Search: “model-releases”

Event Cameras for Melt-Pool Monitoring in Additive Manufacturing: A Benchmark and a Cross-Machine Transfer Analysis

arXiv:2610.06973v1 Announce Type: new Abstract: Melt-pool monitoring is central to qualifying metal additive manufacturing (AM), yet no public event-camera benchmark exists for this domain. Event came

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Model Releases

Evidence-Bound Reasoning: Neuro-Semantic Verification of Biomedical AI in Glioblastoma Radiogenomics

DGX agent

arXiv:2610.08660v1 Announce Type: new Abstract: Background: Biomedical AI can generate plausible explanations without reliably verifying whether each statement is supported by patient-specific evidenc

model-releasesarxiv-cs-cl

7 Oct 2026

Exact-Solution Volume and Length Generalization in Transformers

arXiv:2610.07676v1 Announce Type: cross Abstract: Research on transformer expressivity shows whether a transformer is capable of solving a given task, but gives little indication of whether the soluti

Explore the top AI papers of the week with our brand-new MCP tools. Connect it to Codex, Claude Code, or Grok Bot.

Explore the top AI papers of the week with our brand-new MCP tools. Connect it to Codex, Claude Code, or Grok Bot. Introducing MCP tools for @dair_ai. Connect the MCP to your Codex/Claude/Grok Bot to

model-releasesdair-ai--x

Explore, Then Commit: Measurement-Efficient Scientific Law Discovery with Language Models

arXiv:2610.07620v1 Announce Type: new Abstract: Scientific law discovery requires selecting measurements and converting evidence into a governing equation. We evaluate an explore-then-commit protocol

Extending Music Annotation Schemas: Zero-Shot Prediction or Few-Shot Adaptation?

arXiv:2610.06920v1 Announce Type: cross Abstract: Automatic music annotation is typically tackled under the assumption of a fixed annotation schema. In practice, commercial music catalogs often need t

Extending Pathwise Gradients to Discrete Random Variables via Finite-Order Relaxation

arXiv:2610.07786v1 Announce Type: new Abstract: Pathwise gradients are preferred for continuous random variables because they are unbiased, low variance, and work with a single sample. For discrete va

FactorBench: A Portfolio-Aware Benchmark for Automated Factor Mining

arXiv:2610.06947v1 Announce Type: cross Abstract: Factor mining seeks to discover signals from financial data that predict future asset returns and guide portfolio construction. Automated factor minin

FastH3 V2/V3: Project Status

model-releasesr-stablediffusion

https://preview.redd.it/pr5bl6rcezth1.png?width=834&format=png&auto=webp&s=dca7440c56e169b53a586182368829f848805c9a They released FastH3 V2 three weeks ago: https://www.reddit.com/r/StableDiffusion/co

Federated Bayesian Surveillance of Mechanical Thrombectomy Adverse Events: A Population Risk Layer for Surgical Digital Twins

model-releasesarxiv-cs-ro

arXiv:2610.08464v1 Announce Type: cross Abstract: Learned surgical simulators and world models can roll out plausible procedural futures, but they carry no grounded estimate of how often interventiona

Federated Mixture-of-Experts Alignment on Mobile Edge Networks under Data Heterogeneity

arXiv:2603.21276v2 Announce Type: replace-cross Abstract: The growing demand for on-device large language model (LLM) services on mobile edge devices has driven the adoption of Mixture-of-Experts (MoE

Fine-Tuning VLM for Enhancing AI's Spatial Intelligence: Understanding 3D and 2D Rotations

arXiv:2610.04206v2 Announce Type: replace Abstract: Spatial intelligence is a fundamental skill in multiple domains, such as Science, Technology, Engineering, and Mathematics (STEM), Medicine, Archite

FlowCF: Sparse Counterfactual Explanations for Mixed-Type Tabular Data using Flow Matching

arXiv:2610.08537v1 Announce Type: cross Abstract: In the field of Explainable AI (XAI), counterfactual (CF) explanations interpret a model's decision by suggesting the changes to the input that would

Forensic Reserve: Eliciting Latent Knowledge for Image Forgery Detection

arXiv:2610.08639v1 Announce Type: new Abstract: As generated images become increasingly realistic, reliable forgery detection is essential for maintaining trust in visual information. However, existin

FOSLS-deRhaNN: native de Rham neural classes for H(div) and H(curl) with applications to first-order system least-squares neural network methods for partial differential equations

arXiv:2610.08016v1 Announce Type: cross Abstract: We construct neural approximation classes native to the graph spaces H(div) and H(curl), in two and three dimensions and, for H(div), in any dimension

From the Drosophila Visual Connectome to General-Purpose Computer Vision

arXiv:2610.08418v1 Announce Type: new Abstract: Biological connectomes encode structured solutions to visual computation that may provide reusable inductive biases for artificial vision. We develop Co

