6 papers
Learning to Theorize the World from Observation
Doojin Baek, Gyubin Lee, Junyeob Baek +2
What does it mean to understand the world? Contemporary world models often operationalize understanding as accurate future prediction in latent or observation space. Developmental…
Generative Recursive Reasoning
Junyeob Baek, Mingyu Jo, Minsu Kim +3
How should future neural reasoning systems implement extended computation? Recursive Reasoning Models (RRMs) offer a promising alternative to autoregressive sequence extension by p…
Discrete JEPA: Learning Discrete Token Representations without Reconstruction
Junyeob Baek, Hosung Lee, Christopher Hoang +2
The cornerstone of cognitive intelligence lies in extracting hidden patterns from observations and leveraging these principles to systematically predict future outcomes. However, c…
Slot-MLLM: Object-Centric Visual Tokenization for Multimodal LLM
Donghwan Chi, Hyomin Kim, Yoonjin Oh +7
Recently, multimodal large language models (MLLMs) have emerged as a key approach in achieving artificial general intelligence. In particular, vision-language MLLMs have been devel…
Dreamweaver: Learning Compositional World Models from Pixels
Junyeob Baek, Yi-Fu Wu, Gautam Singh +1
Humans have an innate ability to decompose their perceptions of the world into objects and their attributes, such as colors, shapes, and movement patterns. This cognitive process e…
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer
Chang Chen, Junyeob Baek, Fei Deng +3
Despite the recent advancements in offline RL, no unified algorithm could achieve superior performance across a broad range of tasks. Offline \textit{value function learning}, in p…