Knowledge catalogue
arXiv:2604.06210v2 Announce Type: cross Abstract: As LLMs are globally deployed, aligning their cultural value orientations is critical for safety and user engagement. However, existing benchmarks fac
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Download the Tesla Robotaxi app NEWS: Tesla has updated their Robotaxi app. What's new: • New tips section, which displays how many seats are available in the car, tells you that the vehicle lights wi
arXiv:2604.03540v2 Announce Type: replace Abstract: Although multi-step generative policies achieve strong performance in robotic manipulation by modeling multimodal action distributions, they require
arXiv:2602.13669v4 Announce Type: replace Abstract: Recent multi-modal video generation models have achieved high visual quality, but their prohibitive latency and limited temporal stability hinder re
arXiv:2604.07607v1 Announce Type: cross Abstract: Robot learning increasingly depends on large and diverse data, yet robot data collection remains expensive and difficult to scale. Egocentric human da
arXiv:2604.08292v1 Announce Type: new Abstract: The autonomous operation of tracked mobile manipulators in rescue missions requires not only ensuring the reachability and safety of robot motion but al
Epic corruption, endless propaganda, security force crackdowns and false flag operations, election interference by a hostile foreign dictatorship… That’s Orbán’s Hungary today and, unless America wake
arXiv:2604.06914v1 Announce Type: new Abstract: In this paper, we study a vehicle-to-infrastructure (V2I) system where distributed base stations (BSs) acting as road-side units (RSUs) collect multimod
arXiv:2604.07378v1 Announce Type: new Abstract: Autonomous vehicles in interactive traffic environments are often limited by the scarcity of safety-critical tail events in static datasets, which biase
arXiv:2604.07392v1 Announce Type: cross Abstract: Autonomous agents operating in dynamic and safety-critical environments require decision-making frameworks that are both computationally efficient and
arXiv:2604.07577v1 Announce Type: new Abstract: Reliable monitoring of surgical instrument exchanges is essential for maintaining procedural efficiency and patient safety in the operating room. Automa
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arXiv:2601.16074v2 Announce Type: replace Abstract: Industrial Cyber-Physical Systems (CPS) are sensitive infrastructure from both safety and economics perspectives, making their reliability criticall
arXiv:2604.08476v1 Announce Type: new Abstract: Multimodal reasoning models (MRMs) trained with reinforcement learning with verifiable rewards (RLVR) show improved accuracy on visual reasoning benchma
arXiv:2603.04038v2 Announce Type: replace Abstract: Imitation learning (IL) has shown strong potential for contact-rich precision insertion tasks. However, its practical deployment is often hindered b
arXiv:2604.06916v1 Announce Type: cross Abstract: Reinforcement-Learning-based post-training has recently emerged as a promising paradigm for aligning text-to-image diffusion models with human prefere
arXiv:2604.06219v1 Announce Type: cross Abstract: Across the Global North, calls for participatory artificial intelligence (AI) to improve the responsible, safe, and ethical use of AI have increased,
arXiv:2604.07591v1 Announce Type: cross Abstract: Supervised machine learning assumes that labeled data provide accurate measurements of the concepts models are meant to learn. Yet in practice, human
arXiv:2604.06203v1 Announce Type: cross Abstract: The integration of continuous data from built-in sensors and Large Language Models (LLMs) has fueled a surge of 'Sensor-Fused LLM agents' for personal
arXiv:2604.06779v1 Announce Type: new Abstract: We introduce Fleming-Viot Diffusion (FVD), an inference-time alignment method that resolves the diversity collapse commonly observed in Sequential Monte
Garry @Kasparov63 retired from competitive chess over twenty years ago, and most or all of his tournament games are presumably publicly available - and yet I bet he still could crush any LLM that didn
arXiv:2604.06767v1 Announce Type: new Abstract: Language models operate on discrete tokens but compute in continuous vector spaces, inducing a Voronoi tessellation over the representation manifold. We
arXiv:2510.23868v4 Announce Type: replace Abstract: This paper proposes extit{Group-relative Implicit Fine-Tuning (GIFT)}, a reinforcement learning framework for aligning large language models (LLMs
arXiv:2604.08059v1 Announce Type: new Abstract: Embodied agents are increasingly expected to improve over time by updating their executable capabilities rather than rewriting the agent itself. Prior w
arXiv:2604.06215v1 Announce Type: cross Abstract: The governance of frontier general-purpose artificial intelligence has become a public-sector problem of institutional design, not merely a technical
arXiv:2604.07517v1 Announce Type: new Abstract: Building generalist robots capable of performing functional grasping in everyday, open-world environments remains a significant challenge due to the vas
arXiv:2604.07655v1 Announce Type: cross Abstract: Hard-gated safety checkers often over-refuse and misalign with a vendor's model spec; prevailing taxonomies also neglect robustness and honesty, yield
arXiv:2604.08048v1 Announce Type: new Abstract: Classifier-Free Guidance (CFG) is a widely used inference-time technique to boost the image quality of diffusion models. Yet, its reliance on text condi
arXiv:2604.07833v1 Announce Type: new Abstract: Embodied agents are evolving from passive reasoning systems into active executors that interact with tools, robots, and physical environments. Once gran
