All entries

arXiv:2601.17753v2 Announce Type: replace Abstract: Research keyloggers are essential for cognitive studies of text production, yet most fail to capture the on-screen transformations performed by Inpu

applicationsarxiv-cs-cl

HyperGS: Fast and Generalizable Gaussian Video Representation

DGX agent

arXiv:2607.11500v2 Announce Type: replace Abstract: Gaussian Splatting has emerged as an effective representation for video, but existing methods rely on per-video optimization. This leads to slow enc

model-releasesarxiv-cs-cv

4 Aug 2026

HyperODE: Zero-Shot Surrogate for Simulation and Inference of Dynamical Systems

model-releasesarxiv-cs-lg

arXiv:2608.00852v1 Announce Type: new Abstract: Understanding and controlling complex dynamical systems often requires executing thousands of numerical simulations across vast parametric landscapes, w

Hyperparameter Transfer Laws for Non-Recurrent Multi-Path Neural Networks

arXiv:2602.07494v2 Announce Type: replace Abstract: Deeper modern architectures are costly to train, making hyperparameter transfer preferable to expensive repeated tuning. Maximal Update Parametrizat

Local Ai

I added a verify-before-load safety check for Ollama models

I maintain llm-checker, and I’ve added structural model-file validation for Ollama. Ollama stores downloaded models as local blobs. If one is truncated, malformed, or has invalid internal offsets, you

local-air-ollama

I benchmarked the 4 models I had pulled. The 1.1GB one beat the 2GB one at math and lost badly at extraction.

152 generations, deterministic grading (exact number/string/JSON/regex), no LLM judge on my 16GB laptop. task type | deepseek-r1:1.5b (1.1GB) | llama3.2:3b (2.0GB) | gemma:2b | codellama 7b arithmetic

model-releasesr-ollama

I built a DwarfStar-inspired Vulkan/Metal inference engine for Qwen3.6-35B-A3B on 16 GB machines

Disclosure: I’m the author and maintainer of QuarkStar. I built QuarkStar, a small native inference engine inspired by Antirez’s DwarfStar. QuarkStar currently supports: Qwen3.6-35B-A3B, using the sam

IACM-RL: Intent-Aware Context Management and Reinforcement Learning for Complex Tool Invocation under Dynamic Intent Fluctuations

arXiv:2608.02110v1 Announce Type: new Abstract: Executing long-horizon tool invocations in real-world environments is severely challenged by dynamic user intent noise. Existing methods attempt robustn

safetyarxiv-cs-cl

Identifiability-Aware Source Apportionment in City-Scale Advection-Diffusion Systems

arXiv:2608.00050v1 Announce Type: cross Abstract: Source apportionment from sparse urban air-quality sensors is an inverse problem limited by sensor placement, wind-driven transport, background variat

IDraw: Artist Verification from Digital Drawing Images

arXiv:2608.01737v1 Announce Type: new Abstract: As digital drawings are increasingly shared online, reliable authorship verification has become important for protecting artists and resolving disputes.

If you missed today's K3 on Fireworks webinar, we've got you covered. We'll be partnering with @arizeai to chat more models on Thursday, Aug…

model-releasesfireworks-ai--x

If you missed today's K3 on Fireworks webinar, we've got you covered. We'll be partnering with @arizeai to chat more models on Thursday, August 6th. Sign up below! Next session, August 6 we'll be co l

Illuminating Visual Identity in Universal Multimodal Embeddings

model-releasesarxiv-cs-cl

arXiv:2608.01794v1 Announce Type: cross Abstract: Universal Multimodal Embeddings (UMEs) aim to unify various modalities and tasks into a shared representation space. In recent years, this field has w

Image-Space Rule Discovery

arXiv:2608.00490v1 Announce Type: new Abstract: Can image-editing models discover visual rules in image space and complete problem-solving end-to-end? We tackle this question in the spirit of a human

iMontage: Unified, Versatile, Highly Dynamic Many-to-many Image Generation

arXiv:2511.20635v3 Announce Type: replace Abstract: Pre-trained video models learn powerful priors for generating high-quality, temporally coherent content. While these models excel at temporal cohere

tutorialsarxiv-cs-cv

Applications

Implicit Neural Representations for Multimodal Longitudinal Image Imputation and Interpolation

arXiv:2608.02324v1 Announce Type: new Abstract: Longitudinal multiparametric MRI is central to follow-up imaging in oncology, yet real-world clinical data are characterised by missing sequences, heter

applicationsarxiv-cs-cv

inclusionAI/Ling-3.0-flash · Hugging Face

The Ling-3.0-flash MoE is now open-weighted at 124B A5B params. I know the original announcements were before the Kimi K3, DeepSeek-V4-Flash and Qwen3.8 hype, but this model might still have a good ni

inclusionAI/Ling-3.0-flash weights are up on Hugging Face — MIT, BF16 plus an official FP8

