8 citations · 10 across the 11 of their papers we have counts for
5 papers · 1 filter
InTraGen: Trajectory-controlled Video Generation for Object Interactions
Zuhao Liu, Aleksandar Yanev, Ahmad Mahmood +7
Advances in video generation have significantly improved the realism and quality of created scenes. This has fueled interest in developing intuitive tools that let users leverage v…
Deep Policy Gradient Methods Without Batch Updates, Target Networks, or Replay Buffers
Gautham Vasan, Mohamed Elsayed, Alireza Azimi +5
Modern deep policy gradient methods achieve effective performance on simulated robotic tasks, but they all require large replay buffers or expensive batch updates, or both, making…
Streaming Deep Reinforcement Learning Finally Works
Mohamed Elsayed, Gautham Vasan, Elena Sorina Lupu +1
Learning from a stream of experience as it arrives, also known as streaming learning, is a core part of natural learning. However, reliable streaming learning has remained a persis…
Revisiting Sparse Rewards for Goal-Reaching Reinforcement Learning
Gautham Vasan, Yan Wang, Fahim Shahriar +3
Many real-world robot learning problems, such as pick-and-place or arriving at a destination, can be seen as a problem of reaching a goal state as soon as possible. These problems,…
VURF: A General-purpose Reasoning and Self-refinement Framework for Video Understanding
Ahmad Mahmood, Ashmal Vayani, Muzammal Naseer +2
Recent studies have demonstrated the effectiveness of Large Language Models (LLMs) as reasoning modules that can deconstruct complex tasks into more manageable sub-tasks, particula…