GAMEGO: Training Game-Dev Agents with Synthetic Trajectories Anchored in Real-World Assets

arXiv:2610.06910v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have demonstrated remarkable capabilities in web front-end execution, with browser-based game generation

GeneICL: A Tabular Foundation Model for Bulk Transcriptomics

arXiv:2610.08694v1 Announce Type: new Abstract: Gene expression is widely measured in biomedicine, yet clinical outcome prediction remains challenging due to high dimensionality, strong feature correl

Generalizable Dense Reward for Long-Horizon Robotic Tasks

arXiv:2604.00055v2 Announce Type: replace-cross Abstract: Existing robotic foundation policies are trained primarily via large-scale imitation learning. While such models demonstrate strong capabiliti

Geometric Coherence via Weighted Matching for 3D Heterogeneous Multi-Agent Reach-Avoid Games

model-releasesarxiv-cs-ro

arXiv:2610.06882v1 Announce Type: new Abstract: We study assignment quality in 3D heterogeneous multi-agent reach-avoid games and identify a recurring failure mode of cardinality-only matching in geom

GeoPID: Decomposing and Steering Visual Information in Vision-Language Models

arXiv:2610.08401v1 Announce Type: cross Abstract: While recent vision-language models (VLMs) have shown outstanding performance across diverse applications, they tend to under-use visual information a

GIVE-KWS: Gated Injection of Visual Evidence for Noise-Robust Query-by-Example Keyword Spotting

arXiv:2610.07046v1 Announce Type: cross Abstract: Visual speech promises noise-robust keyword spotting, yet a visual stream is not necessarily used. On a tri-modal query-by-example keyword spotting (Q

Gmail. Google Sheets. Slack. Salesforce. i.e. the four horsemen of Monday. On AutomationBench, Mistral Large 4 took on 657 business workflow…

model-releasesmistral-ai--x

Gmail. Google Sheets. Slack. Salesforce. i.e. the four horsemen of Monday. On AutomationBench, Mistral Large 4 took on 657 business workflows across simulated workplace apps, all four included, finish

Google launches Playground, a browser-based, no-code AI game creation platform available to US users aged 18+, powered by Gemini, Nano Banana, and Lyria (Jay Peters/The Verge)

Jay Peters / The Verge: Google launches Playground, a browser-based, no-code AI game creation platform available to US users aged 18+, powered by Gemini, Nano Banana, and Lyria — Google Playground is

model-releasestechmeme

GPT-6 and Intelligent UI, now rolling out in ChatGPT for everyone. Intelligent UI in ChatGPT delivers fast, interactive answers that make ev…

GPT-6 and Intelligent UI, now rolling out in ChatGPT for everyone. Intelligent UI in ChatGPT delivers fast, interactive answers that make everyday questions more visual, complex topics easier to grasp

model-releasesopenai--x

GPU Upgrade advice

model-releasesr-localllama

Upgrade Question If we say the 'budget max' is 1700-1800, and this could include upgrading to a Taichi motherboard: With a new motherboard, no need to bifurcate 1. Would you add a second 5060Ti (16GB)

HARL-A: An Extensible Benchmark Framework for Heterogeneous Multi-Agent Adversarial Reinforcement Learning in IsaacLab

arXiv:2510.01264v2 Announce Type: replace Abstract: Progress in adversarial multi-agent reinforcement learning (MARL) for robotics has been hampered by a lack of shared, extensible infrastructure that

Harmful SFT Leaves a Continuous Trace in LLM Checkpoint Updates

arXiv:2610.07518v1 Announce Type: cross Abstract: Safety auditing of post-trained large language models typically relies on model behavior, requiring model execution and depending on the coverage of a

Harness Engineering for Software Engineering via Modular Executable Dev-Primitives

arXiv:2610.07832v1 Announce Type: cross Abstract: Large language models (LLMs) equipped with terminal access have demonstrated strong capabilities in automating software engineering tasks. However, ex

Have I Seen Enough? Frozen Video-Language Models Encode Evidence Readiness

arXiv:2610.08560v1 Announce Type: cross Abstract: Streaming video-language models must decide not only what to answer, but whether the evidence needed for the current question has arrived. Existing sy

High-dimensional online calibration from harmonic weights

arXiv:2610.07740v1 Announce Type: cross Abstract: We study the online calibration of multidimensional forecasts over an arbitrary convex set YsubseteqR^d relative to an arbitrary error norm |dot|_{L}.

