Knowledge catalogue
arXiv:2604.05779v2 Announce Type: replace-cross Abstract: While large language models (LLMs) demonstrate strong capabilities across diverse user queries, they still suffer from hallucinations, often a
arXiv:2608.20561v1 Announce Type: cross Abstract: Diffusion models (DMs) have emerged as powerful generative priors for MRI reconstruction with promising results. Yet DM-based methods require extensiv
arXiv:2608.19556v1 Announce Type: cross Abstract: Streaming autoregressive diffusion models enable real-time, long-horizon video generation, but their training objectives optimize local frame predicti
arXiv:2608.19529v1 Announce Type: cross Abstract: Many real-world AI systems represent entities, behaviors, and structured information using discrete machine-native symbols rather than natural languag
Agree with @gdb that we need to arm cyber defenders much more than they are now, both with APIs and open models. The real cybersecurity risk of AI is asymmetry of power, capabilities and ressources be
IQ quants are particularly slow on CPU at large batch sizes (what you'd see for imatrix and perplexity) Benchmark numbers I ran PPL against master and this PR to get speed and numbers on --chunks 50 f
arXiv:2608.18182v1 Announce Type: new Abstract: Small NLP models, especially BERT-family encoders, remain important in industrial workloads such as classification, ranking, and retrieval even in the e
arXiv:2608.18367v1 Announce Type: cross Abstract: Accurate localization and segmentation of the optic disc (OD) are important for retinal image analysis and glaucoma assessment, yet remain challenging
arXiv:2608.18984v1 Announce Type: new Abstract: Museum and archival datasets do not mirror historical artistic production, but materialize the contingent histories of collecting, preservation, catalog
arXiv:2608.18258v1 Announce Type: new Abstract: Robot-Assisted Feeding (RAF) systems are essential for assisting individuals with disabilities or motor impairments in eating tasks. Manipulating granul
arXiv:2603.29865v2 Announce Type: replace-cross Abstract: Wildfires cause major losses worldwide, and the frequency of fire-weather conditions is likely to increase in many regions. We study the alloc
arXiv:2608.18309v1 Announce Type: new Abstract: Registering images acquired with different microscopy modalities is essential for relating complementary measurements of the same specimen. In correlati
arXiv:2608.17120v1 Announce Type: new Abstract: Children learn hundreds of words over the first years of their lives, in a process that begins slowly but quickly picks up speed. Prior models describe
arXiv:2608.17095v1 Announce Type: new Abstract: Vision-language-action (VLA) driving models couple a reasoning stage with a diffusion-based trajectory decoder, but do not give a direct way to redirect
https://huggingface.co/inclusionAI/Ling-3.0-tiny-base https://huggingface.co/inclusionAI/Ling-3.0-flash-base-midtrain https://huggingface.co/inclusionAI/Ling-3.0-flash-base-30T https://huggingface.co/
arXiv:2608.17605v1 Announce Type: cross Abstract: Conversational AI is moving beyond isolated text prompts toward sustained, multimodal interaction. In real conversations, users clarify goals, revise
arXiv:2603.09872v2 Announce Type: replace Abstract: Recent work has found that contemporary language models such as transformers can become so good at next-word prediction that the probabilities they
arXiv:2608.17747v1 Announce Type: new Abstract: Although text-to-image diffusion models exhibit remarkable generative power, concept erasure techniques are essential for preventing harmful content. Ex
arXiv:2608.17268v1 Announce Type: cross Abstract: Curriculum learning has been widely adopted in the post-training of large language models by organizing training data from easy to hard. However, its
arXiv:2608.14591v1 Announce Type: cross Abstract: The integration of artificial intelligence (AI) and wireless communications is widely regarded as a core objective of sixth-generation (6G) systems. H
arXiv:2608.14631v1 Announce Type: new Abstract: As consumers increasingly turn to AI chatbots for skincare advice, the technical accuracy of Large Language Models (LLMs) in cosmetic chemistry remains
arXiv:2608.15475v1 Announce Type: cross Abstract: Quantized Vision-Language-Action (VLA) models expose a weight-fault surface: Rowhammer-style faults can corrupt deployed INT8 bits. We present the fir
arXiv:2608.14630v1 Announce Type: cross Abstract: Human decision-making is often shaped by a range of well-documented cognitive biases. As large language models (LLMs) become increasingly integrated i
arXiv:2608.14632v1 Announce Type: cross Abstract: Diffusion large language models (D-LLMs) have emerged as a promising paradigm for text generation. However, similar to autoregressive LLMs, D-LLMs rem
arXiv:2508.21290v2 Announce Type: replace-cross Abstract: jina-code-embeddings is a novel code embedding model suite designed to retrieve code from natural language queries, perform technical question
arXiv:2503.00992v2 Announce Type: replace Abstract: In this paper we leverage psychological methods to investigate LLMs' conceptual mastery in applying rules. We introduce a novel procedure to match t
arXiv:2608.15725v1 Announce Type: new Abstract: Predictive models in clinical and regulated settings must be accurate and fully auditable. Tree ensembles deliver strong accuracy on tabular data, but t
arXiv:2608.15504v1 Announce Type: new Abstract: Encrypted traffic classification is vital for network security, yet real-world deployments are inherently sensitive to rare but high-loss errors such as
arXiv:2608.16786v1 Announce Type: new Abstract: Inference-time quality-enhancement methods are an effective and widely adopted means of improving diffusion models without expensive retraining. We stud
arXiv:2402.01826v2 Announce Type: replace-cross Abstract: Current blood pressure (BP) technologies and standards were established decades ago, and these standards are still used worldwide today, often
arXiv:2608.13472v1 Announce Type: cross Abstract: Analog circuit design is a time-consuming, iterative process in a nonlinear and high-dimensional design space that relies heavily on expert intuition.
