Knowledge catalogue
arXiv:2312.01886v4 Announce Type: replace Abstract: Large vision-language models (LVLMs) have demonstrated their incredible capability in visual question answering. However, this rich visual interacti
arXiv:2610.05775v1 Announce Type: new Abstract: A video assistant must speak when its instruction warrants a response and stay silent otherwise. We introduce a benchmark that evaluates this decision f
https://huggingface.co/google/embeddinggemma-2 EmbeddingGemma 2 is an open multimodal embedding model built by Google DeepMind which maps text (incl. code), images, video, and audio inputs—and combina
Introducing GeoGuess Bench! A benchmark to measure how good AI models are at playing GeoGuessr. We gave each model 210 photos from around the world, asked it to predict where each photo was taken, and
Introducing Mistral Large 4: Le chonk Mistral are back in the game. Today they're releasing a preview of Mistral Large 4, a 1 trillion parameter, 49 billion active parameter model trained on their own
arXiv:2505.17919v2 Announce Type: replace Abstract: Residual connections are foundational to modern neural networks, yet the standard additive update provides no explicit mechanism for structured inte
arXiv:2610.04721v1 Announce Type: new Abstract: Structural diagrams are widely used to represent complex systems and relational information across scientific, engineering, procedural, and spatial doma
arXiv:2610.03956v1 Announce Type: cross Abstract: We propose a data-driven framework for estimating the Bayesian Cramer-Rao bound (CRB) in high-dimensional imaging systems with complex, analytically i
New Zealand-based LawVu Ltd., a legal artificial intelligence startup, today announced the launch of Lens, an AI contract analysis tool that gives in-house legal teams visibility into risks and obliga
arXiv:2610.05428v1 Announce Type: cross Abstract: We study learning in continuous games when players receive only pairwise preference feedback, revealing which of two actions is preferred but neither
arXiv:2606.14222v2 Announce Type: replace Abstract: The rapid evolution of Time Series Foundation Models (TSFMs) has advanced zero-shot forecasting across diverse domains. Inspired by the current form
arXiv:2610.05879v1 Announce Type: cross Abstract: We present the Prior-Fitted Language Model (PFLM), a 300M-parameter byte-level transformer pretrained only on samples from a synthetic non-linguistic
Learning from data as we observe it is easy for humans, but most machine learning models have limited ability to learn from new data that they have not seen during training. Prior-fitted networks (the
arXiv:2610.04936v1 Announce Type: new Abstract: Class-imbalance methods implicitly assume that the minority class is uniformly undersampled relative to the majority class. However, in many real-world
arXiv:2610.05564v1 Announce Type: cross Abstract: Text embedding models trained with contrastive learning learn to follow task instructions from instruction-paired data, while instruction-tuned LLMs a
let me introduce you to the langchain stack 1. langgraph gives you this level of control 2. traces give you the complete run lineage 3. version your skills and instructions in context hub 4 & 5. deepa
Like Jev, I believe RL will unlock several more like this, slashing the cost of critical agent operations. flow-1 is competitive in performance, but a huge cost-saver for finding failures in agent tra
arXiv:2502.07397v3 Announce Type: replace-cross Abstract: Linear bandits have long been a central topic in online learning, with applications ranging from recommendation systems to adaptive clinical t
**llm-mistral 0.16** is a language‑model plugin that provides programmatic access to Mistral models via the official Mistral API. It exposes wrapper functions for sending requests, receiving responses
Release: llm-openai-decisions 0.1a0 OpenAI released their new Jev-style Decisions API, as previously announced at last week's DevDay. Since I already have an llm-typesafe plugin for talking to Jev, I
Hey guys, it's Merve from Hugging Face! I've recently given a talk in a dev conference about llama.cpp + but also covering basic concepts like prefill vs decode, memory types, speculative decoding etc
Last time when I posted on this subReddit to share my work, the response almost made me cry because a tiny demo got so many people talking about this In the past 2 months Ive been training a new model
arXiv:2610.04351v1 Announce Type: new Abstract: Feed-forward 3D Gaussian Splatting (3DGS) increasingly aggregates multi-view evidence with heavy learned 3D networks. We propose LoCoSplat (Local-Contex
arXiv:2610.04441v1 Announce Type: new Abstract: Large language models can intervene in reinforcement learning through both reward design and action selection, yet aggregate performance offers an incom
arXiv:2610.05899v1 Announce Type: new Abstract: Instance-level roof-to-footprint offset (RFO) prediction is central to extracting building footprints from off-nadir imagery. Query-based pipelines comm
arXiv:2610.05501v1 Announce Type: new Abstract: In this study, we propose a novel rule-based interpretable choice model, Logic-Logit, designed to effectively learn and explain human choices. Choice mo
arXiv:2610.05109v1 Announce Type: new Abstract: Recently, unified high-definition image restoration has attracted considerable attention; however, existing models tend to excessively increase their de
arXiv:2610.05265v1 Announce Type: new Abstract: Looped language models provide a parameter-efficient way to scale iterative test-time computation by repeatedly executing a shared recurrent core. Post-
arXiv:2610.04507v1 Announce Type: new Abstract: Double descent has sparked considerable interest, with recent work relating it to the data, the model and the learning configuration. Practical fine-tun
arXiv:2603.09737v2 Announce Type: replace Abstract: Semantic occupancy prediction enables dense 3D geometric and semantic understanding for autonomous driving. However, existing camera-based approache
