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arXiv:2609.19155v1 Announce Type: new Abstract: In Human-LLM dialogue, follow-up user utterances may implicitly conflict with earlier intents, leading the LLM to misinterpret user needs and generate i

arXiv:2609.20680v1 Announce Type: cross Abstract: Scalable machine learning in challenging underwater environments is strongly limited by the lack of labeled real-world training data. This data is oft

arXiv:2609.19897v1 Announce Type: new Abstract: Historical archives pose a difficult retrieval problem for retrievalaugmented generation systems: documents are OCR-degraded, heterogeneous across genre

arXiv:2609.20646v1 Announce Type: new Abstract: A vision-language-action (VLA) policy with a flow-matching action expert generates each action chunk (a short command sequence) by integrating a learned

arXiv:2503.24203v3 Announce Type: replace-cross Abstract: Traffic Engineering (TE) in large-scale networks like cloud Wide Area Networks (WANs) and Low Earth Orbit (LEO) satellite constellations is a

arXiv:2609.20465v1 Announce Type: new Abstract: We train neural networks on synthesized frames to approach the optimum Bayes estimator for dense emitter localization. The result justifies the future w

arXiv:2609.20214v1 Announce Type: cross Abstract: Early transformer fault diagnosis is challenged by nonlinear dissolved-gas interactions, overlapping fault signatures, and limited labeled data, while

arXiv:2510.09011v4 Announce Type: replace Abstract: In our deployed travel-planning service, most users give minimal inputs or free-form requests rather than the structured constraint checklists assum

arXiv:2609.20510v1 Announce Type: cross Abstract: Machine learning interatomic potentials (MLIPs) learn the mapping from atomic positions to potential energy. The forces, the negative gradient of this

arXiv:2609.19844v1 Announce Type: cross Abstract: AI-generated RTL verification plans can satisfy a provider schema yet fail at the boundary to trusted execution. We present SecTB-RTL, an auditable fr

TypeSafe’s Jev classifies, scores, and routes without generating text — up to hundreds of times cheaper than an LLM judge. What that changes for evals, confidence routing, and application architecture

arXiv:2609.19200v1 Announce Type: new Abstract: Underwater visuomotor policy learning has focused primarily on single manipulators, while bimanual imitation learning has been studied largely in air. W

arXiv:2609.19702v1 Announce Type: new Abstract: Autoregressive image generation has emerged as a paradigm for multimodal AI systems due to its compatibility with transformer-based LLM serving infrastr

arXiv:2509.20666v2 Announce Type: replace-cross Abstract: Human-AI collaboration often requires dividing complex tasks into complementary subtasks. As a task unfolds, users may want to shift which sub

arXiv:2609.20731v1 Announce Type: new Abstract: Vision-based underwater target tracking is challenged by unreliable depth measurements and unknown target motion. This paper proposes a stereo visual-se

arXiv:2609.19878v1 Announce Type: cross Abstract: Multimodal reasoning requires models to draw on information from multiple modalities throughout the reasoning process. Yet existing methods often conc

arXiv:2609.19690v1 Announce Type: cross Abstract: Daily locomotion encompasses diverse activities and frequent transitions between them, yet most exoskeleton controllers are designed for a single acti

arXiv:2609.20089v1 Announce Type: new Abstract: Self-evolving methods reduce the need for human-annotated trajectories by allowing tool-using agents to generate their own training data. Yet existing m

arXiv:2609.20808v1 Announce Type: new Abstract: Hostile rhetoric toward social groups can normalize exclusion and justify mistreatment, as well as contribute to rising polarization and political viole

arXiv:2609.20630v1 Announce Type: new Abstract: Search advertising connects user intent with commercial content and plays a critical role in platform monetization. Recent systems typically align pretr

arXiv:2609.20114v1 Announce Type: new Abstract: Collecting real-world navigation data for mobile robots typically requires platform-specific teleoperation, making large-scale collection expensive and

arXiv:2609.20582v1 Announce Type: new Abstract: Human manipulation videos provide rich motion and interaction cues for acquiring robot skills without robot demonstrations. Video generation models synt

arXiv:2609.19554v1 Announce Type: cross Abstract: Spatial intelligence requires more than describing object locations. Under incomplete observation, models must identify and acquire missing evidence,

