Search: “models”

arXiv:2604.17581v1 Announce Type: new Abstract: How much data is enough to make a scientific discovery? As biomedical datasets scale to millions of samples and AI models grow in capacity, progress inc

arXiv:2604.18521v1 Announce Type: new Abstract: Epidemic forecasting has become an integral part of real-time infectious disease outbreak response. While collaborative ensembles composed of statistica

Introducing ml-intern, the agent that just automated the post-training team @huggingface It's an open-source implementation of the real research loop that our ML researchers do every day. You give it

arXiv:2512.04677v5 Announce Type: replace Abstract: Audio-driven avatar interaction demands real-time, streaming, and infinite-length generation -- capabilities fundamentally at odds with the sequenti

arXiv:2604.17428v1 Announce Type: new Abstract: As video generation models achieve unprecedented capabilities, the demand for robust video evaluation metrics becomes increasingly critical. Traditional

arXiv:2503.16549v2 Announce Type: replace Abstract: Despite strong results on many tasks, multimodal large language models (MLLMs) still underperform on visual mathematical problem solving, especially

arXiv:2601.03190v3 Announce Type: replace Abstract: Machine unlearning aims to forget sensitive knowledge from Large Language Models (LLMs) while maintaining general utility. However, existing approac

arXiv:2604.18418v1 Announce Type: new Abstract: Recent advances in deep research systems enable large language models to retrieve, synthesize, and reason over large-scale external knowledge. In medici

arXiv:2604.17982v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) still struggle with vision hallucination, where generated responses are inconsistent with the visual input. Exist

arXiv:2604.18203v1 Announce Type: new Abstract: Multimodal LLMs can accurately perceive numerical content across modalities yet fail to perform exact multi-digit multiplication when the identical unde

arXiv:2604.16515v1 Announce Type: new Abstract: The rapid proliferation of Multimodal Large Language Models (MLLMs) has enabled mobile agents to execute high-stakes financial transactions, but their a

arXiv:2602.06663v2 Announce Type: replace Abstract: Unified multimodal models (UMMs) have shown impressive capabilities in generating natural images and supporting multimodal reasoning. However, their

arXiv:2506.13674v3 Announce Type: replace Abstract: Parameter-Efficient Fine-Tuning (PEFT) methods have become crucial for rapidly adapting large language models (LLMs) to downstream tasks. Prefix-Tun

arXiv:2604.16396v1 Announce Type: new Abstract: Islamic inheritance law (ilm al-mawar{i}th) presents a challenging domain for evaluating large language models' structured reasoning capabilities, requi

arXiv:2604.18580v1 Announce Type: cross Abstract: Modern sequence models are dominated by Transformers, where self-attention mixes information from the visible context in an input-dependent way. Howev

arXiv:2604.16913v1 Announce Type: cross Abstract: Decentralized Autonomous Organizations (DAOs) are inclined explore Small Language Models (SLMs) as edge-native constitutional firewalls to vet proposa

arXiv:2510.00546v5 Announce Type: replace Abstract: Large Reasoning Models (LRMs) allocate substantial inference-time compute to Chain-of-Thought (CoT) reasoning, improving performance on mathematics,

arXiv:2601.00296v2 Announce Type: replace Abstract: Most colorization models condition only on a single reference, typically the first frame of the scene. However, this approach ignores other sources

arXiv:2508.17434v2 Announce Type: replace Abstract: Real-world image super-resolution (Real-ISR) focuses on recovering high-quality images from low-resolution inputs that suffer from complex degradati

arXiv:2603.19684v2 Announce Type: replace Abstract: Automatic tooth segmentation and identification from intra-oral scanned 3D models are fundamental problems in digital dentistry, yet most existing a

arXiv:2604.16542v1 Announce Type: cross Abstract: Safety guardrails have become an active area of research in AI safety, aimed at ensuring the appropriate behavior of large language models (LLMs). How

arXiv:2512.01643v2 Announce Type: replace Abstract: Test-Time Training (TTT) has recently emerged as a promising direction for efficient sequence modeling. TTT reformulates attention operation as an o

arXiv:2601.04609v2 Announce Type: replace Abstract: Vision-language models (VLMs) are increasingly used to make visual content accessible via text-based descriptions. In current systems, however, desc

arXiv:2504.10466v2 Announce Type: replace Abstract: Large-scale pre-trained image-to-3D generative models have exhibited remarkable capabilities in diverse shape generations. However, most of them str

arXiv:2601.07160v2 Announce Type: replace Abstract: To meet the ever-increasing demand for computational efficiency, Neural Processing Units (NPUs) have become critical in modern AI infrastructure. Ho

