6 citations · 11 across the 16 of their papers we have counts for
5 papers · 1 filter
Training Emergent Joint Associations: A Reinforcement Learning Approach to Creative Thinking in Language Models
Mukul Singh, Ananya Singha, Aishni Parab +2
Associative thinking--the ability to connect seemingly unrelated ideas--is a foundational element of human creativity and problem-solving. This paper explores whether reinforcement…
Do Code Models Suffer from the Dunning-Kruger Effect?
Mukul Singh, Somya Chatterjee, Arjun Radhakrishna +1
As artificial intelligence systems increasingly collaborate with humans in creative and technical domains, questions arise about the cognitive boundaries and biases that shape our…
Collaboration and Conflict between Humans and Language Models through the Lens of Game Theory
Mukul Singh, Arjun Radhakrishna, Sumit Gulwani
Language models are increasingly deployed in interactive online environments, from personal chat assistants to domain-specific agents, raising questions about their cooperative and…
FormaT5: Abstention and Examples for Conditional Table Formatting with Natural Language
Mukul Singh, José Cambronero, Sumit Gulwani +5
Formatting is an important property in tables for visualization, presentation, and analysis. Spreadsheet software allows users to automatically format their tables by writing data-…
TST: Target Similarity Tuning Meets the Real World
Anirudh Khatry, Sumit Gulwani, Priyanshu Gupta +4
Target similarity tuning (TST) is a method of selecting relevant examples in natural language (NL) to code generation through large language models (LLMs) to improve performance. I…