Knowledge catalogue
arXiv:2607.18269v2 Announce Type: replace Abstract: The wisdom of crowds -- the finding that aggregating judgments across individuals often outperforms the best individual -- has been extensively stud
arXiv:2512.02473v2 Announce Type: replace-cross Abstract: Video world models have attracted significant attention for their ability to produce high-fidelity future visual observations conditioned on p
Incredibly proud of the Sakana AI team. We have developed an orchestration model right here out of Japan that achieves state-of-the-art performance on real-world cybersecurity benchmarks! 🎌 Introducin
SSI should open-source an opus-tier model. 1. it nearly closes the us/china gap on the os frontier 2. they don't want to waste compute allocation on inference, releasing os will enable continued full
arXiv:2607.13622v1 Announce Type: new Abstract: Miniature hybrid underwater gliders have attracted increasing attention for long-endurance ocean observation and confined-space inspection. Large-range
arXiv:2512.18965v2 Announce Type: replace Abstract: Structured State Space Models (SSMs), which are at the heart of the recently popular Mamba architecture, are powerful tools for sequence modeling. H
arXiv:2607.13929v1 Announce Type: new Abstract: Financial observations are continuous, heterogeneous, and noisy, whereas decoder-only next-token models are usually built around discrete symbolic input
arXiv:2607.13389v1 Announce Type: new Abstract: Reinforcement Learning (RL) post-training is increasingly used to adapt foundation models for reasoning, planning, and feedback-driven robot-learning pi
arXiv:2510.18315v2 Announce Type: replace-cross Abstract: We investigate how embedding dimension affects the emergence of an internal 'world model' in a transformer trained with reinforcement learning
Interesting surprise drop from Thinky! The Inkling model looks pretty solid on benchmarks, and it has some little surprises in its architecture: - Small conv layers in several places - An RMSNorm for
arXiv:2607.12520v1 Announce Type: new Abstract: What a frontier model recalls about a person or tool from its own weights -- before any retrieval step -- often shapes the first description a human see
arXiv:2601.14584v2 Announce Type: replace Abstract: Accurately modeling longitudinal brain MRI progression is crucial for understanding neurodegenerative diseases and predicting individualized structu
Cohere warns that computational investment alone does not guarantee success in building AI models, emphasizing that many companies spend substantial resources on computing infrastructure without achie
arXiv:2607.08522v1 Announce Type: new Abstract: The inherent rigidity of fixed-size benchmarks makes them an inefficient tool for model evaluation. Diverse evaluation objectives, including model ranki
arXiv:2607.08375v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have advanced end-to-end autonomous driving. However, existing methods either lack comprehensive world cognition o
arXiv:2607.06925v1 Announce Type: new Abstract: Compact world models that condition on a language goal promise to ground relations such as ``put the red block left of the blue block'' using a sparse s
Is Meta AI back? Haven't seen Mark post in three years here. Plus, the model is available via API. Not to mention the courage to announce it the same week as the long-awaited GPT-5.6. Great timing if
arXiv:2607.06993v1 Announce Type: new Abstract: Customer behavior modeling underpins recommendation, marketing, and decision support, yet existing approaches either optimize predictive accuracy withou
arXiv:2607.06757v1 Announce Type: new Abstract: Agent-based modeling (ABM) has the capability to model millions of individuals and their interactions, which is useful for policy making. However, ABMs
Meta Platforms Inc. today launched a new flagship large language model optimized to power multi-agent automation workflows. Muse Spark 1.1 is available in the company’s Meta AI chatbot service and via
arXiv:2511.13726v2 Announce Type: replace-cross Abstract: We propose RT (Refine Thought), a method that can enhance the semantic reasoning ability of text embedding models. The method obtains the fina
arXiv:2607.05966v1 Announce Type: new Abstract: Long-horizon failure in world models is conventionally attributed to compounding error, a generic framing that does not distinguish what kind of error c
Meta Platforms Inc. today debuted an image generation model that can write code and search the web. Muse Image is the second algorithm released to date by Meta Superintelligence Labs, the company’s ar
arXiv:2607.05744v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is the dominant way coding agents discover and invoke external tools. A server advertises each tool through a tools/l
We've usually stayed away from model comparisons but 5.6 vs Fable is a unique situation We've never had a case where the team is so completely convinced on which one is better Here's the timeline of o
arXiv:2506.11389v4 Announce Type: replace Abstract: As the cost of pretraining large language models grows, there is continued interest in strategies to improve learning efficiency during this core tr
arXiv:2607.03346v1 Announce Type: cross Abstract: Accurate and efficient dataset valuation is essential for enabling fair and transparent data marketplaces, especially when multiple contributors provi
arXiv:2508.16181v2 Announce Type: replace-cross Abstract: Cross-organizational collaboration in Model-Based Systems Engineering (MBSE) faces many challenges in achieving semantic alignment across inde
arXiv:2607.02846v1 Announce Type: new Abstract: Large language model (LLM) agents can improve through accumulated experience, but free-form textual memories become difficult to maintain, validate, and
arXiv:2607.02872v1 Announce Type: new Abstract: Dynamic knowledge graphs are ubiquitous in today's AI applications, as we represent molecular structures, social relationships, and language information
