15 citations · 16 across the 5 of their papers we have counts for
5 papers
Towards a universal language of concepts: A survey
Aishni Parab
Humans can learn and generalize novel concepts from sparse data because they express knowledge in rich structural formats. In this paper, we propose that programs are a strong cand…
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…
Analysis of Error Sources in LLM-based Hypothesis Search for Few-Shot Rule Induction
Aishni Parab, Hongjing Lu, Ying Nian Wu +1
Inductive reasoning enables humans to infer abstract rules from limited examples and apply them to novel situations. In this work, we compare an LLM-based hypothesis search framewo…
Enhancing Creativity in Large Language Models through Associative Thinking Strategies
Pronita Mehrotra, Aishni Parab, Sumit Gulwani
This paper explores the enhancement of creativity in Large Language Models (LLMs) like vGPT-4 through associative thinking, a cognitive process where creative ideas emerge from lin…
CLERA: A Unified Model for Joint Cognitive Load and Eye Region Analysis in the Wild
Li Ding, Jack Terwilliger, Aishni Parab +4
Non-intrusive, real-time analysis of the dynamics of the eye region allows us to monitor humans' visual attention allocation and estimate their mental state during the performance…