Knowledge catalogue
arXiv:2601.21297v2 Announce Type: replace Abstract: We introduce Deep QP Safety Filter, a fully data-driven safety layer for black-box dynamical systems. Our method learns a Quadratic-Program (QP) saf
Ollama consistently fails to run any model on Apple M5 hardware running macOS 26, with the Metal backend failing to initialize and the runner process terminating with a 500 Internal Server Error. The
arXiv:2508.04559v3 Announce Type: replace Abstract: Recent diffusion-based approaches have made significant advances in image-based virtual try-on, enabling more realistic and end-to-end garment synth
arXiv:2604.12175v1 Announce Type: new Abstract: Recent advances in image editing have heightened the need for reliable Image Editing Quality Assessment (IEQA). Unlike traditional methods, IEQA require
arXiv:2604.12319v1 Announce Type: new Abstract: Multimodal semantic segmentation has emerged as a powerful paradigm for enhancing scene understanding by leveraging complementary information from multi
arXiv:2604.09979v1 Announce Type: cross Abstract: Self-supervised representation learning is central to modern machine learning because it extracts structured latent features from unlabeled data and e
arXiv:2604.10805v1 Announce Type: new Abstract: Accurate distance estimation from monocular cameras is essential for intelligent monitoring systems. In many deployments, image coordinates are mapped t
arXiv:2604.09628v1 Announce Type: cross Abstract: Explainable AI (XAI) has evolved in response to expectations and regulations, such as the EU AI Act, which introduces regulatory requirements on AI-po
arXiv:2512.19049v2 Announce Type: replace Abstract: Synthesizing realistic human-object interaction (HOI) is essential for 3D computer vision and robotics, underpinning animation and embodied control.
arXiv:2604.11083v1 Announce Type: cross Abstract: Text-to-motion generation is driven by learning motion representations for semantic alignment with language. Existing methods rely on either continuou
Introducing Kernels on the Hugging Face Hub ✨ What if shipping a GPU kernel was as easy as pushing a model? - Pre-compiled for your exact GPU, PyTorch & OS - Multiple kernel versions coexist in one pr
arXiv:2507.14800v2 Announce Type: replace-cross Abstract: With the advanced reasoning, contextual understanding, and information synthesis capabilities of large language models (LLMs), a novel paradig
arXiv:2604.10927v1 Announce Type: new Abstract: We propose LiveGesture, the first fully streamable, speech-driven full-body gesture generation framework that operates with zero look-ahead and supports
arXiv:2604.11552v1 Announce Type: cross Abstract: Voice imitation aims to transform source speech to match a reference speaker's timbre and speaking style while preserving linguistic content. A straig
arXiv:2604.11295v1 Announce Type: new Abstract: This paper proposes novel passive-dynamic walkers formed by two cross-shaped frames and eight viscoelastic elements. Since it is a combination of two fo
arXiv:2603.23516v2 Announce Type: replace-cross Abstract: Long-term memory is a cornerstone of human intelligence. Enabling AI to process lifetime-scale information remains a long-standing pursuit in
arXiv:2511.20577v3 Announce Type: replace Abstract: Real-world time series often exhibit strong non-stationarity, complex nonlinear dynamics, and behavior expressed across multiple temporal scales, fr
arXiv:2602.17709v2 Announce Type: replace-cross Abstract: All-atom molecular simulation serves as a quintessential ``computational microscope'' for understanding the machinery of life, yet it remains
arXiv:2604.11014v1 Announce Type: new Abstract: Ultra-high-definition (UHD) video denoising requires simultaneously suppressing complex spatio-temporal degradations, preserving fine textures and chrom
We achieved state-of-the-art performance in predicting which of 4.2 million genetic variants cause diseases by interpreting a genomics model, in a new preprint with @MayoClinic. We're now releasing an
Nous Research posted a status update on X acknowledging service disruptions affecting model availability through their Nous Portal. The announcement indicated the team was actively working to restore
Stanford HAI: 2026 AI Index Report: AI capability is accelerating, not plateauing, the US-China model gap has closed, the US leads in data centers and AI investment, and more — AI's influence on socie
arXiv:2511.22963v2 Announce Type: replace-cross Abstract: Enabling humanoid robots to follow free-form language commands is critical for seamless human-robot interaction, collaborative task execution,
arXiv:2511.06756v3 Announce Type: replace Abstract: Over-smoothing remains a fundamental challenge in deep Graph Neural Networks (GNNs), where repeated message passing causes node representations to b
arXiv:2604.08903v1 Announce Type: new Abstract: Pansharpening aims to generate high-resolution multispectral (HRMS) images by fusing low-resolution multispectral (LRMS) and high-resolution panchromati
We just OCR'd 27,000 arxiv papers into Markdown using an open 5B model, 16 parallel HF Jobs on L40S GPUs, and a mounted bucket. Total cost: $850 Total time: ~29 hours Jobs that crashed: 0 This now pow
Let’s be honest… everyone was waiting to see how Tesla FSD 14.3 would handle Manhattan. @scotsrule08 and I took my 2026 HW4 Model Y out for a 2-hour drive through NYC - and it seriously delivered. Thi
Nous Research has introduced a new feature in their Hermes Agent system that allows users to use the `/compress ` command to influence how the compaction model prioritizes and retains information. Thi
very memgpt / sarah wooders coded. memory isn’t a layer, it is the system. most teams think they’re choosing a model, but they’re really choosing where their memory lives and like ben thompson says, o
We’re thrilled to announce @MiniMax_AI M2.7 is now available Day-0 on Fireworks for commercial use. This self-evolving agentic model delivers frontier-level performance across: → Software engineering
arXiv:2604.06220v1 Announce Type: cross Abstract: Sign language recognition (SLR) is vital for bridging communication gaps between deaf and hearing communities. Vision-based approaches suffer from occ
arXiv:2601.21708v2 Announce Type: replace Abstract: Large language models (LLMs) excel across many tasks, yet inference is still dominated by strictly token-by-token autoregression. Existing accelerat
I rest my case: Mythos isn’t AGI. It’s not even better at biology than the last model. It’s tuned to particular things, not a giant advance towards general intelligence. Same as it ever was. @GaryMarc
arXiv:2604.01130v3 Announce Type: replace Abstract: As sports training becomes more data-driven, traditional dart coaching based mainly on experience and visual observation is increasingly inadequate
arXiv:2604.06831v1 Announce Type: cross Abstract: Current LLM-based services typically require users to submit raw text regardless of its sensitivity. While intuitive, such practice introduces substan
(1/5) FP4 hardware is here, but 4-bit attention still kills model quality, blocking true end-to-end FP4 serving. To fix that, we propose Attn-QAT, the first systematic study of quantization-aware trai
Fardis Makraduli ([@f_makraduli](https://x.com/f_makraduli)) shared a post about attending the AI Engineer ([@aiDotEngineer](https://x.com/aiDotEngineer)) event, noting shared themes and networking...
