Knowledge catalogue
“They have been running literally the same play for seven years: scare, hype (evoking media interest), and (eventually) release. Scare, hype, release. And repeat. Is it that hard to see?” 👇🏼 - @GaryMa
arXiv:2606.11119v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) is a promising approach for enhancing reasoning and agentic behavior in large language models. H
arXiv:2509.25017v2 Announce Type: replace-cross Abstract: Wildfires are among the most severe natural hazards, posing a significant threat to both humans and natural ecosystems. The growing risk of wi
arXiv:2606.09958v1 Announce Type: cross Abstract: In mixed-traffic environments where autonomous and human-driven vehicles may co-exist, motion planning for autonomous vehicles requires anticipating t
Want to learn more about the Far-Field ASR benchmark? Join Treble's webinar tomorrow, June 11th, with @shinjiw_at_cmu, Cohere's @Julianfmack, and other industry leaders discussing the future of far-fi
We need more real time data on how AI may be impacting the economy - this is a really useful addition. Today, the Stanford @DigEconLab launches the AI Economic Indicators, a new platform for tracking
arXiv:2606.10229v1 Announce Type: cross Abstract: We study whether demonstration-curation metrics that detect defective training episodes also improve the downstream behavior-cloning policy that train
arXiv:2606.09899v1 Announce Type: cross Abstract: A central goal of mechanistic interpretability is to identify which internal components causally drive a language model's behavior. Because these impo
Claude Fable efficiently processes tokens at high speed when initiating workflows, demonstrating rapid token consumption during execution. This observation from Ethan Mollick highlights the computatio
When you hear AI 'safety' you should hear 'censorship' and 'control' instead. All of us surveilled and spied by safeguards of loving grace. Today it's intelligent Terms of Service control. You can't d
arXiv:2606.10302v1 Announce Type: new Abstract: Open-ended generation tasks often require a set of meaningfully different outputs, yet large language models often produce similar generations. Existing
👇@zerohedge confirms what I said here and in my May 29 Marcus on AI newsletter. Tokenmaxxing RIP. This morning @zerohedge out with a report on the death of Tokenmaxxing 'Microsoft’s AI Chief added to
arXiv:2603.04125v2 Announce Type: replace Abstract: Few-Shot Action Recognition (FS-AR) has shown promising results but is often limited by a closed-set assumption that fails in real-world open-set sc
arXiv:2512.07355v2 Announce Type: replace Abstract: Two traditions of interpretability have evolved side by side but seldom spoken to each other: Concept Bottleneck Models (CBMs), which prescribe what
arXiv:2606.08093v1 Announce Type: new Abstract: Pathology is the cornerstone of modern medicine, where accurate decision-making relies heavily on evidence-based practices. While artificial intelligenc
arXiv:2606.09073v1 Announce Type: cross Abstract: Reinforcement learning from human feedback (RLHF) is bottlenecked by reward hacking, where the policy exploits errors in a proxy reward model (RM) and
arXiv:2606.08105v1 Announce Type: new Abstract: When attention concentrates on a single token, a sink, what is the model actually computing? Attention sinks are ubiquitous in softmax transformers, yet
arXiv:2606.09734v1 Announce Type: cross Abstract: Training parameterised quantum circuits (PQCs) on quantum hardware is bottlenecked by the measurement cost of gradient estimation, which under the par
arXiv:2606.09104v1 Announce Type: cross Abstract: Deep reinforcement learning (DRL) frameworks for portfolio optimization have shown promise for their ability to learn allocation rules dynamically fro
arXiv:2606.08696v1 Announce Type: cross Abstract: Counterfactual recourse aims to provide actionable feature changes that would alter an unfavorable decision made by a predictive model. In practice, a
arXiv:2606.09100v1 Announce Type: cross Abstract: Community detection is a fundamental problem in the analysis of complex networks. It has applications across social, biological, and financial domains
Also, I found that Hermes Agent + Nemotron 3 Ultra is a mighty combo! Excited to launch a new way to upskill with AI agents. This is how we are making it possible for anyone to learn to build with cod
arXiv:2606.09383v1 Announce Type: new Abstract: Conventional dynamics analysis of the human body is often constrained by the need for contact force and torque sensors and controlled laboratory environ
arXiv:2606.07638v1 Announce Type: cross Abstract: Image generative models, though widely used as creative tools, offer limited support for the kind of compositional control that photographers and visu
arXiv:2606.08761v1 Announce Type: cross Abstract: W4A4 quantization promises full utilization of INT4 Tensor Cores, yet group dequantization overhead on CUDA Cores has driven existing systems to mixed
Joe Rossignol / MacRumors: Apple says 79% of all iPhones and 86% of iPhones released in the past four years were running iOS 26 as of June 7, vs. 82% and 88% for iOS 18 before WWDC 2025 — Apple has sh
arXiv:2606.09648v1 Announce Type: cross Abstract: Multi-modal data management has emerged as a central research topic in the database community, spanning data integration, semantic query processing, a
arXiv:2606.09634v1 Announce Type: cross Abstract: 3D object detection is the backbone of perception for automated vehicles (AV) and broader intelligent transportation systems applications. Long-range
Aujourd'hui, Cohere a annoncé un nouveau partenariat avec le gouvernement du Québec. Le Québec est depuis longtemps l'un des écosystèmes d'IA les plus importants au monde. Nous sommes fiers de collabo
Amazon Web Services Inc. today introduced an artificial intelligence tool designed to help organizations lower their cloud bills. AWS FinOps Agent is initially available in public preview. It’s the la
