3 papers
cs.CV2026
MetaSampling: Making Frame Samplers Efficient for Long-Video Question Answering
Ashim Dahal, Bikramjit Banerjee
Frame selection is an important component of long-video question answering (VQA) with Multimodal Large Language Models (MLLMs). Existing frame-selection methods improve over simple…
cs.LG2026
ConTraIRL: Factorized Contrastive Abstractions for Transferable IRL
Yikang Gui, Bikramjit Banerjee, Prashant Doshi
Reward transfer in Inverse Reinforcement Learning (IRL) is unreliable when policies must generalize to unseen combinations of environment dynamics and task goals. We propose Factor…
cs.LG2024
Quasimetric Value Functions with Dense Rewards
Khadichabonu Valieva, Bikramjit Banerjee
As a generalization of reinforcement learning (RL) to parametrizable goals, goal conditioned RL (GCRL) has a broad range of applications, particularly in challenging tasks in robot…