Knowledge catalogue
arXiv:2610.14341v1 Announce Type: new Abstract: We present CoPlanVLM, which uses a Vision Language Model (VLM) to translate a single natural-language instruction and image into coordinated paths for a
arXiv:2610.17083v1 Announce Type: new Abstract: Large Language Models (LLMs) are predominantly trained on imperative programming languages, and existing work on LLM-based robot programming reflects th
arXiv:2511.20088v3 Announce Type: replace Abstract: In recent years, VAD (Visual Anomaly Detection) has attracted significant attention due to its high interpretability, as it provides visual explanat
arXiv:2601.07632v5 Announce Type: replace Abstract: Discrete motion tokenization has recently enabled Large Language Models (LLMs) to serve as versatile backbones for motion understanding and motion-l
Foo Yun Chee / Reuters: Google DeepMind and Google Cloud plan to provide up to 200 European scientific researchers with access to their frontier AI models and $3M in compute credits — Google DeepMind
arXiv:2610.17948v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) have attracted increasing research attention due to their bidirectional attention and arbitrary order decoding.
Duncan Riley / SiliconANGLE: Harmonic Security, which uses small language models to inspect employee interactions with AI tools, raised a 50M Series B, taking its total funding to 76M — Workplace arti
arXiv:2602.08302v2 Announce Type: replace Abstract: Delayed generalization, where training accuracy becomes nearly perfect substantially before test accuracy, has often been studied in the context of
arXiv:2610.15173v1 Announce Type: cross Abstract: We investigate whether a physics foundation model (PFM) pretrained for PDE forecasting can be repurposed for closed-loop fluid-flow control. We constr
arXiv:2610.17540v1 Announce Type: cross Abstract: Textual reasoning before acting has improved vision-language-action (VLA) models, but at the cost of latency: every action conditioned on the reasonin
arXiv:2610.18459v1 Announce Type: new Abstract: External tools can extend the capabilities of small language models (SLMs), enabling their deployment in resource constrained environments. However, the
arXiv:2610.14896v1 Announce Type: new Abstract: Humanoid Behavior Foundation Models (BFMs) can execute impressive motions, but downstream applications such as loco-manipulation demand high whole-body
arXiv:2605.05886v2 Announce Type: replace Abstract: Dense hand contact estimation requires both high-level semantic understanding and fine-grained geometric reasoning of human interaction to accuratel
arXiv:2507.14777v2 Announce Type: replace Abstract: We investigate foundational questions about the interplay between memorization and learning in large language models (LLMs). When an LLM generates a
arXiv:2502.08598v3 Announce Type: replace Abstract: Diffusion models have been widely adopted as a powerful generative framework across numerous scientific domains, yet their inherently iterative samp
Chao Kong / South China Morning Post: Leading Chinese mathematicians launch an alliance, including eight orgs and aiming for 1,000+ scientists, to focus on developing specialized AI models for math —
arXiv:2610.12741v1 Announce Type: new Abstract: We interpret Transformer networks as learned approximations to a hybrid probabilistic-inference procedure that combines max-product Loopy Belief Propaga
arXiv:2412.06534v5 Announce Type: replace-cross Abstract: Understanding the internal mechanisms of deep neural networks remains a central challenge in machine learning. In computer vision, one promisi
arXiv:2511.05940v3 Announce Type: replace-cross Abstract: Score-based diffusion models have emerged as a powerful class of generative methods, with successful applications across diverse domains. Desp
arXiv:2603.17524v2 Announce Type: replace-cross Abstract: We study fine-grained execution-constraint following in vision-language-action (VLA) models. Given an invariant task goal, the policy must fol
arXiv:2603.25015v2 Announce Type: replace-cross Abstract: System prompt instructions that cooperate in English compete in Spanish, with the same semantic content, but opposite interaction topology. We
arXiv:2606.16253v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models increasingly rely on high-frequency multi-camera observations, making visual communication a major bottlen
arXiv:2610.10990v1 Announce Type: new Abstract: Unified multimodal diffusion large language models (dLLMs) offer a single architecture for both image generation and multimodal understanding, but their
arXiv:2610.10933v1 Announce Type: cross Abstract: Spiking language models face a tradeoff between representing continuous semantic features over short temporal windows and retaining costly nonlinear a
arXiv:2610.10812v1 Announce Type: new Abstract: Small language models (SLMs) have been increasingly adopted for onboard robot operation because they enable intelligent decision-making. However, existi
arXiv:2610.11401v1 Announce Type: cross Abstract: World Action Models (WAMs) enable generalist robot manipulation by conditioning an action expert on representations from a pretrained video Diffusion
arXiv:2610.11355v1 Announce Type: new Abstract: Researchers increasingly use ChatGPT to revise their papers, and recent GPT versions often narrow or even retract the authors' claims. We call such chan
arXiv:2610.09427v1 Announce Type: new Abstract: World-Action Models (WAMs) utilize future visual prediction as an intermediate reasoning process to guide action generation. However, existing WAMs typi
arXiv:2610.10196v1 Announce Type: new Abstract: LiDAR point clouds of humans are extremely expensive to collect and annotate, thus represent a scarce resource that hinders the development of human ana
arXiv:2610.09940v1 Announce Type: cross Abstract: Joint-embedding predictive architectures (JEPAs) predict masked or future observations in representation space, offering a natural source of predictiv
