10 citations · 33 across the 14 of their papers we have counts for
7 papers · 1 filter
The Majority is not always right: RL training for solution aggregation
Wenting Zhao, Pranjal Aggarwal, Swarnadeep Saha +3
Scaling up test-time compute, by generating multiple independent solutions and selecting or aggregating among them, has become a central paradigm for improving large language model…
Agentic-R1: Distilled Dual-Strategy Reasoning
Weihua Du, Pranjal Aggarwal, Sean Welleck +1
Current long chain-of-thought (long-CoT) models excel at mathematical reasoning but rely on slow and error-prone natural language traces. Tool-augmented agents address arithmetic v…
OptimalThinkingBench: Evaluating Over and Underthinking in LLMs
Pranjal Aggarwal, Seungone Kim, Jack Lanchantin +4
Thinking LLMs solve complex tasks at the expense of increased compute and overthinking on simpler problems, while non-thinking LLMs are faster and cheaper but underthink on harder…
L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning
Pranjal Aggarwal, Sean Welleck
Reasoning language models have shown an uncanny ability to improve performance at test-time by ``thinking longer''-that is, by generating longer chain-of-thought sequences and henc…
AutoMix: Automatically Mixing Language Models
Pranjal Aggarwal, Aman Madaan, Ankit Anand +10
Large language models (LLMs) are now available from cloud API providers in various sizes and configurations. While this diversity offers a broad spectrum of choices, effectively le…
Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning and Coding with LLMs
Pranjal Aggarwal, Aman Madaan, Yiming Yang +1
A popular approach for improving the correctness of output from large language models (LLMs) is Self-Consistency - poll the LLM multiple times and output the most frequent solution…
SemSup-XC: Semantic Supervision for Zero and Few-shot Extreme Classification
Pranjal Aggarwal, Ameet Deshpande, Karthik Narasimhan
Extreme classification (XC) involves predicting over large numbers of classes (thousands to millions), with real-world applications like news article classification and e-commerce…