arXiv:2608.13262v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) have advanced primarily through architectural innovation, while training regimes for large-scale heterogeneous c
Open models are improving at an unprecedented rate. Congrats to the whole @Zai_org team. Ollama will support GLM-5.3 upon the open release! ❤️ Get ready to code. Introducing GLM-5.3: Built to Code. Re
arXiv:2608.11631v1 Announce Type: new Abstract: In open-domain human-computer interaction scenarios, large language models (LLMs) frequently encounter user queries that are ambiguous or incomplete. In
arXiv:2608.11937v1 Announce Type: new Abstract: Foundation models for time-dependent partial differential equations (PDEs) are trained on large and diverse collections of physical systems and can gene
I think this will turn out to be wrong, and not just because I suspect there are greater returns to more intelligent models than people expect Economic value comes from agents, not chatbots. And accur
arXiv:2608.11941v1 Announce Type: new Abstract: We construct OEIS Open, a benchmark based on 492 open mathematical conjectures from the OEIS, formalized in Lean by Tsoukalas et al. Whereas these conje
arXiv:2510.06710v3 Announce Type: replace Abstract: Recent studies have demonstrated the potential of reinforcement learning (RL) to improve the task performance of vision-language-action (VLA) models
arXiv:2604.18064v2 Announce Type: replace Abstract: Human motion world models should capture motion's intentionality by being executable: adaptable to different actions and capable of assessing motion
arXiv:2208.11582v2 Announce Type: replace-cross Abstract: The wide spread of false information online, including misinformation and disinformation, has become a major problem for our highly digitised
arXiv:2512.08240v2 Announce Type: replace-cross Abstract: Vision-language models (VLMs) rely on hundreds of visual tokens, leading to high computational and memory costs. Existing compression methods
arXiv:2602.01530v2 Announce Type: replace Abstract: Modern autoregressive Vision-Language Models (VLMs) can generate fluent answers while their visual-token representations become weakly tied to the i
arXiv:2608.10530v1 Announce Type: cross Abstract: Large Language Models (LLMs) have undergone a shift from stateless conversational interfaces to autonomous agents capable of multi-step planning, tool
arXiv:2608.11174v1 Announce Type: new Abstract: Regulating the latent space to an isotropic Gaussian distribution provides a stable and information-maximized landscape for world model planning. Howeve
arXiv:2608.07984v1 Announce Type: new Abstract: Field-based agricultural computer vision is important for precision agriculture, yet it largely depends on expensive annotations and costly adaptation o
arXiv:2608.07550v1 Announce Type: new Abstract: Vision-language models return structured chest-radiograph findings through interfaces exposing no confidence score, so a receiving institution cannot re
arXiv:2608.08082v1 Announce Type: new Abstract: Classifier-free guidance (CFG) is usually kept on throughout masked diffusion language model decoding, although its benefit varies across prompts and ov
arXiv:2608.07981v1 Announce Type: new Abstract: Streaming world models predict future visual states online while maintaining physically coherent dynamics over long horizons. However, their rollouts of
arXiv:2608.08815v1 Announce Type: new Abstract: Traffic sign recognition (TSR) models based on deep neural networks achieve strong clean-data performance but remain vulnerable to physically realizable
arXiv:2608.09233v1 Announce Type: cross Abstract: Flow-matching models are now a mainstream method to image generation, but its adaptation to diverse downstream scenarios typically relies on post-trai
arXiv:2608.09876v1 Announce Type: cross Abstract: Physically consistent motion planning remains a fundamental challenge in embodied AI, as generated trajectories must strictly conform to real-world ex
arXiv:2608.09516v1 Announce Type: new Abstract: World Action Models (WAMs) jointly learn environmental dynamics and robot actions, introducing priors over physical evolution into embodied control. How
arXiv:2511.20849v2 Announce Type: replace-cross Abstract: We introduce a new tokenizer for language models that minimizes the average tokens per character, thereby reducing the number of tokens needed
arXiv:2608.07562v1 Announce Type: new Abstract: Urban flooding poses an escalating threat to transportation infrastructure, yet no operational system provides real-time, street-level flood-depth estim
arXiv:2608.08199v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly involved in group decision-making with other LLMs and humans. Yet it remains unclear whether their influen
arXiv:2608.09400v1 Announce Type: cross Abstract: Research regarding the sign language recognition mostly relies on RGB images, whileas sign language datasets that provide depth images are limited. Po
arXiv:2608.08512v1 Announce Type: new Abstract: Evolving documents, such as laws, tax codes, and software documentation, are amended, replaced, and sometimes reverted over time, so a question has diff
arXiv:2509.24039v2 Announce Type: replace-cross Abstract: If topography is a fundamental feature of the brain, it should influence both how neurons are arranged in space (i.e. explain brain maps) and
arXiv:2608.07003v1 Announce Type: new Abstract: Training-free text-to-high-resolution image generation has recently attracted growing research attention. However, existing studies on this task primari
On August 10 2026 at 1:39 AM UTC, user Itamar Friedman (@itamar_mar) posted a short tweet asking whether Anthropic’s potential launch of its own chips would prompt NVIDIA to release frontier AI models