Knowledge catalogue
Anthropic PBC, the developer and provider of the Claude artificial intelligence model family, said it’s offering a special credit pool for users who want to use agentic tools with its large language m
Anthropic PBC today launched an offering called Claude for Small Business that is designed to expand the adoption of its chatbot among entrepreneurs. The feature bundle is the fifth market-specific ve
any time a model router company drops data, its worth browsing. here we learn that gemini leads in education and personal assistants (?!), ant leads in vibecoding and koding and back office (?!), and
arXiv:2605.13724v1 Announce Type: cross Abstract: Few-step video generation has been significantly advanced by consistency distillation. However, the performance of consistency-distilled models often
APPLEBAUM: Russia's war in Ukraine is sometimes described, including recently by American Vice President, as if it were nothing more than territorial dispute, kind of scuffle over lines on map. But wh
This article discusses designing and implementing data pipelines capable of processing large-scale multimodal datasets (combining text, images, video, audio, etc.) using Ray, an open-source distribute
arXiv:2605.13517v1 Announce Type: cross Abstract: Vector Quantized Variational Autoencoder (VQ-VAE) has become a fundamental framework for learning discrete representations in image modeling. However,
arXiv:2605.12575v1 Announce Type: cross Abstract: Whole-slide image (WSI) multiple instance learning (MIL) classifiers can achieve strong slide-level AUC while leaving the full-bag prediction opaque.
Are scaling laws finally working for time series foundation models? Today, @datadoghq is releasing Toto 2.0 weights in Apache 2.0 on @huggingface. It's a family of open-weights TSFMs from 4M to 2.5B p
Ollama offers several memory management settings, including the ability to reduce context length (context window) to decrease VRAM usage, which can save 0.2-0.4GB for 7-8B models when reduced from 8K
Portable Reachy Mini is likely a compact, mobile robotic arm or manipulation device, with this post from Hugging Face's CEO Clem Delangue presumably announcing or promoting its availability or readine
AI trust infrastructure is quickly becoming a critical requirement as enterprises scale intelligent systems across their operations. The focus is shifting from simple data protection to securing, gove
arXiv:2605.12879v1 Announce Type: new Abstract: Doubly-stochastic attention has emerged as a transport-based alternative to row-softmax attention, with recent Transformer variants using it to reduce a
arXiv:2605.12845v1 Announce Type: cross Abstract: Assembling objects from parts requires understanding multimodal instructions, linking them to 3D components, and predicting physically plausible 6-DoF
arXiv:2605.13450v1 Announce Type: new Abstract: Measuring the creativity of large language models (LLMs) is essential for designing methods that can improve creativity and for enhancing our scientific
arXiv:2605.12964v1 Announce Type: new Abstract: Flow-based generation in high-dimensional spaces is difficult because velocity prediction requires modeling high-dimensional noise, even when data has s
arXiv:2605.13442v1 Announce Type: new Abstract: Autonomous robotic exploration in remote and extreme environments allows scientists to model complex transport phenomena and collective behaviors descri
arXiv:2512.10931v3 Announce Type: replace Abstract: Many state-of-the-art LLMs are trained to think before giving their answer. Reasoning can greatly improve language model capabilities, but it also m
arXiv:2605.13548v1 Announce Type: cross Abstract: Existing robotic foundation models, while powerful, are predicated on an implicit assumption of temporal homogeneity: treating all actions as equally
Attention @arxiv authors: Our Code of Conduct states that by signing your name as an author of a paper, each author takes full responsibility for all its contents, irrespective of how the contents wer
arXiv:2605.13784v1 Announce Type: new Abstract: Conventional transformer inference engines are request-driven, paying an O(n) prefill cost on every query. In streaming workloads, where data arrives co
arXiv:2602.02560v2 Announce Type: replace-cross Abstract: Lung cancer remains the leading cause of cancer mortality, driving the development of automated screening tools to alleviate radiologist workl
arXiv:2605.12937v1 Announce Type: cross Abstract: Anti-facial recognition (AFR) image filters alter images in ways that are subtle to people but blinding to computer vision. Yet, despite widespread in
Unified identity security platform provider Permiso Security Inc. today launched AI agent runtime security capabilities that give security teams continuous visibility into agent activity across cloud
arXiv:2605.06390v2 Announce Type: replace Abstract: A leading proposal for aligning artificial superintelligence (ASI) is to use AI agents to automate an increasing fraction of alignment research as c
arXiv:2601.15161v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used for clinical decision support, where hallucinations and unsafe suggestions may pose direct
Automating AI research is the next major step in AI We let Claude Code (Opus 4.7) and Codex (GPT 5.5) run autonomously on the nanoGPT speedrun optimizer track using our idle compute. ~10k runs, ~14k H
The search did not return specific information about the b9140 release. Based on the context, b9140 is a specific build number from the llama.cpp project releases. llama.cpp is an LLM inference implem
Release b9142 is an intermediate build of llama.cpp, a C/C++ library for running large language model inference on consumer hardware. llama.cpp performs inference on various large language models and
The search results show releases near b9143 (specifically b9134 was the most recent) but do not contain specific details about b9143 itself. Based on the available information: llama.cpp is a C/C++ im
