Knowledge catalogue
arXiv:2610.04536v1 Announce Type: new Abstract: Underwater manipulation couples visual decisions, contact forces and a thruster-controlled floating base. We introduce WasserMan, to our knowledge the f
arXiv:2610.04151v1 Announce Type: new Abstract: Content-provenance standards such as C2PA let a platform recover a stripped manifest through a soft binding: an invisible watermark read from the conten
A while ago, I posted here getting OSS-120B and GLM-4.6 playing full games of Civilization V. Since then, models have moved pretty far, and we wanted a better understanding about models' capabilities
arXiv:2610.03278v1 Announce Type: new Abstract: As dexterous hands proliferate, collecting data and training policies separately for every morphology becomes increasingly impractical. Scalable cross-e
arXiv:2610.02298v1 Announce Type: cross Abstract: 3D editing methods are usually tested on a single edit, yet an asset is built through a long sequence of revisions, each of which must implement the r
arXiv:2610.02608v1 Announce Type: new Abstract: Time series forecasting (TSF) increasingly drives decisions in transportation, energy, finance, healthcare, and infrastructure, yet current evaluation r
arXiv:2610.00542v1 Announce Type: new Abstract: Continual imitation learning evaluates whether a robot can learn new knowledge without forgetting previously learned skills. However, retaining task per
arXiv:2610.00523v1 Announce Type: new Abstract: Conformal prediction guarantees marginal coverage, but a single calibration threshold can still spread that coverage unevenly, over-covering easy region
arXiv:2610.00713v1 Announce Type: new Abstract: When a graph neural network (GNN) explainer produces an unexpected attribution on a molecule, the attribution alone cannot reveal whether the explainer
arXiv:2609.39058v1 Announce Type: cross Abstract: Reconfigurable Intelligent Surfaces (RIS) are emerging as a key technology for programmable wireless environments in the beyond the fifth generation (
arXiv:2505.14717v2 Announce Type: replace-cross Abstract: Scientific machine learning uses simulation data to train surrogate models for fast physical-field prediction across geometries. Local shape e
arXiv:2609.38886v1 Announce Type: new Abstract: Recent advances in robot learning have enabled manipulation policies to perform increasingly diverse tasks and generalize across environments. However,
arXiv:2609.39203v1 Announce Type: new Abstract: Accurate velocity measurement is a fundamental requirement for autonomous surface and underwater vehicles. Commonly, velocity is provided by a Doppler v
Hello everyone. I've recently ran some experiments comparing DDR4/PCIe4 and DDR5/PCIe5 for AI workstations on a pre-training run, and would like to hear yours thoughts. First of all, and as a summary
arXiv:2609.39146v1 Announce Type: new Abstract: Multi-agent debate (MAD) can improve large language model (LLM) reasoning by allowing multiple agents to exchange and critique their answers to the same
arXiv:2609.39437v1 Announce Type: new Abstract: Large language models (LLMs) encode substantial latent geographic knowledge, yet they reason poorly over space and are unreliable when queried from coor
arXiv:2609.38867v1 Announce Type: new Abstract: Large language model (LLM) computer-use agents are typically evaluated with clean written instructions, despite speech being an increasingly popular int
arXiv:2609.37559v1 Announce Type: new Abstract: To serve as real-world personal assistants, streaming video models need persistent memory that retains past experiences for later use. Yet existing stre
arXiv:2609.36777v1 Announce Type: new Abstract: Frontier coding agents can now write and execute code that authors 3D environments, but whether they reliably understand 3D structure and precisely cont
arXiv:2609.34790v2 Announce Type: replace-cross Abstract: LLM agents operate in persistent collaborative environments involving multiple users, communities, memories, files, and tools. Community bound
arXiv:2609.35823v1 Announce Type: new Abstract: Vision-language models (VLMs) have made substantial progress in autonomous driving, but their success has primarily been studied in ego-centric scenes.
