Knowledge catalogue
arXiv:2610.07652v1 Announce Type: cross Abstract: The ability to interact with articulated objects is essential for embodied intelligent systems, but collecting large-scale real-world demonstrations f
arXiv:2610.07121v1 Announce Type: new Abstract: Diffusion large language models dLLMs) have emerged as a promising alternative to autoregressive language models through bidirectional diffusion-based t
Some early first-hand accounts of encountering a narrow superhuman intelligence as mathematicians grapple with the hundreds of big AI proofs released by OpenAI. Problems solved in inhuman ways that ma
arXiv:2610.07499v1 Announce Type: new Abstract: Multimodal wearable systems must remain reliable when sensor streams become noisy or unavailable. Existing multimodal test-time adaptation (TTA) methods
The Information: Source: Nvidia considered a last-minute OpenRouter bid, telling its leadership it was prepared to make a generous offer, but OpenRouter didn't want to wait — This July, Nvidia caught
Wall Street Journal: Sources: Broadcom has been working to arrange more than $50B in financing for OpenAI's custom AI chip; Oracle is in talks on financing for a big chip purchase — Apollo, Blackstone
arXiv:2610.08573v1 Announce Type: new Abstract: Cooperative perception improves autonomous driving by sharing complementary observations among vehicles and roadside infrastructure for 3D object detect
arXiv:2610.08713v1 Announce Type: new Abstract: Embodied agents must reason about 3D space while the video is still arriving, answering questions as soon as they have observed enough of the scene. VLM
arXiv:2510.17826v2 Announce Type: replace-cross Abstract: Building a working mental model of a protein typically requires weeks of reading, cross-referencing crystal and predicted structures, and insp
arXiv:2610.07204v1 Announce Type: cross Abstract: Recent AI alignment work often frames alignment as a pre-deployment optimization problem: collect human feedback, learn preferences or principles, fin
arXiv:2610.07484v1 Announce Type: new Abstract: Self-supervised EEG models often reconstruct masked waveforms or predict discrete codes. We study a task-aligned alternative: masked band-power predicti
arXiv:2610.08021v1 Announce Type: new Abstract: Simulation-based inference (SBI) has become a powerful approach to Bayesian inference in complex scientific models whose likelihoods are difficult or im
arXiv:2610.07237v1 Announce Type: new Abstract: A model that learns from its own outputs inherits more than their correctness: it inherits which solutions it produces. We formulate Looped Self-Distill
arXiv:2610.08076v1 Announce Type: new Abstract: Frontier LLM agents have been shown to be capable of solving increasingly complex tasks for which humans have measurable solutions. This begs the pertin
arXiv:2610.08647v1 Announce Type: new Abstract: LLM-based agents solve complex multi-step tasks, but sequential execution incurs substantial latency. In principle, parallelizing work across multiple a
arXiv:2610.08403v1 Announce Type: new Abstract: Large Language Models (LLMs) require substantial computational resources, limiting their deployment on resource-constrained hardware. Ternary LLMs mitig
arXiv:2610.07763v1 Announce Type: new Abstract: The rapid progress of LLM-based multi-agent systems (MAS) has shown that they largely outperform single agents on coding, math, and QA tasks, where exec
arXiv:2610.07717v1 Announce Type: cross Abstract: Transformers have exhibited impressive empirical success across various domains, but their theoretical foundations remain less developed. This work co
arXiv:2610.06940v1 Announce Type: new Abstract: Continual adaptation of language models can change their output distribution on prompts learned earlier, while retaining every old prompt-answer pair ma
arXiv:2511.20718v3 Announce Type: replace-cross Abstract: Reinforcement learning (RL) algorithms such as PPO and GRPO are widely used to train large language models (LLMs) for multi-turn agentic tasks
arXiv:2610.08649v1 Announce Type: new Abstract: Video-language models are ranked by multiple-choice accuracy on frames from a uniform grid. The grid has two parameters, a rate and a phase, and benchma
arXiv:2610.07430v1 Announce Type: new Abstract: Reducing nonstationarity in a persistent time series entails deciding how much of its temporal dependence to remove. In finance, fractional differencing
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:2610.06991v1 Announce Type: new Abstract: Joint molecular phenotype prediction is complicated by small joint-positive populations and overlapping histological features across alternative molecul
arXiv:2610.07625v1 Announce Type: cross Abstract: Automated research systems increasingly run LLM agents over long horizons, but more inference does not by itself produce more progress: agents replay
arXiv:2610.06874v1 Announce Type: cross Abstract: Reinforcement-learning quadrotor controllers are usually trained under simplified wind models, yet the impact of wind-field fidelity, as opposed to ma
arXiv:2610.08652v1 Announce Type: cross Abstract: Diffusion models are increasingly used as surrogates for expensive simulators in weather prediction, molecular dynamics, and materials design. In thes
arXiv:2610.07348v1 Announce Type: cross Abstract: Training large language models (LLMs) is resource-intensive, and adapting them for diverse deployment scenarios with varying computational constraints
arXiv:2610.07814v1 Announce Type: cross Abstract: How far can stochastic gradient descent ascent (SGDA) go by tuning its timescale ratio and step sizes in nonconvex min-max games? We answer this quest
arXiv:2512.23441v2 Announce Type: replace-cross Abstract: Temporally aware image representations are crucial for capturing disease progression in 3D volumes of longitudinal medical datasets. However,
arXiv:2610.07006v1 Announce Type: new Abstract: Learning effective representations helps characterize the structure and dynamics of equity markets from financial data with a low signal-to-noise ratio.
