Search: “safety”

when you think about it SpaceX has cumulatively lost a lot less than OpenAI so maybe it’s a bargain? or maybe we just shouldn’t value compan…

when you think about it SpaceX has cumulatively lost a lot less than OpenAI so maybe it’s a bargain? or maybe we just shouldn’t value companies at a trillion dollars until they actually show evidence

26 May 2026

Safety

Workflow cleanup tools for ComfyUI: Visual Fold, group folding, and node alignment

DGX agent

Visual Fold is a tool for simple visual organization of ComfyUI workflows that does not turn selected nodes into a subgraph or change workflow logic. Group folding and node alignment features enable c

safetyr-stablediffusion

26 May 2026

X-DiffVLA: X-Embodied Diffusion Action Heads for Vision-Language-Action Models

arXiv:2605.25044v1 Announce Type: new Abstract: Learning universal policies from cross-embodied data remains a fundamental challenge in robotics. Although Vision-Language-Action (VLA) models are pre-t

26 May 2026

XRPO: Pushing the limits of GRPO with Targeted Exploration and Exploitation

arXiv:2510.06672v3 Announce Type: replace Abstract: Reinforcement learning algorithms such as GRPO have driven recent advances in large language model (LLM) reasoning. While scaling the number of roll

26 May 2026

100% agree. and this is important. and it will affect you, personally.

100% agree. and this is important. and it will affect you, personally. The SpaceX IPO is the most brazen retail fleecing in modern market history. NASDAQ has REWRITTEN the index rules specifically for

4DThinker: Thinking with 4D Imagery for Dynamic Spatial Understanding

arXiv:2605.05997v2 Announce Type: replace Abstract: Dynamic spatial reasoning from monocular video is essential for bridging visual intelligence and the physical world, yet remains challenging for vis

ALIVE: Awakening LLM Reasoning via Adversarial Learning and Instructive Verbal Evaluation

arXiv:2602.05472v2 Announce Type: replace Abstract: The quest for expert-level reasoning in Large Language Models (LLMs) has been hampered by a persistent extit{reward bottleneck}: traditional reinfor

ARMS: Automatic Reward Shaping for Sparse-Reward Multi-Agent Reinforcement Learning

arXiv:2605.23562v1 Announce Type: cross Abstract: Sparse rewards are a major bottleneck in multi-agent reinforcement learning (MARL), where simultaneous learning induces non-stationarity and makes rew

As one of the first people to warn about a possible AI backlash—years ago—let me tell you this: it’s going to get much, much worse. It break…

As one of the first people to warn about a possible AI backlash—years ago—let me tell you this: it’s going to get much, much worse. It breaks my heart that AI—something I spent my whole life thinking

Assessing Predictive Models for Fairness Based on Movement Patterns

arXiv:2605.23234v1 Announce Type: new Abstract: Assessing the spatial fairness of predictive models involves establishing whether they are statistically penalizing (favoring) individuals associated wi

B-GRTO: Bootstrapped Group Relative Tool Optimization for Referring Segmentation

arXiv:2605.23500v1 Announce Type: new Abstract: Segmentation is a fundamental task in computer vision, underpinning pixel-level scene understanding and serving as a cornerstone for applications rangin

Beyond Binary Edits Robust Multimodal Knowledge Editing with Adversarial Subspace Alignment

arXiv:2605.23780v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) need efficient mechanisms to update knowledge without degrading existing capabilities. While intrinsic multimod

Beyond VLM-Based Rewards: Diffusion-Native Latent Reward Modeling

arXiv:2602.11146v2 Announce Type: replace-cross Abstract: Preference optimization for diffusion and flow-matching models relies on reward functions that are both discriminatively robust and computatio

Bridging AI and Clinical Reasoning: Abductive Explanations for Alignment on Critical Symptoms

arXiv:2602.13985v2 Announce Type: replace Abstract: Artificial intelligence (AI) has demonstrated strong potential in clinical diagnostics, often achieving accuracy comparable to or exceeding that of

CapTrack: Multifaceted Evaluation of Forgetting in LLM Post-Training

arXiv:2603.06610v2 Announce Type: replace Abstract: Large language model (LLM) post-training enhances latent skills, unlocks value alignment, improves performance, and enables domain adaptation. Unfor

Class-Dependent Hybrid Data Augmentation for Multiclass Migraine Classification under Severe Class Imbalance

arXiv:2605.23453v1 Announce Type: new Abstract: We conducted a reproducibility-oriented re-evaluation of prior migraine classification studies, correcting for data leakage and metric bias. We then int