arXiv:2609.19879v1 Announce Type: new Abstract: Question answering has advanced rapidly with large language models, but predominantly for high-resource languages, in both text and spoken settings. Spo

arXiv:2609.19681v1 Announce Type: new Abstract: Cooperative autonomous driving in the IoT-to-Edge-to-Cloud continuum requires system-level validation across vehicles, infrastructure sensors, edge-side

arXiv:2609.19813v1 Announce Type: new Abstract: Predicting the future trajectories of surrounding vehicles in autonomous driving is important for collision risk assessment and safe ego-vehicle path pl

arXiv:2609.19628v1 Announce Type: new Abstract: We present VGGT-GS SLAM, a monocular 3D Gaussian Splatting SLAM system designed for uncalibrated videos. Starting from feed-forward VGGT pose and depth

arXiv:2609.20744v1 Announce Type: new Abstract: Video diffusion models repeatedly process long spatiotemporal token sequences during denoising, making attention a major computational bottleneck. Linea

arXiv:2609.19664v1 Announce Type: new Abstract: Video agents have made substantial progress in long-video understanding. Yet effective video-agent systems require costly, time-consuming manual design

arXiv:2609.19340v1 Announce Type: new Abstract: Humanoid loco-manipulation requires adaptive whole-body coordination to seamlessly integrate locomotion and physical interaction. Despite recent advance

arXiv:2609.19158v1 Announce Type: new Abstract: Knowledge graphs are usually integrated into question answering by encoding a retrieved subgraph with a graph neural network and fusing it with the lang

arXiv:2609.20477v1 Announce Type: new Abstract: Rebar insertion is among the most repetitive and physically demanding tasks on construction sites, and a contact-rich problem at 1.4 mm clearance. The p

arXiv:2609.20303v1 Announce Type: new Abstract: Classical philosophical corpora pose three compounding challenges for language resources: they exist in several languages without parallel alignment, th

arXiv:2601.07315v5 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) have demonstrated remarkable potential in multimodal reasoning. However, they can have spatial blindness and log

arXiv:2609.20191v1 Announce Type: cross Abstract: Running vision-language navigation fully onboard an aerial robot is hard, since grounding, planning, and control must share limited compute and a sing

Wake up, people! What we should actually fear, near term, is not so much rogue superintelligence as unleashed agentic AI hacking the internet at scale: “[If you have enough money], you can now instruc

arXiv:2609.20570v1 Announce Type: new Abstract: This paper presents the kinematic and dynamic modeling, trajectory generation, and stability analysis of an 8-degree-of-freedom (DOF) biped robot walkin

arXiv:2509.24368v3 Announce Type: replace-cross Abstract: We introduce the first watermark tailored for diffusion language models (DLMs), an emergent LLM paradigm able to generate tokens in arbitrary

We are aware of a claim alleging unauthorized access to our systems. Following a thorough investigation, we have found no evidence to support this claim and can confirm that our systems have not been

We just released the first version of our Creative Writing benchmark, comparing 24 LLMs against human writers across 475 writing prompts. Creative writing is subjective, so the rankings aren't meant t

arXiv:2609.19647v1 Announce Type: cross Abstract: A neural turbulence closure defines a new boundary-value problem, R(U)=N(U)+F(U)=0, with a coupled Jacobian J(U)=N'(U)+F'(U), where N is the original

we've been diving into how Jev can help with agents @sydneyrunkle will do a deep dive on this next week - come join! Hot topic livestream: Learn about Jev A buzzy new model Jev, by @typesafeai, report

arXiv:2609.20423v1 Announce Type: new Abstract: Document parsing converts document images into structured content and requires reliable performance across diverse layouts and acquisition conditions. Y

arXiv:2609.19212v1 Announce Type: new Abstract: Systematic generalization, the ability to solve novel problems by recombining known atomic elements, is central to human intelligence but difficult to s

arXiv:2609.19182v1 Announce Type: new Abstract: Benchmarks are central to how progress in large language models (LLMs) is assessed and communicated. Yet model rankings alone reveal little about how ev

arXiv:2609.20612v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) lets a language model learn from a frozen copy of itself that sees an answer or a worked solution. Giving the teacher