3 papers
cs.AI2026
Hierarchical Experimentalist Agents
Abhranil Chandra, Sankaran Vaidyanathan, Utsav Dhanuka +2
Large language models (LLMs) are increasingly used to take actions in the real world and support human decision-making, yet most agents rely on parametric knowledge, fixed post-tra…
cs.AI2026
Shape of Thought: When Distribution Matters More than Correctness in Reasoning Tasks
Abhranil Chandra, Ayush Agrawal, Arian Hosseini +4
We present the surprising finding that a language model's reasoning capabilities can be improved by training on synthetic datasets of chain-of-thought (CoT) traces from more capabl…
cs.AI2025
VideoAgent: Self-Improving Video Generation
Achint Soni, Sreyas Venkataraman, Abhranil Chandra +4
Video generation has been used to generate visual plans for controlling robotic systems. Given an image observation and a language instruction, previous work has generated video pl…