Went public in the last few minutes, both repos ungated. Ling-3.0-flash, BF16, 24 shards, ~255GB Ling-3.0-flash-fp8, official FP8, ~128GB 127.5B total, they quote 5.1B active. What jumped out at me in

Inference-Time Policy Alignment for Fair Reinforcement Learning

arXiv:2608.00175v1 Announce Type: new Abstract: Deep reinforcement learning (RL) agents achieve strong performance by optimizing scalar reward functions. However, once deployed, the policies of these

safetyarxiv-cs-lg

Applications

Inferring Relative Consequences of Mechanical Ventilation from Observational Data Using Game-Based Comparisons

arXiv:2510.15127v3 Announce Type: replace-cross Abstract: Identifying the effects of mechanical ventilation (MV) protocols in critical care requires analyzing data from heterogeneous patient-ventilato

applicationsarxiv-cs-lg

InfiniSplat: Implicit Gaussian Decoding for Large-Baseline Monocular View Synthesis

arXiv:2608.02437v1 Announce Type: new Abstract: Single-image feed-forward 3D Gaussian Splatting (3DGS) aims to directly generate a renderable 3D scene representation from one input image, avoiding the

Information-Theoretic Foundations for Machine Learning

arXiv:2407.12288v5 Announce Type: replace-cross Abstract: The progress of machine learning over the past decade is undeniable. In retrospect, it is both remarkable and unsettling that this progress wa

tutorialsarxiv-cs-lg

InstancePin: Instance-Addressable Layout-to-Image Diffusion via Coordinate Pinning

arXiv:2608.00588v1 Announce Type: new Abstract: Layout-to-image diffusion models have achieved impressive semantic controllability by conditioning generation on category-level segmentation maps. Howev

Instruction-Conditioned Exploration with Asymmetric Reinforcement Learning and Self-Distillation

arXiv:2608.02087v1 Announce Type: cross Abstract: Post-training Large Language Models (LLMs) with Reinforcement Learning (RL) has become an important tool for improving model capabilities, but the LLM

safetyarxiv-cs-cl

Intention Inference Under Execution Noise: Separating Aleatoric and Epistemic Uncertainty in Social Dilemmas

arXiv:2608.02440v1 Announce Type: cross Abstract: In noisy social dilemmas, intended actions are stochastically corrupted before execution, so an observed defection may reflect hostile intent or actio

Interaction Dynamics MPC for Knee Rehabilitation Exoskeletons: A Closed-Loop SEA Outer-Loop Study

arXiv:2606.13485v3 Announce Type: replace-cross Abstract: Safe rehabilitation is an interaction-dynamics problem: the controller must regulate a prescribed motion while absorbing involuntary spasm, vo

safetyarxiv-cs-ro

Interaction Is Not Necessary for Order-Optimal 1-Bit Mean Estimation

arXiv:2608.02538v1 Announce Type: cross Abstract: This paper is concerned with one-bit mean estimation, where each independent sample is represented by a single binary message. We consider distributio

InteracVid: Building a Real Interactive Audio-Visual Response Dataset from Live-Chat Videos

arXiv:2608.01157v1 Announce Type: new Abstract: Large language models have made text the default medium for human--AI interaction, buttext alone cannot express the full range of responses required by

Agents

Intern-S1-MO: Long-horizon Reasoning Agent for Olympiad?Level Mathematical Problem Solving

arXiv:2512.10739v3 Announce Type: replace Abstract: Large Reasoning Models (LRMs) have expanded the mathematical reasoning frontier through Chain-of-Thought (CoT) techniques and Reinforcement Learning

agentsarxiv-cs-cl

Interpretability-Guided Soft Pruning of Attention Heads in Vision Transformers

arXiv:2608.00264v1 Announce Type: new Abstract: Vision foundation models, such as DINOv2, learn highly expressive representations but rely on massive, opaque architectures that demand substantial comp

tutorialsarxiv-cs-cv

Interpretable machine learning for predicting splitting strength of asphalt concrete: insights from SHAP analysis

model-releasesarxiv-cs-lg

arXiv:2608.00956v1 Announce Type: new Abstract: This paper presents an interpretable machine-learning framework for predicting the splitting strength (ST) of asphalt concrete and supporting data-drive

Interpretable Machine Learning for Traffic Congestion Prediction: Unveiling the Impact of Different COVID-19 Periods

model-releasesarxiv-cs-lg

arXiv:2608.01180v1 Announce Type: new Abstract: Traffic congestion prediction is essential for congestion mitigation, but the COVID-19 pandemic and related control measures altered travel behavior and

