Good training settings for Chroma1-HD
Chroma1-HD is recommended for quick fine-tuning or LoRA on high-resolution 1024x1024 images . The model applies a quadratic remapping to timestep sampling to ensure training visits tail regions more o
Knowledge catalogue
Chroma1-HD is recommended for quick fine-tuning or LoRA on high-resolution 1024x1024 images . The model applies a quadratic remapping to timestep sampling to ensure training visits tail regions more o
arXiv:2604.14980v1 Announce Type: cross Abstract: Building on recent advances in AI, hybrid decision making (HDM) holds the promise of improving human decision quality and reducing cognitive load. We
arXiv:2604.13180v1 Announce Type: new Abstract: Recent advances in agentic AI have enabled increasingly autonomous workflows, but existing systems still face substantial challenges in achieving reliab
arXiv:2410.08329v3 Announce Type: replace Abstract: Computational wave imaging (CWI) extracts hidden structure and physical properties of a volume of material by analyzing wave signals that traverse t
arXiv:2604.13495v1 Announce Type: new Abstract: Alzheimer's disease (AD) progresses heterogeneously across individuals, motivating subject-specific synthesis of follow-up magnetic resonance imaging (M
arXiv:2604.13409v1 Announce Type: new Abstract: In clinical practice, the robustness of deep learning models for multimodal brain tumor segmentation is severely compromised by incomplete MRI data. Thi
arXiv:2603.29159v2 Announce Type: replace Abstract: Providing timely and accurate learning support in large-scale online coding courses is challenging, particularly in resource-constrained contexts. W
arXiv:2604.13479v1 Announce Type: cross Abstract: Semantic segmentation of histopathology images under class imbalance is typically addressed through frequency-based loss reweighting, which implicitly
There's a broadly held misconception in AI that methods that scale well are simple methods -- even, that simple methods usually scale. This is completely wrong. Pretty much none of the truly simple me
arXiv:2604.12574v1 Announce Type: new Abstract: Detecting amyloid-eta (Aeta) positivity is crucial for early diagnosis of Alzheimer's disease but typically requires PET imaging, which is costly, invas
IC LoRAs are a technique for controlling video generation, likely enabling fine-grained stylistic or motion control through specialized LoRA (Low-Rank Adaptation) models applied to video workflows. Th
arXiv:2604.12874v1 Announce Type: new Abstract: The rapid advancement of AI has changed the character of HPC usage such as dimensioning, provisioning, and execution. Not only has energy demand been am
This Reddit post is a reminder to the r/MachineLearning community about an upcoming Ask Me Anything (AMA) session with Max Welling, Chief AI Officer at CuspAI and Professor of Machine Learning at the
arXiv:2604.12970v1 Announce Type: cross Abstract: Multimodal federated learning enables privacy-preserving collaborative model training across healthcare institutions. However, a fundamental challenge
Linus Lee and the Sandbar team have been exploring the design and architecture of a Stream SDK that integrates AI agents and voice capabilities as core, readily accessible features. The project appear
Face and head swapping capabilities are available for LTX 2.3, primarily through external LoRA models and ComfyUI workflows rather than built-in native features. A dedicated face replacement workflow
Reuters: AWS launches Amazon Bio Discovery, an AI-powered application designed to speed up drug development, giving scientists access to biological foundation models — Amazon's (AMZN.O) cloud unit on
This r/StableDiffusion post documents a community experiment exploring techniques for generating images of two identical-looking subjects ('twins') using Stable Diffusion without relying on a LoRA mod
arXiv:2604.11623v1 Announce Type: new Abstract: We introduce Context Kubernetes, an architecture for orchestrating enterprise knowledge in agentic AI systems, with a prototype implementation and eight
A tool shared on r/StableDiffusion, the Danbooru Dataset Filter is a local search utility that enables fast, metadata-based filtering across 10M+ Danbooru anime images without needing to download the
Today, we're thrilled to announce that BigQuery Graph is now available in preview. With BigQuery Graph, we’ve built an easy-to-use, highly scalable graph analytics solution for data engineers, data an
This Reddit thread from r/StableDiffusion discusses best practices for captioning training datasets when fine-tuning LoRA models on LTX 2.3, Lightricks' video generation model. The community emphasis
'Monde Noveau' is a Reddit post on r/StableDiffusion showcasing an AI-generated animation created in a flipbook-style aesthetic, accompanied by the public release of a custom LoRA (Low-Rank Adaptation
arXiv:2512.02393v3 Announce Type: replace-cross Abstract: Agentic systems are modern software systems: they consist of orchestrated modules, expose interfaces, and are deployed in software pipelines.
