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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

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

DGX agent

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

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25 May 2026

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.

👇@davidSacks raises some interesting points here, which deserve an answer, but arguably gets the solution exactly backwards. Are we not now…

👇@davidSacks raises some interesting points here, which deserve an answer, but arguably gets the solution exactly backwards. Are we not now already leaving unelected private companies precisely the ab

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

Empowering 9-1-1 Calltaking Training with Generative AI: Experiences and Lessons Learned

arXiv:2602.13241v2 Announce Type: replace-cross Abstract: Emergency call-takers form the first operational link in public safety response, handling over 240 million calls annually while facing a susta

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

Fast-dDrive: Efficient Block-Diffusion VLM for Autonomous Driving

arXiv:2605.23163v1 Announce Type: new Abstract: End-to-end autonomous driving via Vision-Language-Action (VLA) models demands a precarious balance between high-fidelity trajectory planning and efficie

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

General Hazard Detection

arXiv:2605.23304v1 Announce Type: new Abstract: Hazard, as an abstract concept, is typically defined through cognitive-level logical reasoning rather than concrete examples. In contrast, existing haza

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

Graph-based Complexity Forecasts in UK En Route Airspace Using Relevant Aircraft Interactions

arXiv:2605.23696v1 Announce Type: new Abstract: Effectively managing Air Traffic Control Officer (ATCO) workload is crucial in maintaining operational safety. Group supervisors use tools that estimate

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

Human-in-the-Loop Multi-Agent Ventilator Decision Support with Contextual Bandit Preference Learning

arXiv:2605.23320v1 Announce Type: new Abstract: Ventilator decision support requires sequential decisions that track evolving physiology and disease trajectories while respecting safety boundaries and

If enough other companies report the same, the bubble pops. 🫧

Gary Marcus comments on how widespread reporting of similar issues or problems across multiple companies can lead to a collapse of confidence or a 'bubble pop' in a particular sector or narrative. The

If you live in the UK, and care about the risk from superintelligence, please read below!

If you live in the UK, and care about the risk from superintelligence, please read below! URGENT: The UK Parliament just selected 20 MPs to introduce a bill of their choosing. This is an unprecedented

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Information Access of the Oppressed: Freirean Design for Emancipatory Information Access

arXiv:2601.09600v3 Announce Type: replace-cross Abstract: Online information access (IA) platforms are targets of authoritarian capture. We explore the question of how to safeguard our platforms and e

Infra-Bayesian Reinforcement Learning Agents Outperform Classical RL For Worst-Case Robustness

arXiv:2605.23146v1 Announce Type: cross Abstract: Classical reinforcement learning assumes the agent interacts with a fixed environment whose behavior does not depend on the agent's policy. This assum

Instrumentation for Imitation Learning: Enhancing Training Datasets for Clothes Hanger Insertion

arXiv:2605.23847v1 Announce Type: new Abstract: Large behaviour models have transformed the field of robotic manipulation, but prohibitive data requirements have thus far prevented a revolution simila

IntentScore: Intent-Conditioned Action Evaluation for Computer-Use Agents

arXiv:2604.05157v2 Announce Type: replace Abstract: Computer-Use Agents (CUAs) leverage large language models to execute GUI operations on desktop environments, yet they generate actions without evalu

interesting to listen to this years later. what held up? what changed?

interesting to listen to this years later. what held up? what changed? I had a podcast where I was fortunate to have amazing guests. This was just as GPT 3 came out. Despite LLMs exceeding so many exp

it’s great! you can pay for the infrastructure that will eventually take your jobs! and if it fails and the bubble bursts? you can bail the …

it’s great! you can pay for the infrastructure that will eventually take your jobs! and if it fails and the bubble bursts? you can bail the hyperscalers out, and watch your pension fund die. The CEO o

I've yet to see, or hear of a company that is winning against its competition, because said company is spending more on AI tools, or using i…

I've yet to see, or hear of a company that is winning against its competition, because said company is spending more on AI tools, or using it better than the competition. Ways I see companies win: - b

Learning Kernel-Based MDPs from Episodic Preferential Feedback

arXiv:2605.23650v1 Announce Type: cross Abstract: Human feedback often arrives as preferences rather than calibrated numeric rewards, motivating reinforcement learning from preferential feedback, also

“Like nuclear energy, AI must be at the service of all and of the common good. Decisions about technology must never be separated from consc…

“Like nuclear energy, AI must be at the service of all and of the common good. Decisions about technology must never be separated from conscience and responsibility.” I agree with this sentiment by @P

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MaMa: A Game-Theoretic Approach for Designing Safe Agentic Systems

arXiv:2602.04431v2 Announce Type: replace Abstract: LLM-based multi-agent systems have demonstrated impressive capabilities, but they also introduce significant safety risks when individual agents fai