56 citations · 84 across the 30 of their papers we have counts for
8 papers · 1 filter
Scaling Competence, Shrinking Reasoning: Cognitive Signatures in Language Model Learning
Mukul Singh, Ananya Singha, Arjun Radhakrishna +1
We analyze reasoning in language models during task-specific fine-tuning and draws parallel between reasoning tokens--intermediate steps generated while solving problem and the hum…
ConDABench: Interactive Evaluation of Language Models for Data Analysis
Avik Dutta, Priyanshu Gupta, Hosein Hasanbeig +6
Real-world data analysis tasks often come with under-specified goals and unclean data. User interaction is necessary to understand and disambiguate a user's intent, and hence, esse…
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…
TEN: Table Explicitization, Neurosymbolically
Nikita Mehrotra, Aayush Kumar, Sumit Gulwani +2
We present a neurosymbolic approach, TEN, for extracting tabular data from semistructured input text. This task is particularly challenging for text input that does not use special…
LLM-Guided Compositional Program Synthesis
Ruhma Khan, Sumit Gulwani, Vu Le +3
Program synthesis from input-output examples, also called programming by example (PBE), has had tremendous impact on automating end-user tasks. Large language models (LLMs) have th…