Knowledge catalogue
arXiv:2606.05441v1 Announce Type: cross Abstract: We investigate how to make small tabular foundation models effective for High-Dimensional, Low-Sample Size (HDLSS) tabular prediction without retraini
arXiv:2606.05326v1 Announce Type: cross Abstract: We study the dynamics of gradient descent in the Edge of Stability regime, where the learning rate is large enough to induce persistent oscillations i
arXiv:2606.06303v1 Announce Type: cross Abstract: Controllable generation with discrete diffusion models is often hindered by high computational overhead or the need for retraining. In this paper, we
arXiv:2606.05217v1 Announce Type: cross Abstract: We exhibit an exact correspondence between sampling with score-based diffusion models and adiabatic transport of ground states for a family of Schrodi
This analysis from yesterday looks even more apt today — especially after we heard that the model providers have gone to Washington in search of handouts. ⚠️Why didn’t the hyperscalers wait until afte
arXiv:2606.05330v1 Announce Type: new Abstract: Large language models can shift human beliefs across high-stakes domains, but most persuasion studies rely on pre/post belief change. These endpoint mea
arXiv:2606.06186v1 Announce Type: new Abstract: Vision-Language Models (VLMs), such as CLIP, have shown strong zero-shot generalization but remain highly vulnerable to adversarial perturbations, posin
arXiv:2606.05840v1 Announce Type: cross Abstract: Nonlinear Model Predictive Control requires solving a constrained nonlinear program (NLP) in real-time at every sampling instant, a computational bott
arXiv:2308.10897v2 Announce Type: replace Abstract: We present a framework for generating appropriate facial responses from a listener in dyadic social interactions based on the speaker's words. Given
arXiv:2606.06120v1 Announce Type: new Abstract: Contrastive Analysis aims to separate factors that are common between two data distributions from those that are salient to only one of them. Existing c
arXiv:2606.05936v1 Announce Type: new Abstract: Modern language models rely on pretraining filters to remove undesirable content from training corpora and inference-time guardrails to suppress undesir
arXiv:2606.05254v1 Announce Type: cross Abstract: World-action models (WAMs) jointly generate future video and robot actions through iterative diffusion, achieving strong performance on manipulation b
Introducing Ideogram 4 from @ideogram_ai on Together AI, an open image model built for design with strong text rendering, layout control, and native 2K image generation. AI natives can now use Ideogra
arXiv:2602.08503v2 Announce Type: replace-cross Abstract: Self-correction is essential for solving complex reasoning problems in vision-language models (VLMs). However, existing reinforcement learning
arXiv:2508.20693v2 Announce Type: replace-cross Abstract: Ontologies and taxonomies of research fields are critical for managing and organising scientific knowledge, as they facilitate efficient class
arXiv:2606.06103v1 Announce Type: new Abstract: Medical image segmentation is often framed as a search for stronger architectures, but this can obscure a more fundamental question: what does the datas
Michael Considine / CNBC: OpenAI confirms it will comply with President Trump's EO that asks AI companies to allow the US government to assess their models' capabilities before release — OpenAI has co
arXiv:2606.06060v1 Announce Type: new Abstract: Modern diffusion models generate high-quality images and videos, but their iterative denoising process makes inference expensive. Feature caching accele
arXiv:2606.05194v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly being deployed to make decisions that require trading off near-term gains against long-term consequences
Wow Ideogram-4.0 is immediately going into my @ComfyUI library of models. Ideogram even joins the top 10 all-around image leaderboard joining Microsoft, Google, Grok and OpenAI. In the Image Arena: op
1/ 🔥 @NoPriorsPod x @LatentSpacePod chat with @SatyaNadella at @Microsoft Build. He has the sharpest mental models of any public company CEO I've interviewed. $MSFT is at its heart still a tools compa
arXiv:2606.04177v1 Announce Type: cross Abstract: Interpretable linguistic features offer a promising approach for explaining why a given text appears machine-generated, particularly for non-expert us
arXiv:2606.04775v1 Announce Type: cross Abstract: Text-to-video (T2V) models trained on large-scale web data can generate undesired content, motivating interventions that reduce harmful outputs withou
arXiv:2606.04613v1 Announce Type: new Abstract: Vision-Language Models (VLMs) struggle when applied to medical image-text data, yet the tools available to diagnose this failure remain limited. Existin
arXiv:2601.09719v3 Announce Type: replace-cross Abstract: Pre-Layer Normalization (Pre-LN) is the de facto choice for large language models (LLMs) and is crucial for stable pretraining and effective t
arXiv:2601.22396v2 Announce Type: replace-cross Abstract: Despite the growing utility of Large Language Models (LLMs) for simulating human behavior, the extent to which these synthetic personas accura
arXiv:2606.04535v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer bidirectional attention and parallel generation, enabling them to exploit global context and naturally s
arXiv:2606.04922v1 Announce Type: cross Abstract: Current prompt-based and adapter-based tuning of vision-language models (VLMs) is attractive for medical imaging, where clinical data sensitivity favo
arXiv:2606.04516v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) significantly advances LLM reasoning, yet it faces a dilemma: standard supervised scaling is thr
arXiv:2602.03920v2 Announce Type: replace Abstract: Robot Foundation Models (RFMs) represent a promising approach to developing general-purpose home robots. Given the broad capabilities of RFMs, users
