Knowledge catalogue
Thoughts: 1. Harness > models 2. Enterprises will jump on using zenith-shaped things to optimize costs (esp. with open source models) Can't wait to try @ii_posts You don't need Fable for the most comp
arXiv:2606.26432v1 Announce Type: new Abstract: Tabular foundation models achieve strong accuracy on choice prediction tasks, but their predictions often violate the economic logic those tasks require
arXiv:2606.21395v1 Announce Type: new Abstract: Atomistic structure and natural language have long been modeled separately, with language models either calling atomistic models as tools or being fine-
arXiv:2508.20906v3 Announce Type: replace Abstract: While foundation models have revolutionized fields such as natural language processing and computer vision, their potential in graph machine learnin
This episode discusses the growing landscape of open-source AI models, contrasts the approaches and philosophies of Model Labs versus Agent Labs in AI development, and explores fundamental limitations
arXiv:2606.12025v1 Announce Type: new Abstract: Finite element (FE) modeling of safety-critical infrastructure such as bridge barriers requires high-fidelity nonlinear dynamic analysis, yet the curren
arXiv:2606.11289v1 Announce Type: new Abstract: Diffusion models have consistently driven progress in text-to-image generation. However, it is challenging to attribute recent progress to specific mode
arXiv:2602.22962v2 Announce Type: replace Abstract: Data-driven models are revolutionizing weather forecasting. To optimize training efficiency and model performance, this paper analyzes empirical sca
arXiv:2509.23982v2 Announce Type: replace-cross Abstract: Preference alignment is a critical step in making Large Language Models (LLMs) useful and aligned with (human) preferences. Existing approache
arXiv:2606.12385v1 Announce Type: new Abstract: Modern LLM training pipelines increasingly rely on other models to generate data, filter corpora, judge outputs, and guide development decisions. These
'Switch to a cheaper model to save money' is a problem because cheaper models are worse (maybe they are good enough for a particular purpose, but still worse). More often a better approach is hierarch
arXiv:2310.05264v5 Announce Type: replace-cross Abstract: In this work, we investigate an intriguing and prevalent phenomenon of diffusion models which we term as 'consistent model reproducibility': g
arXiv:2606.09548v1 Announce Type: cross Abstract: Federated Learning (FL) allows a set of clients to collectively train a global model without sharing local training data. Giving the responsibility of
arXiv:2606.03540v1 Announce Type: new Abstract: Existing human attention (saliency) modeling methods persist as highly fragmented across modalities, scenes, and task formulations. Consequently, even w
arXiv:2606.02765v1 Announce Type: cross Abstract: Model dimension (d_{model}) is a fundamental hyperparameter in transformer language models, yet its role in setting the geometric limits of feature re
arXiv:2606.03603v1 Announce Type: cross Abstract: World models and multimodal large language models (MLLMs) provide complementary capabilities for predicting future outcomes from static visual observa
Jay Peters / The Verge: Microsoft debuts MAI-Thinking-1, its first advanced reasoning AI model, trained “from the ground up on clean data, without distillation from third-party models” — MAI-Thinking-
Super excited to announce seven new world-class MAI models today. They represent what we consider a new era in AI designed to keep you in control and on the frontier. First is our text foundation mode
arXiv:2605.30963v1 Announce Type: cross Abstract: We present AMix-2, a protein-text foundation model that establishes protein as a native modality in large language models (LLMs), unifying protein und
arXiv:2510.27607v3 Announce Type: replace Abstract: Augmenting vision-language-action models (VLAs) with world models is promising for robotic policy learning but faces challenges in jointly predictin
I cannot verify this claim as it references a future date (the URL timestamp appears invalid) and describes a model version (GPT-5.5 Pro) that doesn't exist in current public releases. The post appear
arXiv:2605.30219v1 Announce Type: new Abstract: Long-horizon interactions require language models to manage accumulating information: when to update their state, when to preserve their state, and what
arXiv:2605.27286v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) are transforming the forecasting paradigm through large-scale cross-domain pretraining. However, most existing T
arXiv:2602.05202v2 Announce Type: replace Abstract: Aligning video generative models with human preferences remains challenging: current approaches rely on Vision-Language Models (VLMs) for reward mod
arXiv:2605.23861v1 Announce Type: cross Abstract: Causal generative modeling is essential for developing reliable and transparent AI systems capable of counterfactual reasoning. While existing approac
arXiv:2510.07962v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated remarkable progress in reasoning, often through supervised fine-tuning (SFT). However, SFT is resourc
arXiv:2604.07303v2 Announce Type: replace Abstract: Understanding and modeling animal behavior is essential for studying collective motion, decision-making, and bio-inspired robotics. Yet, evaluating
arXiv:2605.17276v1 Announce Type: cross Abstract: While scaling laws have established a fundamental framework for foundation models in natural language processing, their applicability to electrocardio
GLM-5.1 from @Zai_org is now live on OrcaRouter • #1 open-source model on SWE-Bench Pro • Beats closed source models on real-world repo repair benchmarks • MIT licensed • 200K context • Built for long
arXiv:2510.02453v3 Announce Type: replace-cross Abstract: Frontier language models are deployed as black-box services, where model weights cannot be modified and customization is limited to prompting.
