Search: “models”

When training Grok 4.3, we spoke directly with devs and businesses to understand what they actually needed: a model that’s fast, affordable,…

model-releaseselon-musk--x

When training Grok 4.3, we spoke directly with devs and businesses to understand what they actually needed: a model that’s fast, affordable, and great at tool calling. The result is a daily driver tha

1 May 2026

Model Releases

5/5 Maestro automatically searches across this space (model ensembles, scaling strategies, execution policies), maps the Pareto frontier, an…

DGX agent

5/5 Maestro automatically searches across this space (model ensembles, scaling strategies, execution policies), maps the Pareto frontier, and surfaces the full accuracy–cost–latency tradeoff surface.

model-releasesai21-labs--x

30 Apr 2026

ACPO: Anchor-Constrained Perceptual Optimization for Diffusion Models with No-Reference Quality Guidance

arXiv:2604.26348v1 Announce Type: cross Abstract: Diffusion models have achieved remarkable success in image generation, yet their training is predominantly driven by full-reference objectives that en

Decoupled Prototype Matching with Vision Foundation Models for Few-Shot Industrial Object Detection

model-releasesarxiv-cs-cv

arXiv:2604.26404v1 Announce Type: new Abstract: Industrial object detection systems typically rely on large annotated datasets, which are expensive to collect and challenging to maintain in industrial

Delineating Knowledge Boundaries for Honest Large Vision-Language Models

arXiv:2604.26419v1 Announce Type: cross Abstract: Large Vision-Language Models (VLMs) have achieved remarkable multimodal performance yet remain prone to factual hallucinations, particularly in long-t

Industry

Elon Musk confirms xAI used OpenAI’s models to train Grok

In a federal courtroom in California on Thursday, Elon Musk testified that his own AI startup, xAI, has used OpenAI's models to improve its own. The matter at question is model distillation, a common

industrythe-verge-ai

Lifting Embodied World Models for Planning and Control

arXiv:2604.26182v1 Announce Type: cross Abstract: World models of embodied agents predict future observations conditioned on an action taken by the agent. For complex embodiments, action spaces are hi

safetyarxiv-cs-ai

Mistral AI made the TIME100 Most Influential Companies list for 2026 — and the top 10 for AI. Why we're proud: customers run frontier models…

model-releasesmistral-ai--x

Mistral AI made the TIME100 Most Influential Companies list for 2026 — and the top 10 for AI. Why we're proud: customers run frontier models in production on their own terms, on their own infrastructu

PEOPLE ARE NOW RUNNING CLAUDE CODE WITH LOCAL AI MODELS TO AVOID API COSTS. By connecting tools like Ollama and Gemma 4, developers can buil…

PEOPLE ARE NOW RUNNING CLAUDE CODE WITH LOCAL AI MODELS TO AVOID API COSTS. By connecting tools like Ollama and Gemma 4, developers can build apps locally with unlimited usage and no monthly billing.

model-releasesollama--x

PPG-Based Affect Recognition with Long-Range Deep Models: A Measurement-Driven Comparison of CNN, Transformer, and Mamba Architectures

arXiv:2604.26078v1 Announce Type: new Abstract: Photoplethysmography (PPG) is increasingly used in wearable affective computing due to its low cost and ease of integration into consumer devices. Recen

Progressive Semantic Communication for Efficient Edge-Cloud Vision-Language Models

arXiv:2604.26508v1 Announce Type: cross Abstract: Deploying Vision-Language Models (VLMs) on edge devices remains challenging due to their substantial computational and memory demands, which exceed th

q3-MuPa: Quick, Quiet, Quantitative Multi-Parametric MRI using Physics-Informed Diffusion Models

arXiv:2512.23726v2 Announce Type: replace-cross Abstract: The 3D fast silent multi-parametric mapping sequence with zero echo time (MuPa-ZTE) is a novel quantitative MRI (qMRI) acquisition that enable

Risk Reporting for Developers' Internal AI Model Use

arXiv:2604.24966v1 Announce Type: cross Abstract: Frontier AI companies first deploy their most advanced models internally, for weeks or months of safety testing, evaluation, and iteration, before a p

safetyarxiv-cs-ai

Train a TensorFlow object detection model – then deploy it on a robot 🤖 Iulia Feroli (@iuliaferoli) shows how to turn a notebook into a rea…

model-releasesclem-delangue--x

Train a TensorFlow object detection model – then deploy it on a robot 🤖 Iulia Feroli (@iuliaferoli) shows how to turn a notebook into a real-time object detection app. This tutorial works for any proj

Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising

arXiv:2604.26694v1 Announce Type: cross Abstract: We propose X-WAM, a Unified 4D World Model that unifies real-time robotic action execution and high-fidelity 4D world synthesis (video + 3D reconstruc

