1 citations · 1 across the 4 of their papers we have counts for
5 papers
Seq-Flow: Efficient Probabilistic Forecasting with Self-Rollout Error Control
Yinan Huang, Shitij Govil, Bo Dai +1
Many scientific forecasting tasks require updating a distribution over future trajectories as new observations arrive. Conventional diffusion and flow models generate each forecast…
HEPTv2: End-to-End Efficient Point Transformer for Charged Particle Reconstruction
Siqi Miao, Shitij Govil, Jack P. Rodgers +5
Charged-particle tracking -- reconstructing trajectories from sparse detector measurements -- is a fundamental high-energy-physics inference problem and a canonical example of lear…
Locality-Sensitive Hashing-Based Efficient Point Transformer for Charged Particle Reconstruction
Shitij Govil, Jack P. Rodgers, Yuan-Tang Chou +9
Charged particle track reconstruction is a foundational task in collider experiments and the main computational bottleneck in particle reconstruction. Graph neural networks (GNNs)…
The Challenge of Teaching Reasoning to LLMs Without RL or Distillation
Wei Du, Branislav Kisacanin, George Armstrong +22
Reasoning-capable language models achieve state-of-the-art performance in diverse complex tasks by generating long, explicit Chain-of-Thought (CoT) traces. While recent works show…
Pre-training Graph Neural Networks with Structural Fingerprints for Materials Discovery
Shuyi Jia, Shitij Govil, Manav Ramprasad +1
In recent years, pre-trained graph neural networks (GNNs) have been developed as general models which can be effectively fine-tuned for various potential downstream tasks in materi…