About
Semantic understanding of the world is essential for robots to make safe and informed decisions, to adapt to changing environmental conditions, and to enable efficient interactions with other agents. In pursuit of semantic understanding, agents must be able to (i) interpret and represent high-level goals, agnostic of their physical morphology and despite irrelevant aspects of their environments; they must be able to (ii) reason, i.e., to extract abstract concepts from observations in the real-world, logically manipulate these concepts, then leverage the results for inference on downstream tasks; and they must be able to (iii) execute morphology-, environment-, and socially-appropriate behaviors towards those high-level goals.

Despite substantial recent advancements in the use of pre-trained, large-capacity models (i.e., foundation models) for difficult robotics problems, methods still struggle in the face of several practical challenges that relate to real-world deployment, e.g., cross-domain generalization, adaptation to dynamic and human-shared environments, and lifelong operation in open-world contexts. This workshop intends to sponsor discussion of new hybrid methodologies—those that combine representations from foundation models with modeling mechanisms that may prove useful for semantic reasoning and abstract goal understanding, including neural memory mechanisms, procedural modules (e.g., cognitive architectures), neuro-symbolic representations (e.g., knowledge/scene graph embeddings), chain-of-thought reasoning mechanisms, robot skill primitives and their composition, 3D scene representations (e.g., NeRFs), etc.

Intended audience. We aim to bring together engineers, researchers, and practitioners from different communities to enable avenues for interdisciplinary research on methods that could facilitate the deployment of semantics-aware and generalizable embodied agents in unstructured and dynamic real world environments. In addition to the organizers, the presenters, panelists, and technical program committee are drawn from the following (sub-)communities: Robot Learning, Embodied AI, Planning + Controls, Cognitive Robotics, Neuro-Symbolism, Natural Language Processing, Computer Vision, and Multimodal Machine Learning. We likewise intend to attract an audience from these diverse sub-communities to contribute to compelling discussions.

Event Information This is a primarily in-person workshop, held at the 2025 Robotics Science and Systems conference (RSS), in Los Angeles, United States on 21 June 2025, starting at 14:00 PT.

Speakers and Panelists

Schedule

Time
14:00		Organizers Introductory Remarks
14:10		Keynote 1: Jesse Thomason Title TBD Abstract Abstract TBD
14:30		Keynote 2: Luigi Palmieri Title TBD Abstract Abstract TBD
14:50		Keynote 3: Dorsa Sadigh Title TBD Abstract Abstract TBD
15:10		Spotlight Talks.
15:30		Coffee Break, Socializing, Posters
16:20		Keynote 4: Ted Xiao Title TBD Abstract Abstract TBD
16:40		Keynote 5: Manolis Savva Title TBD Abstract Abstract TBD
17:00		Keynote 6: Lerrel Pinto Title TBD Abstract Abstract TBD
17:20		Keynote 7: Yonatan Bisk Title TBD Abstract Abstract TBD
17:20		Keynote 8: Marc Toussaint Title TBD Abstract Abstract TBD
17:40		Debate: Implicit/Data-emergent Reasoning Capabilities versus Explicit Reasoning Mechanisms? Panelists: Jesse Thomason, Luigi Palmieri, Dorsa Sadigh, Ted Xiao, Manolis Savva, Lerrel Pinto, Yonatan Bisk, Marc Toussaint
18:25		Organizers Closing Remarks

Call for Papers

Targeted Topics

In addition to the RSS subject areas, we especially invite paper submissions on various topics, including (but not limited to):

• Neural architectures leveraging demonstrations as prompts
• Goal understanding through few-shot demonstrations
• Novel abstractions, representations, and mechanisms for few-shot learning
• Retrieval-augmentation mechanisms used in learning and task-execution
• Agentic frameworks for failure reasoning, self-guidance, test-time adaptation, etc.
• LLM-based action models for robot control; large action models
• Semantic representations for generalizable policy learning
• World models used for reasoning and optimization

Submission Guidelines

RSS SemRob 2025 suggests 4+N or 8+N paper length formats — i.e., 4 or 8 pages of main content with unlimited additional pages for references, appendices, etc. However, like RSS 2025, we impose no strict page length requirements on submissions; we trust that authors will recognize that respecting reviewers’ time is helpful to the evaluation of their work.

Submissions are handled through CMT: https://cmt3.research.microsoft.com/SEMROB2025

We will accept the official LaTeX or Word paper templates, provided by RSS 2025.

Our review process will be double-blind, following the RSS paper submission policy for Science/Systems papers.

All accepted papers will be invited for poster presentations; the highest-rated papers, according to the Technical Program Committee, will be given spotlight presentations. Accepted papers will be made available online on this workshop website as non-archival reports, allowing authors to also submit their works to future conferences or journals. We will highlight the Best Paper Award during the closing remarks at the workshop event.

Important Dates

• Submission deadline: TBD, 23:59 AOE.
• Author Notifications: TBD, 23:59 AOE.
• Camera Ready: TBD, 23:59 AOE.
• Workshop: 21 June 2025, 14:00-18:30 CET

Organizers