arXiv:2307.01139v2 Announce Type: replace-cross Abstract: Instruction finetuning is a popular paradigm to align large language models (LLM) with human intent. Despite its popularity, this idea is less
arXiv:2511.05782v2 Announce Type: replace Abstract: Unsupervised domain adaptation for medical image segmentation remains a significant challenge due to substantial domain shifts across imaging modali
arXiv:2604.10800v1 Announce Type: cross Abstract: Learned classifiers deployed in agentic pipelines face a fundamental reliability problem: predictions are probabilistic inferences, not verified concl
Yann LeCun shared or engaged with a post on X expressing concern about the erosion of public health infrastructure in the United States, specifically referencing the potential resurgence of eradicated
EinsteinArena is an open-source benchmarking platform developed by Together AI designed to evaluate and rank AI models, with a live public leaderboard tracking model performance. The project welcomes
This Reddit post from r/StableDiffusion discusses a community comparison or showcase involving a 'Zit LoRA' — a Stable Diffusion LoRA model — examining how it performs differently when applied to face
This r/StableDiffusion post addresses a common beginner question about whether Stable Diffusion can be used to generate new images based on an existing original character (OC), such as one from fan ar
This isn't the only result. As of April 11, agents have set 11 new SOTA results on open problems including: → Erdős minimum overlap problem → Second autocorrelation inequality → Tammes problem (n=50)
This Reddit post from r/MachineLearning discusses an experiment in which a transformer model was fine-tuned or prompted to encode the niche biological fact that wombats produce cube-shaped droppings —
This Reddit thread from r/StableDiffusion discusses community recommendations for choosing the best base model on which to train a LoRA (Low-Rank Adaptation) capturing M.C. Escher's distinctive tessel
Francois Chollet, AI researcher and creator of Keras, argues that good design is fundamentally an act of compression — distilling an enormous number of implementation decisions, constraints, and consi
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In the enterprise landscape, data is often highly fragmented across multiple source systems. Data curation is the process of organizing, cleaning, and enriching raw data to transform it into high-qual
arXiv:2604.07102v1 Announce Type: cross Abstract: Activation-based steering can personalize large language models at inference time, but its effects in educational settings remain unclear. We study pe
The reason symmetry is so important in physics is because symmetry is a highly effective compression operator. If a system is invariant under some symmetry, you only need to explain one axis of it. Sc
Simplicity is a very strong signal of model quality. Galileo's heliocentric model was directionally correct, but its predictive power was quite bad compared to the much older Ptolemaic model, because
We should view the history of physics as a long-running program synthesis task. Kepler and Newton were searching the space of possible symbolic models to find the simplest one that would best satisfy
arXiv:2610.15371v1 Announce Type: cross Abstract: Gnani-Evon-v3.3-30B-A3B is a long-context hybrid Mamba-Transformer mixture-of-experts model for reasoning, instruction following, and tool use in Engl
arXiv:2610.14356v1 Announce Type: new Abstract: AI-enabled systems must remain dependable when the conditions under which they operate change (e.g., due to input perturbations, distribution shifts, or
arXiv:2610.14382v1 Announce Type: new Abstract: Agentic AI systems operating over geospatial data require more than autonomous reasoning and tool use; they must also support explicit orchestration, sp
arXiv:2610.03998v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used as synthetic personas representing survey respondents. Their validity as substitutes for particul
arXiv:2610.18314v1 Announce Type: new Abstract: This work discusses and tests the potential of reaction graphs for material synthesis, in which events consist of reaction steps (actions) and their out
arXiv:2610.19625v1 Announce Type: new Abstract: We propose DAGFormer, a Transformer language model whose cross-layer connections are planned by a jointly trained topology predictor. Beyond the residua
arXiv:2610.19525v1 Announce Type: cross Abstract: Verifiable instruction-following benchmarks emphasize output-constraint satisfaction but can overlook whether responses meaningfully answer the underl
arXiv:2610.19157v1 Announce Type: cross Abstract: Code generation models are actively being used in professional and educational settings. However, the competence of large language models (LLMs) to ge
GPT-Rosalind is built to support that work: helping researchers reason across scientific literature and biological data, with scientists bringing the expertise and judgment to evaluate the evidence. E
arXiv:2610.19185v1 Announce Type: new Abstract: Evaluation of large language models (LLMs) remains largely pre-scientific: it involves many design decisions, with little guidance on how to make them.
arXiv:2610.19568v1 Announce Type: new Abstract: Latent reasoning replaces natural-language chains of thought with compact continuous 'soft-token' representations, reducing the number of intermediate t
arXiv:2610.20350v1 Announce Type: cross Abstract: Preference optimization ranks final answers and trajectory RL maximizes aggregate returns, yet neither credits the local change that turns a flawed re
arXiv:2610.18522v1 Announce Type: new Abstract: Reusable skills let LLM agents load task-specific instructions on demand, but they make execution depend on implicit routing over skill metadata. We tes
arXiv:2610.15714v1 Announce Type: new Abstract: Healthcare agents must transform longitudinal clinical evidence into reliable actions through heterogeneous tools and stateful workflows, conditions und
arXiv:2606.20235v2 Announce Type: replace-cross Abstract: Academic paper search is a core step in scientific research, and LLM-based search agents are emerging as a promising paradigm for iterative, i
arXiv:2610.16127v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly explored in the Architecture, Engineering, and Construction (AEC) domain, yet their reliability in regul
Banger paper from Stanford, Together AI, and colleagues. Why is this an interesting paper? Today's LLM agents must write out every reasoning step as text before they can search, run code, or take acti
arXiv:2610.14024v1 Announce Type: new Abstract: Physics time-series data are central to fundamental discoveries involving dark matter, neutrinos, and gravitational waves. Machine learning has shown st
arXiv:2610.17733v1 Announce Type: new Abstract: Rubric-based reinforcement learning (RL) evaluates responses against explicit criteria to construct rewards, offering a viable way to train large langua