arXiv:2610.08208v1 Announce Type: cross Abstract: We introduce STRUCTURALCOST, a self-paced reading dataset of 475 participants and 40,800 observations isolating the processing cost of long-distance s
arXiv:2610.08322v1 Announce Type: new Abstract: Selective forecasting abstains on high-risk test windows under a retained-coverage budget. Existing gates such as TEM (Brusokas et al., 2025) score each
arXiv:2610.07726v1 Announce Type: new Abstract: Videofluoroscopic Swallowing Study (VFSS) is one of the gold standard for diagnosing swallowing disorders, providing dynamic X-ray imaging of the swallo
arXiv:2610.07470v1 Announce Type: cross Abstract: Combinatorial Thompson sampling (CTS) draws independent posterior samples for every arm, so its exploration dynamics ignore any relation among arms. W
arXiv:2610.08018v1 Announce Type: new Abstract: Reliable tool use requires more than triggering a mechanism or matching a query to an API description. Before selecting a specific tool, an agent must f
arXiv:2610.07332v1 Announce Type: cross Abstract: Long-horizon LLM agents are frequently implemented using sparse mixture-of-experts (MoE) models, yet the co-design of agentic behavior and MoE structu
As the title suggests I'm currently trying to make a modal to identify which app is being used. The thing is I don't have labelled data and generating it is out of question since that is a lot of work
Never saw mimo2.6, now im doubting mistral 4 wont land either ... I feel trapped but im not sue its worth the $100 ... just few options anyone know any details behind the change? submitted by /u/stack
Artificial intelligence companies that can help even bigger companies to get paid are likely to make a fair bit of money themselves, if the example of Stuut Inc. is any indication. The company today s
Mike Wheatley / SiliconANGLE: Stuut, which uses AI agents to automate enterprise order-to-cash cycles and serves 150+ clients, raised a 52.5M Series B led by Insight, for 93M total funding — Artificia
arXiv:2610.08126v1 Announce Type: cross Abstract: Product Identification has sprung up to become one of the most challenging problems in the automation of the retail industry. With the new industry 5.
arXiv:2610.07472v1 Announce Type: new Abstract: Remotely operated vehicles (ROVs) are widely used to explore and inspect underwater environments such as caves, shipwrecks, and submerged infrastructure
arXiv:2610.08098v1 Announce Type: cross Abstract: AI agents increasingly rely on modular third-party 'skills' that are dynamically selected by skill routers to execute complex tasks. While recent stud
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:2609.33678v2 Announce Type: replace Abstract: We introduce SWE-Game, a benchmark of 247 tasks grounded in 41 executable reference Godot games spanning 13 gameplay categories in 2D and 3D. Five t
arXiv:2610.08420v1 Announce Type: new Abstract: We establish a polynomial sample complexity separation between symmetry-aware and symmetry-agnostic feature learning. We study growing-rank multi-index
arXiv:2610.08161v1 Announce Type: cross Abstract: Ambient documentation systems are rapidly gaining adoption, yet their impact on clinical note quality remains poorly characterized. We introduce MedCo
arXiv:2610.08554v1 Announce Type: cross Abstract: While HCI increasingly examines AI-safety for youth, the literature lacks a comprehensive view of what risks have been identified, how they are addres
arXiv:2610.07098v1 Announce Type: cross Abstract: Large transformer-based models increasingly depend on multi-GPU execution, which requires frequent collective communication among GPUs. Existing commu
arXiv:2512.23065v4 Announce Type: replace Abstract: The introduction of BERT established encoder-only transformer models as a foundational paradigm in natural language processing. Encoder-only models
arXiv:2610.07621v1 Announce Type: new Abstract: Robots that autonomously determine their actions from language instructions and sensory observations could perform new contact-rich manipulation tasks w
arXiv:2610.07559v1 Announce Type: new Abstract: Recent progress in tabular foundation models suggests that training on synthetic tasks can substantially improve in-context learning capabilities, with
arXiv:2610.06994v1 Announce Type: cross Abstract: Backdoor-defense leaderboards print a clean-accuracy drop and read it as removal cost. Measured on the poisoned victim alone, the drop cannot separate
arXiv:2610.07529v1 Announce Type: new Abstract: Wave-based processors promise fast, energy-efficient Fourier layers for neural operators. They are usually validated on randomly sampled devices, but us
arXiv:2610.07527v1 Announce Type: new Abstract: We introduce Task-Space Imitation Guidance for Efficient Reinforcement Learning (TIGER), a reward-construction and pretraining framework for sparse-rewa
arXiv:2610.06824v2 Announce Type: replace Abstract: We introduce TasteVal, a benchmark to evaluate the experimental research taste of frontier models. We define research taste as the ability to pick i
arXiv:2610.07096v1 Announce Type: new Abstract: Robotic haircutting requires controlled tool motion near the head while simultaneously accounting for communication, visual feedback, tool actuation, an
arXiv:2610.05437v2 Announce Type: replace Abstract: Computer-use agents need to capture procedural knowledge of how people use software. User telemetry offers a scalable source of this knowledge. Howe
arXiv:2610.06855v1 Announce Type: cross Abstract: Scalable driver identification requires embedding models that maintain discriminative performance as fleet size grows, yet existing triplet-loss formu