2 citations · 2 across the 6 of their papers we have counts for
6 papers
Equilibrium Forcing: Adaptive Video Generation Without Noise Conditioning
Hansen Jin Lillemark, Alex Rojas, Zachary Novack +5
Standard autoregressive video generation algorithms based on Diffusion and Flow Matching rely on rigid training objectives and static sampling schedules, limiting inference procedu…
Geometric Priors for Generalizable World Models via Vector Symbolic Architecture
William Youngwoo Chung, Calvin Yeung, Hansen Jin Lillemark +3
A key challenge in artificial intelligence and neuroscience is understanding how neural systems learn representations that capture the underlying dynamics of the world. Most world…
Flow Equivariant World Models: Memory for Partially Observed Dynamic Environments
Hansen Jin Lillemark, Benhao Huang, Fangneng Zhan +2
Embodied systems experience the world as 'a symphony of flows': a combination of many continuous streams of sensory input coupled to self-motion, interwoven with the dynamics of ex…
Collaborating Action by Action: A Multi-agent LLM Framework for Embodied Reasoning
Isadora White, Kolby Nottingham, Ayush Maniar +5
Collaboration is ubiquitous and essential in day-to-day life -- from exchanging ideas, to delegating tasks, to generating plans together. This work studies how LLMs can adaptively…
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna +70
This paper describes the 2nd edition of the ICML Topological Deep Learning Challenge that was hosted within the ICML 2024 ELLIS Workshop on Geometry-grounded Representation Learnin…
Simple and Effective Input Reformulations for Translation
Brian Yu, Hansen Lillemark, Kurt Keutzer
Foundation language models learn from their finetuning input context in different ways. In this paper, we reformulate inputs during finetuning for challenging translation tasks, le…