arXiv:2603.19873v2 Announce Type: replace Abstract: Fine-tuning foundation models for Earth Observation is computationally expensive, with high training time and memory demands for both training and d
arXiv:2511.15684v2 Announce Type: replace-cross Abstract: Foundation models have transformed machine learning for language and vision, but achieving comparable impact in physical simulation remains a
arXiv:2607.02182v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit remarkable reasoning capabilities, but their task-specific fine-tuning is notoriously plagued by overconfidence,
arXiv:2607.00371v1 Announce Type: cross Abstract: Visual AutoRegressive modeling (VAR) has pioneered a coarse-to-fine multi-scale autoregressive generative paradigm, demonstrating strong capabilities
arXiv:2509.21013v4 Announce Type: replace-cross Abstract: Given the prohibitive cost of pre-training large language models, it is essential to leverage smaller proxy models to optimize datasets before
arXiv:2606.30689v1 Announce Type: cross Abstract: Spec-Driven Development (SDD) frameworks guide Large Language Model (LLM)-powered code generation through formal specifications, yet they differ funda
arXiv:2606.30773v1 Announce Type: cross Abstract: We introduce a novel technique for scalable sampling of spin-system states with continuous symmetries using diffusion models. By applying our approach
GLM 5.2 just became the first open-source model to lead a category on APEX-SWE. It scored a 55.3% Pass@1 on Integration, the top score we've recorded for any model, open or closed source. On the overa
arXiv:2601.14251v2 Announce Type: replace Abstract: We present LightOnOCR-2-1B, a 1B-parameter end-to-end multilingual vision--language model that converts document images (e.g., PDFs) into clean, nat
arXiv:2606.31209v1 Announce Type: new Abstract: Interactive traffic simulation is a vital world model for autonomous driving. A central challenge in long-horizon simulation is modeling sustained multi
arXiv:2606.30695v1 Announce Type: cross Abstract: Single-cell drug perturbation models should predict not only transcriptional response magnitude, but also whether a treatment alters the proliferative
arXiv:2606.30789v1 Announce Type: new Abstract: Group Relative Policy Optimization (GRPO) has become a standard tool for improving the reasoning ability of large language models, yet its training dyna
arXiv:2606.30571v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in open-ended multi-agent settings, but the long-run dynamics of model--model interaction remain po
arXiv:2606.29614v1 Announce Type: cross Abstract: This study examines whether supervised fine-tuning remains necessary for Turkish sentiment analysis in the era of large language models. We compare cl
arXiv:2606.30367v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) in continuous environments requires an agent to ground instructions in egocentric observations while maintaining sp
arXiv:2606.29784v1 Announce Type: cross Abstract: Reliable generative AI models critically rely on expert human annotations to evaluate output quality, yet these 'gold' labels are expensive to collect
arXiv:2606.28421v1 Announce Type: cross Abstract: Text-to-image (T2I) diffusion models typically require substantial computational resources and cloud infrastructure, posing significant challenges for
arXiv:2510.03142v2 Announce Type: replace-cross Abstract: Visual navigation policy is widely regarded as a promising direction, as it mimics humans by using egocentric visual observations for navigati
arXiv:2606.28465v1 Announce Type: cross Abstract: This work examines perturbation generalization in spatial foundation-model embeddings derived from fluorescence microscopy images. Although these mode
arXiv:2606.29644v1 Announce Type: new Abstract: Earth system infrastructures relying on satellite-based technologies, such as Global Positioning System (GPS) communications, are affected by ionospheri
𝗚𝗟𝗠-𝟱.𝟮 (the latest open weights model) is having an Enterprise moment, and it is not an exaggeration.🚀 🔥 We have been impressed by how strongly GLM-5.2 is pushing long-horizon performance .. not just
arXiv:2602.05233v2 Announce Type: replace Abstract: Vision-language-action models have advanced robotic manipulation but remain constrained by reliance on the large, teleoperation-collected datasets d
arXiv:2606.27739v1 Announce Type: new Abstract: Process reward models (PRMs) enhance the reasoning capabilities of large language models (LLMs) by providing fine-grained feedback, yet training PRMs ty
Grok 4.5, based on our 1.5T V9 foundation model, with Cursor data added in supplemental training, is now in private beta at SpaceX & Tesla. Early evals show performance close to, perhaps exceeding Opu
arXiv:2606.25285v1 Announce Type: new Abstract: Post-Training Sparsity (PTS) has emerged as a crucial paradigm for compressing Large Language Models to facilitate efficient deployment on resource-cons
arXiv:2510.09036v2 Announce Type: replace Abstract: Learned world models hold significant potential as neural simulators for robotic manipulation. However, prevalent 2D video-based models inherently l
arXiv:2606.24589v1 Announce Type: new Abstract: Scaling adversarial evaluation of large language models requires both a method for generating hard inputs and a reliable way to confirm that resulting f
arXiv:2505.18542v4 Announce Type: replace Abstract: Extracting structured procedural knowledge from unstructured business documents is a critical yet unresolved bottleneck in process automation. While
arXiv:2509.24118v2 Announce Type: replace Abstract: Electronic health Records (EHRs) have become a cornerstone in modern-day healthcare. They are a crucial part for analyzing the progression of patien
arXiv:2606.20657v1 Announce Type: cross Abstract: Post-training a frontier model is normally weeks of human work: proposing data and recipe changes, launching runs, reading evals, deciding what to kee