Knowledge catalogue
Full-parameter post-training of trillion-parameter-scale MoE models introduces substantial system-level challenges for large-scale distributed training, including severe memory pressure, non-overlappe
arXiv:2607.11327v2 Announce Type: replace-cross Abstract: Model editing keeps large language models (LLMs) up to date without retraining, but temporal facts expose a limitation of the prevailing locat
We're beginning a limited preview of the GPT‑5.6 series: Sol, our flagship model; Terra, a balanced model for everyday work; and Luna, a fast and affordable model. Terra has competitive performance to
Everyone Operating At The Frontier Satya Nadella, Chairman & CEO, Microsoft, interviewed by @saranormous & @eladgil (No Priors) and @swyx (Latent Space) Crossover special at Microsoft Build 2026. Summ
arXiv:2606.01682v1 Announce Type: cross Abstract: Selecting the best response from multiple small-model samples using a stronger scorer is a simple inference-time strategy, but fails when the small mo
arXiv:2606.01481v1 Announce Type: new Abstract: With the rapid advancements in text-to-image diffusion models, generative video models (T2V models) like Sora can now produce short synthetic videos fro
arXiv:2605.08384v1 Announce Type: new Abstract: In this work, we introduce frozen-encoder model composition, a novel approach to multimodal embedding models. We build on the VLM-style architecture, in
Today, we’re thrilled to announce that Gemini 3.1 Flash-Lite, our fastest and most cost-efficient Gemini 3 series model yet, is now generally available. Designed for ultra-low latency, high-volume tas
In this episode of The Agent Factory, Vlad Kolesnikov and I sat down with Omar Sanseviero from the Developer Experience team at Google DeepMind. We explored the groundbreaking release of Gemma 4: a ne
AI is evolving from answering questions to reasoning and taking action. Companies who want to lead in today’s agentic era require computing infrastructure designed and optimized for these new requirem
arXiv:2604.17494v1 Announce Type: new Abstract: Counterfactual explanations (CFEs) are essential for interpreting black-box models, yet they often become invalid when models are slightly changed. Exis
arXiv:2604.18452v1 Announce Type: cross Abstract: Vision-language modeling is rapidly increasing in popularity with an ever expanding list of available models. In most cases, these vision-language mod
arXiv:2508.15815v3 Announce Type: replace Abstract: Modern large language models (LLMs) are typically trained and deployed using structured role tags (e.g. system, user, assistant, tool) that explicit
arXiv:2604.09952v1 Announce Type: new Abstract: Many applications today use large language models for code generation; however, production systems have strict latency requirements that can be difficul
arXiv:2407.08101v4 Announce Type: replace Abstract: Vision-language models have shown impressive progress in recent years. However, existing models are largely limited to turn-based interactions, wher
arXiv:2604.08644v1 Announce Type: new Abstract: This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integr
Users on the r/ollama subreddit reported that the **Gemma 4 E4B** model in Ollama offloads layers to RAM even when GPU VRAM is only partially utilized. This behavior is linked to how Ollama and lla...
Took vLLM-SR d3-edge (0.6B), fine-tuned it with simple SFT + LoRA, and compared it against the much larger d3 (27B). With just a few thousand training examples, the 0.6B model actually outperformed th
arXiv:2610.22131v1 Announce Type: new Abstract: Interactive agents repeatedly choose among a finite set of actions, labels, or ordinal outcomes. Generating a free-form response for each choice adds la
arXiv:2610.20748v1 Announce Type: cross Abstract: Mechanistic interpretability aims to uncover how neural networks use their parameters to implement their impressive neural algorithms. Although previo
arXiv:2610.21308v1 Announce Type: cross Abstract: Consumer phones and wearables increasingly collect physiological time-series data, yet most mobile systems treat these streams as summaries or text ra
Hi r/LocalLLaMA, we're releasing Tyger, a small model that handles full-duplex turn-control for voice agents. What it is Base: NVIDIA Nemotron 3.5 ASR Streaming 0.6B + 14M causal GRU on top. Every 80
arXiv:2610.16717v2 Announce Type: replace Abstract: Does a large language model have a self, and if so, of what kind? We separate two functional levels familiar from biology: a self-index, which disti
arXiv:2610.17702v1 Announce Type: new Abstract: Evaluating the quality of process models discovered from event logs is a fundamental challenge in process mining. Traditional evaluation relies on confo
arXiv:2610.14173v1 Announce Type: cross Abstract: Digital libraries increasingly host scientific publications whose figures encode primary research findings, yet making this visual content searchable,
arXiv:2610.16301v1 Announce Type: new Abstract: Self-attention assigns two functions to one mechanism-where to read and how to mix-at the price of O(L^2) training, an O(T) decode state, and position s
Meet Ollama co-founder & CEO @jmorgan who speaks about open model adoption in the enterprise. Watch the episode 👇 What an amazing interview with @jmorgan, Co-Founder & CEO of @ollama! 8.9M developers
arXiv:2610.18820v2 Announce Type: new Abstract: Large language models (LLMs) generally rely on sampling temperature to regulate the amount of randomness in their outputs. Mainstream methods for select
arXiv:2610.20243v1 Announce Type: new Abstract: Anomaly detection is a fundamental task for time-series analytics, with important implications for the downstream performance of many applications. Desp
What makes NVIDIA Nemotron 3.5 Super VL different? → Text, image, document, and video understanding in one model → Reasoning and tool use with visual context preserved across steps → 120B hybrid MoE (
arXiv:2610.16692v1 Announce Type: new Abstract: We address the Cross-View Object Re-Identification (ReID) task, aiming to match identities across drastically different viewpoints. We focus on Single-V
arXiv:2602.02928v2 Announce Type: replace Abstract: Modern generative models based on diffusion or flow matching transport noise toward the data manifold, without representing the data manifold explic
Grok Voice 3.0 in Grok Bot is 🔥 SpaceXSI just launched Grok Voice 3.0, its new speech-to-speech model, which is currently beating GPT Live 1 and Gemini 3.8 Flash Live on all major benchmarks. I tried
arXiv:2610.18677v1 Announce Type: new Abstract: Online decision-making faces a tension between efficient inference and long-horizon reasoning. Value-based methods rely on short-horizon bootstrapping t
Hello! We've been busy at Telperion with a lot of experimental research (more coming soon). Today, we're announcing the release of our latent attention variants of Qwen3.8-27B. Our latent attention va
arXiv:2603.02225v3 Announce Type: replace Abstract: Learning from feedback advances the capabilities and safety of frontier models, but preference supervision remains costly and difficult to scale. We
arXiv:2508.06163v2 Announce Type: replace-cross Abstract: Merging multiple task-specific fine-tuned checkpoints into a single multi-task model provides an attractive alternative to joint multi-task tr
arXiv:2610.16763v1 Announce Type: new Abstract: Relational learning typically predicts from a database state, but decision making asks a different question: how will that state change under an action?
