70 citations · 407 across the 70 of their papers we have counts for
18 papers · 1 filter
Exploration vs. Fixation: Scaffolding Divergent and Convergent Thinking for Human-AI Co-Creation with Generative Models
Chao Wen, Tung Phung, Pronita Mehrotra +4
Generative AI has democratized content creation, but popular chatbot-based interfaces often prioritize execution, generating fully rendered artifacts right away. This issue can lea…
IndiMathBench: Autoformalizing Mathematical Reasoning Problems with a Human Touch
Param Biyani, Shashank Kirtania, Yasharth Bajpai +2
Reliable autoformalization remains challenging even in the era of large language models (LLMs). The scarcity of high-quality training data is a major bottleneck. Expert annotation…
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…
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…
SWE-Sharp-Bench: A Reproducible Benchmark for C# Software Engineering Tasks
Sanket Mhatre, Yasharth Bajpai, Sumit Gulwani +2
AI coding agents have shown great progress on Python software engineering benchmarks like SWE-Bench, and for other languages like Java and C in benchmarks like Multi-SWE-Bench. How…
Improving Language Agents through BREW: Bootstrapping expeRientially-learned Environmental knoWledge
Shashank Kirtania, Param Biyani, Priyanshu Gupta +4
Large Language Model (LLM)-based agents are increasingly capable of complex, multi-step tasks such as GUI automation, tool use, and data manipulation, yet they cannot learn from ex…
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…
The Invisible Mentor: Inferring User Actions from Screen Recordings to Recommend Better Workflows
Litao Yan, Andrew Head, Ken Milne +4
Many users struggle to notice when a more efficient workflow exists in feature-rich tools like Excel. Existing AI assistants offer help only after users describe their goals or pro…
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…
Bridging Gaps Between Student and Expert Evaluations of AI-Generated Programming Hints
Tung Phung, Mengyan Wu, Heeryung Choi +4
Generative AI has the potential to enhance education by providing personalized feedback to students at scale. Recent work has proposed techniques to improve AI-generated programmin…
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…
Tabularis Formatus: Predictive Formatting for Tables
Mukul Singh, José Cambronero, Sumit Gulwani +2
Spreadsheet manipulation software are widely used for data management and analysis of tabular data, yet the creation of conditional formatting (CF) rules remains a complex task req…
Diffusion is a code repair operator and generator
Mukul Singh, Gust Verbruggen, Vu Le +1
Code diffusion models generate code by iteratively removing noise from the latent representation of a code snippet. During later steps of the diffusion process, when the code snipp…
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…
Why AI Agents Still Need You: Findings from Developer-Agent Collaborations in the Wild
Aayush Kumar, Yasharth Bajpai, Sumit Gulwani +2
Software Engineering Agents (SWE agents) can autonomously perform development tasks on benchmarks like SWE Bench, but still face challenges when tackling complex and ambiguous real…
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…
TableTalk: Scaffolding Spreadsheet Development with a Language Agent
Jenny T. Liang, Aayush Kumar, Yasharth Bajpai +7
Spreadsheet programming is challenging. Programmers use spreadsheet programming knowledge (e.g., formulas) and problem-solving skills to combine actions into complex tasks. Advance…