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cs.AI2026
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…
cs.AI2025
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…
cs.AI2025
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…