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DeformGen: Dynamics-Based Topology Augmentation for Deformable Manipulation Policy Learning

arXiv:2606.25939v1 Announce Type: new Abstract: Demonstration augmentation is proposed for cost-efficient data acquisition, but existing methods are fundamentally limited in deformable manipulation du

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Digital Twin-Driven Adaptive Sim-to-Real Alignment via Reinforcement Learning for Vibration-Based Bearing Health Monitoring Under Data Scarcity

DGX agent

arXiv:2606.24954v1 Announce Type: cross Abstract: Vibration-based health monitoring of rotating machinery requires reliable fault diagnosis under operational data constraints, yet condition assessment

safetyarxiv-cs-cl

25 Jun 2026

DRM: Diffusion-based Reward Model With Step-wise Guidance

arXiv:2605.25661v2 Announce Type: replace Abstract: Current mainstream methods of aligning diffusion models with human preferences typically employ VLM-based reward models. However, these reward model

Dual Agreement Consistency Learning for Semi-Supervised Fetal Ultrasound Segmentation

arXiv:2606.25254v1 Announce Type: cross Abstract: Maternal-fetal US is the primary imaging modality for monitoring fetal development, yet accurate automated segmentation remains challenging due to the

DynaMOMA: Instantaneous Prediction of Grasp Poses for Mobile Manipulation of Dynamic Objects

arXiv:2606.25295v1 Announce Type: new Abstract: Mobile manipulation is a fundamental robotics task and has advanced rapidly in recent years, enabling robots to navigate, reach, and interact with objec

Efficient Adaptive Data Acquisition via Pretrained Belief Representations

arXiv:2606.25197v1 Announce Type: new Abstract: Learning effective policies for adaptive data acquisition remains challenging: posterior-based methods rely on surrogate models and posterior approximat

Evaluation Protocols and Validation for Cameras in Indoor Healthcare Monitoring

arXiv:2606.25284v1 Announce Type: new Abstract: Camera-based monitoring systems are increasingly adopted in healthcare settings for the continuous assessment of patient movement and activities. Howeve

Event-Adaptive Motion Planning with Distilled Vision-Language Model in Safety-Critical Situations

arXiv:2606.25629v1 Announce Type: new Abstract: Robot navigation in safety-critical scenarios faces significant challenges from unforeseen semantic events, where collisions arise primarily from the un

Exclusive: Chainguard extends Repository scanning and policies to Java, Python and containers

Secure software supply chain solution provider Chainguard Inc. today expanded its Chainguard Repository product with malware scanning, policy enforcement and visibility features that now cover Java pa

safetysiliconangle

ext{DT}^2: Decision-Targeted Digital Twins

arXiv:2606.25923v1 Announce Type: new Abstract: A digital twin (DT) is a virtual model of a real-world system that can assist decision-making by simulating scenarios induced by different policies. How

FAST-LIVGO: A Degeneracy-Robust LiDAR-Inertial-Visual-GNSS Fusion Odometry

arXiv:2606.19190v2 Announce Type: replace Abstract: Robust state estimation and mapping in long-term, large-scale, and highly dynamic environments remains a key challenge in robotics. Existing LiDAR-I

Follow Your Track: Precise Skeleton Animation Controlled by 3D Trajectories

arXiv:2606.25344v1 Announce Type: new Abstract: 4D generation aims to animate 3D objects with realistic motion, holding great promise for applications. Existing methods typically decouple 3D asset gen

FORCE: Efficient VLA Reinforcement Fine-Tuning via Value-Calibrated Warm-up and Self-Distillation

arXiv:2606.26006v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are often constrained by the imitation ceiling imposed by sub-optimal data. While Reinforcement Learning (RL) fine-t

ForceBand: Learning Forceful Manipulation with sEMG

arXiv:2606.26093v1 Announce Type: new Abstract: Human demonstrations are a scalable data source for learning robot manipulation policies. However, common sources of human demonstration data, such as m

Fourier Multi-Component and Multi-Layer Neural Networks: Unlocking High-Frequency Potential

arXiv:2502.18959v4 Announce Type: replace Abstract: The architecture of a neural network and the choice of its activation function are both fundamental to its performance. Equally important is ensurin

Fox in the Henhouse: Supply-Chain Backdoor Attacks Against Reinforcement Learning

arXiv:2505.19532v2 Announce Type: replace Abstract: The current state-of-the-art backdoor attacks against Reinforcement Learning (RL) rely upon unrealistically permissive access models, that assume th

