Knowledge catalogue
arXiv:2506.17467v2 Announce Type: replace Abstract: Large language models (LLMs) have shown significant potential to change how we write, communicate, and create, leading to rapid adoption across soci
arXiv:2608.01460v1 Announce Type: new Abstract: Conformal prediction (CP) is a distribution-free framework for uncertainty quantification that has recently been adapted to large language models (LLMs)
arXiv:2608.01985v1 Announce Type: new Abstract: Visual token pruning reduces the computational cost of Vision-Language Models (VLMs) by removing redundant visual tokens. The key is to learn a score th
arXiv:2506.04831v3 Announce Type: replace-cross Abstract: Forecasting how a patient's condition is likely to evolve, including possible deterioration, recovery, treatment needs, and care transitions,
arXiv:2608.01221v1 Announce Type: new Abstract: Autonomous endoscopic navigation can reduce clinicians' operational burden, yet robust control remains challenging due to tissue deformation, transient
arXiv:2608.01572v1 Announce Type: new Abstract: Autonomous driving (AD) systems have advanced rapidly over the past decade; however, robust perception under adverse weather conditions remains a major
arXiv:2608.00635v1 Announce Type: new Abstract: We present FlowPilot, a compact world-action model for real-time onboard UAV navigation from depth. Unlike map-then-optimize pipelines that require loca
arXiv:2608.00726v1 Announce Type: new Abstract: Frozen vision foundation models are commonly evaluated through a single global image embedding, but this interface can conflate missing information with
arXiv:2603.13418v2 Announce Type: replace Abstract: Structured pruning is widely applied to compress large language models (LLMs), but its performance depends heavily on how neuron importance is estim
arXiv:2604.00086v2 Announce Type: replace-cross Abstract: The field of computer vision has experienced significant advancements through scalable vision encoders and multimodal pre-training frameworks.
arXiv:2602.11133v2 Announce Type: replace-cross Abstract: Diffusion language models generate text through iterative refinement, a process that is often computationally inefficient because many tokens
arXiv:2608.00581v1 Announce Type: new Abstract: Off-the-shelf LID and letter heuristics over-label Kazakh-Russian social text as mixed: Russian loanwords inside Kazakh look like code-switching under a
arXiv:2608.02216v1 Announce Type: new Abstract: Vision-language models (VLMs) such as CLIP exhibit remarkable zero-shot capabilities, yet their performance frequently degrades sharply under unexpected
arXiv:2603.03672v2 Announce Type: replace Abstract: The Shapley value provides a principled foundation for data valuation, but exact computation is #P-hard due to the exponential coalition space. Exis
arXiv:2608.00976v1 Announce Type: new Abstract: Fine-grained visual representations are essential for medical image analysis, particularly when diagnostically relevant evidence is subtle and spatially
arXiv:2608.02520v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for health-related advice. Existing research measures their safety with static questions rather than
arXiv:2608.02059v1 Announce Type: new Abstract: Recent advances in unified multimodal models have significantly improved text-guided image editing abilities. In particular, models such as Nano-Banana-
arXiv:2608.00400v1 Announce Type: new Abstract: Nonlocal partial differential equations arise in many applications but are often difficult to model and learn because of the presence of nonlocal operat
arXiv:2409.03901v4 Announce Type: replace Abstract: Remote sensing (RS) image classification is central to Earth observation, but onboard deployment requires models that are accurate, efficient, and r
arXiv:2608.00345v1 Announce Type: new Abstract: A 3D CT scan entering a vision-language model produces a long sequence of visual tokens, often thousands to tens of thousands per volume, and this seque
arXiv:2608.00383v1 Announce Type: cross Abstract: Logical rule induction seeks interpretable rules that transfer across propositional schemas. This requires respecting symmetries: atom naming, example
arXiv:2608.02575v1 Announce Type: new Abstract: Diffusion models rely on stochastic inputs, yet on finite-precision hardware, the 'randomness' they consume is realized as deterministic numerical orbit
arXiv:2608.02157v1 Announce Type: new Abstract: Raman spectroscopy enables non-destructive, label-free molecular characterization across materials science, biomedicine and process monitoring. Predicti
arXiv:2608.00068v1 Announce Type: new Abstract: Construction-safety models must handle concrete deployment risks, such as a worker standing near a scaffold edge without guardrails, rather than only re
arXiv:2510.23816v3 Announce Type: replace Abstract: High spatial resolution satellite imagery is critical for monitoring fine-scale Earth surface processes, but is often limited by cost and revisit ti
arXiv:2608.01676v1 Announce Type: new Abstract: Sparse attention is widely deployed in long-context serving stacks, yet no framework audits how discarding blocks changes the influence of specific cont
arXiv:2608.01017v1 Announce Type: new Abstract: A language model that abandons a correct medical answer under user pushback is more dangerous than one that was simply wrong, because it lends the credi
Zvi Mowshowitz / Don't Worry About the Vase: A detailed recap of the real-world target hacks by OpenAI and Anthropic models, exposing failures in AI alignment training and lack of meaningful supervisi
arXiv:2607.28978v1 Announce Type: new Abstract: This paper proposes an automated classification method of COVID-19 chest CT volumes using improved 3D MLP-Mixer. Novel coronavirus disease 2019 (COVID-1
arXiv:2603.24917v3 Announce Type: replace Abstract: Recent work shows that standard greedy-decoding extraction methods for quantifying memorization in LLMs miss how extraction risk varies across seque