llama.cpp is an open source software library that performs inference on various large language models such as Llama. Build b9144 is an intermediate release version of the llama.cpp project from the gg
The search results show recent llama.cpp releases but don't contain specific details about the b9145 build. Based on the pattern of changes in recent releases, b9145 likely includes updates to SYCL/Le
Release b9148 of llama.cpp adds a non-backtracking tokenizer handler for Qwen3.5 to handle Unicode regex patterns for letters and combining marks, addressing stack overflow issues on long inputs. The
b9150 is a llama.cpp release that adds a custom Unicode regex handler for Qwen3.5's tokenizer to prevent stack overflows on long inputs. The release includes test vocabularies and updated test configu
Release b9151 of llama.cpp includes enhancements to Unicode regex handling for Qwen3.5's tokenizer, adding a custom non-backtracking handler to prevent stack overflows on long inputs. The release also
B9156 is a llama.cpp release that adds enhanced Unicode regex handling for Qwen3.5 tokenization, implementing a non-backtracking handler to prevent stack overflows on long inputs . The release include
B9158 is a llama.cpp release that adds a custom Unicode regex handler for Qwen3.5 tokenization to prevent stack overflows on long inputs. The release includes test vocabulary files and expected output
arXiv:2605.13381v1 Announce Type: new Abstract: As AI-generated synthetic images become increasingly realistic, Vision Transformers (ViTs) have emerged as a cornerstone of modern deepfake detection. H
arXiv:2605.13214v1 Announce Type: cross Abstract: Recent cryptographic results establish that neural networks can be backdoored such that no efficient algorithm can distinguish them from a clean model
Batching for vision models is now available in Beta with our latest MLX engine update 👾 The updated engine also brings major improvements to caching for faster inference overall. Turn on Developer Mod
arXiv:2605.13455v1 Announce Type: new Abstract: Synapses are densely packed submicron structures that dynamically reorganize during learning and memory formation. Longitudinal extit{in vivo} imaging o
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:2605.13088v1 Announce Type: new Abstract: Dynamical modelling is central to many scientific domains, including pharmacometrics, systems biology, physiology, and epidemiology. In these settings,
beautiful tech stack writeup, one of the best i've ever seen in my career. I always advocate that devtools companies write these up, because it fulfils multiple purposes: - tell users the care that go
arXiv:2409.02038v3 Announce Type: replace-cross Abstract: Existing text-to-SQL benchmarks have largely been constructed from public databases with well-structured schemas and simplistic question-SQL p
arXiv:2605.12726v1 Announce Type: new Abstract: Final-token safety probes monitor a single hidden state after prompt prefill, but jailbreak prompts can contain probe-visible unsafe evidence distribute
arXiv:2605.12730v1 Announce Type: new Abstract: Existing AI systems for modeling human behavior operate at the level of individuals or detect events after they occur. As a result, they systematically
arXiv:2510.01502v2 Announce Type: replace-cross Abstract: Current video foundation models, including the strongest self-supervised models such as V-JEPA2, fail to capture how humans organize social in
Yesterday, in Musk v. Altman, before the jurors came in, Sam Altman's team passed up what looked - from a distance - like a little league trophy. It was not. Yvonne Gonzalez Rogers had the lawyers rea
Sam Altman shared a personal reflection on fatherhood, expressing that being a dad has surpassed his already-high expectations more than any other experience in his life. The post highlights how paren
being vulnerable - by far one of the most important applied ai fields is in AI x Healthcare, but nobody on my team knows how to cover it! very fortunate to have @jacobeffron on the pod for this one -
arXiv:2605.12710v1 Announce Type: new Abstract: Residual risk metrics have recently been introduced to assess the safety implications of automated driving systems. Existing approaches typically assume
arXiv:2512.18951v3 Announce Type: replace Abstract: Infants learn not only object categories but also fine-grained visual attributes such as color, size, and texture from limited experience. Prior inf
arXiv:2605.13574v1 Announce Type: cross Abstract: This study investigates deep self-disclosure toward generative AI by examining perceived non-humanity and structural similarity as psychological facto
arXiv:2605.12894v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly deployed in settings where they interact with a wide variety of people, including users who are uncle
arXiv:2605.13520v1 Announce Type: cross Abstract: We address shortcomings of principal component analysis (PCA) for visualizing high-dimensional data lying on a nonlinear low-dimensional manifold via
arXiv:2605.12512v1 Announce Type: cross Abstract: Driven by large language models (LLMs), social bot can autonomously engage in local interactions, whose human-like behaviors enable them to evade soci
arXiv:2605.13383v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) perform computations on graphs by routing the signal between graph regions using a graph shift operator or a message passin
arXiv:2605.13652v1 Announce Type: cross Abstract: Pre-training large language models is dominated by the memory cost of storing full-rank weights, gradients, and optimizer states. Low-rank pre-trainin
arXiv:2509.24728v2 Announce Type: replace Abstract: Latent categorical variables are frequently found in deep learning architectures. They can model actions in discrete reinforcement-learning environm