arXiv:2604.06285v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have become essential for tasks such as image synthesis, captioning, and retrieval by aligning textual and visual inform
arXiv:2604.07650v1 Announce Type: cross Abstract: The rapid growth of the large language model (LLM) ecosystem raises a critical question: are seemingly diverse models truly independent? Shared pretra
arXiv:2603.18203v3 Announce Type: replace Abstract: Current artificial intelligence systems struggle with systematic compositional reasoning: the capacity to recombine known components in novel config
arXiv:2511.03295v3 Announce Type: replace-cross Abstract: Automatic evaluation of ST systems is typically performed by comparing translation hypotheses with one or more reference translations. While e
arXiv:2601.10198v3 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning and generation, serving as the foundation for advanced persona s
I agree totally @Gary. I’ve been saying this since the ChatGPT moment in Nov 22. Thank you for saying it out loud @demishassabis. Too much time and energy being spent on mitigating the unintended cons
I rest my case: Mythos isn’t AGI. It’s not even better at biology than the last model. It’s tuned to particular things, not a giant advance towards general intelligence. Same as it ever was. @GaryMarc
arXiv:2604.07172v1 Announce Type: new Abstract: Calibration is central to reliable semantic uncertainty quantification, yet prior work has largely focused on discrimination, neglecting calibration. As
arXiv:2510.25597v2 Announce Type: replace-cross Abstract: This paper presents a decentralized control framework that incorporates social awareness into multi-agent systems with unknown dynamics to ach
arXiv:2604.07945v1 Announce Type: new Abstract: As the demand for mobile robots continues to increase, social navigation has emerged as a critical task, driving active research into deep reinforcement
Indeed, if the LLM crew would just stick to this narrative, I would have a *lot* less to say 🤷♂️ @GaryMarcus All we want is truth. Instead of overhyping LLMs, they should keep narative: -LLMs are use
arXiv:2604.08192v1 Announce Type: cross Abstract: Reliable generalization metrics are fundamental to the evaluation of machine learning models. Especially in high-stakes applications where labeled tar
arXiv:2510.07809v4 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) empower autonomous mobile agents, yet their security under realistic mobile deployment constraints remain
Just launched at @aiDotEngineer : our official AGI Pills! prescribe one (1) if your colleague is saying we are hitting a wall and/or trying to add inductive bias instead of Trusting The Model Media bt
arXiv:2604.07970v1 Announce Type: cross Abstract: Multi-Agent Path Finding (MAPF) is a fundamental coordination problem in large-scale robotic and cyber-physical systems, where multiple agents must co
arXiv:2604.06691v1 Announce Type: new Abstract: Real world deployment of multi agent reinforcement learning MARL systems is fundamentally constrained by limited compute memory and inference time. Whil
arXiv:2512.17445v2 Announce Type: replace Abstract: LangDriveCTRL is a natural-language-controllable framework for editing real-world driving videos to synthesize diverse traffic scenarios. It represe
arXiv:2604.07941v1 Announce Type: new Abstract: Post-training has become central to turning pretrained large language models (LLMs) into aligned and deployable systems. Recent progress spans supervise
arXiv:2603.10476v2 Announce Type: replace Abstract: LLM alignment has progressed in single-agent settings through paradigms such as RL with human feedback (RLHF), while recent work explores scalable a
arXiv:2604.08425v1 Announce Type: cross Abstract: When humans label subjective content, they disagree, and that disagreement is not noise. It reflects genuine differences in perspective shaped by anno
arXiv:2604.07799v1 Announce Type: new Abstract: Embodied agents are expected to operate persistently in dynamic physical environments, continuously acquiring new capabilities over time. Existing appro
arXiv:2510.13820v3 Announce Type: replace-cross Abstract: This research proposes an extensive technique for monitoring and controlling the industrial parameters using Internet of Things (IoT) technolo
arXiv:2604.06298v1 Announce Type: new Abstract: Recent alignment work on Large Language Models (LLMs) suggests preference optimization can improve reasoning by shifting probability mass toward better
arXiv:2604.08039v1 Announce Type: new Abstract: Interpreting the concepts encoded by individual neurons in deep neural networks is a crucial step towards understanding their complex decision-making pr
arXiv:2604.06571v1 Announce Type: cross Abstract: Missing-person and child-safety investigations rely on heterogeneous case documents, including structured forms, bulletin-style posters, and narrative
arXiv:2603.04300v2 Announce Type: replace Abstract: Foundation models in general promise to accelerate scientific computation by learning reusable representations across problem instances, yet constra
arXiv:2512.19253v4 Announce Type: replace-cross Abstract: We present the first empirical study of machine unlearning (MU) in hybrid quantum-classical neural networks. While MU has been extensively exp
Meta acquired Moltbook, an AI-only social network launched in January 2026 by entrepreneurs Matt Schlicht and Ben Parr, after the platform had gone viral and then faded in popularity. Moltbook is ...
arXiv:2603.22364v2 Announce Type: replace-cross Abstract: Diffusion models have achieved state-of-the-art performance in generative modeling, but their success often relies heavily on classifier-free
arXiv:2509.22981v2 Announce Type: replace Abstract: We study a class of multi-stage stochastic programs, which incorporate modeling features from Markov decision processes (MDPs). This class includes