arXiv:2605.14028v1 Announce Type: new Abstract: Since the emergence of Vision Transformer (ViT), it has been widely used in generative language model and generative visual model. Especially in the cur
arXiv:2605.12843v1 Announce Type: cross Abstract: Model merging aims to combine multiple task-specific expert models into a single model without joint retraining, offering a practical alternative to m
arXiv:2605.13568v1 Announce Type: cross Abstract: Myocardial infarction (MI) is a leading cause of death, and its adverse outcomes are urgent to predict. Yet ECG-based prognostic models underperform b
arXiv:2605.13160v1 Announce Type: cross Abstract: Modern Bayesian optimization and adaptive sampling methods increasingly rely on nonlinear parametric models, yet theoretical guarantees for such model
arXiv:2605.10956v1 Announce Type: cross Abstract: Machine-learned surrogate modeling of advection may accelerate geoscientific models, but existing approaches have either achieved limited speedup or h
GLM models are now live on @tensorix_ai We’re partnering to bring cost-efficient frontier AI models to developers, startups, and enterprises across Europe and beyond — and to back the Sovereign AI eco
arXiv:2509.24244v4 Announce Type: replace Abstract: We study empirical scaling laws for language model merging measured by cross-entropy. Despite its wide practical use, merging lacks a quantitative r
arXiv:2605.08301v1 Announce Type: cross Abstract: Hybrid State-Space models combine Attention with recurrent State-Space Model (SSM) layers, balancing eidetic memory from Attention with compressed fad
arXiv:2512.13618v3 Announce Type: replace Abstract: Representing continuous time is a critical and under-explored challenge in modeling temporal event sequences with large language models (LLMs). Vari
arXiv:2605.10405v1 Announce Type: new Abstract: Selecting the best large language model (LLM) for a fixed benchmark is often expensive, since exhaustive evaluation requires running every model on ever
arXiv:2605.07301v1 Announce Type: new Abstract: Accurately predicting opponents' behavior from interactions is a fundamental capability for large language model (LLM)-based agents in multi-agent and g
arXiv:2605.01185v1 Announce Type: new Abstract: Accelerated magnetic resonance imaging (MRI) enabled by the training of deep learning (DL)-based image recon. models requires large and diverse raw k-sp
Sam Altman, CEO of OpenAI, recommended trying ChatGPT's new instant model, suggesting it performs significantly better than thinking-model-only approaches. The post encourages users who have relied ex
Stanford's latest seminar is a deep dive into the evolution of world modeling in AI. Focuses on the shift in the world model from traditional reconstruction methods toward latent space prediction. Cov
arXiv:2604.25159v1 Announce Type: new Abstract: Landslide investigation relies on sufficient and well-balanced observational data influenced by geological, hydrological, and anthropogenic factors. Ava
arXiv:2604.25416v1 Announce Type: new Abstract: Model-Based Reinforcement Learning distinguishes between physical dynamics models operating on proprioceptive inputs and latent dynamics models operatin
arXiv:2604.22981v1 Announce Type: new Abstract: Reward models in RLHF are trained to score only the final token of a response - a choice that discards rich signal from every intermediate position and
// Agentic World Modeling // Massive 40-author survey just dropped. Cleanest taxonomy of world models in agent research I've seen. (bookmark it) The paper proposes a 'levels × laws' framework. Three c
arXiv:2604.22167v1 Announce Type: cross Abstract: Language models are increasingly capable and are being rapidly deployed on a population-level scale. As a result, the safety of these models is increa
arXiv:2510.21285v4 Announce Type: replace Abstract: Large Reasoning Models (LRMs) achieve strong performance on complex multi-step reasoning, yet they still exhibit severe safety failures such as harm
I'd need to search for this specific Reddit discussion to provide an accurate summary of what was actually discussed. Let me retrieve that information. This Reddit post discusses using AI vision model
arXiv:2604.21686v1 Announce Type: new Abstract: Interactive video generation models such as Genie, YUME, HY-World, and Matrix-Game are advancing rapidly, yet every model is evaluated on its own benchm
arXiv:2506.02132v5 Announce Type: replace Abstract: Large transformer-based language models dominate modern NLP, yet our understanding of how they encode linguistic information relies primarily on stu
arXiv:2604.17153v1 Announce Type: new Abstract: Transforming legal text into executable decision logic is a longstanding challenge in legal informatics. With the rise of LLMs, this task has gained ren
arXiv:2509.12539v2 Announce Type: replace-cross Abstract: We present LEAF ('Lightweight Embedding Alignment Framework'), a knowledge distillation framework for text embedding models. A key distinguish
arXiv:2604.17830v1 Announce Type: new Abstract: Traditional Task and Motion Planning (TAMP) systems depend on physics models for motion planning and discrete symbolic models for task planning. Althoug
arXiv:2604.15611v1 Announce Type: cross Abstract: Latent diffusion models have emerged as powerful generative models in medical imaging, enabling the synthesis of high quality brain magnetic resonance
John Collison / Cheeky Pint: Q&A with ElevenLabs co-founder Mati Staniszewski on how audio models work, the company's business model, the conversational Turing Test, voice agents, and more — Mati Stan
arXiv:2511.05476v4 Announce Type: replace-cross Abstract: Transformer-based language models of code have achieved state-of-the-art performance across a wide range of software analytics tasks, but thei
arXiv:2604.11748v1 Announce Type: new Abstract: Continuous diffusion models have achieved strong performance across domains such as images. However, in language modeling, prior continuous diffusion la