activity
20242026
most citedAn Explainable Deep Neural Network with Frequency-Aware Channel and Spatial Refinement for Flood Prediction in Sustainable Cities

6 citations · 12 across the 8 of their papers we have counts for

collaborators

8 papers

cs.RO2026

WEAVER, Better, Faster, Longer: An Effective World Model for Robotic Manipulation

Arnav Kumar Jain, Yilin Wu, Jesse Farebrother +2

The potential impacts of world models (WMs, i.e., learned simulators) on robotics are far-reaching -- policy evaluation, policy improvement, and test-time planning -- all with limi…

cs.AI2026

Learning the ARTS of Search for Automated Discovery

Gurusha Juneja, Arnav Kumar Jain, Deepak Nathani +2

Scientific discovery can be formulated as an iterative search process over the space of hypotheses and experiments. Contemporary methods navigate this space using heuristics such a…

cs.CV2025★ 6 cited

An Explainable Deep Neural Network with Frequency-Aware Channel and Spatial Refinement for Flood Prediction in Sustainable Cities

Shahid Shafi Dar, Bharat Kaurav, Arnav Jain +3

In an era of escalating climate change, urban flooding has emerged as a critical challenge for sustainable cities, threatening lives, infrastructure, and ecosystems. Traditional fl…

cs.LG2025

A Smooth Sea Never Made a Skilled SAILOR: Robust Imitation via Learning to Search

Arnav Kumar Jain, Vibhakar Mohta, Subin Kim +5

The fundamental limitation of the behavioral cloning (BC) approach to imitation learning is that it only teaches an agent what the expert did at states the expert visited. This mea…

cs.CL2025

Command A: An Enterprise-Ready Large Language Model

Team Cohere, :, Aakanksha +227

In this report we describe the development of Command A, a powerful large language model purpose-built to excel at real-world enterprise use cases. Command A is an agent-optimised…

cs.LG2025

Multi-Turn Code Generation Through Single-Step Rewards

Arnav Kumar Jain, Gonzalo Gonzalez-Pumariega, Wayne Chen +3

We address the problem of code generation from multi-turn execution feedback. Existing methods either generate code without feedback or use complex, hierarchical reinforcement lear…

cs.LG2024

Non-Adversarial Inverse Reinforcement Learning via Successor Feature Matching

Arnav Kumar Jain, Harley Wiltzer, Jesse Farebrother +3

In inverse reinforcement learning (IRL), an agent seeks to replicate expert demonstrations through interactions with the environment. Traditionally, IRL is treated as an adversaria…

cs.SD2024★ 6 cited

LSTMSE-Net: Long Short Term Speech Enhancement Network for Audio-visual Speech Enhancement

Arnav Jain, Jasmer Singh Sanjotra, Harshvardhan Choudhary +6

In this paper, we propose long short term memory speech enhancement network (LSTMSE-Net), an audio-visual speech enhancement (AVSE) method. This innovative method leverages the com…