VLN-Cache: Enabling Token Caching for VLN Models with Visual/Semantic Dynamics Awareness

arXiv:2603.07080v3 Announce Type: replace-cross Abstract: Vision-and-Language Navigation (VLN) increasingly relies on large vision-language models, but their inference cost conflicts with real-time de

we're starting rollout of GPT-5.5-Cyber, a frontier cybersecurity model, to critical cyber defenders in the next few days. we will work with…

model-releasessam-altman--x

we're starting rollout of GPT-5.5-Cyber, a frontier cybersecurity model, to critical cyber defenders in the next few days. we will work with the entire ecosystem and the government to figure out trust

// When to Retrieve During Reasoning // Pay attention to this one, AI devs. (bookmark it) Most RAG systems retrieve once, before the model s…

// When to Retrieve During Reasoning // Pay attention to this one, AI devs. (bookmark it) Most RAG systems retrieve once, before the model starts reasoning. Large reasoning models like o1 and R1 don't

safetydair-ai--x

Carbon-Taxed Transformers: A Green Compression Pipeline for Overgrown Language Models

arXiv:2604.25903v1 Announce Type: cross Abstract: The accelerating adoption of Large Language Models (LLMs) in software engineering (SE) has brought with it a silent crisis: unsustainable computationa

safetyarxiv-cs-lg

CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding

arXiv:2602.01785v2 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved remarkable success in source code understanding, yet as software systems grow in scale, computational eff

CoreFlow: Low-Rank Matrix Generative Models

arXiv:2604.24959v1 Announce Type: new Abstract: Learning matrix-valued distributions from high-dimensional and possibly incomplete training data is challenging: ambient-space generative modeling is co

G-Loss: Graph-Guided Fine-Tuning of Language Models

model-releasesarxiv-cs-cl

arXiv:2604.25853v1 Announce Type: new Abstract: Traditional loss functions, including cross-entropy, contrastive, triplet, and su pervised contrastive losses, used for fine-tuning pre-trained language

IBM Granite just released two multilingual embedding models with 97M and 311M parameters 🤏🏻 ModernBERT-based, 200+ languages, 32K context,…

model-releasesjeremy-howard--x

IBM Granite just released two multilingual embedding models with 97M and 311M parameters 🤏🏻 ModernBERT-based, 200+ languages, 32K context, and built for retrieval, search, similarity, and code. And...

Interpretable Fuzzy Modeling Reveals Population-Level Representation Differences in P300 Brain Computer Interfaces Across Neurodivergent and Neurotypical Cohorts

arXiv:2604.24765v1 Announce Type: cross Abstract: P300-based brain-computer interfaces (BCIs) are widely used for communication, but population heterogeneity may alter the neural patterns available fo

Applications

Introducing the IBM Granite 4.1 family of models

IBM Granite 4.1 is a family of foundation models released by IBM Research designed for enterprise AI applications. The models likely offer improvements in performance, efficiency, and capabilities com

applicationsibm-research

Its a bit frustrating, because Gemini 3.1 Pro is an excellent model and can deliver really good results. But here is GPT-5.5 Pro for compari…

model-releasesethan-mollick--x

Its a bit frustrating, because Gemini 3.1 Pro is an excellent model and can deliver really good results. But here is GPT-5.5 Pro for comparison. Sadly, it took this assignment very seriously and ethic

Measuring the Sensitivity of Classification Models with the Error Sensitivity Profile

arXiv:2604.25765v1 Announce Type: new Abstract: The quality of training data is critical to the performance of machine learning models. In this paper, the Error Sensitivity Profile (ESP) is proposed.

Modeling Human-Like Color Naming Behavior in Context

arXiv:2604.25674v1 Announce Type: new Abstract: Modeling the emergence of human-like lexicons in computational systems has advanced through the use of interacting neural agents, which simulate both le

Pimp My LLM: Leveraging Variability Modeling to Tune Inference Hyperparameters

arXiv:2602.17697v2 Announce Type: replace Abstract: Large Language Models (LLMs) are being increasingly used across a wide range of tasks. However, their substantial computational demands raise concer

Prior-Aligned Data Cleaning for Tabular Foundation Models

arXiv:2604.25154v1 Announce Type: new Abstract: Tabular Foundation Models (TFMs) achieve state-of-the-art zero-shot accuracy on small tabular datasets by meta-learning over synthetic data-generating p

AdapTime: Enabling Adaptive Temporal Reasoning in Large Language Models

arXiv:2604.24175v1 Announce Type: cross Abstract: Large language models have demonstrated strong reasoning capabilities in general knowledge question answering. However, their ability to handle tempor

