Knowledge catalogue
Chinese AI company DeepSeek released a preview of its hotly anticipated next-generation AI model V4 on Friday, saying that the open-source model can compete with leading closed-source systems from US
Cursor has integrated OpenAI's GPT-5.5 model into its IDE, positioning it as the top performer on CursorBench with a 72.8% score. Through a partnership with OpenAI, the model is being offered at a 50%
arXiv:2603.27406v2 Announce Type: replace Abstract: In this paper, the relationship between probabilistic graphical models, in particular Bayesian networks, and causal diagrams, also called structural
We're the #1 open model in Vision and Document Arena! Kimi K2.6 is the new SOTA open model in Vision and Document Arena, with solid gains since Kimi K2.5: - #1 open on Vision Arena (#15 overall), +14
We’ve been using Sakana Fugu internally for our own research and coding. Instead of relying on a single model, it dynamically orchestrates the best combination of open and closed models for any task.
arXiv:2511.17085v3 Announce Type: replace-cross Abstract: The deployment of Large Language Models (LLMs) as tool-using agents causes their alignment training to manifest in new ways. Recent work finds
arXiv:2604.20372v1 Announce Type: cross Abstract: We report the first systematic evidence of hallucination in AI models of fluid dynamics, demonstrated in the canonical problem of hydrodynamically uns
arXiv:2603.07474v2 Announce Type: replace-cross Abstract: What is the interplay between semantic representations learned by language models (LM) from surface form alone to those learned from more grou
arXiv:2602.09781v2 Announce Type: replace-cross Abstract: This study investigates the explainability of generative diffusion models in the context of medical imaging, focusing on Magnetic resonance im
arXiv:2508.06614v2 Announce Type: replace Abstract: As a class of generative artificial intelligence frameworks inspired by statistical physics, diffusion models have shown extraordinary performance i
arXiv:2603.14222v2 Announce Type: replace-cross Abstract: Contrastive pretraining models such as CLIP and CLAP, serve as the ubiquitous perceptual backbones for modern multimodal large models, yet the
arXiv:2604.20398v1 Announce Type: new Abstract: While Large Language Models (LLMs) excel at function-level code generation, project-level tasks such as generating functional and visually aesthetic mul
arXiv:2604.19398v1 Announce Type: new Abstract: Large language models (LLMs) are expensive to serve because model parameters, attention computation, and KV caches impose substantial memory and latency
arXiv:2604.19300v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) have recently achieved strong performance across various audio-centric tasks. However, hallucination, where models
arXiv:2510.04800v3 Announce Type: replace Abstract: Recent progress in large language models demonstrates that hybrid architectures--combining self-attention mechanisms with structured state space mod
arXiv:2604.19043v1 Announce Type: new Abstract: Efficient construction of models capturing the preconditions and effects of actions is essential for applying AI planning in real-world domains. Extensi
arXiv:2604.18878v1 Announce Type: new Abstract: We introduce LegalBench-BR, the first public benchmark for evaluating language models on Brazilian legal text classification. The dataset comprises 3,10
Props to @augmentcode for being one of the first to ship Kimi K2.6 to their users. Open models are now the frontier. Support for Kimi K2.6 is now here in Augment Code! We teamed up with @Kimi_Moonshot
arXiv:2510.06133v2 Announce Type: replace Abstract: Diffusion large language models (dLLMs) generate text through iterative denoising. In commonly adopted parallel decoding schemes, each step confirms
arXiv:2604.16363v1 Announce Type: cross Abstract: Text-to-image models are commercially valuable assets often distributed under restrictive licenses, but such licenses are enforceable only when violat
arXiv:2604.16940v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) accelerates taskspecific large language models (LLMs) development, but the resulting proliferation of finetuned models incu
arXiv:2604.17585v1 Announce Type: new Abstract: Salient object detection (SOD) requires modeling both long-range contextual dependencies and fine-grained structural details, which remains challenging
arXiv:2604.16980v1 Announce Type: new Abstract: Background: Large language models (LLMs) are increasingly proposed for diagnostic support, but few evaluations use real-world multimodal inpatient data,
arXiv:2604.18092v1 Announce Type: new Abstract: Small language models fine-tuned for graph property estimation have demonstrated strong in-distribution performance, yet their generalization capabiliti
arXiv:2604.18564v1 Announce Type: new Abstract: Video world models have achieved remarkable success in simulating environmental dynamics in response to actions by users or agents. They are modeled as
arXiv:2509.26010v2 Announce Type: replace Abstract: Second-order PDE models have been widely used for suppressing multiplicative noise, but they often introduce blocky artifacts in the early stages of
arXiv:2604.17706v1 Announce Type: new Abstract: Visual-Language-Action (VLA) models represent a paradigm shift in embodied AI, yet existing frameworks often struggle with imprecise spatial perception,
arXiv:2510.24235v3 Announce Type: replace Abstract: Reward models (RMs) are central to reinforcement learning from human feedback (RLHF), providing the critical supervision signals that align large la
Please don’t trust your chatbot for medical advice. 🙏 Remember how I used to say that large language models are “frequently wrong, never in doubt”, and how I warned three years ago on 60 Minutes that
arXiv:2506.01770v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved tremendous success in various tasks, yet concerns about their safety and security have emerged. In
