Daniela Rus receives Bavarian Minister-President's High-Tech Prize
Director of CSAIL and MIT professor honored for her contributions to robotics, artificial intelligence, and autonomous systems.
More from the blog
Documenting the tech worker movement
Writing as a participant and researcher, PhD student JS Tan SM ’22 has co-authored a new book about the rise of tech worker protests and the employer backlash that followed.
3 Questions: A new resource to empower young entrepreneurs
Martin Trust Center Managing Director Bill Aulet introduces Dear Dreamer, a free platform for middle and high school students who want to learn about entrepreneurship.
New formulation helps RNA vaccines withstand high temperatures
MIT engineers have found a way to stabilize the lipid nanoparticles used to deliver RNA vaccines, which could allow the vaccines to be more widely distributed.
MIT students gain a humanist lens on technical innovation in Tulsa, Oklahoma
The PKG Center for Social Impact expands Code.Tulsa experiential learning program.
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Transformer-Based Autonomous Driving Models and Deployment-Oriented Compression: A Survey
This survey reviews representative Transformer-based autonomous driving models and organizes them by task role, sensing configuration, and architectural design and analyzes how efficiency constraints reshaping model design choices in practice affects deployability, robustness, and safety.
SurgRAW: Multi-Agent Workflow With Chain of Thought Reasoning for Robotic Surgical Video Analysis
This work introduces SurgCoTBench, the first reasoning-focused benchmark in RAS, and proposes SurgRAW, a clinically aligned Chain-of-Thought (CoT) driven agentic workflow for zero-shot multi-task reasoning in surgery, which surpasses mainstream VLMs and agentic systems and outperforms a supervised model.
AtomicVLA: Unlocking the Potential of Atomic Skill Learning in Robots
This work proposes AtomicVLA, a unified planning-and-execution framework that jointly generates task-level plans, atomic skill abstractions, and fine-grained actions, and introduces a flexible routing encoder that automatically assigns dedicated atomic experts to new skills, enabling continual learning.
Easier Said Than Done: Unpacking Intent-Behavior Gap in Jailbreaking LLM-Based Robots
This paper introduces POEF (POlicy EFfective Jailbreak), an automated red-teaming framework that takes into account the robot-specific constraints during both the optimization and evaluation processes and proposes two defense strategies that mitigate the behavior jailbreak risks.