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Earlier sources: AI and robotics
Robotics combines physical machines with sensing, planning, and control. This AI thread follows learning-based robot policies, simulation, perception, and evaluation in physical environments.
SYMTRI organizes observations from public sources into a living map. Connections reflect shared subject matter; they do not establish causation or endorse a source.
Open in the map ↗41 classified signals in the fourteen-day window. These counts include signals awaiting readable evidence.
Earlier sources
Up to ten sources with readable evidence, ordered by their feed timestamp. These archive sources can be older than the live fourteen-day window. This list is a sample, not a measure of total activity. Dates distinguish paper publication, repository creation, model/dataset activity, Hacker News posts, and KEV catalog additions. “First archived” records when SYMTRI first stored the signal.
- arXiv · Published · First archived
Temporal Gradient Inversion for Private Trajectory Reconstruction in Embodied Reinforcement Learning ↗
Distributed learning in embodied reinforcement-learning agents offers a degree of privacy by retaining raw sensor data on-device and transmitting only policy gradients to the server. Yet temporal structure can amplify this leakage beyond single-frame attacks. We introduce Temporal Reconstruction Attack on Consecutive Encodings (TRACE), an amortized temporal gradient-inversion attack that autoregressively reconstructs the sequence of private observation-action trajectories from per-step policy-learning gradients. The attack exploits two structural signals ignored by prior single-frame methods:…
- GitHub · Repository created · First archived
MIT-CDFG/Survey-AI-for-3D-modeling-Robotics ↗
On the Opportunities and Risks of Frontier Models for 3D Modeling, Computational Design and Robotics (MIT CSAIL CDFG)
- arXiv · Published · First archived
Where Should I Join? Robot Group Joining via Language-Guided Goal Prediction ↗
Social navigation typically assumes a specified goal and focuses on reaching it while respecting social conventions, whereas robot group joining requires predicting where to join based on the group's real-time activity and formation. This is a highly semantic task, yet an important capability for applications such as robotic guide dogs and autonomous mobility scooters. We formulate language-grounded robot group joining: given an observation and a natural-language description of a target group, the robot identifies the relevant group members and predicts socially compliant joining poses. For gr…
- arXiv · Published · First archived
Watch, Recall, Act: Always-On Robots in Concurrent Embodied Streams ↗
An always-on robot faces an endless stream that never resets: instructions arrive and lapse, the scene changes, and its own past actions reshape what it must reason about. Today's action models are built for the opposite: a fixed instruction, no mid-task intervention, single-step reasoning. In an open-ended world a robot must watch a live stream for far-future cues, recall its own far-past actions, and act on them under dual-arm concurrency. We present ARMS (Always-on Robot in Multi-modal Streams), a deliberately simple streaming policy: a single pretrained $π$0.5 backbone augmented by three l…
- arXiv · Published · First archived
Amplify: A Lightweight Library for Reproducible Nonlinear Programming Problems in Robotics ↗
Optimization problems (OPs) are key to solving many challenging research problems in robotics. However, reproducibility still remains a major issue. In this paper, we present Amplify, a lightweight nonlinear programming library aimed at reproducible results of robotic-related trajectory optimization problems. The minimalistic requirements for the 537-line library (80 characters per line) are an Internet connection, familiarity with the AMPL modeling language, and a text editor. Our primary contribution is the formulation of a library where trajectory optimization algorithms are represented dir…
- arXiv · Published · First archived
Beyond Future Prediction: Denoising as Generative Adaptation for Robot Control ↗
Pretrained generative Diffusion Transformers (DiTs) capture rich pixel-level visual and language-conditioned structure through large-scale image and video generation training. A growing line of robot policies builds on this generative prior, but how it should be transferred to control remains unclear, and existing approaches commonly instantiate this transfer through future visual prediction. We ask a more basic question: what a pretrained generative DiT actually contributes to action learning, and how this prior should be adapted for control. We introduce NowWAM, a future-target-free co-train…
- GitHub · Repository created · First archived
roboto-ai/roboto-physical-ai-actions ↗
Roboto actions for physical AI: curate and audit robotics data, convert it to LeRobot (v2.1, v3.0) datasets, merge, up- and down-convert them
- OpenAlex · Published · First archived
Embodied Musical Gesture Analysis from Audio Representations: A Review of Datasets, Audio Descriptors, and Deep Learning Approaches ↗
Machine learning approaches have enabled increasingly powerful analysis of musical audio, allowing computational models to capture complex acoustic patterns related to musical structure, performance, and expression. However, whether learned audio representations preserve information related to the bodily actions underlying musical sound production remains an open research question. This review examines how machine-learned audio representations encode information associated with embodied musical processes by connecting perspectives from embodied music cognition, computational music analysis, an…
- GitHub · Repository created · First archived
v-modal/awesome-jev-tools ↗
A curated list of tools built for Jev — TypeSafe AI's System One model for typed decisions.
- GitHub · Repository created · First archived
dimentary/llm-robotics-playground ↗
A library of experiments using frontier LLMs/VLMs for robotics tasks, currently focusing on GPT-6 Astra.
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How to assess evidence about AI and robotics
Check each original source for its methods, release status, limitations, and supporting data. A repository announcement, a preprint, and a published study provide different kinds of evidence. SYMTRI’s subject classification helps discovery; it does not independently validate the source’s claims.
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