Knowledge catalogue
arXiv:2604.07672v1 Announce Type: new Abstract: This paper presents an empirical study of reset-free reinforcement learning (RL) for real-world agile driving, in which a physical 1/10-scale vehicle le
arXiv:2604.07644v1 Announce Type: new Abstract: We present GPU-SLS, a GPU-parallelized framework for safe, robust nonlinear model predictive control (MPC) that scales to high-dimensional uncertain rob
arXiv:2604.06247v1 Announce Type: cross Abstract: Large Language Models (LLMs) and Vision-Language Models (VLMs) remain highly vulnerable to textual and visual jailbreaks, as well as prompt injections
arXiv:2604.08501v1 Announce Type: cross Abstract: Science currently offers two options for quality assurance, both inadequate. Journal gatekeeping claims to verify both integrity and contribution, but
arXiv:2604.08243v1 Announce Type: new Abstract: Although Large Language Models (LLMs) demonstrate remarkable reasoning capabilities, inherent social biases often cascade throughout the Chain-of-Though
arXiv:2604.07054v2 Announce Type: replace Abstract: Sales dialogues require multi-turn, goal-directed persuasion under asymmetric incentives, which makes them a challenging setting for large language
arXiv:2604.06482v1 Announce Type: cross Abstract: Time-resolved volumetric MR imaging that reconstructs a 3D MRI within sub-seconds to resolve deformable motion is essential for motion-adaptive radiot
arXiv:2603.11394v2 Announce Type: replace Abstract: Patients and clinicians are increasingly using chatbots powered by large language models (LLMs) for healthcare inquiries. While state-of-the-art LLM
arXiv:2604.07100v1 Announce Type: cross Abstract: Empathetic dialogue requires not only recognizing a user's emotional state but also making strategy-aware, context-sensitive decisions throughout resp
arXiv:2604.08167v1 Announce Type: new Abstract: Medical image segmentation traditionally relies on fully supervised 3D architectures that demand a large amount of dense, voxel-level annotations from c
arXiv:2604.06420v2 Announce Type: cross Abstract: In recommender systems, collecting, storing, and processing large-scale interaction data is increasingly costly in terms of time, energy, and computat
arXiv:2604.07349v1 Announce Type: cross Abstract: Exact relevance certification asks which coordinates are necessary to determine the optimal action in a coordinate-structured decision problem. The tr
arXiv:2505.22976v2 Announce Type: replace-cross Abstract: The ability to simulate the world in a spatially consistent manner is a crucial requirements for effective world models. Such a model enables
arXiv:2604.06831v1 Announce Type: cross Abstract: Current LLM-based services typically require users to submit raw text regardless of its sensitivity. While intuitive, such practice introduces substan
arXiv:2604.06662v1 Announce Type: cross Abstract: Generated contents have raised serious concerns about copyright protection, image provenance, and credit attribution. A potential solution for these p
arXiv:2604.06274v1 Announce Type: cross Abstract: In recent years, the pace of development of information technology in various areas has increased drastically, forcing cybersecurity specialists to co
arXiv:2604.08156v1 Announce Type: new Abstract: Rhyme is deceptively intuitive: what is or is not a rhyme is constructed historically, scholars struggle with rhyme classification, and people disagree
arXiv:2509.08016v2 Announce Type: replace Abstract: Video Large Language Models (VideoLLMs) face a critical bottleneck: increasing the number of input frames to capture fine-grained temporal detail le
arXiv:2604.08212v1 Announce Type: new Abstract: General-purpose vision-language models demonstrate strong performance in everyday domains but struggle with specialized technical fields requiring preci
arXiv:2604.06440v1 Announce Type: cross Abstract: Visual prompting (VP) has emerged as a popular method to repurpose pretrained vision models for adaptation to downstream tasks. Unlike conventional mo
arXiv:2603.18474v2 Announce Type: replace Abstract: Precise behavioral control of large language models (LLMs) is critical for complex applications. However, existing methods often incur high training
arXiv:2604.06177v1 Announce Type: cross Abstract: Specialized web tasks in finance, biomedicine, and pharmaceuticals remain challenging due to missing domain priors: queries drift, evidence is noisy,
Leaked code strings discovered on April 7, 2026, by dataminer Gabe Follower in a Steam VR Beta update reveal references to an internal Valve AI system called 'SteamGPT,' which appears designed to ...
arXiv:2602.22220v2 Announce Type: replace-cross Abstract: Quotation recommendation aims to enrich writing by suggesting quotes that complement a given context, yet existing systems mostly optimize sur
Yet another illustration of why LLMs aren’t even close to being AGI. The world’s best LLMs are still terrible at poker. We put each model into a 200bb heads-up NLHE match against GTO Wizard AI. The be
Application security posture management company Apiiro Ltd. today announced the launch of a new command-line interface designed to bring application security directly into artificial intelligence-driv
The specific tweet from @0xSero is not directly accessible, and the search results don't surface the exact model or event being referenced in that post. However, based on the context clues in the t...
The referenced tweet (from @himanshustwts) is not publicly accessible without a login, so its exact content cannot be retrieved. However, based on contextual search results, this post appears to be...
Enterprises are rapidly moving AI workloads from experimentation to production on Google Kubernetes Engine (GKE), using its scalability to serve powerful inference endpoints. However, as these models
The DAIR.AI post references a Claude Code Cheat Sheet consolidating key commands, shortcuts, and best practices for Anthropic's terminal-based agentic coding tool. Claude Code is Anthropic's AI-po...