arXiv:2609.36970v1 Announce Type: new Abstract: The Rashomon effect describes the existence of multiple near-optimal models that achieve comparable performance while offering fundamentally different e
arXiv:2609.38065v1 Announce Type: cross Abstract: Training agents to follow arbitrary instructions is an important goal of multi-task reinforcement learning (RL). Linear temporal logic (LTL) provides
arXiv:2609.37003v1 Announce Type: new Abstract: Vessel perception from space is crucial for a wide range of maritime applications, from traffic monitoring to environmental protection. However, most ex
arXiv:2609.31756v1 Announce Type: new Abstract: Does high image fidelity imply readable screen content in 3D Gaussian Splatting (3DGS)? We introduce 3DGS-SC, a controlled static screen-content dataset
arXiv:2609.32527v1 Announce Type: cross Abstract: Predicting cellular responses to genetic perturbations helps prioritize experiments in single-cell genomics, where exhaustive measurement is infeasibl
arXiv:2609.32740v1 Announce Type: new Abstract: Intraoperative anesthesia requires systems to interpret evolving multimodal evidence, recommend timely management, and revise decisions as patient state
arXiv:2609.34047v1 Announce Type: new Abstract: Multimodal models increasingly interpret visual environments, but their ability to recognize the same building across photographs, floor plans, elevatio
arXiv:2609.34143v1 Announce Type: new Abstract: Existing 3D industrial anomaly detection mainly targets local geometric deviations. In contrast, many industrial anomalies violate object-level design o
arXiv:2609.31792v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models perform strongly on manipulation tasks, their responses to invalid task premises remain underexplored. Exist
arXiv:2609.35645v1 Announce Type: cross Abstract: Code-switching (CS), a seamless alternation between languages within a single utterance, remains a critical challenge in automatic speech recognition
arXiv:2609.31709v1 Announce Type: new Abstract: Cross-dataset transfer in rice leaf disease classification remains a significant challenge, with models trained on one image collection performing subst
arXiv:2609.31870v1 Announce Type: new Abstract: Consistently profitable trading is difficult because equity markets are noisy, non-stationary, and only partially predictable from historical data. We b
arXiv:2609.35269v1 Announce Type: cross Abstract: The rising number of concept unlearning techniques for text-to-image (T2I) diffusion models has produced a fragmented evaluation landscape. Methods ar
arXiv:2609.35226v1 Announce Type: new Abstract: Early detection of oral cancer via photographic imaging presents a promising avenue for large-scale oral cavity screening. However, the development of r
arXiv:2609.34024v1 Announce Type: cross Abstract: Jev is a non-generative 'System One' model that assigns probabilities to predefined answer options and cannot answer outside them. Its accuracy and ca
arXiv:2609.35335v1 Announce Type: new Abstract: Machine learning task type identification is essential for constructing valid ML pipelines, yet in practice it is typically specified manually. We inves
arXiv:2609.32313v1 Announce Type: new Abstract: Memory lets an embodied agent reuse past experience, yet retaining useful information does not ensure that the agent can apply it when conditions change
arXiv:2607.10490v2 Announce Type: replace-cross Abstract: Tool-using large language model (LLM) agents are attractive for network operations, but tickets, alerts, logs, runbooks, and ChatOps messages
arXiv:2609.31670v1 Announce Type: new Abstract: Iterative and generative denoisers are increasingly used under the assumption that multi-step refinement outperforms a single regression pass. We show t
arXiv:2609.35052v1 Announce Type: new Abstract: Video world models must preserve the visual state of the world over time, but existing evaluation protocols often rely on generated histories, video ref
arXiv:2609.34843v1 Announce Type: new Abstract: Audio-video generation using heterogeneous multimodal references has emerged as a new challenge, requiring both compositional control over generation an
arXiv:2609.32863v1 Announce Type: new Abstract: Vehicle-to-Vehicle (V2V) cooperative perception enhances autonomous driving by enabling vehicles to share information beyond their direct line of sight.
arXiv:2609.35035v1 Announce Type: new Abstract: The integration of artificial intelligence into computer-aided design frameworks has sparked a shift in the design of analog integrated circuits (ICs),
arXiv:2609.33354v1 Announce Type: new Abstract: Sign data collection is costly, and teleoperation scales poorly, motivating reuse of large video corpora. Humanoid signing requires converting video-der
arXiv:2609.33359v1 Announce Type: new Abstract: Geometric view synthesis can expand a single wine-label photograph into a training set, but its value with pretrained image encoders is unclear. We stud
arXiv:2609.33180v1 Announce Type: cross Abstract: As recursive self-improvement (RSI) rapidly advances, reliable evaluation becomes critical for guiding adaptive search. RSI typically relies on finite
arXiv:2609.30813v1 Announce Type: new Abstract: Evaluating claim admission in shared agent memory is challenging because repeated claims may be mistaken for independent evidence. An agent may copy or
arXiv:2609.30030v1 Announce Type: new Abstract: A synthetic survey can reproduce the average answer while misrepresenting how people differ, how their answers relate to one another, or how they respon
arXiv:2609.29559v1 Announce Type: new Abstract: Arabic-Russian machine translation (MT) remains under-explored due to the rich morphology of Arabic and low lexical overlap between the two languages. W
arXiv:2609.28673v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as argumentative agents in persuasive dialogues, necessitating rigorous evaluation of their debat
arXiv:2609.29479v1 Announce Type: new Abstract: Prospective clinical actions, the follow-ups, orders, referrals, and instructions that deter-mine what happens to a patient next, are annotated today in
arXiv:2609.29101v1 Announce Type: new Abstract: Medical Named Entity Recognition (NER) for low-resource languages remains a challenging task due to high linguistic variability and a scarcity of domain
arXiv:2609.27208v1 Announce Type: new Abstract: Spatial transcriptomics (ST) measures gene expression in tissue context, but dense capture grids can be costly and may repeatedly sample morphologically
arXiv:2609.28283v1 Announce Type: new Abstract: Several foundation models dedicated to hyperspectral images have recently been made available. These models are trained on large unlabeled datasets and
arXiv:2609.28090v1 Announce Type: cross Abstract: Backtest auditing is a calibration problem: high flaw recall is not useful when the model falsely flags matched clean strategies. We build a 96-item p
arXiv:2609.28236v1 Announce Type: new Abstract: Long-horizon embodied interaction requires agents to retain and continually update information about the environment as they observe, act, and encounter
arXiv:2609.28149v1 Announce Type: cross Abstract: Studies of machine-learning-based power system protection are difficult to compare because task definitions, measurement access, data partitions, metr
Google LLC today made two new text-to-speech models, Gemini 3.8 Flash TTS and Gemini 3.8 Flash-Lite TTS, available through its cloud platform. The algorithms have highly similar application programmin
MLPerf Training v6.1 adds an agentic reinforcement-learning workload that measures how quickly systems can teach a 397-billion-parameter language model to repair real software projects. The post MLPer