David Held

Associate Professor at Carnegie Mellon University | he/him

[David Held @davheld]

@thomas_weng @lakshitadodeja @rai_inst Proud PhD advisor here, great work!

[Thomas Weng @thomas_weng]

My first last-author paper, with @lakshitadodeja and @rai_inst collaborators!

When deploying Behavior Cloning (BC) policies, we encounter performance gaps due to compounding error, subtle task shifts, etc.

We want to be able to post-train BC policies with a few online interactions to quickly improve performance.

Q2RL is what we hoped for in a robot post-training algorithm:
- ✅it starts with BC policy rollouts (no need for large, diverse datasets), and
- ✅it's sample-efficient enough for real-world online reinforcement learning!

See the thread and linked website for more details. Paper and code are released!

[Tal Daniel @TalDaniel8]

I’m attending #ICLR2026 in Rio this week to present LPWM! Friday April 24 Poster Session 3 10:30, Oral Session 4B 3:15p. Happy to chat about self-sup object-centric learning and world models. I’ll be on the job market soon and looking for exciting opportunities!

#ICLR @iclr_conf

[David Held @davheld]

@GlenBerseth Link to slides?

[David Held @davheld]

@GuanyaShi Agreed!

[Guanya Shi @GuanyaShi]

I’m so tired of writing rebuttals to this kind of “lack of novelty” review: “This paper trivially combines A, B, and C, so the algorithmic novelty is limited.”

Technically, most (if not all) robotics papers are convex combinations of existing ideas.

I still deeply appreciate A+B+C papers—especially when they deliver:

- New capabilities: the “trivial combination” unlocks behaviors we simply couldn’t achieve before

- Sensible & organic design: A+B+C is clearly the right composition—not some arbitrary A′+B+C′

- Nontrivial interactions: careful analysis of the dynamics, coupling, or failure modes between A, B, C

- Rehabilitating old ideas: A was dismissed for years, but paired with modern B/C, it suddenly works—and teaches us why

- System-level & "interface" insight: the contribution is not any single piece, but how the pieces talk to each other

- Scaling laws or regimes: identifying when/why A+B+C works (and when it doesn’t)

- Engineering clarity: making something actually work robustly in the real world is not “trivial”

- New problem formulations: sometimes the real novelty is in the reformulation—only under this view does A+B+C make sense.

Maybe worth keeping these in mind when reviewing the next A+B+C paper : )

[David Held @davheld]

Excellent analysis by @Majumdar_Ani, recommended read!

[Anirudha Majumdar @Majumdar_Ani]

https://t.co/3tzZESvF4L

[David Held @davheld]

@siddancha What is the consumer business case for this? Do you mean for some kind of robot sports competition? Or as a training partner for athletes?

[Tal Daniel @TalDaniel8]

🚀 #ICLR2026 Oral 💥
How can we design world models that capture object interactions directly from pixels?
Introducing Latent Particle World Models-the first end-to-end self-supervised, object-centric world model, trained from videos, supporting action/img/lang conditioning.
1/n

[David Held @davheld]

@bowenwen_me Looking forward to it! I would also love to see a comparison to MapAnything or DepthAnything3.

[David Held @davheld]

@m_wulfmeier Robot vacuuming!

[David Held @davheld]

@bowenwen_me Any guesses when you will release the code for this method?

[David Held @davheld]

@vincesitzmann Clarification: you call a point cloud an "intermediate representation" but what about 3D sensors that directly record point clouds? Should we not develop methods that can learn from such data?

[David Held @davheld]

@xwang_lk @jon_barron @TuliMathieu So "natural" just means "recorded using sensors similar to the sensors that humans have"? What about sonar (bats)? And why couldn't some alien species have a lidar sensor built in, making it "natural"?

[David Held @davheld]

@nblqbl Now try this with humans.

[David Held @davheld]

@bowenwen_me Great work! How does it compare to MapAnything or Depth Anything 3?

[David Held @davheld]

@AvivTamar1 What is the max score here? What if I want to say that their ability is much greater than is reflected by their achievements?

[David Held @davheld]

I am filling out a fellowship application letter of recommendation, and one question is: "Applicant's achievements reflect his or her ability: * - select -Not at All; Well; Moderately Well; Very Well; Extremely Well".
If I select "Well" then what does that imply?

[David Held @davheld]

@AvivTamar1 What would a person mean if they said it?

[David Held @davheld]

What are the best slides you have seen to explain transformers to someone who has never seen them before?