Knowledge catalogue
A significant fraction of humanity read this thread. Is anyone prepared to do something about it? Fretting doesn’t count. I resigned from Anthropic today. I spent the last three years doing pretrainin
arXiv:2609.07974v1 Announce Type: cross Abstract: Fairness in clustering has attracted sustained research interest, motivated by the need to ensure equitable representation of protected groups in mach
arXiv:2505.02627v2 Announce Type: replace Abstract: Compositional generalizationnicode{x2013}the ability to systematically process novel combinations of known componentsnicode{x2013}is a hallmark of h
arXiv:2609.06460v1 Announce Type: new Abstract: Recently, Masked Pretraining (MPT) based on reconstruction pretraining tasks has risen to a promising self-supervised learning paradigm across various d
arXiv:2609.07821v1 Announce Type: cross Abstract: Chain-of-Thought (CoT) improves the reasoning ability of Large Language Models (LLMs) but incurs substantial computation and context costs. Existing m
arXiv:2603.18074v2 Announce Type: replace Abstract: Technical-service LLM agents are entering production workflows, where value depends on whether engineers adopt generated replies. Service tickets hi
arXiv:2609.08788v1 Announce Type: new Abstract: Dense self-attention treats all token pairs as equally plausible before learning, an interaction-isotropic prior that can be mismatched to structured si
arXiv:2406.04314v4 Announce Type: replace Abstract: Generating visually appealing images is fundamental to modern text-to-image generation models. A potential solution to better aesthetics is direct p
arXiv:2601.08485v3 Announce Type: replace Abstract: Achieving agile and generalized legged locomotion across terrains requires tight integration of perception and control, especially under occlusions
arXiv:2609.07036v1 Announce Type: cross Abstract: We identify the Flow Moment, a reasoning pattern characterized by sustained, process-confirming verbalizations such as I'm doing, in contrast to the r
Madison Mills / Axios: AI researcher Jacob Coxon says he quit Anthropic after four months, two months before his equity would have vested; he still has equity in prior employer OpenAI — Anthropic rese
arXiv:2512.23515v2 Announce Type: replace-cross Abstract: Signal decay and regime shifts pose recurring challenges for data-driven investment strategies in non-stationary markets, where conventional t
arXiv:2609.05583v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are reshaping computer vision by aligning visual and textual embeddings, allowing models to recognize visual concepts and
arXiv:2609.06978v1 Announce Type: new Abstract: Progress in video anomaly understanding (VAU) has long been limited by inherent deficiencies of real-world anomaly videos, which are hard to collect and
An Anthropic PBC researcher has resigned over concerns that artificial intelligence labs are “gambling with our lives.” Jacob Coxon was part of the company’s AI pretraining team until today. He announ
Evan Hubinger / @evanhub: Anthropic's Alignment Science lead says there is a “>10%” chance AI could kill all humans within the next decade and worries about recursive self-improvement — Jacob is corre
Anyone still denying the risks posed by unregulated AI should read this thread. It’s time to pump the brakes & take action NOW. We need: - Mandatory safeguards - A comprehensive testing regime - Urgen
arXiv:2609.05484v1 Announce Type: new Abstract: Deep learning registration methods routinely stack two kinds of enhancement on a base network: architectural additions such as affine pre-alignment stag
arXiv:2609.08806v1 Announce Type: new Abstract: Arm pose estimation enables applications in fitness, extended reality input, rehabilitation, and life logging. Prior smartwatch-based approaches rely on
arXiv:2607.10655v2 Announce Type: replace Abstract: Robotic foundation models still need task-specific fine-tuning before deployment, and the fine-tuned policies often break under modest changes in sc
arXiv:2509.23454v2 Announce Type: replace-cross Abstract: Biomedical audio signals, such as phonocardiograms (PCG), are inherently rhythmic and contain diagnostic information in both their spectral (t
arXiv:2609.08493v1 Announce Type: cross Abstract: Observing objects grasped by a robot hand is challenging due to severe visual occlusions. Although in-hand manipulation can expose hidden surfaces, ex
arXiv:2609.06094v1 Announce Type: new Abstract: Red-teaming Text-to-Image (T2I) models is essential for safe deployment, yet it remains particularly challenging against implicit adversarial prompts. U
arXiv:2609.08725v1 Announce Type: new Abstract: In online A/B tests for real-time bidding (RTB), control and treatment models are typically trained on a shared serving log that includes data generated
arXiv:2609.06667v1 Announce Type: new Abstract: Adaptive dosing requires policies that reduce tumor burden without excessive toxicity. Learned dosing policies are typically judged against historical o
arXiv:2609.07939v1 Announce Type: new Abstract: We address the problem of discovering repeated elements from a single image. In contrast to existing approaches that depend on large annotated datasets,
Christine Mui / Politico: California Gov. Gavin Newsom signs into law two bills, backed by Anthropic and OpenAI, regulating how outside groups evaluate AI for safety — SAN FRANCISCO — California Gov.