Adaptive Multi-Subspace Representation Steering for Attribute Alignment in Large Language Models

arXiv:2508.10599v4 Announce Type: replace Abstract: Activation steering offers a promising approach to controlling the behavior of Large Language Models by directly manipulating their internal activat

safetyarxiv-cs-ai

Beyond Context: Large Language Models' Failure to Grasp Users' Intent

arXiv:2512.21110v3 Announce Type: replace Abstract: Current Large Language Models (LLMs) safety approaches focus on explicitly harmful content while overlooking a critical vulnerability: the inability

BitRL: Reinforcement Learning with 1-bit Quantized Language Models for Resource-Constrained Edge Deployment

arXiv:2604.24273v1 Announce Type: new Abstract: The deployment of intelligent reinforcement learning (RL) agents on resource-constrained edge devices remains a fundamental challenge due to the substan

Can Compact Language Models Search Like Agents? Distillation-Guided Policy Optimization for Preserving Agentic RAG Capabilities

arXiv:2508.20324v4 Announce Type: replace Abstract: Reinforcement Learning has emerged as a dominant post-training approach to elicit agentic RAG behaviors such as search and planning from language mo

safetyarxiv-cs-cl

Can Large Language Models Really Recognize Your Name?

arXiv:2505.14549v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly being used in privacy pipelines to detect and remedy sensitive data leakage. These solutions oft

CFDLLMBench: A Benchmark Suite for Evaluating Large Language Models in Computational Fluid Dynamics

arXiv:2509.20374v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated strong performance across general NLP tasks, but their utility in automating numerical experime

Diagnostic-Driven Layer-Wise Compensation for Post-Training Quantization of Encoder-Decoder ASR Models

arXiv:2601.02455v2 Announce Type: replace-cross Abstract: Deploying Automatic Speech Recognition (ASR) models on memory-constrained edge devices requires aggressive low-bit weight quantization. Layer-

Dual Control of Linear Systems from Bilinear Observations with Belief Space Model Predictive Control

arXiv:2604.24663v1 Announce Type: cross Abstract: We study finite-horizon quadratic control of linear systems with bilinear observations, in which the control input affects not only the state dynamics

Evaluating Large Language Models on Computer Science University Exams in Data Structures

model-releasesarxiv-cs-cl

arXiv:2604.23347v1 Announce Type: new Abstract: We present a comprehensive evaluation of Large Language Models (LLMs) on Computer Science (CS) Data Structure examination questions. Our work introduces

Evaluation Framework for Highlight Explanations of Context Utilisation in Language Models

arXiv:2510.02629v3 Announce Type: replace Abstract: Context utilisation, the ability of Language Models (LMs) to incorporate relevant information from the provided context when generating responses, r

Excited to support @NVIDIA Nemotron 3 Nano Omni, now available on Fireworks. It's the first open model that handles vision, audio, video, an…

model-releasesfireworks-ai--x

Excited to support @NVIDIA Nemotron 3 Nano Omni, now available on Fireworks. It's the first open model that handles vision, audio, video, and text in a single inference loop. Built for multimodal sub-

Tutorials

Explainable Artificial Intelligence Techniques for Interpretation of Food Models: a Review

arXiv:2504.10527v2 Announce Type: replace Abstract: Artificial Intelligence (AI) has become essential for analyzing complex data and solving highly-challenging tasks. It is being applied across numero

tutorialsarxiv-cs-ai

From Pixels to Explanations: Interpretable Diabetic Retinopathy Grading with CNN-Transformer Ensembles, Visual Explainability and Vision-Language Models

arXiv:2604.23079v1 Announce Type: cross Abstract: The quality of diabetic retinopathy (DR) screening relies on the ability to correctly grade severity; however, many deep-learning (DL) classifiers can

GoClick: Lightweight Element Grounding Model for Autonomous GUI Interaction

model-releasesarxiv-cs-cv

arXiv:2604.23941v1 Announce Type: new Abstract: Graphical User Interface (GUI) element grounding (precisely locating elements on screenshots based on natural language instructions) is fundamental for

Hybrid JIT-CUDA Graph Optimization for Low-Latency Large Language Model Inference

arXiv:2604.23467v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved strong performance across natural language and multimodal tasks, yet their practical deployment remains con

LearnPruner: Rethinking Attention-based Token Pruning in Vision Language Models

arXiv:2604.23950v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have recently demonstrated remarkable capabilities in visual understanding and reasoning, but they also impose significant

safetyarxiv-cs-cv

LLM4SCREENLIT: Recommendations on Assessing the Performance of Large Language Models for Screening Literature in Systematic Reviews

arXiv:2511.12635v2 Announce Type: replace-cross Abstract: Context: Large language models (LLMs) are increasingly used to screen literature for systematic reviews (SRs), but the standard confusion-matr