arXiv:2610.08872v1 Announce Type: cross Abstract: We study community recovery in the sparse symmetric stochastic block model with q communities, average degree d and signal strength lambda through sta
arXiv:2610.09064v1 Announce Type: cross Abstract: When we interact with large language models (LLMs), are we having a conversation? They are designed to invite us to treat them as intelligent interloc
arXiv:2610.07469v1 Announce Type: new Abstract: Explicitly eliciting reasoning substantially improves LLM performance. Existing approaches require a predefined characterization of reasoning, whether t
arXiv:2610.06996v1 Announce Type: cross Abstract: Block diffusion language models keep a large key-value (KV) cache throughout generation and attend to it at every denoising step, limiting both memory
arXiv:2610.07661v1 Announce Type: new Abstract: Massive activations, a phenomenon in which a small number of hidden channels exhibit exceptionally large magnitudes, are pervasive in large language mod
Stevie Bonifield / The Verge: Microsoft opens preorders for the $5,999 Surface RTX Spark Dev Box, with 128GB of unified memory to run local models with 120B+ parameters, shipping in November — Microso
Angel Au-Yeung / Wall Street Journal: OpenRouter: the share of business spending between OpenAI and Anthropic models was roughly even in September, vs. Anthropic commanding a 75% share in January — Bo
arXiv:2610.07936v1 Announce Type: new Abstract: Systematicity, the probabilistic mapping of form to meaning, permeates language at all levels, and sublexical cues have been shown to govern human pseud
arXiv:2610.07954v1 Announce Type: new Abstract: Language-based trajectory predictors represent coordinates as discrete tokens and learn auxiliary tasks such as destination and group reasoning. This fo
arXiv:2610.07756v1 Announce Type: new Abstract: Vision-language-action (VLA) models increasingly rely on diffusion- or flow-matching-based action heads to generate continuous robot actions. These acti
arXiv:2610.06926v1 Announce Type: new Abstract: Robot manipulation systems using Vision-Language-Action (VLA) model backbones typically use just one VLA for task execution. However, individual VLAs do
arXiv:2610.05413v1 Announce Type: new Abstract: Evaluating vision encoders requires metrics that reliably predict their downstream performance in multimodal large language models (MLLMs). Although rec
arXiv:2610.04631v1 Announce Type: new Abstract: Numerical Linear Algebra (NLA) has consistently played a vital role in advancing science by providing tools to solve fundamental problems encountered in
arXiv:2610.05719v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models serve as unified policies for robotic manipulation, yet their expensive inference forces robots to pause between pol
arXiv:2610.02911v1 Announce Type: cross Abstract: Methods for training language models on stale samples are judged by comparisons against importance-corrected baselines. We show that details of the ex
arXiv:2610.02343v1 Announce Type: new Abstract: Geometric understanding supports endoscopic navigation and robotic assistance, but learning reliable endoscopic geometry faces two challenges: scarce ge
arXiv:2610.02784v1 Announce Type: new Abstract: Tactile sensing provides essential contact information for robotic manipulation, yet incorporating it into pretrained vision-language-action (VLA) model
arXiv:2610.02323v1 Announce Type: cross Abstract: Flow-based Vision-Language-Action (VLA) policies generate action chunks by transporting samples from a task-agnostic isotropic Gaussian source. As thi
The AI research community released a set of notable papers between September 28 and October 4, highlighted in a weekly roundup. Key contributions include JAZ, CASD, Agensh, Jev‑Mem, AutoGym, Taste‑Ben
arXiv:2610.00209v1 Announce Type: new Abstract: Reliable recovery of missing measurements is important for monitoring and analysis in energy time-series systems, where fine-grained measurements may co
arXiv:2602.08538v2 Announce Type: replace-cross Abstract: Flow-based generative models have emerged as powerful priors for solving inverse problems. One option is to directly optimize the initial late
Check out jes: An open source real-time guardrails for AI agents, powered by decision models like Jev from @typesafeai Built to guard every step in the agent trajectory: prompts, tool calls, tool resu
arXiv:2609.39971v1 Announce Type: cross Abstract: Vision-language-action (VLA) models can exceed 90% success on in-distribution tasks and withstand nuisance changes that preserve the required action,
3 models are now available on Ollama for use with /v1/systemone: • Nimble: https://ollama.com/library/nimble • Tev1 4b: https://ollama.com/library/tev1:4b • Tev1 0.8b: https://ollama.com/library/tev1:
arXiv:2609.37441v1 Announce Type: new Abstract: Latent world models learn action-conditioned dynamics in representation space and often score candidate actions by Euclidean distance to a goal represen
arXiv:2406.00083v3 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) enhances Large Language Models (LLMs) by retrieving relevant information from external knowledge bases to
arXiv:2609.37837v1 Announce Type: new Abstract: Vision-Language Models (VLMs) remain vulnerable to cross-modal implicit risks: visual and textual inputs that appear benign in isolation can jointly eli
arXiv:2609.36588v1 Announce Type: cross Abstract: We study reinforcement learning (RL) methods for cooperative multi-agent Vision-Language-Action (VLA) models. This problem is challenging because VLAs
arXiv:2609.37165v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models remain brittle under visual distribution shifts, often relying on spurious correlations tied to domain-specific fact
arXiv:2609.37533v1 Announce Type: new Abstract: Masked diffusion models (MDMs) generate sequences by progressively unmasking several tokens per denoising step, but their reverse process is typically f