HouseholdBench: Evaluating Large Language Models as Predictors of Household Economic Behavior

arXiv:2610.07563v1 Announce Type: new Abstract: Large language models (LLMs) have the potential to meet a key goal in economics: a quantitative model of household decision making, across a variety of

How Inefficient Is Natural Gradient Descent? From Exact Optimality to Theta ( sqrt{ log d } ) Divergence

arXiv:2610.07228v1 Announce Type: cross Abstract: Natural gradient descent (NGD) underlies common methods in ML. For dually flat families, idealized NGD on the forward Kullback--Leibler objective foll

How Much Evidence Should a Coding Agent's Self-Correction Carry? Adaptive Dirichlet Evidence for Self-Distillation

arXiv:2610.08514v1 Announce Type: new Abstract: Execution feedback lets coding agents revise programs and learn from their own corrections. A correction's learning weight should reflect both the trans

How Well Do LLMs Reason with Noisy Evidence? An Active Visual Reasoning Benchmark

arXiv:2610.07751v1 Announce Type: new Abstract: Real-world reasoning rarely reduces to static question answering: agents must actively gather information from tools and sensors that are often noisy an

Humanoid Horizon: Extending Task Horizon in Whole-Body Loco-Manipulation via Parallel Training, Dynamic Starting, and Reward Gating

model-releasesarxiv-cs-ro

arXiv:2610.08320v1 Announce Type: new Abstract: Cluttered indoor environments, where large and heavy objects are scattered across diverse surfaces, require humanoid robots to sequentially navigate, gr

I re-trained the DFlash 2 drafter for Ternary Bonsai 2 27B: 2.2x on an L4 (3.2x on code edits with ngram lookup), 1.5x on a Mac, 1.2x in Chrome

model-releasesr-localllama

PrismML's Ternary Bonsai 2 27B fits a 24 GB card or Mac, but decodes at ~30 tok/s on an L4 and ~21 on an M4 Pro. z-lab's DFlash 2 drafter was trained on bf16 Qwen3.8-27B, so it guesses worse on the te

I released an LLM plugin for sending prompts to OpenAI's new Jev-clone decision model that's based on GPT-6 Luna https://simonwillison.net/2…

model-releasessimon-willison--x

Simon Willison released the **“llm-openai-decisions”** plugin (version 0.1a0) on October 7 , 2026. The lightweight library lets developers send prompts directly to OpenAI’s new Jev‑clone decision mode

Identity-Conditioned Score Fusion for Open-Set Person Re-Identification

arXiv:2610.07366v1 Announce Type: new Abstract: Robust person re-identification often combines complementary cues such as face, gait, and body shape. While adaptive fusion typically targets query qual

Image Bitstream Fine-grained Understanding for Privacy-Friendly AIoT

arXiv:2610.08414v1 Announce Type: new Abstract: Image Bitstream Fine-grained Understanding (IBFU) aims to directly perform fine-grained classification and semantic description generation from encoded

ImpactMat: Continuous Material Estimation for Inverse Impact Sound Rendering

arXiv:2610.07061v1 Announce Type: cross Abstract: Impact sound rendering synthesizes the sound produced when a 3D object is struck, but practical renderers often rely on fixed material presets such as

Improving Mixup Calibration with Wasserstein Distributionally Robust Optimization

arXiv:2506.17874v3 Announce Type: replace-cross Abstract: In many real-world applications, ensuring the robustness and stability of deep neural networks (DNNs) is crucial, particularly for image class

Improving Synthetic Data Generation for Argument Mining via Adversarial Reinforcement Learning

arXiv:2610.07699v1 Announce Type: cross Abstract: Argument Mining (AM) is fundamentally constrained by the scarcity of high-quality structure-annotated datasets. While LLMs have shown promise in synth

Independent Multi-Agent Reinforcement Learning with Counterfactual Semantic-Social World Models

arXiv:2610.07704v1 Announce Type: cross Abstract: Fully decentralized multi-agent reinforcement learning (MARL), also referred to as independent learning, requires each agent to learn and act using on

Interpretable Hypergraph Learning via Neural Additive Models

arXiv:2610.07458v1 Announce Type: new Abstract: Hypergraphs offer a natural framework for modeling networked data, where dependencies among entities are governed by higher-order interactions. While hy

Introducing Claude Haiku 5.5

model-releasessimon-willison

As previously promised, here's Anthropic's new fast, low cost model: Introducing Claude Haiku 5.5. The previous Haiku, 4.5, was very much showing its age. It came out almost a year ago, and was priced

Introducing Claude Haiku 5.5 on AWS

model-releasesaws-ml-blog

Claude Haiku 5.5 is now available on Amazon Bedrock and Claude Platform on AWS. According to Anthropic, it is the fastest, most efficient model in the Claude 5.5 family, built for subagents and high-v

Introducing Google Cloud’s U4 compute: Enabling ultra-low latency trading

model-releasesgoogle-cloud-ai

In capital markets, operational success is built on predictable performance and low latency, where even tiny variations in packet timing alter queue priority and trade execution. At the same time, bot