From Forecasting Leaderboards to Deployment Decisions: A Fail-Closed Certification Protocol

arXiv:2606.24996v1 Announce Type: new Abstract: Forecasting leaderboards rank models by predictive quality, but their winners are often read as deployment-ready top-1 advice. That reading can fail whe

From Uncertain to Safe: Conformal Adaptation of Diffusion Models for Safe PDE Control

arXiv:2502.02205v4 Announce Type: replace Abstract: The application of deep learning for partial differential equation (PDE)-constrained control is gaining increasing attention. However, existing meth

Fully Differentiable Neural Forced Alignment via Soft Dynamic Programming

arXiv:2606.25460v1 Announce Type: cross Abstract: Recent advances in sequence modeling have significantly improved ASR systems, bringing them close to human-level recognition accuracy and enhancing ro

G2DP: Diffusion Planning with Spatio-Temporal Grid Guidance

arXiv:2606.26017v1 Announce Type: new Abstract: In autonomous driving, diffusion-based planners have emerged as a promising paradigm for robust motion planning in dense and interactive traffic, as the

GCT-MARL: Graph-Based Contrastive Transfer for Sample-Efficient Cooperative Multi-Agent Reinforcement Learning

arXiv:2606.25073v1 Announce Type: new Abstract: In cooperative multi-agent reinforcement learning (MARL), from a deployment perspective, it is challenging and expensive to train agents from scratch fo

Generalised Medical Phrase Grounding

arXiv:2512.01085v3 Announce Type: replace-cross Abstract: Medical phrase grounding (MPG) maps textual descriptions of radiological findings to corresponding image regions. These grounded reports are e

Generative AI for Safe and Photorealistic Drone Light Shows

arXiv:2606.25458v1 Announce Type: new Abstract: Drone light shows are redefining aerial entertainment, yet their widespread adoption is bottlenecked by labor-intensive, manual animation. While generat

Geometry-Anchored Transport Framework for Exemplar-Free Class-Incremental Learning

arXiv:2606.25347v1 Announce Type: cross Abstract: Exemplar-free class-incremental learning (EFCIL) requires stable decision boundaries within a shifting feature space. While maintaining class-conditio

Grifters and many other salesman are like LLMs. They say things that aren’t always true with absolutely certainty.

Grifters and many other salesman are like LLMs. They say things that aren’t always true with absolutely certainty. Bitcoin has won. Global consensus is that $BTC is digital capital. The four-year cycl

Grok may not be the AGI that Elon promised, but it appears that the man has found his use case.

Grok may not be the AGI that Elon promised, but it appears that the man has found his use case. xAI is betting big on AI video and image generation — but the biggest driver of Grok Imagine may not be

GUI agent: Guided Exploration of User-Sensitive Screens

arXiv:2606.25705v1 Announce Type: new Abstract: LLM agents are increasingly being used to automate tasks for users within an open GUI environment. They inevitably encounter screens containing user-sen

Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty

arXiv:2606.25198v1 Announce Type: new Abstract: Autonomous AI Research promises to accelerate the scientific progress of machine learning. To realise this goal, current Large Language Model (LLM)-base

Homogeneity Bias in Open-Weight LLMs Is Robust to Decoding Hyperparameters

arXiv:2501.02211v2 Announce Type: replace-cross Abstract: Large language models (LLMs) reproduce homogeneity bias -- the tendency to portray marginalized groups as more internally similar than dominan

Imagine if i had a business that gave you 20 bills for 10 bills. As word spread, my customer base would grow. My revenue (how many $10 bil…

Imagine if i had a business that gave you 20 bills for 10 bills. As word spread, my customer base would grow. My revenue (how many $10 bills I collected) would grow. And I would continue to lose money

In the end, will Elon be best known for his efforts to mainstream electric cars, for his rockets, …. or for his efforts to mainstream AI-gen…

In the end, will Elon be best known for his efforts to mainstream electric cars, for his rockets, …. or for his efforts to mainstream AI-generated porn? xAI is betting big on AI video and image genera

It is amazing to me how little the X-verse cares about the rise of authoritarianism in the United States. Is that because most of the “peopl…

It is amazing to me how little the X-verse cares about the rise of authoritarianism in the United States. Is that because most of the “people” here are actually Russian bots? 🤔 More Soviet-style decep

