15 citations · 42 across the 14 of their papers we have counts for
14 papers
Evaluating LLMs in the Context of a Functional Programming Course: A Comprehensive Study
Yihan Zhang, Brigitte Pientka, Xujie Si
Large-Language Models (LLMs) are changing the way learners acquire knowledge outside the classroom setting. Previous studies have shown that LLMs seem effective in generating to sh…
Idiolect: A Reconfigurable Voice Coding Assistant
Breandan Considine, Nicholas Albion, Xujie Si
This paper presents Idiolect, an open source (https://github.com/OpenASR/idiolect) IDE plugin for voice coding and a novel approach to building bots that allows for users to define…
Can ChatGPT Pass An Introductory Level Functional Language Programming Course?
Chuqin Geng, Yihan Zhang, Brigitte Pientka +1
The recent introduction of ChatGPT has drawn significant attention from both industry and academia due to its impressive capabilities in solving a diverse range of tasks, including…
Chronosymbolic Learning: Efficient CHC Solving with Symbolic Reasoning and Inductive Learning
Ziyan Luo, Xujie Si
Solving Constrained Horn Clauses (CHCs) is a fundamental challenge behind a wide range of verification and analysis tasks. Data-driven approaches show great promise in improving CH…
Identifying Different Student Clusters in Functional Programming Assignments: From Quick Learners to Struggling Students
Chuqin Geng, Wenwen Xu, Yingjie Xu +2
Instructors and students alike are often focused on the grade in programming assignments as a key measure of how well a student is mastering the material and whether a student is s…
NSNet: A General Neural Probabilistic Framework for Satisfiability Problems
Zhaoyu Li, Xujie Si
We present the Neural Satisfiability Network (NSNet), a general neural framework that models satisfiability problems as probabilistic inference and meanwhile exhibits proper explai…
Scalar Invariant Networks with Zero Bias
Chuqin Geng, Xiaojie Xu, Haolin Ye +1
Just like weights, bias terms are the learnable parameters of many popular machine learning models, including neural networks. Biases are thought to enhance the representational po…
Novice Type Error Diagnosis with Natural Language Models
Chuqin Geng, Haolin Ye, Yixuan Li +3
Strong static type systems help programmers eliminate many errors without much burden of supplying type annotations. However, this flexibility makes it highly non-trivial to diagno…
Towards Reliable Neural Specifications
Chuqin Geng, Nham Le, Xiaojie Xu +3
Having reliable specifications is an unavoidable challenge in achieving verifiable correctness, robustness, and interpretability of AI systems. Existing specifications for neural n…
Static Code Analyzer Using Micro-Grammar
Hanwen Zhu, Junyoung Jang, Xujie Si
[THIS IS AN UNDERGRADUATE PROJECT] This paper discusses the effectiveness of the bug finder based on "micro-grammar".
Graph Contrastive Pre-training for Effective Theorem Reasoning
Zhaoyu Li, Binghong Chen, Xujie Si
Interactive theorem proving is a challenging and tedious process, which requires non-trivial expertise and detailed low-level instructions (or tactics) from human experts. Tactic p…
Techniques for Symbol Grounding with SATNet
Sever Topan, David Rolnick, Xujie Si
Many experts argue that the future of artificial intelligence is limited by the field's ability to integrate symbolic logical reasoning into deep learning architectures. The recent…
Prioritized Unit Propagation with Periodic Resetting is (Almost) All You Need for Random SAT Solving
Xujie Si, Yujia Li, Vinod Nair +1
We propose prioritized unit propagation with periodic resetting, which is a simple but surprisingly effective algorithm for solving random SAT instances that are meant to be hard.…
Synthesizing Datalog Programs Using Numerical Relaxation
Xujie Si, Mukund Raghothaman, Kihong Heo +1
The problem of learning logical rules from examples arises in diverse fields, including program synthesis, logic programming, and machine learning. Existing approaches either invol…