model releases

Patch-based Memory Gate Model in Time Series Foundation Model

arXiv:2509.18751v4 Announce Type: replace Abstract: Recently reconstruction-based deep models have been widely used for time series anomaly detection, but as their capacity and generalization capabili

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Physics-Informed Implicit Neural Representations for Improved Myocardial Perfusion MRI Quantification

DGX agent

arXiv:2608.11282v1 Announce Type: cross Abstract: Quantifying myocardial perfusion from cardiac magnetic resonance (CMR) can be achieved by fitting tracer-kinetic models to the dynamic contrast-enhanc

model-releasesarxiv-cs-ai

13 Aug 2026

Poor Man's Agentic Modeling: Simulating Large LLM-Agent Societies on a Laptop

arXiv:2608.11215v1 Announce Type: new Abstract: Simulating societies of many large language model (LLM) agents is expensive, yet the questions asked of such simulations are usually macroscopic: phase

Powered by @Cerebras, Ultrafast generates up to 750 tokens per second, bringing our most intelligent model to products and workflows where e…

Powered by @Cerebras, Ultrafast generates up to 750 tokens per second, bringing our most intelligent model to products and workflows where every second counts. Ultrafast is designed for businesses whe

model-releasesopenai--x

Previewing Ultrafast mode: GPT-5.6 Sol at up to 14x the speed. Launching first in the OpenAI API to a select group of customers with expande…

On Aug 13 2026, OpenAI announced a preview of its “Ultrafast” mode for the GPT‑5.6 model, called Sol, which claims inference speeds up to 14× faster than current releases. The feature is initially rol

model-releasesopenai--x

Program Semantic Inequivalence Game with Large Language Models

arXiv:2505.03818v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) can achieve strong performance on everyday coding tasks, but they can fail on complex tasks that require non-triv

Qdrant and Minima Deliver 2.92x More Agentic RAG Tasks per GPU-Hour

Reducing Retrieval and Calls When a retrieval-augmented generation (RAG) agent runs, it often has to plan a search, check the evidence it gets back, and try again when that evidence falls short. Those

model-releasesqdrant

Qwen-MusicAVQA-7B: A Multimodal Model for Music Audio-Visual QA

arXiv:2608.11329v1 Announce Type: cross Abstract: A common approach to adding audio to a vision-language model is to train or adapt a large omni-modal system. We show that a lightweight alternative ca

Qwen3.8 2.4T UD-Q1_0 - 178 token generation - 11 min 38s - 0.25 tokens/sec

model-releasesr-localllama

https://preview.redd.it/nqr9nj5028jh1.png?width=1516&format=png&auto=webp&s=47af40a0737429dc65f2e455b87b2db81725cb14 So I wanted to see... is it possible/viable to run this perhaps once in a while som

RealisticTritonBench: A Benchmark for Triton-Kernel Generation in Real-World AI Frameworks

arXiv:2608.12004v1 Announce Type: cross Abstract: In modern AI frameworks, GPU kernels are key to overall system performance. Combining usability, portability, and near-handwritten CUDA performance, T

RECAST: A Machine-Learning Framework for Correction and Super-Resolution of Coarse-Grid PDE Solvers

arXiv:2608.11572v1 Announce Type: new Abstract: Coarse-grid numerical solvers can substantially reduce the computational cost of time-dependent PDE simulation, but under-resolution often degrades both

RecSys Factory: Bounding LLM Agent Autonomy to Decision Points in the Industrial Recommender Lifecycle

arXiv:2608.11241v1 Announce Type: new Abstract: Deploying LLM agents into industrial recommender operations exposes a three-way tension we frame as the autonomy-determinism-efficiency trilemma: genera

Reducing Per-Sample Interference in Stochastic Optimization

arXiv:2607.16261v2 Announce Type: replace-cross Abstract: Modern optimizers combine gradients from the current mini-batch with historical optimization state, such as momentum or adaptive moments. Whil

Reinforcement Learning based DBMS Buffer Pool Auto-Tuning for Optimal Memory Utilization

arXiv:2608.11239v1 Announce Type: cross Abstract: Administering Database Management Systems (DBMS) instances requires Database Administrators (DBA) to balance performance in terms of Service Level Agr

Reliable Inference in Edge-Cloud Model Cascades via Conformal Alignment

arXiv:2510.17543v3 Announce Type: replace Abstract: Edge intelligence enables low-latency inference via compact on-device models, but assuring reliability remains challenging. We study edge-cloud casc

Representation Finetuning for Continual Learning

arXiv:2603.11201v3 Announce Type: replace-cross Abstract: The world is inherently dynamic, and continual learning aims to enable models to adapt to ever-evolving data streams. While pre-trained models