arXiv:2506.02541v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) can recognize individuals in images and disclose sensitive personal information about them, raising criti
arXiv:2602.14466v2 Announce Type: replace Abstract: With natural language generation becoming a popular use case for language models, the Bias Benchmark for Question-Answering (BBQ) has grown to be an
arXiv:2604.18058v1 Announce Type: new Abstract: We introduce Sonata, a compact latent world model for six-axis trunk IMU representation learning under clinical data scarcity. Clinical cohorts typicall
arXiv:2604.16429v1 Announce Type: cross Abstract: We introduce Mosaic, a probabilistic weather forecasting model that addresses two principal sources of spectral degradation in ML-based weather predic
arXiv:2604.18518v1 Announce Type: new Abstract: Uniform Discrete Diffusion Model (UDM) has recently emerged as a promising paradigm for discrete generative modeling; however, its integration with rein
arXiv:2602.19946v4 Announce Type: replace Abstract: Recent text-to-image (T2I) diffusion models produce visually stunning images and demonstrate excellent prompt following. But do they perform well as
arXiv:2604.15822v1 Announce Type: cross Abstract: Automated classification of electrocardiogram (ECG) signals is a useful tool for diagnosing and monitoring cardiovascular diseases. This study compare
arXiv:2604.15911v1 Announce Type: new Abstract: Video diffusion models have rapidly become the dominant paradigm for high-fidelity generative video synthesis, but their practical deployment remains co
arXiv:2604.15380v1 Announce Type: cross Abstract: We present an exascale workflow for materials discovery using atomistic graph foundation models built on HydraGNN. We jointly train on 16 open first-p
Kimi K2.6 is now available in Hermes Agent. Simply run `hermes update` and use `hermes model` to select a compatible provider hosting the model! Meet Kimi K2.6: Advancing Open-Source Coding 🔹Open-sour
arXiv:2604.16170v1 Announce Type: new Abstract: We introduce neuralCAD-Edit, the first benchmark for editing 3D CAD models collected from expert CAD engineers. Instead of text conditioning as in prior
arXiv:2505.19563v4 Announce Type: replace Abstract: Mathematical reasoning has long been a key benchmark for evaluating large language models. Although substantial progress has been made on math word
arXiv:2604.15756v1 Announce Type: new Abstract: Vision-language models (VLMs) such as CLIP exhibit strong Out-of-distribution (OOD) detection capabilities by aligning visual and textual representation
arXiv:2603.13966v2 Announce Type: replace Abstract: Vision-Language-Action (VLA) models are increasingly evaluated across multiple simulation benchmarks, yet adding each benchmark to an evaluation pip
The continuing gap between the capabilities of Gemini Pro 3.1 (very good model) and the capabilities of the Gemini app/website is odd. The model can do what Claude/GPT can do, but there is a minimal h
arXiv:2505.10846v3 Announce Type: replace Abstract: This paper presents AutoRAN, the first framework to automate the hijacking of internal safety reasoning in large reasoning models (LRMs). At its cor
arXiv:2604.14156v1 Announce Type: new Abstract: Large language models deliver strong generative performance but at the cost of massive parameter counts, memory use, and decoding latency. Prior work ha
arXiv:2604.13354v1 Announce Type: cross Abstract: The discovery of inorganic crystal structures with targeted properties is a significant challenge in materials science. Generative models, especially
arXiv:2604.14152v1 Announce Type: cross Abstract: Ambient AI 'scribe' systems promise to reduce clinical documentation burden, but automatic speech recognition (ASR) errors can remain unnoticed withou
arXiv:2602.03295v2 Announce Type: replace Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) have demonstrated remarkable capabilities. However, their deployment is hindered by s
arXiv:2604.13392v1 Announce Type: new Abstract: Tabular data remains prevalent in high-stakes domains such as healthcare and finance, where predictive models are expected to provide both high accuracy
arXiv:2604.14973v1 Announce Type: cross Abstract: A vision foundation model outputs an embedding vector for an image, which can be affected by common editing operations (e.g., JPEG compression, bright
arXiv:2604.13594v1 Announce Type: cross Abstract: Binary droplet collisions are ubiquitous in dense sprays. Traditional deterministic models cannot adequately represent transitional and stochastic beh
arXiv:2604.13803v1 Announce Type: new Abstract: Vision-language models are increasingly deployed in high-stakes settings, yet their susceptibility to sycophantic manipulation remains poorly understood
arXiv:2512.10877v4 Announce Type: replace Abstract: Discrete diffusion models (DMs) have achieved strong performance in language and other discrete domains, offering a compelling alternative to autore
arXiv:2603.28554v2 Announce Type: replace Abstract: Visual document understanding typically requires separate retrieval and generation models, doubling memory and system complexity. We present Hydra,
arXiv:2510.14232v2 Announce Type: replace-cross Abstract: Competitive programming has become a rigorous benchmark for evaluating the reasoning and problem-solving capabilities of large language models
arXiv:2603.10652v2 Announce Type: replace-cross Abstract: In real-world deployment, vision-language models often encounter disturbances such as weather, occlusion, and camera motion. Under such condit
arXiv:2604.12978v1 Announce Type: new Abstract: Optical character recognition (OCR) has advanced rapidly with the rise of vision-language models, yet evaluation has remained concentrated on a small cl
arXiv:2603.00137v2 Announce Type: replace-cross Abstract: Knowledge tracing (KT) models are commonly evaluated by training on early interactions from all students and testing on later responses. While