Robotics & Embodied AI

Physical AI, robots, and autonomous systems

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Llms

An attack class that passes every current LLM filter - no payload, no injection signature, no log trace

https://shapingrooms.com/research I published a paper today on something I've been calling postural manipulation. The short version: ordi...

Reddit - Artificial Intelligence · 1 min ·
Llms

[R] An attack class that passes every current LLM filter - no payload, no injection signature, no log trace

https://shapingrooms.com/research I've been documenting what I'm calling postural manipulation: a specific class of language that install...

Reddit - Machine Learning · 1 min ·
[2601.07855] RoAD Benchmark: How LiDAR Models Fail under Coupled Domain Shifts and Label Evolution
Machine Learning

[2601.07855] RoAD Benchmark: How LiDAR Models Fail under Coupled Domain Shifts and Label Evolution

Abstract page for arXiv paper 2601.07855: RoAD Benchmark: How LiDAR Models Fail under Coupled Domain Shifts and Label Evolution

arXiv - AI · 3 min ·

All Content

[2602.20813] Pressure Reveals Character: Behavioural Alignment Evaluation at Depth
Llms

[2602.20813] Pressure Reveals Character: Behavioural Alignment Evaluation at Depth

This paper presents a novel evaluation framework for assessing the alignment of language models under realistic pressure, revealing behav...

arXiv - AI · 3 min ·
[2602.20687] How Foundational Skills Influence VLM-based Embodied Agents:A Native Perspective
Llms

[2602.20687] How Foundational Skills Influence VLM-based Embodied Agents:A Native Perspective

This article discusses the limitations of current benchmarks for vision-language model (VLM)-driven embodied agents and introduces Native...

arXiv - AI · 4 min ·
[2602.20659] Recursive Belief Vision Language Model
Llms

[2602.20659] Recursive Belief Vision Language Model

The Recursive Belief Vision Language Model (RB-VLA) addresses limitations in current vision-language-action models by introducing a belie...

arXiv - AI · 4 min ·
Just pull a string to turn these tile patterns into useful 3D structures | MIT Technology Review
Robotics

Just pull a string to turn these tile patterns into useful 3D structures | MIT Technology Review

MIT researchers have developed a method to create 3D structures from flat tiles using a single string pull, inspired by kirigami, with ap...

MIT Technology Review · 4 min ·
Vine-inspired robot fingers can reach out and grab someone | MIT Technology Review
Robotics

Vine-inspired robot fingers can reach out and grab someone | MIT Technology Review

MIT and Stanford engineers have developed a vine-inspired robotic gripper that can gently lift and manipulate objects, with potential app...

MIT Technology Review - AI · 4 min ·
A boost for manufacturing | MIT Technology Review
Robotics

A boost for manufacturing | MIT Technology Review

Suzanne Berger, co-director of MIT's Initiative for New Manufacturing, advocates for revitalizing US manufacturing through innovation and...

MIT Technology Review · 17 min ·
[2601.16449] Emotion-LLaMAv2 and MMEVerse: A New Framework and Benchmark for Multimodal Emotion Understanding
Llms

[2601.16449] Emotion-LLaMAv2 and MMEVerse: A New Framework and Benchmark for Multimodal Emotion Understanding

The paper introduces Emotion-LLaMAv2 and MMEVerse, a new framework and benchmark aimed at enhancing multimodal emotion understanding thro...

arXiv - AI · 4 min ·
[2512.16167] Ev-Trust: An Evolutionary Stable Trust Mechanism for Decentralized LLM-Based Multi-Agent Service Economies
Llms

[2512.16167] Ev-Trust: An Evolutionary Stable Trust Mechanism for Decentralized LLM-Based Multi-Agent Service Economies

The paper presents Ev-Trust, an evolutionary stable trust mechanism designed for decentralized LLM-based multi-agent service economies, a...

arXiv - AI · 4 min ·
[2512.01809] Much Ado About Noising: Dispelling the Myths of Generative Robotic Control
Machine Learning

[2512.01809] Much Ado About Noising: Dispelling the Myths of Generative Robotic Control

This paper evaluates generative control policies in robotics, revealing that their success is due to iterative computation rather than mu...