Attending #AIDev26 by @DeepLearningAI? Join @AI21Labs, @trychroma + @Baseten for a panel on optimizing modern AI systems. Drinks. Nikkei food. No fluff. April 28 | 5PM | Kaiyō SF Register → http://lum

Earlier this year Yann LeCun left Meta because Mark Zuckerberg wouldn't bet the company on JEPA. Last week his group dropped the first JEPA that actually trains end-to-end from raw pixels. 15 million

I've been a K2.5 superfan since it came out. These new numbers for the next version look incredible. You gotta love competition! Meet Kimi K2.6: Advancing Open-Source Coding 🔹Open-source SOTA on HLE w

Kimi K2.6 is an open-source model featuring advanced coding, long-horizon execution, and agent swarm capabilities that is now available via Ollama Cloud . The model excels in coding and agentic tools

arXiv:2604.15833v1 Announce Type: new Abstract: Spatiotemporal modeling has evolved beyond simple time series analysis to become fundamental in structural time series analysis. While current research

arXiv:2504.03621v2 Announce Type: replace Abstract: Classical OCR pipelines decompose document reading into detection, segmentation, and recognition stages, which makes them sensitive to localization

This article analyzes the performance differences between open-source and closed-source AI models in the current landscape, examining factors that influence their relative capabilities and market posi

arXiv:2603.20410v2 Announce Type: replace Abstract: Scientific machine learning is increasingly used to build surrogate models, yet most models are trained under a restrictive assumption in which futu

A user reported satisfaction with Gemma 4 Cloud but switched to GLM 5.1 due to API errors, noting that the alternative model consumes significantly more resources. The post likely discusses the perfor

Morning everyone! I put this merge together yesterday, put it on huggingface to share with Jackrong, and a bunch of people discovered it when it got cloned into Jackrongs repo, and it’s going a bit vi

arXiv:2604.14570v1 Announce Type: new Abstract: Deepfake detectors face growing challenges in generalization as new image synthesis techniques emerge. In particular, deepfakes generated by diffusion m

arXiv:2604.14626v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models have become the dominant architecture for large-scale language models, yet on-premises serving remains fundamentally mem

Ernie Image Turbo is a text-to-image generation model that can run efficiently on consumer-grade hardware like RTX 30 series GPUs with limited VRAM by using INT8 quantization. The post discusses techn

arXiv:2604.14188v1 Announce Type: cross Abstract: Large language models have demonstrated impressive performance across many domains of mathematics and physics. One natural question is whether such mo

arXiv:2511.02135v2 Announce Type: replace Abstract: Large language models (LLMs) have become a popular approach for simulating human behaviors, yet it remains unclear if LLMs are necessary for all sim

arXiv:2511.01014v3 Announce Type: replace Abstract: Instruction-following is a fundamental ability of Large Language Models (LLMs), requiring their generated outputs to follow multiple constraints imp

arXiv:2601.18675v2 Announce Type: replace Abstract: We investigate whether temporal embedding models trained on longitudinal electronic health records can learn clinically meaningful representations w

arXiv:2604.15149v1 Announce Type: new Abstract: As reinforcement Learning with Verifiable Rewards (RLVR) has become the dominant paradigm for scaling reasoning capabilities in LLMs, a new failure mode

LM Studio version 0.4.12 introduces support for Alibaba's Qwen 3.6 model, improved PDF export functionality for chat conversations, and fixes for MCP (Model Context Protocol) servers with OAuth authen

arXiv:2510.17568v5 Announce Type: replace Abstract: Recent 3D feed-forward models, such as the Visual Geometry Grounded Transformer (VGGT), have shown strong capability in inferring 3D attributes of s

arXiv:2503.21970v3 Announce Type: replace Abstract: State-Space Models (SSMs) have attracted considerable attention in Image Restoration (IR) due to their ability to scale linearly sequence length whi