arXiv:2610.20832v1 Announce Type: cross Abstract: Despite their extensive pretraining knowledge and strong reasoning capabilities, large language models (LLMs) struggle to adaptively gather informatio
model: add Muse Spark Open (text, vision and audio) (#30616) model: add Muse Spark Open (text, vision and audio) Muse Spark Open is a latent space MoE: the residual stream stays at 8192 while the 256
arXiv:2610.21565v1 Announce Type: cross Abstract: On-device deployment of large language models (LLMs) is increasingly adopted due to latency and privacy requirements, but exposes proprietary models t
arXiv:2610.21138v1 Announce Type: new Abstract: Feedback noise is pervasive in preference data, arising from subjective human judgments, annotation mistakes, and imperfect LLM judges. Standard reward
arXiv:2610.20877v1 Announce Type: cross Abstract: Early detection of mild cognitive impairment remains a critical bottleneck in dementia care, demanding scalable tools capable of capturing subtle beha
arXiv:2610.22160v1 Announce Type: cross Abstract: Test-time context optimization adapts frozen language models through textual feedback, but ordinary conditional generation provides no separate contro
arXiv:2610.22333v1 Announce Type: new Abstract: Large language models (LLMs) can often tell when they are being tested. This ability, known as evaluation awareness, can lead models to act more cautiou
arXiv:2610.21568v1 Announce Type: new Abstract: Recent multimodal large language models have advanced video understanding, but existing benchmarks mainly evaluate whether models can interpret observed
arXiv:2610.22196v1 Announce Type: new Abstract: External-memory systems extend language-model applications beyond a context window, but their quality depends critically on the model executing the writ
arXiv:2505.21146v2 Announce Type: replace-cross Abstract: While text-to-motion generation is mainstream, integrating explicit spatial constraints has become a standard solution for precise animation.
arXiv:2610.21427v1 Announce Type: new Abstract: Learning from interaction experience is essential for enabling large language models to continually improve during deployment. Context distillation offe
arXiv:2607.18253v2 Announce Type: replace Abstract: Large language model (LLM) query routers typically assign each query to a suitable model that balances response accuracy and monetary cost. Subseque
arXiv:2610.22043v1 Announce Type: cross Abstract: Which inputs drive a language model's financial forecast? We construct synthetic earnings announcements that independently reverse 20-day momentum, no
arXiv:2610.21292v1 Announce Type: new Abstract: Maintaining small path-tracking errors under moving reference frames is essential for robotic manipulation tasks with tight execution tolerances, such a
arXiv:2610.21380v1 Announce Type: new Abstract: Reinforcement learning has brought strong gains to language model reasoning, but its improvements on visual tasks remain less consistent. One difficulty
arXiv:2610.21082v1 Announce Type: new Abstract: Large language model (LLM) agents can keep scientific experiments running for months with little human supervision, but reliable autonomous research als
arXiv:2610.21902v1 Announce Type: new Abstract: Language priors in MLLMs can override visual evidence, impairing visual perception. Existing benchmarks assume shared priors across models and rely sole
arXiv:2602.12405v2 Announce Type: replace-cross Abstract: Reasoning about failures is crucial for building reliable and trustworthy robotic systems. Prior approaches either treat failure reasoning as
arXiv:2610.21900v1 Announce Type: new Abstract: An agent's memory must remain useful as information changes across conversations. A new fact may replace an earlier value without making that value irre
arXiv:2610.19413v1 Announce Type: new Abstract: Virtual reality training for robot-assisted vascular intervention requires accurate robotic control and effective feedback on guidewire--vessel interact
arXiv:2511.17937v2 Announce Type: replace Abstract: Alignment faking is a form of strategic deception in AI in which models selectively comply with training objectives when they infer that they are in
arXiv:2610.17206v1 Announce Type: new Abstract: We propose AutoMARS (Automatic Multi-Agent Risk Assessment), an agentic framework for automatic and scalable comparative risk assessment in supply chain
arXiv:2610.15995v1 Announce Type: cross Abstract: This paper presents AutoSec-RAN, a specification-grounded large language model (LLM) framework for automated security triage of Open Radio Access Netw