Tesla V14.3 self-driving review. The point releases will bring polish. V15 will far exceed human levels of safety, even in completely unsupervised and complex situations. 600 miles in with FSD v14.3 a
Anthropic announced it has grown its ARR from $19B to $30B in just one month, coinciding with the formal unveiling of Claude Mythos Preview — described in leaked company documents as 'by far the m...
I ran five coding tasks against nine models on one RX 9060 XT (16 GB). Each run gets a single spec file in an empty directory and has to produce solution.py and test_solution.py, run its own tests, an
Great paper from NVIDIA sharing an open midtraining recipe for agentic coding. NVIDIA kept SFT identical and added one midtraining stage. SWE-bench Multilingual went from 55.8 to 62.8 on Nemotron 3.5
European 78B A3.4B model is now supported by llama.cpp, I am waiting for some GGUFs https://huggingface.co/Aleph-Alpha/Kolibri-1 Kolibri is Aleph Alpha's mixture-of-experts (MoE) reasoning model, with
Reasoning From Scratch round 8, the finale! This last lecture in the series covers distillation as an efficient alternative to the previous reinforcement learning training runs. (Planning to take a br
arXiv:2603.13049v3 Announce Type: replace Abstract: Global numerical weather prediction (NWP) and artificial intelligence (AI) models often underestimate tropical cyclone (TC) intensity, partly becaus
arXiv:2610.21353v1 Announce Type: new Abstract: Accurate localization is critical for a wide range of applications, including navigation, augmented reality, safety management, and healthcare. However,
arXiv:2603.25370v2 Announce Type: replace-cross Abstract: Probabilistic forecasts provide a principled representation of forecast uncertainty through predictive distributions. Directly propagating pre
arXiv:2610.21238v1 Announce Type: new Abstract: A few well-annotated datasets for land-cover semantic segmentation have recently been introduced to advance the field of earth observation technologies.
arXiv:2610.20630v1 Announce Type: new Abstract: The development of Financial Natural Language Processing (NLP) systems for Brazilian Portuguese is hindered by the scarcity of domain-specific datasets.
arXiv:2610.20921v1 Announce Type: new Abstract: Most debate about releasing capable AI systems treats the choice as binary: keep the model behind an API, or publish the weights. That framing runs toge
arXiv:2610.21323v1 Announce Type: new Abstract: Most vision-language models (VLMs) treat the vision encoder as a static feature extractor: it encodes an image once, independently of the question, and
arXiv:2610.21177v1 Announce Type: new Abstract: Task completion alone does not determine whether a stateful agent satisfied its obligations, and a recorded judgment does not guarantee that its support
arXiv:2508.02276v3 Announce Type: replace-cross Abstract: Autonomous agents, from virtual laboratories to biological data-analysis agents and co-scientists, have begun to turn scientific goals into hy
arXiv:2512.02004v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) encode factual knowledge within hidden parametric spaces that are difficult to inspect or control. While Sparse A
arXiv:2610.21211v1 Announce Type: new Abstract: Proactive robots should anticipate user needs and provide assistance before being explicitly asked. A straightforward approach is to infer human intenti
The tweet from @NousResearch links to a Windows Central article written by Zac Bowden that provides an in‑depth review and benchmark analysis of Nvidia’s RTX Spark. Posted on Oct 16, 2026, the review
arXiv:2610.21882v1 Announce Type: cross Abstract: Embodied spatial intelligence requires more than visual recognition: models must localize entities, reason about their relations, and express this kno
arXiv:2610.21164v1 Announce Type: new Abstract: Dementia severely impairs communication abilities and turns everyday conversations into challenging experiences. Individuals affected by dementia freque
arXiv:2610.21218v1 Announce Type: new Abstract: Agentic large language models have been documented to lose reasoning capability when placed inside a harness, the software that mediates their observati
arXiv:2610.21060v1 Announce Type: cross Abstract: To address sparse terminal rewards in LLM arithmetic reasoning, we propose a Bellman-consistent trajectory RL method. Our framework introduces Traject
arXiv:2610.21760v1 Announce Type: new Abstract: As image generation models become increasingly capable of producing highly realistic content, traditional forensic techniques are struggling to keep up.
arXiv:2610.21403v1 Announce Type: new Abstract: Distribution shifts pose a fundamental challenge to robust multimodal learning. Existing methods typically promote invariance by suppressing environment
arXiv:2610.21184v1 Announce Type: new Abstract: Multi-hop retrieval-augmented generation (RAG) requires an agent to retrieve evidence for a sequence of dependent sub-questions. When a wrong answer lac
arXiv:2610.20794v1 Announce Type: new Abstract: Recent reinforcement learning approaches have improved visual text generation, yet generated images still suffer from incorrect wording and malformed gl
arXiv:2610.21383v1 Announce Type: new Abstract: Block Influence (BI) ranks Transformer blocks for depth pruning from their input-output cosine change, but the ranking depends on the calibration distri
arXiv:2610.21294v1 Announce Type: new Abstract: Transformer-based language models have shown strong capabilities across many tasks and domains. However, prior work shows that, for a given task, not al
arXiv:2610.21006v1 Announce Type: new Abstract: To use language models to help us make decisions we would like to understand the rationale behind the language model's outputs. In principle, the langua
arXiv:2511.16221v2 Announce Type: replace-cross Abstract: Despite their advanced reasoning capabilities, state-of-the-art Multimodal Large Language Models (MLLMs) still lack a core component of human