengthy, repetitive,

Invent a Dataset: Measuring dataset generation abilities with zero seed

arXiv:2610.01674v1 Announce Type: new Abstract: Building datasets remains one of the most manual and brittle parts of AI development. In this technical report, we focus on the most extreme but also mo

IrekoGPT: Turning Structured Pruning into Post-Hoc Slimmable LLMs

arXiv:2610.00426v1 Announce Type: new Abstract: We introduce IrekoGPT, a post-hoc method for converting pretrained LLMs into slimmable models whose width can be adjusted at inference time. Building on

Is Success All You Need? Investigating the Impact of Input Perturbations on VLA Behaviour in Tabletop Manipulation Tasks

model-releasesarxiv-cs-ro

arXiv:2610.01351v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have achieved high task success rates on robot manipulation task benchmarks. More recently, there has been an emphas

ITC-MoE: Importance-guided Token-aware Compression for MoE Diffusion Language Models

arXiv:2610.01296v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) Diffusion Language Models (DLMs) offer flexible parallel decoding and increased model capacity, but their large number of exper

Je suis honoré d’avoir été sélectionné par le premier ministre @MarkJCarney pour rejoindre le nouveau Conseil national sur l’intelligence ar…

model-releasesyoshua-bengio--x

Je suis honoré d’avoir été sélectionné par le premier ministre @MarkJCarney pour rejoindre le nouveau Conseil national sur l’intelligence artificielle, qui aura pour mission de soutenir le Gouvernemen

Jev-IDS: System One Models for Network Intrusion Detection

arXiv:2610.01079v1 Announce Type: cross Abstract: Machine-learning Network Intrusion Detection Systems (IDS) depend on substantial labeled datasets and task-specific training, whereas Large Language M

JevSpawn: Adaptive Agentic Inference through Compositional Action Spaces

arXiv:2610.00437v1 Announce Type: new Abstract: LLM agents generate intermediate reasoning and actions token by token, making extended interactions slow and computationally expensive. Jev-style models

JoinGR: Learning to Traverse Join Graphs for Table Retrieval

arXiv:2610.01064v1 Announce Type: cross Abstract: Retrieving the right tables is a prerequisite for Text-to-SQL over realistic databases. Dense table retrievers rank schema elements independently, but

K-Dense BYOK: An Open-Source AI Research Assistant That Runs Locally and Keeps a Hash-Chained Lab Notebook

arXiv:2610.00074v1 Announce Type: new Abstract: K-Dense BYOK (bring your own keys) is a free, open-source AI research assistant for scientists in any field that runs on the researcher's own computer.

KaliBench: A Fine-Grained Benchmark for Cybersecurity Tool Use on Kali Linux with Runtime-Free Verifiable Rewards

arXiv:2610.02206v1 Announce Type: cross Abstract: LLMs are increasingly applied to cybersecurity workflows, where they are expected to translate analysts' intent into tool invocations. However, existi

Kepler: Auditable World Models for ARC-AGI-3

arXiv:2610.00834v1 Announce Type: new Abstract: ARC-AGI-3 evaluates agents in interactive environments whose rules and objectives must be inferred from observation. We present Kepler, an open-source h

LabBook: Harnessing Experimental History for Efficient LLM-Driven Discovery

arXiv:2610.00675v1 Announce Type: cross Abstract: Evolutionary approaches to LLM-driven discovery often generate new programs from a small set of selected ancestors. This keeps contexts manageable but

Learn to build a custom harness, folks. Mods in Claude Code, DeepSeek Harness, and now Pi Durable. What do these all have in common? Increas…

Learn to build a custom harness, folks. Mods in Claude Code, DeepSeek Harness, and now Pi Durable. What do these all have in common? Increased extensibility. Builders need coding agents and harnesses

model-releasesdair-ai--x

Learning Rate Transfer for Hybrid Transformer-SSM Architectures

arXiv:2610.01172v1 Announce Type: new Abstract: We study learning rate (LR) scaling for hybrid architectures combining Transformer and State-Space Model (SSM) blocks, a class adopted by several recent

Learning to Predict Distributions over Weight Updates for Test-Time Adaptation

arXiv:2610.01934v1 Announce Type: new Abstract: Hypernetworks have recently shown success in dynamically adapting the parameters of Large Language Models (LLMs) at runtime based on signals such as tas

Learning to Sell: Reinforcement Learning for Strategic Large Language Model Agents in Multi-Product Markets

arXiv:2609.33289v2 Announce Type: replace Abstract: Autonomous large language model (LLM) agents operating in multi-product markets must make sequential decisions under information asymmetry and resou

Legal Research Bench: Measuring End-to-End Reliability in Long-Horizon Legal Research Agents

arXiv:2610.00609v1 Announce Type: new Abstract: Legal research is a core and time-consuming legal workflow. Lawyers must identify controlling authority, verify that it remains valid, reconcile statute

Legal text classification in Korean sexual offense cases: from traditional machine learning to large language models with XAI insights

arXiv:2610.00087v1 Announce Type: cross Abstract: The advancement of natural language processing (NLP) has expanded AI-based text classification in the legal domain. However, accurately classifying le

llama, server: add /v1/systemone API (models: laya, julia-1, lev, openjev, kev) by ngxson · Pull Request #29818 · ggml-org/llama.cpp

Now you can jev without jev https://huggingface.co/ggml-org/OpenJev-GGUF https://huggingface.co/ggml-org/lev-GGUF https://huggingface.co/ggml-org/Julia-1-GGUF https://huggingface.co/ggml-org/Laya-GGUF

Looping Beyond Twice: A Scalable Recipe for Looped Mixture-of-Experts

arXiv:2610.01153v1 Announce Type: cross Abstract: Looped Transformers introduce recurrent depth as a new scaling axis for LLMs: by repeatedly applying shared Transformer blocks, they increase effectiv

Lower Bounds for Stochastic First-Order Algorithms with Variance Reduction in Nonconvex--Concave Minimax Optimization

arXiv:2610.01662v1 Announce Type: cross Abstract: We establish complexity lower bounds for stochastic first-order algorithms in nonconvex--concave minimax optimization, allowing algorithms to use vari

M^2Weather: A Benchmark for Joint Multi-Station and Multi-Variable Weather Forecasting

arXiv:2610.00370v1 Announce Type: new Abstract: Station weather forecasting is fundamentally shaped by both complex spatial dependencies across stations and strong physical coupling among weather vari

Madeleine: Learning Involuntary Recall for Conversational Memory from Simulated Lives

arXiv:2610.01118v1 Announce Type: cross Abstract: A long-term conversational assistant must recall the right memory at the right moment, yet the memory that matters most is often not similar to what t

MapLightning: Online Vectorized HD Map Construction with 1D Map Tokens

model-releasesarxiv-cs-cv

arXiv:2610.01905v1 Announce Type: new Abstract: Online vectorized HD map construction is essential for scaling safe autonomous driving and requires accurate, real-time inference. Prior methods typical