6 citations · 10 across the 8 of their papers we have counts for
6 papers · 1 filter
Unsupervised Process Reward Models
Artyom Gadetsky, Maxim Kodryan, Siba Smarak Panigrahi +2
Process Reward Models (PRMs) are a powerful mechanism for steering large language model reasoning by providing fine-grained, step-level supervision. However, this effectiveness com…
HeurekaBench: A Benchmarking Framework for AI Co-scientist
Siba Smarak Panigrahi, Jovana Videnović, Maria Brbić
LLM-based reasoning models have enabled the development of agentic systems that act as co-scientists, assisting in multi-step scientific analysis. However, evaluating these systems…
BigDocs: An Open Dataset for Training Multimodal Models on Document and Code Tasks
Juan Rodriguez, Xiangru Jian, Siba Smarak Panigrahi +40
Multimodal AI has the potential to significantly enhance document-understanding tasks, such as processing receipts, understanding workflows, extracting data from documents, and sum…
Improved Canonicalization for Model Agnostic Equivariance
Siba Smarak Panigrahi, Arnab Kumar Mondal
This work introduces a novel approach to achieving architecture-agnostic equivariance in deep learning, particularly addressing the limitations of traditional layerwise equivariant…
Equivariant Adaptation of Large Pretrained Models
Arnab Kumar Mondal, Siba Smarak Panigrahi, Sékou-Oumar Kaba +2
Equivariant networks are specifically designed to ensure consistent behavior with respect to a set of input transformations, leading to higher sample efficiency and more accurate a…
Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
Arnab Kumar Mondal, Siba Smarak Panigrahi, Sai Rajeswar +2
The accurate modeling of dynamics in interactive environments is critical for successful long-range prediction. Such a capability could advance Reinforcement Learning (RL) and Plan…