Knowledge catalogue
arXiv:2607.00885v1 Announce Type: cross Abstract: Recent advances in neural rendering have established 3D Gaussian Splatting (3DGS) as a highly efficient representation for novel view synthesis, enabl
in case you needed more evidence that tokenmaxxing was a stupid idea Meta burns 2.65B a year on AI tokens. at 300K for a Meta engineer, that's enough to pay ~9,000 engineers for a full year. now ask y
arXiv:2607.00434v1 Announce Type: new Abstract: Vision-language models (VLMs) have become a paradigm for multimodal learning, yet remain unstable due to object hallucination, weak visual grounding, an
arXiv:2607.01222v1 Announce Type: new Abstract: Recent 3D generative models can synthesize high-quality geometry but often struggle to reproduce intricate textures from reference images, largely due t
This article examines the infrastructure approaches and strategies that leading AI companies use to support their AI development and deployment at scale. It likely covers key components such as data p
arXiv:2603.16085v2 Announce Type: replace-cross Abstract: Recent breakthroughs in 3D generation have enabled the synthesis of high-fidelity individual assets. However, generating 3D compositional obje
Grace Kay / The Information: Internal memo: Tesla plans to impose a 200-per-week limit for staff's AI spending beginning July 6; the tally excludes beta versions of xAI products — Tesla told employees
arXiv:2607.00477v1 Announce Type: new Abstract: A total of seven categorical encoding methods were tested on the IEEE-CIS fraud benchmark dataset (590,540 records, 3.5% positives, 8 high-cardinality c
arXiv:2502.18975v2 Announce Type: replace Abstract: Machine learning models are inherently bound to the distribution of the training data, often exploiting non-causal shortcuts. As a result, achieving
arXiv:2607.00026v1 Announce Type: new Abstract: An invariant extended Kalman filter (IEKF) is developed for state estimation of serial rigid manipulators with an arbitrary number of links, formulated
arXiv:2603.16432v3 Announce Type: replace Abstract: Unsupervised physical parameter estimation from video lacks a common benchmark: existing methods evaluate on non-overlapping synthetic data, the sol
arXiv:2607.01232v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become a central component of post-training large language models (LLMs), yet little is understood about how RL adapta
arXiv:2607.00145v1 Announce Type: new Abstract: Inertial navigation systems aided by three-dimensional landmark measurements constitute a fundamental problem in robotic perception and state estimation
David Holz, CEO of Midjourney, expressed enthusiasm about Marcin joining the team and appreciated him creating video content at the Midjourney office. The post highlights internal company culture and
I've been blogging a few of my Fable experiments today, most recently I had it more-or-less one-shot a CLI coding agent on top of my LLM Python library https://simonwillison.net/2026/Jul/2/llm-coding-
I've heard a lot of questions about Fable's availability on subscription plans. While it will come off subscriptions after July 7th, we aim to restore Fable as a standard part of our subscriptions as
This post discusses running a prompt through an AI agent mode feature, comparing results between standard and agent modes, with the author noting positive outcomes from the agent mode implementation.
arXiv:2607.00031v1 Announce Type: new Abstract: To perform complex manipulation planning, autonomous robots are required to abstract continuous, high-dimensional sensorimotor interactions into discret
arXiv:2607.00058v1 Announce Type: new Abstract: Image quality is critical for accurate medical diagnosis. However, MRI, CT, and ultrasound images are often of low resolution and quality due to cost co
Summer is heating up — and GeForce NOW is taking players along for the ride. Start the month with Monopoly: Star Wars Heroes vs. Villains, bringing a galaxy far, far away to the iconic board-game fran
arXiv:2607.00329v1 Announce Type: cross Abstract: Recursive Feature Machines (RFMs) are a class of kernel machines that utilize the Average Gradient Outer Product (AGOP) as a mechanism for feature lea
arXiv:2510.13537v2 Announce Type: replace-cross Abstract: On-device deployment of Large Language Models (LLMs) frequently leverages Low-Rank Adapters (LoRAs) to support diverse downstream tasks under
arXiv:2601.14232v2 Announce Type: replace-cross Abstract: Pixel-based reinforcement learning agents often fail under purely visual distribution shift even when latent dynamics and rewards are unchange
arXiv:2603.16943v2 Announce Type: replace-cross Abstract: Skeleton-based action recognition is widely applied in sensor-based systems, including human-computer interaction and intelligent surveillance
Swyx expressed interest in organizing a meet and greet at AIE (likely an industry event or conference) and was seeking a host organization or company willing to host him at their booth. The post appea
Zheping Huang / Bloomberg: Kling AI, the Kuaishou AI video generator spin-off, raised 2B at a 15B pre-money valuation and says the round could extend to as much as 3B — China's Kling AI has raised an
arXiv:2607.00482v1 Announce Type: new Abstract: Reasoning language models frequently overthink: generating extended chains of behaviors such as hedging, approach abandonment, and self contradiction th
arXiv:2603.26270v2 Announce Type: replace-cross Abstract: Smart contracts govern billions of dollars in decentralized finance (DeFi), yet automated vulnerability detection remains challenging because
arXiv:2607.01000v1 Announce Type: new Abstract: Recent research has increasingly focused on understanding how Transformers store and process knowledge, as well as how this knowledge can be edited. Res
arXiv:2606.13695v2 Announce Type: replace-cross Abstract: Mineral prospectivity modelling (MPM) underpins exploration economics, yet most operational pipelines reduce to data-driven classifiers traine