arXiv:2507.07297v2 Announce Type: replace Abstract: Recent advances in large vision-language models have led to impressive performance in visual question answering and multimodal reasoning. However, i
arXiv:2610.04963v1 Announce Type: new Abstract: Graph few-shot class-incremental learning (GFSCIL) requires a model to continually recognize emerging classes from only a few labeled nodes while preser
Malware reverse-engineering: solving an out-of-distribution investigation task. When faced with an unknown binary, Mistral Large 4 reverse-engineers it end-to-end. In this case, it concludes the sampl
arXiv:2610.06751v1 Announce Type: new Abstract: Matrix completion underlies problems from tabular imputation to causal inference, yet existing tabular foundation models treat it as entry-by-entry pred
arXiv:2602.01081v2 Announce Type: replace Abstract: Medical Anomaly Detection (MedAD) offers a promising direction for medical image analysis with Large Multimodal Models (LMMs). However, progress is
arXiv:2610.04800v1 Announce Type: cross Abstract: Graphical consoles offer a practical interface for medical acquisition assistance, allowing agents to work through the controls and visual feedback us
Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workl
arXiv:2610.04195v1 Announce Type: cross Abstract: Personal AI agents in enterprise multi-tenant deployments share a common vector store for long-term memory. Shared embedding spaces create a surface f
I’ve been building this for a long fucking time, and tonight I finally released Memoria 1.0.0. I built it because I actually wanted to use it. I wanted a real memory layer for local LLM applications t
Introducing InferBench: A benchmark testing how well frontier LLMs infer a user's priorities from their instructions. We tested 12 LLMs across 20 scenarios with 2.8k conversations to see which models
Mistral 4 is pretty good at lawyer bench and cyber security bench, but give it's European heritage, one can only assume it's also good at regulation bench Meet Mistral Large 4, aka Le Chonk. • 1T para
Mistral can pelican now! https://tools.simonwillison.net/markdown-svg-renderer?url=https%3A%2F%2Fgist.github.com%2Fsimonw%2F0db8b8196e57711b352f6c5857cf5b35#response-1 Meet Mistral Large 4, aka Le Cho
My comment on Mistral Large 4 — Hacker News. wren6991: The benchmark is saturated. Frontier models are tested with an armadillo in fishnet tights jaywalking on Mars. OK well I couldn't resist this one
Mistral Large 4 against the field: efficiently reasoning over diverse complex challenges. CTF speedrun: 19 challenges, with tool calls and solve times grounded in actual runs. It solved 18 of the 19.
Mistral AI announced that its new model, Mistral Large 4, is among the world's most powerful AI systems specifically designed for cybersecurity tasks. The tweet shared on October 6, 2026 highlights th
Carl Franzen / VentureBeat: Mistral launches a preview of Mistral Large 4, or Le Chonk, a 1T model it claims tops any open model developed in the US or Europe; weights are due October 27 — Mistral is
Mistral AI SAS today opened access to Mistral Large 4, its most capable large language model to date. On launch, the LLM is available in public preview through the company’s cloud platform. Mistral pl
Sabrina Ortiz / The Deep View: Mistral releases Mistral Large 4, dubbed “le Chonk”, a 1T-parameter open-weight model for general agentic capabilities, trained on 4,000 Grace Blackwell GPUs — Most flag
Mistral Blog: Mistral says it trained ML4 “from scratch” using 3,800 Nvidia Grace Blackwell GPUs in its data centers in Europe and much of its training data was multilingual — Le Chonk — Today, we're
arXiv:2610.04307v1 Announce Type: cross Abstract: Machine Learning (ML) methods promise a fast solution process for Optimal Power Flow (OPF). While inconsistent test cases, implementations, and evalua
arXiv:2510.13276v2 Announce Type: replace Abstract: The rapid advancement of long-context vision language models (LCVLMs) has led to a significant expansion of their context windows. However, an exten
arXiv:2610.05289v1 Announce Type: new Abstract: Recent advances in 3D Gaussian Splatting (3DGS) have achieved remarkable performance in novel view synthesis, yet deploying both static and dynamic Gaus
guys do you still remember K2 Horizon? https://huggingface.co/IFM/K2-Horizon-MoVA-36B-A4B-GGUF https://huggingface.co/IFM/K2-Horizon-32B-GGUF https://huggingface.co/IFM/K2-Horizon-3.7B-GGUF https://hu
arXiv:2411.12426v3 Announce Type: replace Abstract: Real-world applications of stereo matching, such as autonomous driving, place stringent demands on both safety and accuracy. However, learning-based
arXiv:2610.06378v1 Announce Type: new Abstract: The rapid evolution of video generation has narrowed the perceptual gap between authentic and synthetic videos, making generalizable AI-generated video
arXiv:2610.04802v1 Announce Type: new Abstract: This project explores how multiple cognitive radars can learn to share limited wireless spectrum with other radio users without interfering with one ano
arXiv:2610.04456v1 Announce Type: new Abstract: Deep learning models for crop leaf disease recognition routinely report near-perfect accuracy yet are typically trained and evaluated on a single datase
arXiv:2603.27170v2 Announce Type: replace Abstract: Relative camera pose is a basic geometric cue for visual re-localization and scene understanding. When using images alone, visual evidence may not s
arXiv:2607.17938v2 Announce Type: replace Abstract: Object-level mapping and topological navigation reason about whole objects, yet the correspondences they rely on are computed over keypoints or pixe
Enterprises and individual developers frequently run multiple AI inference models. The right architecture can simplify how the models are called while also providing centralized governance. In this po