Interpretable MEG Decoding of Perceived Speech: Cortical Sources and the Stimulus Features That Drive Retrieval

arXiv:2608.01481v1 Announce Type: new Abstract: Short segments of perceived speech can be retrieved from non-invasive magnetoencephalographic (MEG) recordings by deep networks trained with a CLIP-styl

Interpretable Recognition of Cognitive Distortions in Natural Language Texts

arXiv:2511.05969v2 Announce Type: replace Abstract: We propose a new approach to multi-factor classification of natural language texts based on weighted structured patterns such as N-grams, taking int

researcharxiv-cs-cl

Introducing Database Operations Agents: The future of autonomous database management

model-releasesgoogle-cloud-ai

As part of the Agentic Data Cloud launch at Google Cloud Next ‘26, we announced two AI-powered database agents to simplify database management. These include the Database Onboarding Agent for Day 0 op

🛡️Introducing Shieldstral, Mistral’s 3B open-weights model for content safety that can be deployed on-device 🧵 http://mistral.ai/news/shie…

model-releasesmistral-ai--x

Mistral AI introduced Shieldstral, a 3‑billion‑parameter, open‑weights model designed for content‑safety tasks and capable of on‑device deployment. The announcement was shared via a tweet from @Mistra

Introducing Web Search on Amazon Bedrock for foundation model grounding

Today, we are introducing the general availability of Web Search on Amazon Bedrock. It is a server-side built-in tool that grounds model responses in current web knowledge. With Web Search, grounding

tutorialsaws-ml-blog

Investigating Social Bias in Narrative Image Generation

arXiv:2608.01780v1 Announce Type: new Abstract: Text-to-image (T2I) generation models are increasingly embedded in applications such as media content creation and education, raising concerns about how

safetyarxiv-cs-cv

Invisible Ink Threats: Adversarial Goals Behind Legitimate Tasks in Computer-Use Agents

arXiv:2608.02018v1 Announce Type: new Abstract: Computer-use agents (CUAs), which empower large language models to autonomously operate operating systems and the web, are increasingly vulnerable to in

safetyarxiv-cs-cv

IoU-PD: IoU-Aware Privileged Distillation for Visual Grounding with Multimodal Large Language Models

arXiv:2607.15732v2 Announce Type: replace Abstract: Visual grounding with multimodal large language models is commonly formulated as autoregressive coordinate generation, where a model outputs boundin

Is LM Studio abandoning their core product?

Some of you may be aware that a few weeks ago, LM Studio announced a new agent, Bionic. This is pretty much an agentic harness for both local models and paid cloud models. But most aren't aware that L

Isotonic Bradley-Terry Model for Paired Comparison Data

arXiv:2608.02081v1 Announce Type: new Abstract: In this paper, we study prediction problems for paired comparison data, for example, predicting the win probability between two unmatched players and ra

tutorialsarxiv-cs-lg

Agents

Israeli startup Zenity bags $125M in funding to build the security layer for AI agents

Artificial intelligence security startup Zenity Ltd. said today it has closed on a 125 million Series C round of funding to expand its platform, which secures autonomous agents in production across la

agentssiliconangle

ISRS-DETR: Detection-Guided Click Propagation for Remote Sensing Interactive Segmentation

arXiv:2608.02468v1 Announce Type: new Abstract: Interactive segmentation reduces the prohibitive cost of pixel-level annotation by allowing users to delineate objects with a few clicks. However, apply

It's the Decoding Format, Not the Perturbation: Auditing Consistency-Based Selection for Vision-Language Test-Time Scaling

arXiv:2608.01207v1 Announce Type: new Abstract: Test-time scaling lifts large language model reasoning by sampling many candidate solutions and selecting among them, yet the same recipe transfers poor

JADE-GS: Joint Allocation of Deblurring Evidence for Event-Assisted 3D Gaussian Splatting

arXiv:2607.14990v2 Announce Type: replace Abstract: Neural radiance fields and 3D Gaussian Splatting assume that each training image is a sharp and geometrically consistent observation of the scene. M

June launches with $20M to speed up enterprise software projects

model-releasessiliconangle

June.ai Technologies Inc., a startup that uses artificial intelligence to modernize enterprise software environments, launched today with 20 million in funding. The pre-seed round was led by Time Vent

Just on Time: Token-Level Early Stopping for Diffusion Language Models

arXiv:2602.11133v2 Announce Type: replace-cross Abstract: Diffusion language models generate text through iterative refinement, a process that is often computationally inefficient because many tokens

researcharxiv-cs-cl

Local Ai

K-space Gaussian Representation for Parallel MRI

arXiv:2608.00075v1 Announce Type: new Abstract: Accelerated magnetic resonance imaging (MRI) aims to recover the k-space signal from acquired measurements, where accurate estimation of missing samples

local-aiarxiv-cs-cv