arXiv - Machine Learning · 4 min ·
[2511.05275] TwinVLA: Data-Efficient Bimanual Manipulation with Twin Single-Arm Vision-Language-Action Models
Machine Learning

[2511.05275] TwinVLA: Data-Efficient Bimanual Manipulation with Twin Single-Arm Vision-Language-Action Models

The paper presents TwinVLA, a modular framework for bimanual manipulation using two single-arm Vision-Language-Action models, enhancing d...

arXiv - Machine Learning · 3 min ·
[2510.25850] Debate2Create: Robot Co-design via Multi-Agent LLM Debate
Llms

[2510.25850] Debate2Create: Robot Co-design via Multi-Agent LLM Debate

The paper introduces Debate2Create, a framework for robot co-design that utilizes multi-agent LLM debate to optimize robot morphology and...

arXiv - Machine Learning · 3 min ·
[2510.12206] Controllable Collision Scenario Generation via Collision Pattern Prediction
Robotics

[2510.12206] Controllable Collision Scenario Generation via Collision Pattern Prediction

This paper introduces a novel method for generating controllable collision scenarios for autonomous vehicles, enhancing safety evaluation...

arXiv - Machine Learning · 4 min ·
[2510.18316] MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile Manipulation
Machine Learning

[2510.18316] MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile Manipulation

The paper presents MoMaGen, a novel approach for generating diverse datasets for multi-step bimanual mobile manipulation by addressing re...

arXiv - Machine Learning · 4 min ·
[2509.16650] Safe and Near-Optimal Control with Online Dynamics Learning
Ai Infrastructure

[2509.16650] Safe and Near-Optimal Control with Online Dynamics Learning

This article presents a novel approach to safe and near-optimal control in dynamic environments, utilizing online dynamics learning to en...

arXiv - Machine Learning · 4 min ·
[2510.11103] A Primer on SO(3) Action Representations in Deep Reinforcement Learning
Robotics

[2510.11103] A Primer on SO(3) Action Representations in Deep Reinforcement Learning

This paper explores SO(3) action representations in deep reinforcement learning, focusing on their implications for robotic control tasks...

arXiv - AI · 4 min ·
[2510.09469] Towards Information-Optimized Multi-Agent Path Finding: A Hybrid Framework with Reduced Inter-Agent Information Sharing
Robotics

[2510.09469] Towards Information-Optimized Multi-Agent Path Finding: A Hybrid Framework with Reduced Inter-Agent Information Sharing

This paper presents a hybrid framework for Multi-Agent Path Finding (MAPF) that minimizes inter-agent information sharing while maintaini...

arXiv - AI · 4 min ·
[2510.04891] SocialHarmBench: Revealing LLM Vulnerabilities to Socially Harmful Requests
Llms

[2510.04891] SocialHarmBench: Revealing LLM Vulnerabilities to Socially Harmful Requests

The paper introduces SocialHarmBench, a dataset designed to evaluate the vulnerabilities of large language models (LLMs) to socially harm...

arXiv - Machine Learning · 4 min ·
[2509.24243] SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions
Robotics

[2509.24243] SafeFlowMatcher: Safe and Fast Planning using Flow Matching with Control Barrier Functions

The paper presents SafeFlowMatcher, a new planning framework that integrates flow matching with control barrier functions to ensure safe ...

arXiv - AI · 4 min ·
[2508.00017] Generative Logic: A New Computer Architecture for Deterministic Reasoning and Knowledge Generation
Machine Learning

[2508.00017] Generative Logic: A New Computer Architecture for Deterministic Reasoning and Knowledge Generation

The paper introduces Generative Logic (GL), a new computer architecture designed for deterministic reasoning and knowledge generation, ut...

arXiv - AI · 4 min ·
[2507.20174] LRR-Bench: Left, Right or Rotate? Vision-Language models Still Struggle With Spatial Understanding Tasks
Llms

[2507.20174] LRR-Bench: Left, Right or Rotate? Vision-Language models Still Struggle With Spatial Understanding Tasks

The paper introduces LRR-Bench, a benchmark for evaluating Vision-Language Models (VLMs) on spatial understanding tasks, revealing signif...

arXiv - AI · 4 min ·
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