Repurposing RGB-based Foundation Model for Depth Estimation on Thermal Images Using Hierarchical Supervision

arXiv:2608.11564v1 Announce Type: new Abstract: Depth estimation from thermal images is highly valuable for robotic applications in adverse conditions, such as nighttime and rainy weather. Recent stud

Retrofitting Recurrent Depth into a Pretrained Language Model: Installation, Extrapolation, Transfer, and Retention at Two Parameter Budgets

arXiv:2608.11233v1 Announce Type: cross Abstract: A dense, pretrained language model can be retrofitted with recurrent depth and learn an iterative latent transition that persists after outcome-only a

Retry, Switch, or Abstain? Learning Strategy-Aware Tool-Use Policies via Controlled Error Injection

arXiv:2608.11977v1 Announce Type: new Abstract: Tool-using LLM agents are commonly trained and evaluated in environments where tool calls succeed reliably, yet deployed tools can fail transiently, per

ReXrank: A Public Leaderboard for AI-Powered Radiology Report Generation

arXiv:2411.15122v2 Announce Type: replace-cross Abstract: AI-driven models have demonstrated significant potential in automating radiology report generation for chest X-rays. However, there is no stan

RoadWeaver: Large-Scale Lane-Level HD Map Generation from Scratch for Autonomous Driving Simulation

arXiv:2608.11580v1 Announce Type: cross Abstract: Autonomous driving simulation requires diverse and scalable lane-level HD maps to support long-horizon evaluation across complex road networks. Existi

RoboHarness: A Memory-Augmented Policy Harness for Vision-Language-Action Model Robustness via In-Context Adaptation

model-releasesarxiv-cs-ro

arXiv:2603.24060v3 Announce Type: replace Abstract: Despite the promise of Vision-Language-Action (VLA) models as generalist robotic controllers, their robustness against perceptual noise and environm

Robust and Efficient Noisy-Label Time-Series Classification via Dynamic Time Warping Based Granular Ball Computing

arXiv:2608.11704v1 Announce Type: cross Abstract: Dynamic Time Warping (DTW)-based Nearest-Neighbor (NN) classifiers are effective for time-series classification but are vulnerable to mislabeled train

Rubric Dropout: A Simple Way to Mitigate Reward Hacking in Rubric-as-Reward RL

arXiv:2608.11669v1 Announce Type: cross Abstract: Reinforcement learning against rubrics, lists of criteria graded by an LLM judge, has become a standard way to post-train language models on tasks wit

SAG: SQL-Retrieval Augmented Generation with Query-Time Dynamic Hyperedges

model-releasesarxiv-cs-cl

arXiv:2608.12129v1 Announce Type: new Abstract: While retrieval-augmented generation (RAG) has proven effective at giving LLMs access to external knowledge, mainstream dense-retrieval implementations

SCOPE-Router: Cost-Aware Open-Set VLM Routing for Execution-Oriented Tasks

arXiv:2608.12127v1 Announce Type: new Abstract: Model routing aims to select the most suitable model from a candidate pool for each query, balancing quality and cost. Existing VLM routing research is

SegPAR: Class-Centric Decision-Based Sparse Attack for Semantic Segmentation

arXiv:2608.11285v1 Announce Type: cross Abstract: Despite the practical relevance of sparse decision-based black-box threats, they have received limited attention in semantic segmentation. To bridge t

Self-Evolving Code-with-Image Reasoning

arXiv:2608.11292v1 Announce Type: new Abstract: Multimodal models increasingly reach for tools when solving visual tasks (crop, zoom, rotate, brighten), a paradigm known as thinking-with-images. The c

Self-Evolving Embodied Agents via Skill-Harness Evolution

model-releasesarxiv-cs-cl

arXiv:2608.11350v1 Announce Type: new Abstract: Embodied agents are increasingly built as systems around foundation models, where performance depends not only on model weights but also on the skills,

Self-Harness: Harnesses That Improve Themselves

model-releasesarxiv-cs-cl

arXiv:2606.09498v2 Announce Type: replace Abstract: The performance of LLM-based agents is jointly shaped by their base models and the harnesses that mediate their interaction with the environment. Be

Semantic Lenia: Emergence of Homeostatic Solitons within the Semantic Space of Large Language Models

arXiv:2608.11657v1 Announce Type: cross Abstract: We introduce Semantic Lenia, an artificial life framework that transforms Large Language Model (LLM) inference from a static optimization problem into

