Knowledge catalogue
arXiv:2606.25591v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have recently demonstrated strong generalization in robotic manipulation, yet their applicability to whole-body, con
Women are not suitable for dealing with the amount of violence necessary to maintain civilization. This is, again, because women are wired to care for babies with whom 'zero' violence is the correct a
Work at OpenAI is being transformed by agents, in every department. Across our entire company, people are using Codex to do work that is more complex, longer-running, and increasingly cross-functional
wouldn’t it be funny if greed undid OpenAI? 🚨BREAKING: OPENAI IPO DELAYED Altman told everyone OpenAI is worth a TRILLION dollars His own advisors warned him that retail investors aren’t buying it… ga
Nous Research has introduced a feature that allows users to create and hatch their own digital pets within the Hermes platform, with the ability to share these pets with others. This update likely enh
GLM-5.2 achieved token generation speeds of 318 tokens per second, surpassing the previously reported 280 tokens per second benchmark, with indications that further performance improvements are possib
Lucas Ropek / TechCrunch: YouTube rolls out changes to Shorts, including adding a setting to double playback speed, eliminating the “dislike” button, and more — YouTube is rolling out a series of chan
arXiv:2606.25034v1 Announce Type: new Abstract: General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversaria
AI21 Labs announced achieving the #1 ranking on DeepResearch Bench II without developing any new agents, suggesting they improved performance through optimization of existing systems or methodology ra
NASA cancelled the Exploration Upper Stage (EUS) after spending more than $3.5 billion with no operational flights, opting instead to shift toward commercial hardware like Centaur V. On February 26, 2
AI21 Labs reports that a leading deep research agent achieved a score of approximately 45 six months prior, after which the research community focused on developing improved agents to surpass this ben
3/3 We took 7 weak agents (ranks 7-13, none scoring >45) from the leaderboard & merged them into 1 report/task. Essentially boosting for deep research. The result: New #1 DRB II TotalScore of 64.38. F
arXiv:2606.23964v1 Announce Type: cross Abstract: Self-supervised learning in fluorescence microscopy often relies on 2D projections, despite the inherently three-dimensional nature of cells. We prese
arXiv:2606.24257v1 Announce Type: new Abstract: High-quality 3D vehicle assets are essential for autonomous driving simulation. Although multi-view diffusion-based paradigms enable controllable single
400T tokens is what production adoption looks like. Teams are moving real workloads to open models because they want frontier quality, better tokenomics, and more control over inference. Together AI g
5.2 could be better with more RL ... Deepswe's benchmark results are my own experience. I've used all models, GLM 5.2 ≈ Claude Opus 4.6–4.7. Kimi 2.7 code more like inference optimization. Looking for
This appears to be a brief post or reference to an 8-minute duration, likely related to a video, audio clip, or event duration shared by Elon Musk on X (formerly Twitter). Without access to the specif
arXiv:2606.24115v1 Announce Type: cross Abstract: Vision-language models (VLMs) are prone to hallucination, which remains a major barrier to their safe deployment in clinical practice. To date, most h
arXiv:2604.00725v2 Announce Type: replace Abstract: End-to-end OCR for historical newspapers remains challenging, as models must handle long text sequences, degraded print quality, and complex layouts
arXiv:2606.23977v1 Announce Type: new Abstract: Efficient sorter diversion control of automated material handling systems (MHS) is critical for optimizing operational efficiency in large-scale warehou
arXiv:2307.13127v3 Announce Type: replace-cross Abstract: Data used to train predictive models via empirical risk minimization (ERM) often contain sensitive personal information. While differential pr
arXiv:2606.24168v1 Announce Type: cross Abstract: Automated diabetic retinopathy (DR) grading from colour fundus photographs can achieve strong predictive performance, but clinical interpretation requ
arXiv:2606.24509v1 Announce Type: cross Abstract: Due to the wide use of graph-structured data in different fields of industry and science, the development of Graph Foundation Models (GFMs) has recent
arXiv:2601.06351v2 Announce Type: replace Abstract: Anticlustering is an NP-hard combinatorial optimization problem that consists of partitioning a set of objects into equal-sized groups called anticl
arXiv:2606.23699v1 Announce Type: new Abstract: Instrumented bicycle studies have produced direct field evidence on vehicle passing behavior, but extracting overtaking events from continuous rear-faci
arXiv:2510.04033v2 Announce Type: replace Abstract: Modern computer systems rely on syslog, a universal protocol that records critical events across heterogeneous infrastructure. Medicine's rapidly gr
A huge moment for open source AI - as token usage skyrockets across orgs, so do concerns over cost & data/vendor lock-in & necessity of a multi-AI strategy Keep an eye on @Lux_Capital portfolio cos @h
arXiv:2606.23719v1 Announce Type: cross Abstract: Laser powder bed fusion (LPBF) is a promising additive manufacturing technique that suffers from quality assurance concerns. Predicting melt pools fro
Agent memory systems often follow a three-step iterative process: executing the agent to generate traces, analyzing those traces through some evaluation mechanism, and then updating the agent based on
This entry examines research showing a discrepancy between people's stated AI usage and their actual behavior, revealing that many individuals who claim they don't use AI are unknowingly or covertly u
