Search: “models”

arXiv:2605.21850v1 Announce Type: new Abstract: Recent development of agents has renewed demand for long-context reasoning capacity of LLMs. However, training LLMs for this capacity requires costly lo

arXiv:2605.22183v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a promising paradigm for generalist robotic manipulation. A common design in current architectures m

arXiv:2605.20734v1 Announce Type: cross Abstract: A large language model (LLM) agent that sends messages can leak data inside them. Destination allowlists and content scanners do not police whether an

Ollama has added MLX support for Qwen3.5 and Gemma 4 , with both MLX and NVFP4 quantization variants available for these models. There have been issues with broken Qwen3.6 NVFP4 generation on Ollama ,

arXiv:2605.22435v1 Announce Type: new Abstract: Hate speech and misinformation frequently co-occur online, amplifying prejudice and polarization. Given their scale, using Large Language Models (LLMs)

arXiv:2605.21932v1 Announce Type: new Abstract: Multi-Robot Task Allocation (MRTA) is a central challenge in decentralized multi-agent systems, where teams of robots must cooperatively assign and exec

arXiv:2605.21082v1 Announce Type: new Abstract: Large Language Model (LLM) based agents have demonstrated proficiency in multi-step interactions with graphical user interfaces (GUIs). While most resea

llama.cpp build b9276 introduces support for hybrid DNA tokenization with new pre-type dispatching and tokenizer implementations, alongside fixes for VRAM leaks in Multi-Token Prediction (MTP) models

arXiv:2605.21766v1 Announce Type: new Abstract: Being able to relight human performance is a fundamental task for post production and content creation. We present BodyReLux, a subject-specific video d

arXiv:2605.22411v1 Announce Type: new Abstract: Large language model (LLM) agents still struggle with long-term memory question answering, where answer-supporting evidence is often scattered across lo

arXiv:2510.17991v3 Announce Type: replace-cross Abstract: Flow Matching (FM) underpins many state-of-the-art generative models, yet recent results indicate that Transition Matching (TM) can achieve hi

arXiv:2605.21540v1 Announce Type: cross Abstract: The proliferation of large language models has introduced a new paradigm of synthetic political communication in which narratives may be generated, se

arXiv:2602.08028v1 Announce Type: cross Abstract: To address the instability of unguided reasoning paths in standard Chain-of-Thought prompting, recent methods guide large language models (LLMs) by fi

arXiv:2605.22051v1 Announce Type: new Abstract: Generating high-fidelity visual effects (VFX) typically demands massive datasets and prohibitive computational power due to the intricate coupling of sp

arXiv:2509.09215v2 Announce Type: replace Abstract: Large language models (LLMs)-empowered autonomous agents are transforming both digital and physical environments by enabling adaptive, multi-agent c

arXiv:2605.22208v1 Announce Type: new Abstract: Multimodal Large Language Model (MLLM)-driven image restoration agent demonstrates effectiveness in degradation coupling scenarios by flexibly selecting

arXiv:2605.22273v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong performance across diverse multimodal tasks, but their adversarial robustness in visible-infrared (VI

arXiv:2605.22057v1 Announce Type: new Abstract: Enterprise routers assign queries to expert agents, yet deployed profiles stay static while agents evolve (prompts, tools, models), and developers rarel

Great to see @CommonCrawl using and recommending @huggingface Buckets for large constantly evolving training datasets! If you have private models or datasets, try it and let us know what you think abo

arXiv:2605.22695v1 Announce Type: new Abstract: Viewpoint change invariance and action temporal consistency are critical aspects for the effective deployment of human action detection of untrimmed vid

arXiv:2605.22189v1 Announce Type: new Abstract: Occlusion-aware prediction remains a critical challenge in autonomous driving due to the inherent uncertainty of unobserved regions. Existing approaches

arXiv:2605.12321v2 Announce Type: replace Abstract: Large language models (LLMs) show strong potential for Intelligent Transportation Systems (ITS), particularly in tasks requiring situational reasoni

arXiv:2605.22269v1 Announce Type: new Abstract: Long streaming video QA remains challenging due to growing visual tokens and limited reasoning length of large language models (LLMs). KV-caching stores