Classical State Preparation for Variational Quantum Algorithms via Reinforcement Learning

arXiv:2605.23138v1 Announce Type: cross Abstract: Variational Quantum Algorithms (VQAs) potentially offer a pathway to practical quantum advantage, but their optimization is heavily hindered by barren

ClimateChat-300K: A Multi-Modal Facebook Dataset for Understanding Diverse Perspectives in Climate Communication

arXiv:2605.23326v1 Announce Type: new Abstract: We present ClimateChat-300K, a large-scale dataset of 299,329 public Facebook posts about climate change collected between May 2020 and May 2024 through

Coloring the Noise: Adversarial Sobolev Alignment for Faithful Image Super Resolution

arXiv:2605.23264v1 Announce Type: cross Abstract: Generative priors in Image Super-Resolution (SR) often compromise faithful restoration, we attribute this limitation to a fundamental spectral misalig

Composing People Together: Iterative Pose-Image Generation for Multi-Person Interaction Scenes

arXiv:2605.23178v1 Announce Type: new Abstract: Despite recent progress, text-to-image models still struggle to generate semantically diverse and compositionally accurate multi-person interaction scen

Contrastive Distribution Matching for Amortized Sequential Monte Carlo in Discrete Diffusion

arXiv:2605.23346v1 Announce Type: new Abstract: Discrete diffusion models have emerged as powerful frameworks for generating structured categorical data. However, efficiently sampling from reward-tilt

Controlled Personalization in Legacy Media Online Services: A Case Study in News Recommendation

arXiv:2510.09136v2 Announce Type: replace-cross Abstract: Personalized news recommendations have become a standard feature of large news aggregation services, optimizing user engagement through automa

Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning

arXiv:2605.23315v1 Announce Type: cross Abstract: Large language models trained under diverse objectives and architectures have been shown to develop increasingly similar internal representations, an

CoReVAD: A Contextual Reasoning Framework for Training-Free Video Anomaly Detection

arXiv:2605.23116v1 Announce Type: cross Abstract: Existing Video Anomaly Detection (VAD) methods typically rely on task-specific training, leading to strong domain dependency and high training costs.

Debiased Negative Mining Improves Out-of-distribution Detection with Pre-trained Vision-Language Models

arXiv:2605.23797v1 Announce Type: cross Abstract: Aiming at identifying unexpected inputs from unknown classes, out-of-distribution (OOD) detection has emerged as a pivotal approach to enhancing the r

Differences in Typological Alignment in Language Models' Treatment of Differential Argument Marking

arXiv:2602.17653v2 Announce Type: replace Abstract: Recent work has shown that language models (LMs) trained on synthetic corpora can exhibit typological preferences that resemble cross-linguistic reg

Diffusion and Flow Matching Models for Tabular Data: A Survey

arXiv:2502.17119v2 Announce Type: replace-cross Abstract: Deep generative models have made rapid progress in image, text, audio, and video generation, and are increasingly being applied to structured

Direct Dynamic Retargeting for Humanoid Imitation Learning from Videos

arXiv:2605.23762v1 Announce Type: new Abstract: Imitation Learning from monocular video demonstrations provides a scalable approach for teaching complex skills to humanoid robots. However, translating

Disentangling Interaction and Bias Effects in Opinion Dynamics of Large Language Models

arXiv:2509.06858v2 Announce Type: replace-cross Abstract: Large Language Models are increasingly used to simulate human opinion dynamics, yet the effect of genuine interaction is often obscured by sys

Dreaming Smoothly and Sample Efficiently with Gradient Penalized Latent Dynamics

arXiv:2605.23089v1 Announce Type: cross Abstract: Model-based reinforcement learning improves sample efficiency by learning a world model. However, existing latent world models such as DreamerV3 do no

Droneulator: A Portable UAV Simulator for Agricultural Workflows with RotorPy and Godot 4

arXiv:2605.23386v1 Announce Type: new Abstract: Agricultural UAV research requires simulators that integrate realistic 3D scenes, high-fidelity vehicle dynamics, and robotics middleware, while remaini

Dynamic Weight-based Temporal Aggregation for Low-light Video Enhancement Under Extreme Noise

arXiv:2510.09450v2 Announce Type: replace Abstract: Low-light video enhancement (LLVE) is challenging due to noise, low contrast, and color degradation. While learning-based methods enable fast infere

