Knowledge catalogue
arXiv:2604.22367v1 Announce Type: cross Abstract: Sign language research has achieved significant progress due to the advances in large language models (LLMs). However, the intrinsic ability of LLMs t
arXiv:2604.22238v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models promise generalist robot manipulation, but are typically trained and deployed as short-horizon policies that assume
arXiv:2604.21956v1 Announce Type: new Abstract: Timely detection of concerning events is an important problem in clinical practice. In this paper, we consider the problem of conditional anomaly detect
arXiv:2604.21960v1 Announce Type: cross Abstract: Computed Tomography (CT) is a widely used imaging modality in medical and industrial applications. To limit radiation exposure and measurement time, t
arXiv:2511.13193v2 Announce Type: replace Abstract: Multi-agent systems (MAS) built on large language models (LLMs) often suffer from inefficient 'free-for-all' communication, leading to exponential t
Creative studios are being asked to do something fundamentally different now. Not just great work, but foundational systems for experience, brand, and content that their clients can own, extend, and b
arXiv:2604.00813v3 Announce Type: replace-cross Abstract: End-to-end autonomous driving has evolved from the conventional paradigm based on sparse perception into vision-language-action (VLA) models,
arXiv:2604.22167v1 Announce Type: cross Abstract: Language models are increasingly capable and are being rapidly deployed on a population-level scale. As a result, the safety of these models is increa
arXiv:2604.22595v1 Announce Type: new Abstract: CLIP has demonstrated strong generalization in visual domains through natural language supervision, even for video action recognition. However, most exi
Every AI discussion ultimately rests on two questions: how good can AI get? And how fast? They are predictions about the s-curve shape. Everything else (job impact, potential risks, etc.) is downstrea
arXiv:2505.14234v2 Announce Type: replace-cross Abstract: Entropic measures like Shannon entropy (SE), its quantum mechanical analogue von Neumann entropy, and Kullback-Leibler divergence (KL) are key
arXiv:2604.22416v1 Announce Type: cross Abstract: Latent variables pose a fundamental challenge to causal discovery and inference. Conventional local methods focus on direct neighbors but fail to prov
arXiv:2604.22615v1 Announce Type: new Abstract: Embodied foundation models have achieved significant breakthroughs in robotic manipulation, yet they still depend heavily on large-scale robot demonstra
arXiv:2507.13706v2 Announce Type: replace Abstract: This paper introduces two quasi-metrics for performance assessment of multi-object tracking (MOT) algorithms. One quasi-metric is an extension of th
arXiv:2604.22407v1 Announce Type: cross Abstract: Many continual-learning methods modify gradients upstream (e.g., projection, penalty rescaling, replay mixing) while treating Adam as a neutral backen
arXiv:2604.22750v1 Announce Type: new Abstract: The wide adoption of AI agents in complex human workflows is driving rapid growth in LLM token consumption. When agents are deployed on tasks that requi
How do AI Agents spend your money? Most teams treat agent token costs as a rounding error even though the data says they shouldn't. New paper presents the first systematic study of how agents actually
arXiv:2601.17060v2 Announce Type: replace-cross Abstract: Artificially intelligent systems have become remarkably sophisticated. They hold conversations, write essays, and seem to understand context i
arXiv:2604.22739v1 Announce Type: new Abstract: Social interactions dominate our perceptions of the world and shape our daily behavior by attaching social meaning to acts as simple and spontaneous as
arXiv:2512.16251v5 Announce Type: replace-cross Abstract: We introduce the Consensus-Bottleneck Asset Pricing Model (CB-APM), which embeds aggregate analyst consensus as a structural bottleneck, treat
arXiv:2604.22411v1 Announce Type: new Abstract: Even when decoding with temperature T=0, large language models (LLMs) can produce divergent outputs for identical inputs. Recent work by Thinking Machin
arXiv:2604.22302v1 Announce Type: new Abstract: Recent text-to-image (T2I) models have demonstrated impressive capabilities in photorealistic synthesis and instruction following. However, their reliab
arXiv:2604.01907v2 Announce Type: replace-cross Abstract: Annotated 3D scene data is scarce and expensive to acquire, while abundant unlabeled videos are readily available on the internet. In this pap
Last year we introduced new geospatial analytics capabilities integrated for BigQuery. Building on this, we announced an expanded suite of tools at Google Cloud Next ‘26, designed to help your busines
arXiv:2512.05794v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) are a mechanistic interpretability technique that have been used to provide insight into learned concepts within la
arXiv:2602.06019v2 Announce Type: replace Abstract: Existing techniques for accelerating language model inference, such as speculative decoding, require training auxiliary speculator models and buildi
arXiv:2410.21548v3 Announce Type: replace Abstract: Large language models have drastically changed the prospects of AI by introducing technologies for more complex natural language processing. However
On Star Price's new @hitpausepod podcast, ControlAI's US Director Connor Leahy (@NPCollapse) explains how AIs can already tell when they're being tested. Currently, we can still catch them cheating, b
Ineffable Intelligence is building a superlearner—an AI system that discovers knowledge through its own experience rather than human data, using reinforcement learning without pre-training. The compan
arXiv:2411.04680v5 Announce Type: replace Abstract: Differential privacy (DP) is a formal privacy framework that enables training machine learning (ML) models while protecting individuals' data. As po