Introducing Magenta RealTime 2 🎺 - Open model for live music generation - Just 2.4B parameters, perfect for on-device - Low latency control - Control with audio, MIDI, and text We're releasing it with
It seems like @GaryMarcus was right: the AI revenue models are imploding Sam Altman said AI budgeting has recently become a 'huge issue' for some companies, something that 'never came up' earlier this
Locally is now LM Studio’s mobile app. And today we're bringing LM Link to iPhone. Use your largest local models over a secure, end-to-end encrypted connection, anywhere you go. Download the app now:
arXiv:2606.04534v1 Announce Type: new Abstract: Agile quadrotor flight in cluttered scenes requires more than a reactive mapping from a depth image to a control command: the vehicle must remember whic
arXiv:2606.04027v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) generate text by iteratively denoising partially masked sequences under bidirectional context, exposing a safe
Ben Thompson / Stratechery: Q&A with Satya Nadella on Microsoft's competitive position, MAI models, OpenAI, the software business, GitHub Copilot, Project Solara, data centers, and more — An interview
arXiv:2606.04396v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) generate responses by iteratively unmasking and revising many positions in parallel. This process leaves a rich
arXiv:2606.04576v1 Announce Type: cross Abstract: Learning Value-at-Risk (VaR) and Expected Shortfall (ES) is important for managing financial risks effectively. Existing approaches with limited param
arXiv:2606.04974v1 Announce Type: new Abstract: Diffusion large language models (DLLMs) enable non-autoregressive generation by iteratively denoising corrupted token sequences with bidirectional conte
arXiv:2606.04287v1 Announce Type: cross Abstract: Generating realistic and diverse graphs is a key problem in machine learning, with applications in molecular discovery, circuit design, cybersecurity,
arXiv:2510.13796v3 Announce Type: replace Abstract: Symbol grounding (Harnad, 1990) describes how symbols such as words acquire their meanings by connecting to real-world sensorimotor experiences. Rec
arXiv:2601.11214v5 Announce Type: replace Abstract: We present T^star, a simple TraceRL-based training curriculum for progressive block-size scaling in masked diffusion language models (MDMs). Startin
arXiv:2606.03903v1 Announce Type: new Abstract: Diffusion-weighted imaging (DWI) is used for whole-body cancer screening, but it typically requires a long acquisition time. When the scan time is reduc
arXiv:2606.03270v1 Announce Type: cross Abstract: Foundation models have sparked a revolution via a pretraining-adaptation paradigm, with recent efforts extending this success to graphs. Unlike other
At this point, I suspect you could put endpoints named 0pus 4.8 & GPT 5.S in your apps powered by open-source models and it would get massive usage without people complaining. The power of 'frontier'
arXiv:2606.03398v1 Announce Type: cross Abstract: Formal languages have proven to be effective conduits to understand the inner mechanisms of transformers. Past work has shown that transformers traine
arXiv:2508.03668v2 Announce Type: replace Abstract: Click-Through Rate (CTR) prediction, a core task in recommendation systems, estimates user click likelihood using historical behavioral data. Modeli
Day 2 at #MSBuild is about what it takes to move beyond generic foundation models. Think customization, inference performance, and getting production-ready AI deployed at scale. @chahvivi will lead a
arXiv:2601.11667v2 Announce Type: replace-cross Abstract: Transformer architectures deliver state-of-the-art accuracy via dense full-attention, but their quadratic time and memory complexity with resp
Fundamental's NEXUS is a foundation model designed specifically for tabular data, trained on billions of tabular datasets using Amazon SageMaker HyperPod to understand non-linear relationships across
arXiv:2606.03240v1 Announce Type: new Abstract: Current Vision--Language--Action (VLA) models often optimize for semantic grounding, whereas executable manipulation requires geometry-aware spatial ali
arXiv:2606.02857v1 Announce Type: cross Abstract: Zeroth-order (ZO) optimization is a memory-efficient alternative to backpropagation for fine-tuning large language models, but its deployment is limit
Ideogram 4.0 is now natively supported on ComfyUI @ideogram_ai v4.0 is an open-weight 9.3B text-to-image foundation model. It is exclusively trained on structured JSON caption datasets for precise sce
I'm finally launching this agent tomorrow! Will be free, open source, and powered exclusively by open models on @togethercompute. Will also drop a full guide on how it works! Building an agent that ca
Introducing Ideogram 4.0: the best open image model in the world. Think it. Make it. Own it. Download the weights, fine-tune on your own data, and run it on your hardware. Live on every Ideogram plan
arXiv:2512.09106v4 Announce Type: replace Abstract: Diffusion (Large) Language Models (dLLMs) now match the downstream performance of their autoregressive counterparts on many tasks, while holding the
Most people, including really accomplished people, don't have an accurate mental model of how LLMs operate (and why would they?) You see this in wide beliefs that AI is just copying from known sources
arXiv:2606.02623v1 Announce Type: cross Abstract: Solving time-dependent partial differential equations (PDEs) is an important problem in computational science and engineering. Physics-informed neural
arXiv:2511.10055v2 Announce Type: replace Abstract: The performance of image generation has been significantly improved in recent years. However, the study of image screening is rare, and its performa
arXiv:2502.02748v4 Announce Type: replace Abstract: Predicting properties of crystals from their structures is a fundamental yet challenging task in materials science. Unlike molecules, crystal struct