6 papers
Inference-Time Rethinking with Latent Thought Vectors for Math Reasoning
Deqian Kong, Minglu Zhao, Aoyang Qin +10
Standard chain-of-thought reasoning generates a solution in a single forward pass, committing irrevocably to each token and lacking a mechanism to recover from early errors. We int…
Place Cells as Multi-Scale Position Embeddings: Random Walk Transition Kernels for Path Planning
Minglu Zhao, Dehong Xu, Deqian Kong +2
The hippocampus supports spatial navigation by encoding cognitive maps through collective place cell activity. We model the place cell population as non-negative spatial embeddings…
Latent Adaptive Planner for Dynamic Manipulation
Donghun Noh, Deqian Kong, Minglu Zhao +4
We present the Latent Adaptive Planner (LAP), a trajectory-level latent-variable policy for dynamic nonprehensile manipulation (e.g., box catching) that formulates planning as infe…
Latent Plan Transformer for Trajectory Abstraction: Planning as Latent Space Inference
Deqian Kong, Dehong Xu, Minglu Zhao +6
In tasks aiming for long-term returns, planning becomes essential. We study generative modeling for planning with datasets repurposed from offline reinforcement learning. Specifica…
Latent Thought Models with Variational Bayes Inference-Time Computation
Deqian Kong, Minglu Zhao, Dehong Xu +8
We propose a novel class of language models, Latent Thought Models (LTMs), which incorporate explicit latent thought vectors that follow an explicit prior model in latent space. Th…
A minimalistic representation model for head direction system
Minglu Zhao, Dehong Xu, Deqian Kong +2
We present a minimalistic representation model for the head direction (HD) system, aiming to learn a high-dimensional representation of head direction that captures essential prope…