Junyi Zhang

@junyi42

Ph.D. @Berkeley_AI. research intern @physical_int. ex @GoogleDeepMind, @MSFTResearch. vision, generative model, robotics.

junyi42.com

Joined July 2022

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Junyi Zhang
@junyi42
Mar 9
𝗢𝗻𝗲 𝗺𝗲𝗺𝗼𝗿𝘆 𝗰𝗮𝗻’𝘁 𝗿𝘂𝗹𝗲 𝘁𝗵𝗲𝗺 𝗮𝗹𝗹. We present 𝗟𝗼𝗚𝗲𝗥, a new 𝗵𝘆𝗯𝗿𝗶𝗱 𝗺𝗲𝗺𝗼𝗿𝘆 architecture for long-context geometric reconstruction. LoGeR enables stable reconstruction over up to 𝟭𝟬𝗸 𝗳𝗿𝗮𝗺𝗲𝘀 / 𝗸𝗶𝗹𝗼𝗺𝗲𝘁𝗲𝗿 𝘀𝗰𝗮𝗹𝗲, with
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Junyi Zhang
@junyi42
Oct 23
We trained an agent with native visual world modeling ability. It imagines counterfactual outcomes to plan ahead. SFT teaches it to imagine; agentic RL makes it even more adaptable. We’ve released everything: agima.net
Jiaxin Ge
@jiaxin_ge_
Oct 23
We trained an imaginative agent! ✨ Agima: an omni agent that plans by imagining futures. 𝗦𝗙𝗧: Directly generalizes to harder tasks! 𝟮%→𝟰𝟬%, beats GPT-5.6 Sol (𝟮𝟬%). 𝗥𝗟: New ways to imagine emerge! Imagines a second plan only if the first one fails (𝟯𝟮%→𝟭𝟬𝟬%).
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Junyi Zhang
@junyi42
Jul 16
"The latent world representation is a program, not a vector" Finding the right representation to be inverse-graphics is really important. Really cool work!
Haven Feng
@HavenFeng
Jul 16
Today, we’re introducing [schema]: a harness reaching 99% RHAE with Opus 4.8 + Fable 5 and 95.35% with GPT-5.6 Sol on ARC-AGI-3 Public set. [schema] makes an LLM think like a physicist. 🧵
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Junyi Zhang
@junyi42
Jun 19
Children learn from play. Can robots do the same? We propose 𝐏𝐥𝐚𝐲𝐟𝐮𝐥 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐑𝐨𝐛𝐨𝐭 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠, a paradigm that gives embodied coding agents a play stage before downstream tasks arrive, and instantiate it with 𝐑𝐀𝐓𝐬 (Robotics Agent Teams), where robots
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Junyi Zhang
@junyi42
Jun 17
Very impressive effort, congrats on the team!!
Ritvik Singh
@ritvik_singh9
Jun 17
Introducing ABC: open data, training, and infrastructure for robotics. We release the largest teleop dataset to date, and extensively investigate design decisions, pretraining, and post-training techniques. @arthurallshire @Cinnabar233 @adamrasb @redstone_hong @davidrmcall
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