SenseNova-Vision: a 7B open model that does segmentation, depth, detection, OCR, and 3D reconstruction with no task-specific heads

model-releasesr-localllama

Stumbled across this new vision model, SenseNova-Vision. It's a 7B MoT model, Apache 2.0 license, which is cool. The main idea is it treats pretty much all computer vision stuff as just one generation

SoftWater: Class-Aware Rate Allocation for Softmax Quantization

arXiv:2608.12026v1 Announce Type: new Abstract: Post-training quantization pipelines routinely leave the softmax output layer in high precision. Yet in small LLMs with modern vocabularies, the head ho

SpaceXAI releases flagship Grok 4.6 model with advanced reasoning capabilities

model-releasessiliconangle

SpaceXAI today released Grok 4.6, a large language model that it says can outperform Anthropic PBC’s Claude Fable 5 in some areas. SpaceXAI was known as xAI until last month. The Elon Musk-founded art

SteeringSafety: Benchmarking Representation Steering in LLMs Across Safety Perspectives

arXiv:2509.13450v3 Announce Type: replace Abstract: We introduce SteeringSafety, a benchmark for evaluating representation steering methods across nine safety perspectives spanning 18 datasets. While

StellaVLA: In-Context Structured Demonstration for Generalizable Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2608.11671v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models can follow instructions and manipulate objects, but their performance often collapses out of distribution (OOD), whe

Surfsvr: 2D Surface Priors as 3D Geometric Regularizers for Sparse Voxel Reconstruction

arXiv:2608.11938v1 Announce Type: new Abstract: Sparse voxel reconstruction offers an efficient representation for high-fidelity 3D modeling, yet its geometry is commonly optimized from local photomet

TangPoetryBench: A Multi-Dimensional Benchmark and Rubric-Conditioned Evaluator for Poetry-to-Image Generation

arXiv:2608.11452v1 Announce Type: cross Abstract: Text-to-image (T2I) models are increasingly asked to illustrate literary and cultural content, yet we cannot measure how well an image renders the mea

Test-Time Hallucination Control in Large Vision-Language Models

arXiv:2608.11474v1 Announce Type: new Abstract: Object Hallucination in large vision-language models (LVLMs), where models generate non-factual content about input images, remains a critical barrier t

The Next Challenge for Agentic Cybersecurity: A Realistic, Contamination-Free Reverse Engineering Benchmark

arXiv:2608.11469v1 Announce Type: cross Abstract: AI agents are rapidly improving in cybersecurity capabilities when the source code is available for analysis, yet much of the software most consequent

The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy

arXiv:2607.11175v2 Announce Type: replace Abstract: The growing ability of large language models and vision-language models to jointly interpret and reason over images and text is reshaping medical im

The top 10% of enterprises use plugins twice as often and skills six times as often as typical firms. These frontier firms are not ahead by …

According to a Twitter post by OpenAI on August 13, 2026, the top 10% of enterprises adopt AI plugins twice as frequently and leverage skills—such as model‐based knowledge and reasoning—six times more

model-releasesopenai--x

The Wording Effect: Quantifying Two-Way Drift in LLM Benchmark Performance

arXiv:2608.11694v1 Announce Type: cross Abstract: A benchmark score comes from a single phrasing of each problem. That single phrasing is treated as if it stood for the whole space of ways the same pr

This week we launched the world's most accurate document extraction agent over real-world documents. Introducing LlamaExtract Agentic Plus …

model-releasesjerry-liu--x

This week we launched the world's most accurate document extraction agent over real-world documents. Introducing LlamaExtract Agentic Plus 💫 . It is a complete document extraction model+harness engine

Towards an approach to multivariate outlier detection for District Heating System data

arXiv:2608.11375v1 Announce Type: new Abstract: In this paper, we test different methods for multivariate detection of outliers in the data of transmitted heat energy in the selected substation of loc

Towards Query-Agnostic RAG Evaluation via Query Coverage and Claim Verifiability

arXiv:2608.11238v1 Announce Type: new Abstract: Retrieval-augmented generation improves the factuality of large language models by grounding responses in retrieved evidence, yet existing evaluation fr

TRACE Bench: Task-driven Roleplay Agentic Checklist Evaluation

arXiv:2608.11236v1 Announce Type: cross Abstract: Roleplay evaluation should do more than assign a single score: it should reveal which role requirements were tested, which failed, and which dialogue

TRACES: A Benchmark for Epistemic Reliability in Scientific Reasoning by LLMs

arXiv:2608.11415v1 Announce Type: cross Abstract: Large language models are being proposed as agents in scientific workflows, in domains where no downstream verifier exists. Such deployment assumes th