arXiv:2607.28934v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly involved in the distribution of scarce resources, raising concerns about biased allocations based on cha
arXiv:2607.28667v1 Announce Type: cross Abstract: Recent work has shown that classifying large language models (LLMs)' responses can be distinguished by modeling token embeddings as trajectories of a
.@huggingface CEO @ClementDelangue says the recent OpenAI-linked cyberattack highlights the growing risks posed by rapidly-evolving AI models. Speaking to @edludlow, Delangue says that open-source AI
arXiv:2603.17205v3 Announce Type: replace-cross Abstract: Domain-specific finetuning is essential for dense retrievers, yet not all data pairs contribute equally to the learning process. We introduce
arXiv:2507.22580v2 Announce Type: replace-cross Abstract: Automated Program Repair (APR) seeks to automatically correct software bugs without requiring human intervention. However, existing tools tend
An exclusive report by Reuters today has surfaced evidence that suggests Chinese artificial intelligence firms have been leveraging the outputs of American frontier models developed by OpenAI Group PB
The Inference Engineering Masterclass: 10x faster models, quantization, speculative decoding, Rubin, & self-optimizing AI https://www.latent.space/p/inference-eng @Baseten @philipkiely and @waterloo_i
arXiv:2607.29334v1 Announce Type: cross Abstract: Conversational AI developed by geopolitical rivals reaches citizens worldwide, raising concerns that it could sway public opinion or be rejected as fo
arXiv:2607.28887v1 Announce Type: cross Abstract: Large language models increasingly write and repair production code, yet evidence is mounting that their test-passing patches leave codebases harder t
Using optimization at inference time is a foundational concept of Energy-Based Models (EBM) and Objective-Driven AI architectures (ODAI). When the variables to be inferred are continuous, it makes sen
Lily Hay Newman / Wired: Experts say US law is unprepared for rogue AI agents and models, as recent OpenAI and Anthropic incidents raise questions over legal liability and repercussions — Both major A
# Running DeepSeek-V4-Flash-0731 (155 GB MoE) on a DGX Spark with vLLM-Moet 2-bit quantization I used Deepseek-v4-Flash-0731 cloud API settig up vllm-moet to run deepseek-v4-flash with MTP locally on
Built my 1st inference machine and have been tweaking models trying to get the most out of my modest hardware. I think I’m at a good place but I’m testing with my own prompts. I’ve looked into some of
2/ a cost benchmark showed the same coding task running three to four times cheaper, depending purely on the harness wrapped around the model. Same intelligence, wildly different accuracy and cost, de
I'm currently using the gemma4:31b-cloud, and it is pretty good, but sometimes it gets confused. Are there more free tier models out there I should try out? or is gemma4 the cap of free tier cloud mod
Hello all - i just got a new mac mini with 24GB of RAM and wanting to run local AI for Home Assistant and Hermes. I have been struggling to find a snapy model that will work with my machine. Currently
arXiv:2607.28236v1 Announce Type: cross Abstract: Pre-trained language models have significantly improved sentence representation learning, yet their embedding remain sensitive to semantic preserving
arXiv:2607.27773v1 Announce Type: new Abstract: LLM agents increasingly rely on long-term memory to support multi-session interaction and personalization. However, existing agent memory systems are de
arXiv:2603.12055v3 Announce Type: replace Abstract: Continual learning of pretrained vision-language models (VLMs) is prone to catastrophic forgetting, yet current approaches adapt to new tasks withou
Bloomberg: Cybersecurity experts fault Anthropic and OpenAI for sloppy safeguards and inadequate human oversight after their models broke into outside organizations — Cybersecurity experts are faultin
arXiv:2607.27420v1 Announce Type: cross Abstract: Humanity's Last Exam (HLE) is widely used to evaluate frontier language models. HLE organizes its questions into eight subject-domain categories, whos
arXiv:2607.27522v1 Announce Type: new Abstract: As decision-making processes grow more complex, machine learning tools have become essential for tackling business and societal challenges. However, man
arXiv:2607.28607v1 Announce Type: new Abstract: Aligning large language models to prevent them attributing consciousness to themselves inadvertently alters their representations of mindedness in other
So you’ve got a 3090 or maybe even a 5090? Or more likely a 4060 8GB Ti. You wanna try local AI, you don’t know what it can/can’t do. 1) Install the best model you can. If you have a 3090 or a 5090, t
Eduardo Baptista / Reuters: Papers and patents: Chinese military researchers distilled OpenAI and Anthropic models to train domestic AI systems and advance China's defense capabilities — Chinese milit
Security at the foundation requires openness at the foundation. As open-weight models become critical infrastructure for the next generation of software, the systems around them must be transparent, i
arXiv:2607.27599v1 Announce Type: cross Abstract: Building generalizable agents for diverse applications remains a fundamental challenge. While imitation learning-based policies succeed in specific tr
arXiv:2607.27585v1 Announce Type: new Abstract: As primary consumers in the marine food chain, zooplankton play a crucial role in maintaining marine ecological balance. However, the Segment Anything M
arXiv:2607.26533v1 Announce Type: new Abstract: Graph Foundation Models (GFMs) aim to learn transferable knowledge from multi-domain graphs and adapt to unseen scenarios. As a fundamental source of re
arXiv:2607.26369v1 Announce Type: new Abstract: Rotary Position Embedding (RoPE) has been widely adopted in transformer-based large language models. However, its log-linear frequency schedule, origina