arXiv:2506.12851v3 Announce Type: replace-cross Abstract: Humanoid robots are promising to acquire various skills by imitating human behaviors. However, existing algorithms are only capable of trackin
arXiv:2606.17416v2 Announce Type: replace-cross Abstract: Multilingual speaker verification remains challenging because language-dependent acoustic variability causes speaker identity to become entang
arXiv:2607.01225v1 Announce Type: cross Abstract: Prior work on imitation learning from suboptimal demonstrations typically relies on compressed supervision signals such as confidence estimates, discr
arXiv:2511.04500v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed as decision-making agents in high-stakes domains and as imitators of human behavior in the so
last day at @aiDotEngineer and i'll be at the Expo's poster area explaining the year's best survey paper on Agent Memory (Hu et al), as we did for @latentspacepod's Paper Club live from the floor with
Yohei Nakajima hosted a networking event in San Francisco bringing together the BabyAGI and Physical AI communities for casual conversation and relationship-building. The event likely focused on discu
arXiv:2403.19645v2 Announce Type: replace Abstract: The rapid advancement of diffusion models has enabled the generation of high-fidelity images from textual prompts, yet achieving precise, disentangl
arXiv:2607.00955v1 Announce Type: cross Abstract: Implicit neural representations (INRs) are well suited to cardiac motion estimation, providing continuous, compact representations of motion fields. H
arXiv:2512.11173v4 Announce Type: replace Abstract: Achieving precise positioning of the mobile manipulator's base is essential for successful manipulation actions that follow. Most of the RGB-based n
arXiv:2607.00033v1 Announce Type: cross Abstract: Dexterous robot manipulation can benefit from the abundance of human demonstrations, but transferring such demonstrations to robot policies remains ch
arXiv:2607.00257v1 Announce Type: new Abstract: Accurate prediction of complex dynamical systems from noisy measurements remains a significant challenge in scientific computing. Kernel ridge regressio
arXiv:2607.00066v1 Announce Type: new Abstract: Endovascular interventions are high-stakes procedures requiring precise device operation within complex and tortuous vascular anatomies. Autonomous endo
arXiv:2607.00534v1 Announce Type: new Abstract: We present STT-LfD, a unified Learning from Demonstration (LfD) framework that integrates motion learning with control for unknown Euler-Lagrange system
arXiv:2607.00442v1 Announce Type: cross Abstract: Reinforcement learning (RL) for quadruped locomotion commonly depends on fixed, hand-crafted, and Markovian reward functions that limit both interpret
arXiv:2607.00392v1 Announce Type: cross Abstract: Unsupervised Reinforcement Learning (URL) aims to pre-train scalable, skill-conditioned policies without extrinsic rewards, serving as a foundation fo
Large language models can exhibit emergent reasoning behaviors, often manifested as recurring lexical patterns (e.g., “wait,” indicating verification). However, complex reasoning trajectories remain s
arXiv:2607.00374v1 Announce Type: cross Abstract: Composed Image Retrieval (CIR) retrieves a target image from a reference image and a textual modification. While supervised CIR relies on costly tripl
arXiv:2607.00622v1 Announce Type: new Abstract: Video anomaly understanding (VAU) relies on sparse, context-dependent cues. However, existing passive paradigms suffer from observational aliasing, wher
Diffusion (Large) Language Models (dLLMs) now match the downstream performance of their autoregressive counterparts on many tasks, while holding the promise of being more efficient during inference. O
arXiv:2607.00017v1 Announce Type: cross Abstract: Long-term conversational agents are expected to remember past interactions, but memory is useful only when the right evidence is recalled for the righ
arXiv:2607.00296v1 Announce Type: cross Abstract: Human motion forecasting in unconstrained real-world videos remains challenging due to the ambiguity of future behaviors and the presence of noisy mul
arXiv:2607.00958v1 Announce Type: new Abstract: Time series are central to modern data mining applications, from industrial telemetry and server metrics to finance and physiology, yet time-series self
Maggie Eastland / Bloomberg: Letter: chip sector group SEMI, including Micron and Samsung, warns Scott Bessent US policies affecting prices or production capacity would worsen the shortage — Governmen
arXiv:2607.00228v1 Announce Type: cross Abstract: Modern time-domain surveys such as the Zwicky Transient Facility (ZTF) generate hundreds of thousands of alerts each night, making real-time decisions
arXiv:2607.00251v1 Announce Type: cross Abstract: While most image deblurring techniques directly restore the spatial image variable, we propose an amplitude and phase decomposition recognizing the im
arXiv:2607.00784v1 Announce Type: cross Abstract: Vision-language pretraining remains dominated by contrastive objectives, whereas vision-only self-supervised learning has largely adopted non-contrast
arXiv:2607.00016v1 Announce Type: cross Abstract: Information localization within massive repositories is a cornerstone of agentic LLM systems. While synthetic data-driven optimization has proven succ
arXiv:2607.00654v1 Announce Type: new Abstract: Video anomaly detection (VAD) with multimodal large language models has shown strong potential, yet most existing methods still depend on large-scale an
arXiv:2607.01205v1 Announce Type: new Abstract: We present Linkify, a framework for learning from interface-augmented assembly graphs to enable context-aware part retrieval in mechanical assemblies. W
arXiv:2607.00375v1 Announce Type: new Abstract: We present LIST3R, an instance-aware framework for long-sequence 3D reconstruction inspired by the way humans organize spatial memory around stable and