Nicki Minaj template dropped… so I became the baddie. 🔥🚀 @Grok @Imagine Media Template Drop @SpaceX Starship Baddie (inspired by @NICKIMINAJ) Modeled by @SadieSupaDoge https://grok.com/imagine/templat

Open-source clinical AI is a niche that most days feels like shouting into a PubMed-shaped void. And yet. 5,000 of you are here, building OpenMed in the open with me. Thank you. More models, more data

arXiv:2605.22015v1 Announce Type: new Abstract: Diffusion Transformer (DiT) has emerged as a powerful model architecture for generating high-quality images and videos. In the case of video DiT, 3D Spa

arXiv:2605.22013v1 Announce Type: new Abstract: Understanding 3D point clouds through language remains a fundamental challenge in computer graphics and visual computing, due to the irregular structure

arXiv:2605.22231v1 Announce Type: new Abstract: We introduce a novel 3D hand pose estimator that can accurately recover the shape and pose of people's hands in a room from afar, typically from fixed c

arXiv:2605.22771v1 Announce Type: new Abstract: Large language models (LLMs) exhibit systematic political bias across a variety of sensitive contexts. We find that LLMs handle counterpart topics from

arXiv:2506.14648v2 Announce Type: replace Abstract: Preference-based Reinforcement Learning (PbRL) methods provide a solution to avoid reward engineering by learning reward models based on human prefe

arXiv:2507.03674v3 Announce Type: replace Abstract: Extracting structured information from scientific literature is critical for accelerating discovery, yet Large Language Models (LLMs) often struggle

Thanks for sharing this. The Huggingface Hub, instead of being considered as a huge dataset, should be considered as a dynamic discovery engine that can be directly executed and verified. Most models

View the official memo here. An internal model at OpenAI has autonomously disproved a central conjecture in discrete geometry, a mathematical field with applications in cryptography, wireless device c

Gary Marcus discusses the current state of large language models (LLMs), likely covering their capabilities, limitations, and practical applications in AI. The post probably addresses key challenges s

This is the most interesting paper I have read this week. The authors test a wide range of LLMs on a massive dataset of behavioural experiments, with more than 200,000 participants and nearly 26 milli

arXiv:2605.22709v1 Announce Type: cross Abstract: Electromagnetic (EM) side-channel analysis traditionally assumes a stationary, close-proximity probe - a threat model that underestimates aerial adver

U.S. President Donald Trump has delayed the signing of an executive order designed to regulate advanced artificial intelligence models. “I didn’t like certain aspects of it. I postponed it,” Trump tol

arXiv:2605.21906v1 Announce Type: new Abstract: Computed tomography (CT) is a central to three-dimensional medical imaging, yet CT-based artificial intelligence remains fragmented across task-specific

arXiv:2605.21654v1 Announce Type: cross Abstract: Reinforcement learning substantially improves pretrained language models, but it remains understudied why critic-free methods such as PPO and GRPO wor

arXiv:2601.23224v2 Announce Type: replace Abstract: Existing multimodal large language models for long-video understanding predominantly rely on uniform sampling and single-turn inference, limiting th

arXiv:2602.01334v2 Announce Type: replace Abstract: Vision tool-use reinforcement learning (RL) can equip vision language models with visual operators such as crop-and-zoom and achieves strong perform

arXiv:2605.22823v1 Announce Type: new Abstract: Video Large Language Models (Video-LLMs) have made rapid progress on temporal video understanding, yet many fail at a basic perceptual primitive: signed

arXiv:2605.22718v1 Announce Type: new Abstract: Autoregressive video diffusion models have enabled real-time, action-conditioned world generation. However, sustaining a persistent world, where revisit

arXiv:2503.02885v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have gained traction in educational settings, often framed as virtual tutors or teaching assistants. Following ea

arXiv:2605.21313v1 Announce Type: new Abstract: Deep neural networks have achieved impressive performance on a variety of tasks, but their brittleness to distributional shifts remains a significant ba

arXiv:1908.05972v3 Announce Type: replace Abstract: This paper significantly improves on, and finishes to validate, an approach proposed in previous research in which safety outcomes were predicted fr