A message to the Republicans in congress and the Trump administration. Please stop treating legal immigration like just another issue to be fine tuned and start treating it like the existential threat
IBM Research presents a framework for benchmarking quantum optimization algorithms, addressing the need for standardized methods to evaluate quantum computing performance on optimization problems. The
arXiv:2603.05962v2 Announce Type: replace Abstract: To address the limitations of existing open-vocabulary object recognition methods, including high system complexity, substantial training costs, and
arXiv:2602.22346v2 Announce Type: replace Abstract: Autonomous mobile service robots, such as lawnmowers or cleaning robots, operating in human-populated environments need to reason about human-human
arXiv:2606.24172v1 Announce Type: cross Abstract: More than a billion people communicate in Indic languages, yet the natural language processing infrastructure serving them remains fragmented and unde
arXiv:2606.24696v1 Announce Type: cross Abstract: Physics-informed surrogate models can accelerate computational fluid dynamics simulations. However, many existing methods reproduce global flow patter
arXiv:2505.14251v2 Announce Type: replace Abstract: We study the problem of differentially private second moment estimation and present a new algorithm that achieve strong privacy-utility trade-offs e
arXiv:2504.01482v3 Announce Type: replace-cross Abstract: This paper develops a model-based framework for continuous-time policy evaluation (CTPE) in reinforcement learning, incorporating both Brownia
arXiv:2606.24510v1 Announce Type: new Abstract: Rare diseases affect millions of individuals worldwide, yet timely diagnosis remains a major public health challenge due to scarcity of specialized clin
arXiv:2606.23741v1 Announce Type: cross Abstract: Causal reasoning, which encompasses the discovery of causal structures and the inference of causal effects, is fundamental to data-driven decision mak
arXiv:2606.24176v1 Announce Type: new Abstract: Reliable structural health monitoring (SHM) of offshore wind turbine (OWT) support structures requires fast state estimation from sparse measurements. R
A tangible comparison of GLM performance stacked against Opus 4.8 on web tasks by @nutlope. GLM 5.2 is chattier, but still faster when served by @togethercompute and over 3x cheaper. Announcing GLM Ar
arXiv:2606.24140v1 Announce Type: new Abstract: Discrete flow matching (DFM) provides a principled framework for generative modeling on discrete state spaces via continuous-time Markov chain dynamics.
arXiv:2606.23720v1 Announce Type: cross Abstract: We present an integrated framework that unifies runtime verification and model-based diagnosis within the stream specification language LOLA. By encod
arXiv:2606.23835v1 Announce Type: new Abstract: ABACUS is a unified vision-language model that handles object counting, crowd counting, referring-expression counting, and count-faithful image generati
arXiv:2606.24618v1 Announce Type: new Abstract: In ontology-based data access (OBDA), multiple data sources are integrated via mappings to an ontology. We consider an OBDA setting based on existential
arXiv:2406.13041v3 Announce Type: replace Abstract: Lower-bound analyses for nonconvex strongly-concave minimax optimization problems have shown that stochastic first-order algorithms require at least
arXiv:2606.24369v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a dominant post-training paradigm, driving the emergence of high-performance RL systems such as veRL for autoregr
arXiv:2606.24156v1 Announce Type: new Abstract: Visual token reduction has emerged as an effective strategy for accelerating Multimodal Large Language Models (MLLMs). Many existing methods prune token
NVIDIA NeMo AutoModel is a tool designed to accelerate the fine-tuning process of transformer models by automating model selection and configuration. The solution leverages NVIDIA's NeMo framework to
arXiv:2606.24834v1 Announce Type: new Abstract: LLM-based dialogue assistants have become mainstream tools for software developers, yet current evaluation benchmarks focus exclusively on functional co
Speculative decoding is a technique for reducing inference latency in large language models by using a smaller, faster model to generate candidate tokens that are then verified by a larger model in pa
arXiv:2606.12824v2 Announce Type: replace-cross Abstract: AI governance for medical imaging is formalizing: the 2026 ACR-SIIM Practice Parameter recommends local acceptance testing and ongoing drift m
arXiv:2606.24292v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated impressive vision-language understanding, yet still struggle with fine-grained perception in
arXiv:2606.24756v1 Announce Type: new Abstract: Few-shot image recognition requires models to adapt to new classes from a small labeled support set. Hebbian fast-weight memory can provide temporary as
arXiv:2606.24483v1 Announce Type: cross Abstract: The deployment of unmanned aerial vehicles (UAV) as open radio units (O-RUs) in 6G cellular systems presents a promising opportunity to achieve scalab
This article discusses a collaboration between AMD and Vultr to implement AI solutions in the property insurance sector, leveraging AMD's processors and Vultr's cloud infrastructure. The partnership l
arXiv:2606.24484v1 Announce Type: new Abstract: WordArt (artistic text) features highly customized fonts, textures, and layouts, making WordArt-oriented scene TExt Recognition (WATER) substantially mo
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:2407.06312v2 Announce Type: replace-cross Abstract: Many systems resist analytical modeling, making data-driven inference of dynamics important. Yet data-driven methods can fail to converge or g