Processing loan applications traditionally takes a staggering amount of time going through paperwork - ~dozens of hours every month looking at the loan application and cross-checking it with user-subm
arXiv:2604.22169v1 Announce Type: cross Abstract: Generic group-based RL assumes that sampled rollout groups are already usable learning signals. We show that this assumption breaks down in sparse-hit
arXiv:2604.22154v1 Announce Type: cross Abstract: Emerging AI systems in behavioral health and psychiatry use multi-step or multi-agent LLM pipelines for tasks like assessing self-harm risk and screen
arXiv:2604.22749v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for text generation tasks from everyday use to high-stakes enterprise and government applications, in
arXiv:2603.26041v3 Announce Type: replace Abstract: In recent years, GUI visual agents built upon Multimodal Large Language Models (MLLMs) have demonstrated strong potential in navigation tasks. Howev
arXiv:2604.22109v1 Announce Type: cross Abstract: Large language models (LLMs) possess strong persuasive capabilities that outperform humans in head-to-head comparisons. Users report consulting LLMs t
arXiv:2510.11586v2 Announce Type: replace Abstract: Many in-silico simulations of human survey responses with large language models (LLMs) focus on generating closed-ended survey responses, whereas LL
This is totally wrong. Blaming the user is missing the point that (a) coding agents have been overhyped and (b) can’t reliably obey the rules given to them in system prompts and other guardrails. Sorr
arXiv:2601.03779v2 Announce Type: replace Abstract: We explore intrinsic dimension (ID) of LLM representations as a marker of linguistic complexity. Specifically, we test whether ID differences across
arXiv:2604.22177v1 Announce Type: new Abstract: Multimodal MRI offers complementary information for brain tumor segmentation, but clinical scans often lack one or more modalities, which degrades segme
arXiv:2602.07038v2 Announce Type: replace-cross Abstract: Key Information Extraction (KIE) from real-world documents remains challenging due to substantial variations in layout structures, visual qual
arXiv:2604.22555v1 Announce Type: new Abstract: Estimating racial disparity requires individual-level race data, which are often unavailable due to the sensitivity of collecting such information. To a
arXiv:2604.21993v1 Announce Type: new Abstract: We study the detection of transient liquidity erosion ('crumbling quotes') in electronic limit order books, where observable quote deterioration may ref
NEW paper from Alibaba. A 30B MoE with only 3B active params matches Qwen3-235B on real tool-use workloads. AgenticQwen-30B-A3B: 50.2 average on TAU-2 + BFCL-V4 Multi-Turn. AgenticQwen-8B: 47.4. Both
Whether there or more or less jobs, they will certainly change, and professions will compete to gain jurisdiction over valuable ones, in large part through regulation, requiring credentials, and appea
Qwen's latest model improvements focus on achieving more consistent and uniform performance quality across different artistic styles and aesthetic domains, reducing the variability in output quality t
Comprehensive Multilingual Text Rendering： Better glyph accuracy, more consistent typography, and cleaner layouts even in complex compositions. It handles mixed-language scenarios more gracefully as w
Every time I tell AI utopianists that biology is too complex for AI to 'solve', they cite the success of AlphaFold. No, AlphaFold did not 'solve' protein folding. It gets broad structures correct ~70-
GPT-5.5 prompting guide Now that GPT-5.5 is available in the API, OpenAI have released a wealth of useful tips on how best to prompt the new model. Here's a neat trick they recommend for applications
r/LocalLLaMA is a subreddit community dedicated to discussing and sharing resources about running large language models locally on personal computers, covering topics like model optimization, hardware
I think that academia has not absorbed the fact that AI agents are now good enough to independently reconstruct complex papers without access to code or the papers themselves; just the methods & data.
SpaceX's shocking competence: 'Somebody I know once worked for @SpaceX and they were asked what it was like, and he said, 'It's like being dropped into a zone of shocking competence.' Everybody is ult
Spot on 🎯 We don't need frontier intelligence to automate searches and sending emails - We don't need trillion parameter models to be able to summarize articles or technical documents - We don't need
There is also too much focus on two issues in discussions of paper reviewing: hallucinations & privacy. Hallucinations are not gone, but the latest models rarely hallucinate sources (& it is relativel
What if instead of building one giant AI, we evolved a coordinator to orchestrate a diverse team of specialized AIs? 🐟 Excited to share our new paper: “TRINITY: An Evolved LLM Coordinator”, published
A few weeks ago, I was forwarded an email from a journalist named “Michael Chen,” asking for comment on an AI bill in Tennessee. All signs suggest Michael Chen is not a real person, and the publicatio
API is Available Today! 🔹 Keep base_url, just update model to deepseek-v4-pro or deepseek-v4-flash. 🔹 Supports OpenAI ChatCompletions & Anthropic APIs. 🔹 Both models support 1M context & dual modes (T
arXiv:2604.21529v1 Announce Type: cross Abstract: Applying the concept of controlled self-organization in agent-based Cyber-Physical Energy Systems (CPES) is a promising approach to ensure system robu
Are LLMs really more important than fire or electricity? “Honestly, a ton of what we’ve developed in my lifetime amounts to scaling up the delivery of information and entertainment and the frictionles
arXiv:2604.20850v1 Announce Type: cross Abstract: Dense retrieval systems rank passages by embedding similarity to a query, but multi-hop questions require passages that are associatively related thro