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Recent research has highlighted the potential of large language models (LLMs) to improve their problem-solving capabilities with the aid of suitable external tools. In our work, we further advance this concept by introducing a closed-loop…

Machine Learning · Computer Science 2024-03-12 Tianle Cai , Xuezhi Wang , Tengyu Ma , Xinyun Chen , Denny Zhou

The purpose of this paper is to address some of the challenges of formally specifying components of shared-memory concurrent programs. The focus is to provide an abstract specification of a component that is suitable for use both by clients…

Programming Languages · Computer Science 2018-10-24 Ian J. Hayes

This paper describes our experiences creating Tornado: a practical and efficient heterogeneous programming framework for managed languages. The novel aspect of Tornado is that it turns the programming of heterogeneous systems from an…

Programming Languages · Computer Science 2018-03-02 James Clarkson , Christos Kotselidis

Human beings possess the most sophisticated computational machinery in the known universe. We can understand language of rich descriptive power, and communicate in the same environment with astonishing clarity. Two of the many contributors…

Computation and Language · Computer Science 2021-01-01 Karthikeya Ramesh Kaushik , Andrea E. Martin

We consider the problem of automatically inferring specifications in the branching-time logic, Computation Tree Logic (CTL), from a given system. Designing functional and usable specifications has always been one of the biggest challenges…

Logic in Computer Science · Computer Science 2023-10-24 Rajarshi Roy , Daniel Neider

Component-Based Development (CBD) is a popular approach to mitigating the costs of creating software systems. However, it is not clear to what extent the core component selection and adaptation activities of CBD can be implemented to…

Software Engineering · Computer Science 2022-05-11 Todd Wareham , Marieke Sweers

Large Language Models (LLMs) have demonstrated impressive ability in generation and reasoning tasks but struggle with handling up-to-date knowledge, leading to inaccuracies or hallucinations. Retrieval-Augmented Generation (RAG) mitigates…

Databases · Computer Science 2026-03-13 Ziting Wang , Haitao Yuan , Wei Dong , Gao Cong , Feifei Li

Most modern software systems (operating systems like Linux or Android, Web browsers like Firefox or Chrome, video encoders like ffmpeg, x264 or VLC, mobile and cloud applications, etc.) are highly-configurable. Hundreds of configuration…

Software Engineering · Computer Science 2019-06-10 Juliana Alves Pereira , Hugo Martin , Mathieu Acher , Jean-Marc Jézéquel , Goetz Botterweck , Anthony Ventresque

The Object Constraint Language (OCL) has been widely used in the modeling community to complement software models for precisely defining constraints and business rules for the modeled systems. There is a limited number of tools supporting…

Software Engineering · Computer Science 2025-03-04 Fitash Ul Haq , Jordi Cabot

This paper describes the design and implementation of CRAQL (Composable Repository Analysis and Query Language), a new query language for source code. The growth of source code mining and its applications suggest the need for a query…

Programming Languages · Computer Science 2019-01-29 Blake Johnson , Rahul Simha

Correctness-by-Construction (CbC) is an incremental program construction process to construct functionally correct programs. The programs are constructed stepwise along with a specification that is inherently guaranteed to be satisfied. CbC…

Logic in Computer Science · Computer Science 2024-02-14 Tobias Runge , Tabea Bordis , Alex Potanin , Thomas Thüm , Ina Schaefer

This research addresses the question, which characteristics a cognitive architecture must have to leverage the benefits of natural language in Co-Constructive Task Learning (CCTL). To provide context, we first discuss Interactive Task…

Robotics · Computer Science 2025-09-03 Manuel Scheibl , Birte Richter , Alissa Müller , Michael Beetz , Britta Wrede

Feature attribution methods, such as SHAP and LIME, explain machine learning model predictions by quantifying the influence of each input component. When applying feature attributions to explain language models, a basic question is defining…

Human-Computer Interaction · Computer Science 2025-09-26 Alan Boyle , Furui Cheng , Vilém Zouhar , Mennatallah El-Assady

Long context large language models (LLMs) are deployed in many real-world applications such as RAG, agent, and broad LLM-integrated applications. Given an instruction and a long context (e.g., documents, PDF files, webpages), a long context…

Cryptography and Security · Computer Science 2025-06-27 Yanting Wang , Wei Zou , Runpeng Geng , Jinyuan Jia

Large language models (LLMs) are often augmented with tools to solve complex tasks. By generating code snippets and executing them through task-specific Application Programming Interfaces (APIs), they can offload certain functions to…

Computation and Language · Computer Science 2024-03-14 Lifan Yuan , Yangyi Chen , Xingyao Wang , Yi R. Fung , Hao Peng , Heng Ji

Neurons are the fundamental building blocks of deep neural networks, and their interconnections allow AI to achieve unprecedented results. Motivated by the goal of understanding how neurons encode information, compositional explanations…

Computer Vision and Pattern Recognition · Computer Science 2025-11-27 Biagio La Rosa , Leilani H. Gilpin

Owing to the impressive general intelligence of large language models (LLMs), there has been a growing trend to integrate them into recommender systems to gain a more profound insight into human interests and intentions. Existing LLMs-based…

Information Retrieval · Computer Science 2024-10-29 Chuang Zhao , Xing Su , Ming He , Hongke Zhao , Jianping Fan , Xiaomeng Li

Adaptation of software components is an important issue in Component Based Software Engineering (CBSE). Building a system from reusable or Commercial-Off-The-Shelf (COTS) components introduces a set of issues, mainly related to…

Software Engineering · Computer Science 2014-12-02 Marco Autili , Paola Inverardi , Massimo Tivoli

Efficient instruction tuning aims to enhance the ultimate performance of large language models (LLMs) trained on a given instruction dataset. Curriculum learning as a typical data organization strategy has shown preliminary effectiveness in…

Computation and Language · Computer Science 2025-11-04 Yangning Li , Tingwei Lu , Yinghui Li , Yankai Chen , Wei-Chieh Huang , Wenhao Jiang , Hui Wang , Hai-Tao Zheng , Philip S. Yu

Large language model (LLM) platforms, such as ChatGPT, have recently begun offering an app ecosystem to interface with third-party services on the internet. While these apps extend the capabilities of LLM platforms, they are developed by…

Cryptography and Security · Computer Science 2024-07-30 Umar Iqbal , Tadayoshi Kohno , Franziska Roesner
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