Release b9585 of llama.cpp fixes granite speech model inference by applying embedding scale when deepstack is not used . The release was published on June 9, 2026, and represents a bug fix within the
arXiv:2606.09048v1 Announce Type: cross Abstract: Removing intermediate representations and separately trained decoding stages has become an important direction in generative modeling. In text-to-spee
arXiv:2511.03877v2 Announce Type: replace Abstract: Social and collaborative platforms emit multivariate time-series traces in which early interactions -- such as views, likes, or downloads -- are fol
arXiv:2606.08285v1 Announce Type: new Abstract: Large language models (LLMs) and agentic systems are increasingly proposed for financial trading, yet their reported performance remains difficult to co
arXiv:2606.08454v1 Announce Type: new Abstract: Activation steering provides a lightweight inference-time mechanism for controlling large language models (LLMs) by modifying their internal activation
arXiv:2606.07519v1 Announce Type: cross Abstract: We introduce the novel task of bidirectional small-granularity search between code and text, where the queries are small snippets of text or code and
arXiv:2606.06895v1 Announce Type: cross Abstract: The deployment of embodied artificial intelligence via world-model-based robotics presents a transformative opportunity for blockchain infrastructure,
arXiv:2606.09257v1 Announce Type: cross Abstract: High-Dimensional Low-Sample Size (HDLSS) tabular domains (e.g., omics) are characterized by n ll m, where n = number of samples, and m = number of fea
btw insane amounts of alpha in telling claude code to 'review my code for issues' on Fable rn while it is not pay per use be prepared to be in abject horror that you shipped anything to prod without a
but but i thought it was magic? What we learned testing Claude Fable/Mythos 5 on Vending-Bench: > Performance: Makes less money than Opus 4.7 and GPT-5.5 > Alignment: A step back. (Opus 4.8 was better
arXiv:2606.07790v1 Announce Type: new Abstract: Multi-agent LLM systems increasingly rely on communication protocols for coordination, yet their robustness under adversarial and structural constraints
arXiv:2606.09237v1 Announce Type: new Abstract: Time-of-flight cameras are popular in robotics for providing direct depth information while being compact, inexpensive, and robust to lighting condition
arXiv:2606.08969v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for medical summarization, but their outputs can omit medically important information and introduce
arXiv:2603.24388v2 Announce Type: replace Abstract: Medical imaging models frequently fail when deployed across hospitals, scanners, populations, or imaging protocols due to domain shift, limiting the
arXiv:2602.22919v2 Announce Type: replace Abstract: Cardiac cine magnetic resonance imaging (MRI) is central to functional cardiac assessment, yet a full current cine sequence may not always be direct
arXiv:2606.09639v1 Announce Type: new Abstract: The fidelity and structural diversity of training datasets fundamentally determine the capabilities of video generation models. While commercial systems
arXiv:2606.09180v1 Announce Type: new Abstract: We present our submission to the CVPR 2026 Argoverse 2 Scenario Mining Challenge. Our system uses a four-stage pipeline: (1) autonomous code generation
Claude Fable 5 is now available for use in the Cursor IDE, achieving a new state-of-the-art performance on CursorBench with a score of 72.9%, an 8-point improvement over the previous best result. This
Claude Fable 5 has been integrated into Devin and achieved the top ranking on FrontierCode, Cognition AI's benchmark for real-world engineering tasks. This integration represents an advancement in Dev
Nous Research announced support for Claude Fable 5 integration with Hermes Agent through the Nous Portal, offering new users a promotional one-month free trial of the Plus plan for the first 500 signu
arXiv:2606.09520v1 Announce Type: cross Abstract: Can a general-purpose large language model design molecules with the precision of a seasoned chemist? Current LLM-based frameworks answer this questio
arXiv:2606.09577v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as code generators, where silently wrong programs pose real safety and reliability risks. Relia
arXiv:2603.04177v2 Announce Type: replace-cross Abstract: LLM coding agents can generate working code, but their solutions often accumulate complexity, duplication, and architectural debt. Human devel
arXiv:2606.09751v1 Announce Type: new Abstract: Foundation models are moving from response generation into operational roles. They plan across steps, call tools, request human input, coordinate with o
arXiv:2410.05662v4 Announce Type: replace Abstract: Most federated learning (FL) approaches assume a fixed device set. However, real-world scenarios often involve devices dynamically joining or leavin
arXiv:2601.20503v2 Announce Type: replace-cross Abstract: White matter hyperintensities (WMH) and ischaemic stroke lesions (ISL) are key imaging biomarkers of cerebral small vessel disease (SVD) detec
arXiv:2606.08158v1 Announce Type: cross Abstract: Large language models (LLMs) can generate factually inconsistent claims, motivating accurate and scalable hallucination detectors. Prior work largely
arXiv:2603.09995v2 Announce Type: replace-cross Abstract: Behavioral interview evaluation using large language models presents unique challenges that require structured assessment, realistic interview
arXiv:2606.09090v1 Announce Type: cross Abstract: Developers increasingly provide AI coding assistants with persistent context through configuration files such as CLAUDE.md, AGENTS.md, and .cursorrule
arXiv:2606.07604v1 Announce Type: cross Abstract: Analyzing attention weights has become a standard approach for interpreting the information flow of Large Language Models (LLMs). However, this approa