EDGE-OPD: Internalizing Privileged Context with Evidence Guided On-Policy Distillation

arXiv:2605.23493v1 Announce Type: new Abstract: On-Policy Distillation (OPD) has gained wide attraction as an LLM post-training paradigm due to its effectiveness in improving capabilities without intr

Energy per Successful Goal: Goal-Level Energy Accounting for Agentic AI Systems

arXiv:2605.22883v1 Announce Type: new Abstract: Current AI energy benchmarks measure consumption at the granularity of a single model invocation or training run. For classical single-turn workloads th

Entropy-Aware On-Policy Distillation of Language Models

arXiv:2603.07079v2 Announce Type: replace-cross Abstract: On-policy distillation is a promising approach for transferring knowledge between language models, where a student learns from dense token-lev

EquiSumm : A Gender Bias-Aware Framework for Inclusive Tweet Summarization

arXiv:2605.23412v1 Announce Type: new Abstract: While social media platforms, such as Twitter, provide a medium for large-scale opinion sharing during news events, it is manually impossible for indivi

FIRMA: FIbonacci Ring Model Aggregation for Privacy-preserving Federated Learning

arXiv:2605.22898v1 Announce Type: new Abstract: Federated learning protocols face a structural trilemma: canonical server-based aggregation~ite{mcmahan2017} creates a single point of failure and gradi

for the years it was the opposite bashing AI gets more views than it used to BECAUSE PEOPLE FIGURED OUT HOW GREEDY MOST OF THE TECH OLIGARCH…

for the years it was the opposite bashing AI gets more views than it used to BECAUSE PEOPLE FIGURED OUT HOW GREEDY MOST OF THE TECH OLIGARCHS ARE. even the Pope felt it was time to speak out. Bashing

Foundation Protocol: A Coordination Layer for Agentic Society

arXiv:2605.23218v1 Announce Type: new Abstract: Autonomous agents are moving from tools into a layer of social infrastructure: they browse, purchase, deploy software, manage systems, and increasingly

Four Simple Proprioceptive Estimators for Legged Robots

arXiv:2605.23100v1 Announce Type: new Abstract: Legged robots carry an IMU, but the inertial solution drifts because consumer-grade IMUs are noisy. However, the feet create intermittent contacts with

From Correctness to Preference: A Framework for Personalized Agentic Reinforcement Learning

arXiv:2605.23382v1 Announce Type: new Abstract: Agentic reinforcement learning (Agentic RL) has achieved strong progress in tasks with clear success signals. However, many real-world agent application

From the Patrick Boyle Channel on YouTube discussing the upcoming SpaceX IPO: Based on its filing, SpaceX has lost ~ $37 Billion over 24 yea…

From the Patrick Boyle Channel on YouTube discussing the upcoming SpaceX IPO: Based on its filing, SpaceX has lost ~ $37 Billion over 24 years. The worst performance of any company which has gone publ

Geo-Align: Video Generation Alignment via Metric Geometry Reward

arXiv:2605.23903v1 Announce Type: new Abstract: Camera-controlled video generation has achieved remarkable progress in recent years. However, existing video-to-video re-rendering methods primarily rel

Goal-Conditioned Agents that Learn Everything All at Once

arXiv:2605.23551v1 Announce Type: cross Abstract: A goal-conditioned reinforcement learning agent exploring an environment will see a wealth of information throughout a trajectory, most of which is di

🚨 Google DeepMind CEO Sir Demis Hassabis: “Today’s systems, are nowhere near [AGI]. Doesn’t matter how many Erdős problems you solve… I thi…

🚨 Google DeepMind CEO Sir Demis Hassabis: “Today’s systems, are nowhere near [AGI]. Doesn’t matter how many Erdős problems you solve… I think it’s far, far from what a true invention or someone like a

Graph Alignment Topology as an Inductive Bias for Grounding Detection

arXiv:2605.22963v1 Announce Type: cross Abstract: Large Language Models (LLMs) are optimized to produce distributionally plausible continuations rather than to explicitly verify whether generated prop

Great that so many of you have enjoyed my deconstructions of Elon, Zuckerberg, and that OpenAI dude, but this is much more important:

Great that so many of you have enjoyed my deconstructions of Elon, Zuckerberg, and that OpenAI dude, but this is much more important: ⚠️⚠️⚠️i don’t think most people understand the implications of the

How about if you change your social media name to Kekius Maximus?

Gary Marcus humorously suggests changing one's social media name to 'Kekius Maximus,' likely commenting on internet culture, meme terminology, or the absurdity of online personas. The post appears to