It would be very useful to understand more about the government safety concerns associated with frontier AI releases so we could (a) know wh…

It would be very useful to understand more about the government safety concerns associated with frontier AI releases so we could (a) know what risks everyone will face if/when open source reaches Myth

safetyethan-mollick--x

Learning Action Priors for Cross-embodiment Robot Manipulation

arXiv:2606.26095v1 Announce Type: cross Abstract: Most Vision-Language-Action (VLA) models build on a Vision-Language Model (VLM) backbone by attaching an action module and optimizing the full policy

Learning Asynchronous Upper-body Task-space Trajectory Tracking Policy for Humanoid Robots

arXiv:2606.25706v1 Announce Type: new Abstract: High-level humanoid planners often output sparse task-space, low-rate trajectories, whereas whole-body controllers run at high frequency. This creates t

Learning Optimization Proxies for Sequential Contextual Stochastic Programs: An Order Fulfillment Application

arXiv:2606.25362v1 Announce Type: cross Abstract: Sequential contextual stochastic programs model real-time decision systems in which each time epoch commits to an action under uncertainty whose conse

Learning Robot Visual Navigation in Crowds via Intention-Aware Scene Representations

arXiv:2606.26047v1 Announce Type: new Abstract: Robot crowd navigation requires the ability to infer human intentions while accounting for the structural constraints of the environment. Currently, dee

Learning Subset-Shared Invariances for Domain Generalization with Mixture-of-Experts

arXiv:2606.25665v1 Announce Type: new Abstract: Domain generalization (DG) aims to learn a model from one or more source domains that generalizes to an unseen target domain without accessing target da

Learning with a Single Rollout via Monte Carlo Pass@k Critic

arXiv:2606.25451v1 Announce Type: new Abstract: Estimating token-level advantages in reinforcement learning (RL) for language models remains challenging because scaling up episodic experience collecti

Lightweight PCGAE-Net: Parallel CrossGate Attention and Bottleneck AutoEncoder for Efficient 5G Channel Prediction

arXiv:2606.25401v1 Announce Type: cross Abstract: Accurate channel state information (CSI) prediction is essential for proactive beamforming and resource management in 5G massive MIMO systems, yet the

LLM-Based Scientific Peer Review: Methods, Benchmarks, and Reliability Challenges

arXiv:2606.25057v1 Announce Type: new Abstract: The rapid growth of scientific submissions has pushed traditional peer review toward its scalability limits, motivating the exploration of large languag

Long-Term Simulation Exposes Cognitive-Developmental Risks in AI Companions

arXiv:2606.25396v1 Announce Type: new Abstract: AI companions powered by large language models increasingly interact with cognition-developing users, including children and adolescents, creating risks

Looks like OpenAI’s IPO will be delayed until 2027. • might be a sign that their finances don’t look compelling yet. • gives Anthropic time …

Looks like OpenAI’s IPO will be delayed until 2027. • might be a sign that their finances don’t look compelling yet. • gives Anthropic time to go first If they can bump up the valuation by $999.3 bill

love that one of my readers made her own, explicit set of public predictions. 🙏

love that one of my readers made her own, explicit set of public predictions. 🙏 I want to post my predictions for 2ish years horizon. AI stock bubble collapses due to fundamentals not working out with

Low-Complexity Policy Tessellations in Structured Markov Decision Processes

arXiv:2606.25593v1 Announce Type: new Abstract: We study optimal-policy geometry in structured Markov decision processes. While approximate dynamic programming and reinforcement learning typically app

Low Variance Trust Region Optimization with Independent Actors and Sequential Updates in Cooperative Multi-agent Reinforcement Learning

arXiv:2606.25526v1 Announce Type: new Abstract: Cooperative multi-agent reinforcement learning assumes each agent shares the same reward function and can be trained effectively using the Trust Region

MAPL: Multi-Objective Preference Learning for Robot Locomotion

arXiv:2606.25398v1 Announce Type: new Abstract: Reward design remains a major bottleneck in reinforcement learning for robot locomotion, where successful policies often depend on carefully tuned, task

MedGuards: Multi-Agent System for Reliable Medical Error Detection and Correction

arXiv:2606.25651v1 Announce Type: new Abstract: As Large Language Models (LLMs) are increasingly deployed in healthcare settings, accurate error detection and correction in generated or existing text