arXiv:2609.07430v1 Announce Type: new Abstract: How robot body configuration shapes human intervention during approach remains underexplored. We conducted a within-participants study with 41 participa
arXiv:2609.06931v1 Announce Type: new Abstract: Invasive coronary angiography (CAG) is the gold standard for diagnosing coronary artery disease, but interpretation varies substantially among observers
arXiv:2609.08638v1 Announce Type: new Abstract: An action chunk can span several stages of a manipulation task, yet a label for its first step describes only the current stage. We introduce Chunk-Alig
arXiv:2609.08853v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) is a family of RL methods that learn a model of the environment and use it for action selection, making it wel
arXiv:2609.05783v1 Announce Type: cross Abstract: In autonomous driving, Bird's-Eye View (BEV) representations provide a structured, top-down abstraction of the vehicle's surroundings and have become
arXiv:2510.09712v4 Announce Type: replace Abstract: The proliferation of Large Language Models (LLMs) has enabled a new class of psychologically grounded malicious comments, shifting fake news attacks
arXiv:2603.21913v2 Announce Type: replace Abstract: In structured multi-agent transportation systems, agents often must follow predefined routes, making spatial rerouting undesirable or impossible. Th
arXiv:2609.06433v1 Announce Type: new Abstract: The generation of safety-critical traffic scenarios is essential for training and evaluating autonomous vehicles. Prior approaches typically perturb the
arXiv:2508.11854v3 Announce Type: replace Abstract: As 3D Gaussian Splatting (3DGS) gains rapid adoption in safety-critical tasks for efficient novel-view synthesis from static images, how might an ad
arXiv:2609.07086v1 Announce Type: cross Abstract: Transformers are a dominant architecture in modern machine learning, powering applications across vision, language, and beyond. At the core of their s
arXiv:2609.05821v1 Announce Type: cross Abstract: Vision-language models (VLMs) often answer new questions about recurring visual content, where reusing the key-value (KV) cache can avoid re-encoding
arXiv:2503.15895v2 Announce Type: replace Abstract: This paper investigates whether sequential context improves goal-conditioned Reinforcement Learning in sparse-reward manipulation tasks. While Hinds
arXiv:2601.22475v2 Announce Type: replace Abstract: Building a generalist robot policy requires continuously integrating new skills while preserving previously acquired behaviors. Directly optimizing
arXiv:2609.06140v1 Announce Type: cross Abstract: Agents can turn shared infrastructure into a channel for coordinated intrusion. The Hugging Face incident and a separate public-wiki investigation sho
arXiv:2609.05832v1 Announce Type: new Abstract: Integrating visuomotor policies or Vision-Language-Action (VLA) models with force/torque (F/T) perception has demonstrated significant progress in imita
arXiv:2609.07499v1 Announce Type: new Abstract: Training-free collaborative pipelines that integrate Vision Foundation Models such as CLIP, SAM, and DINO achieve strong open-vocabulary dense predictio
arXiv:2609.07753v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) is an important modality in a wide range of imaging applications due to its versatile, long range and near all weather op
arXiv:2609.06302v1 Announce Type: new Abstract: Embodied visual tracking requires a robot not only to react to the current view, but to choose actions that preserve or recover future evidence of a mov
arXiv:2509.25180v3 Announce Type: replace Abstract: Existing text-to-image diffusion models excel at generating high-quality images, but face significant efficiency challenges when scaled to high reso
arXiv:2609.08711v1 Announce Type: new Abstract: We present DCLP++, a local navigation frameworkthat uses footprint clearance as the geometric basis for studying relative motion features in dynamic env
arXiv:2609.09119v1 Announce Type: new Abstract: Dexterous manipulation involves contact-rich and fine-grained interactions with the physical world, posing significant challenges for existing vision-la
arXiv:2609.07618v1 Announce Type: cross Abstract: Environments are increasingly populated by multiple robots performing independent tasks with limited prior knowledge of each other. Deploying such mul
arXiv:2406.08697v4 Announce Type: replace-cross Abstract: Offline reinforcement learning enables evaluation and optimization of sequential decisions from historical data, when it is not possible to de
arXiv:2510.23258v2 Announce Type: replace-cross Abstract: Autonomous robotic navigation in real-world environments requires exploration to acquire environmental information as well as goal-directed na
arXiv:2609.06007v1 Announce Type: new Abstract: Guided depth completion methods heavily depend on RGB quality and alignment, while unguided ones often suffer from limited precision due to the absence
arXiv:2609.07072v1 Announce Type: new Abstract: Graphic designs, such as posters, advertisements, and infographics, are an important medium for communicating information and shaping understanding. Unl
arXiv:2609.07747v1 Announce Type: new Abstract: Human videos are an abundant source of dexterous manipulation behaviors, but they lack tactile information that is crucial for contact-rich interaction.
arXiv:2602.18613v2 Announce Type: replace Abstract: Standard reranking evaluations study how a reranker orders candidates returned by an upstream retriever. This setup couples ranking behavior with re
arXiv:2609.08650v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has been central to the recent success of Large Reasoning Models. However, while RLVR significantl
arXiv:2609.06593v1 Announce Type: cross Abstract: Choosing when to translate multilingual documents is a central routing problem in text classification: translation can improve predictions for some la
Gary Marcus will discuss his “case for boycotting generative AI” during a CBC segment scheduled to air at 7:45 p.m. ET tonight. The argument is outlined in his Substack post titled *The Case for Boyco
arXiv:2609.08123v1 Announce Type: cross Abstract: A robot that can be taught a new task from a handful of demonstrations has to work out for itself what it still cannot do, and then ask for exactly th
arXiv:2609.08337v1 Announce Type: new Abstract: On-policy distillation (OPD) transfers teacher knowledge on student-generated trajectories, but efficient sampled objectives reduce the teacher distribu