PaperFlume
⌕
Accounts · soon

Library · RL for control

0:00

TopoCut: Learning Multi-Step Cutting with Spectral Rewards and Discrete Diffusion Policies

Liquan Wang, Jiangjie Bian, Eric Heiden, Animesh Garg

CoRL 2025 10:43 12 chapters CC BY 4.0 · adaptation, not endorsed by the authors Source checked · visual review incomplete

Download the deck .pptx Transcript .txt · cited Captions .vtt

Editable text and shapes, not pictures of slides.

Feedback

Was this worth your five minutes?

We are in beta. Tell us whether it helped — and if something is wrong, tell us that too.

Not rated
Goes to a person, not a form queue.
Next

Papers near this one.

Walkthroughs

5:41

Learning to Act Through Contact: A Unified View of Multi-Task Robot Learning

shares Mobile manipulation
6:45

ManiGuard: A Benchmark and Data Suite for Specification-Grounded Safety Evaluation and Improvement of Robotic Manipulation

2608.17386
shares VLA models
6:45

RHO: Your Coding Agent is Secretly a Roboticist

2606.16458
shares Multimodal LLMs

Short cuts

0:55

Learning to Act Through Contact: A Unified View of Multi-Task Robot Learning

shares Mobile manipulation
0:57

ManiGuard: A Benchmark and Data Suite for Specification-Grounded Safety Evaluation and Improvement of Robotic Manipulation

2608.17386
shares VLA models
0:57

RHO: Your Coding Agent is Secretly a Roboticist

2606.16458
shares Multimodal LLMs
Authors

Want one of these for your paper?

Send the PDF and we make the walkthrough, the deck and the reel. It stays private unless you publish it yourself.

Add your paper How it works
01

Something people finishFive minutes of method beats a PDF nobody opens past the abstract.

02

Slides for your next talkAn editable deck built from your own figures, with the narration in the notes.

03

A cut you can postFifty seconds, vertical, for the places a paper link gets ignored.

04

A page that can be foundA cited transcript sits on the page, so the words in your method are searchable.

Based on “TopoCut: Learning Multi-Step Cutting with Spectral Rewards and Discrete Diffusion Policies” by Liquan Wang, Jiangjie Bian, Eric Heiden, Animesh Garg · CoRL 2025 · CC BY 4.0 · licence checked 2026-10-24 · Changed from the original: rewritten as a narrated walkthrough with slides, using the paper's own figures. An adaptation, not endorsed by its authors.

Request takedown — we aim to answer within 72 hours.