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As large language models (LLMs) advance toward expert-level performance in engineering domains, reliable reasoning under user-specified constraints becomes critical. In circuit analysis, for example, a numerically correct solution is…

Software Engineering · Computer Science 2026-04-23 Mayank Ravishankara

As the landscape of software engineering evolves, introductory programming courses must go beyond teaching syntax to foster comprehensive technical competencies and professional soft skills. This paper reports on a pedagogical experience in…

Computers and Society · Computer Science 2026-03-20 Santiago Berrezueta-Guzman , Vanesa Metaj , Stefan Wagner

Recent advances in large language models (LLMs) have shown that test-time scaling can substantially improve model performance on complex tasks, particularly in the coding domain. Under this paradigm, models use a larger token budget during…

Artificial Intelligence · Computer Science 2026-04-21 Jiaxin Fang , Runyuan He , Sahil Bhatia , Neel Gajare , Alvin Cheung

Higher educational institutions constantly look for ways to meet students' needs and support them through graduation. Recent work in the field of learning analytics have developed methods for grade prediction and course recommendations.…

Applications · Statistics 2019-06-12 Prableen Kaur , Agoritsa Polyzou , George Karypis

There are repetitive patterns in strategies of manipulating source code. For example, modifying source code before acquiring knowledge of how a code works is a depth-first style and reading and understanding before modifying source code is…

Software Engineering · Computer Science 2016-12-01 Zahra Karimia , Ahmad Baraani-Dastjerdia , Nasser Ghasem-Aghaeea , Stefan Wagner

Understanding collaboration patterns in introductory programming courses is essential, as teamwork is a critical skill in computer science. In professional environments, software development relies on effective teamwork, navigating diverse…

Software Engineering · Computer Science 2024-10-29 Santiago Berrezueta-Guzman , Patrick Bassner , Stefan Wagner , Stephan Krusche

The introductory programming course (CS1) at the university level is often perceived as particularly challenging, contributing to high dropout rates among Computer Science students. Identifying when and how students encounter difficulties…

Computers and Society · Computer Science 2026-04-28 Denis Zhidkikh , Ville Isomöttönen , Toni Taipalus

In Programming by Example, a system attempts to infer a program from input and output examples, generally by searching for a composition of certain base functions. Performing a naive brute force search is infeasible for even mildly involved…

Artificial Intelligence · Computer Science 2012-09-19 Aditya Krishna Menon , Omer Tamuz , Sumit Gulwani , Butler Lampson , Adam Tauman Kalai

Reading, understanding and explaining code have traditionally been important skills for novices learning programming. As large language models (LLMs) become prevalent, these foundational skills are more important than ever given the…

Human-Computer Interaction · Computer Science 2024-03-12 Paul Denny , David H. Smith , Max Fowler , James Prather , Brett A. Becker , Juho Leinonen

The most common method to auto-grade a student's submission in a CS1 or a CS2 course is to run it against a pre-defined test suite and compare the results against reference results. However, this technique cannot be used if the correctness…

Artificial Intelligence · Computer Science 2024-10-22 Aaryen Mehta , Gagan Aryan

The instruction hierarchy, which establishes a priority order from system messages to user messages, conversation history, and tool outputs, is essential for ensuring consistent and safe behavior in language models (LMs). Despite its…

In situations where forecasters are scored on the quality of their probabilistic predictions, it is standard to use `proper' scoring rules to perform such scoring. These rules are desirable because they give forecasters no incentive to lie…

Methodology · Statistics 2020-08-25 Spencer Greenberg

Curriculum learning (CL), motivated by the intuition that learning in increasing order of difficulty should ease generalization, is commonly adopted both in pre-training and post-training of large language models (LLMs). The intuition of CL…

Computation and Language · Computer Science 2026-03-31 Maximilian Mordig , Andreas Opedal , Weiyang Liu , Bernhard Schölkopf

Preference learning is a widely adopted post-training technique that aligns large language models (LLMs) to human preferences and improves specific downstream task capabilities. In this work we systematically investigate how specific…

Computation and Language · Computer Science 2024-12-23 Joongwon Kim , Anirudh Goyal , Aston Zhang , Bo Xiong , Rui Hou , Melanie Kambadur , Dhruv Mahajan , Hannaneh Hajishirzi , Liang Tan

Exact structured inference with neural network scoring functions is computationally challenging but several methods have been proposed for approximating inference. One approach is to perform gradient descent with respect to the output…

Computation and Language · Computer Science 2019-07-09 Lifu Tu , Kevin Gimpel

Scoring rules are an established way of comparing predictive performances across model classes. In the context of survival analysis, they require adaptation in order to accommodate censoring. This work investigates using scoring rules for…

Machine Learning · Computer Science 2024-11-14 Philipp Kopper , David Rügamer , Raphael Sonabend , Bernd Bischl , Andreas Bender

Users often interpret and select agent skills through their SKILL markdown specifications. To protect users, existing audits mainly focus on malicious or unsafe skills. We study the complementary question of whether specifications help…

Human-Computer Interaction · Computer Science 2026-05-21 Zikai Alex Wen

Introductory programming courses often emphasize mastering syntax and basic constructs before progressing to more complex and interesting programs. This bottom-up approach can be frustrating for novices, shifting the focus away from problem…

Computers and Society · Computer Science 2024-10-07 Chris Kerslake , Paul Denny , David H Smith , James Prather , Juho Leinonen , Andrew Luxton-Reilly , Stephen MacNeil

Recent years have seen growing interest in the retrofitting of type systems onto dynamically-typed programming languages, in order to improve type safety, programmer productivity, or performance. In such cases, type system developers must…

Programming Languages · Computer Science 2016-05-05 Esben Andreasen , Colin S. Gordon , Satish Chandra , Manu Sridharan , Frank Tip , Koushik Sen

Process mining leverages event data extracted from IT systems to generate insights into the business processes of organizations. Such insights benefit from explicitly considering the frequency of behavior in business processes, which is…

Formal Languages and Automata Theory · Computer Science 2025-07-10 Tian Li , Artem Polyvyanyy , Sander J. J. Leemans