arXiv:2610.15076v1 Announce Type: new Abstract: Plasma experiments observe coupled physical states through sparse, heterogeneous, and incomplete diagnostics. We present a proof of concept toward a mul
arXiv:2610.13522v1 Announce Type: new Abstract: Action-conditioned world models offer a promising foundation for generalist robotic intelligence by predicting the consequences of actions. However, exi
We're launching Precision Numerics by releasing Boole-1.7B, a 1-bit version of Qwen3-1.7B. 247 MB packed weights: 13.9× smaller than BF16. 85.9% of the BF16 model’s average score across our 10-task ev
arXiv:2610.12495v1 Announce Type: cross Abstract: Small language models trained on a single local machine leave little room for architectural trial and error. Kairos combines bidirectional gated-Delta
arXiv:2610.13637v1 Announce Type: cross Abstract: Machine learning models are increasingly used for automated feature extraction from weakly annotated bioimaging data, such as microscopy and cytomorph
arXiv:2610.13123v1 Announce Type: cross Abstract: A solid understanding of the predictive success of deep neural networks (DNNs) remains elusive. For example, while many data-dependent metrics exist t
Not to get too annoying about it but its worth noting that many of the 5,000 people at the labs with access to advanced model still haven't used them to their full extent: its all cybersecurity & math
arXiv:2610.11716v1 Announce Type: cross Abstract: We describe a 4-tensor attention model that predicts the next semantic state of a scene, for video generation and robot planning. A window of states h
arXiv:2610.11537v1 Announce Type: cross Abstract: Flow models generate trajectories from an initial distribution to a target distribution by solving an ordinary differential equation defined by a velo
arXiv:2610.11986v1 Announce Type: new Abstract: Vision-language models (VLMs) show great potential for damage assessment after a disaster, but a recurring deficiency is that they are reluctant to decl
**Summary** TinyFish showcases a streamlined workflow for moving their web‑native machine‑learning model from post‑training into production using Databricks AI Runtime. The article details the deploym
arXiv:2610.11174v1 Announce Type: new Abstract: While recent video generation models synthesize highly realistic visuals, they lack a genuine understanding of intrinsic real-world logic. Existing meth
arXiv:2610.11599v1 Announce Type: cross Abstract: Journals and conferences have begun to screen submitted manuscripts for text written using large language models (LLMs). The reliability of this scree
arXiv:2610.12194v1 Announce Type: new Abstract: World modeling has emerged as an effective co-training objective for robot policies, giving rise to World Action Models (WAMs) that jointly predict acti
an open model just beat Jev outright on clinical decisions 🔥 pplx-decider v1.1 got 643 of 669 right vs 628 for Jev, at 42% less per decision and about the same speed. and you can download the weights
arXiv:2610.09549v1 Announce Type: new Abstract: And-Inverter Graphs (AIGs) are fundamental representations for logic synthesis and verification in Electronic Design Automation (EDA). As structured rep
arXiv:2610.10301v1 Announce Type: new Abstract: Modern applications of AI rely on increasingly complex models. Explainable AI (XAI) has emerged as a set of techniques aimed at improving model transpar
arXiv:2610.07677v1 Announce Type: new Abstract: In this paper, we show that standard evaluations of high-resolution Model Inversion Attacks (MIAs) significantly underestimate training-data privacy lea
arXiv:2610.08703v1 Announce Type: new Abstract: In K-12 mathematics tutoring, student-tutor dialogue provides rich evidence of learners' problem-solving processes and sources of difficulty. Learning a
Anthropic: Anthropic launches Claude Haiku 5.5, the first Haiku model with effort controls, for high-volume, cost-sensitive tasks like summary and classification requests — Introducing Claude Haiku 5.
arXiv:2607.17669v2 Announce Type: replace Abstract: Drone-based object detection technology has advanced rapidly, becoming increasingly sophisticated and efficient. Recently, research trends have expa
arXiv:2610.05370v2 Announce Type: replace Abstract: Generative reward models (GRMs) are important for LLM optimization. Unlike scalar reward models, GRMs generate natural-language critiques alongside