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Recently, the emergence of large language models (LLMs) has motivated integrating language descriptions into graphs, forming text-attributed graphs (TAGs) that enhance model encoding capabilities from a data-centric perspective. A review of…

Machine Learning · Computer Science 2026-02-03 Zhihan Zhang , Xunkai Li , Lei Zhu , Guang Zeng , Bowen Fan , Yanzhe Wen , Hongchao Qin , Rong-Hua Li , Guoren Wang

Graphs are a generalized concept that encompasses more complex data structures than trees, such as difference lists, doubly-linked lists, skip lists, and leaf-linked trees. Normally, these structures are handled with destructive assignments…

Programming Languages · Computer Science 2022-09-13 Jin Sano , Naoki Yamamoto , Kazunori Ueda

Large language models (LLMs) achieve impressive results over various tasks, and ever-expanding public repositories contain an abundance of pre-trained models. Therefore, identifying the best-performing LLM for a given task is a significant…

Computation and Language · Computer Science 2025-11-13 Idan Kashani , Avi Mendelson , Yaniv Nemcovsky

In the logic programming paradigm, a program is defined by a set of methods, each of which can be executed when specific conditions are met during the current state of an execution. The semantics of these programs can be elegantly…

Logic in Computer Science · Computer Science 2024-10-02 Matteo Acclavio , Roberto Maieli

Instead of a monolithic programming language trying to cover all features of interest, some programming systems are designed by combining together simpler languages that cooperate to cover the same feature space. This can improve usability…

Programming Languages · Computer Science 2018-04-13 Gabriel Scherer , Max New , Nick Rioux , Amal Ahmed

Extending Large Language Models (LLMs) to advanced applications requires reliable structured output generation. Existing methods which often rely on rigid JSON schemas, can lead to unreliable outputs, diminished reasoning capabilities, and…

Computation and Language · Computer Science 2024-10-25 Chandra Irugalbandara

LLM-powered systems require complex multi-step decision-making abilities to solve real-world tasks, yet current planning approaches face a trade-off between the high latency of inference-time search and the limited generalization of…

Artificial Intelligence · Computer Science 2026-04-17 Xin Xie , Dongyun Xue , Wuguannan Yao , Mingxiao Feng , Wengang Zhou , Xiang Qi , Houqiang Li , Peng Zhang

This paper presents an operational semantics for UML activity diagrams. The purpose of this semantics is three-fold: to give a robust basis for verifying model correctness; to help validate model transformations; and to provide a…

Logic in Computer Science · Computer Science 2016-04-11 Zamira Daw , Rance Cleaveland

Domain-specific languages are becoming increasingly important. Almost every application touches multiple domains. But how to define, use, and combine multiple DSLs within the same application? The most common approach is to split the…

Programming Languages · Computer Science 2016-12-13 Piotr Danilewski , Philipp Slusallek

When a new programming language appears, the syntax and intended behaviour of its programs need to be specified. The behaviour of each language construct can be concisely specified by translating it to fundamental constructs (funcons),…

Programming Languages · Computer Science 2023-08-22 Peter D. Mosses

Temporal Logic (TL) can be used to rigorously specify complex high-level specification for systems in many engineering applications. The translation between natural language (NL) and TL has been under-explored due to the lack of dataset and…

Computation and Language · Computer Science 2024-03-25 Yongchao Chen , Rujul Gandhi , Yang Zhang , Chuchu Fan

Large Language Models (LLMs) have demonstrated remarkable improvements in reasoning and planning through increased test-time compute, often by framing problem-solving as a search process. While methods like Monte Carlo Tree Search (MCTS)…

Artificial Intelligence · Computer Science 2025-06-06 Nathan Herr , Tim Rocktäschel , Roberta Raileanu

Large language models (LLMs) have revolutionized natural language processing by achieving state-of-the-art performance across various tasks. Recently, their effectiveness as embedding models has gained attention, marking a paradigm shift…

Computation and Language · Computer Science 2025-07-28 Chongyang Tao , Tao Shen , Shen Gao , Junshuo Zhang , Zhen Li , Kai Hua , Wenpeng Hu , Zhengwei Tao , Shuai Ma

Source code comes in different shapes and forms. Previous research has already shown code to be more predictable than natural language as well as highlighted its statistical predictability at the token level: source code can be natural.…

Software Engineering · Computer Science 2025-04-14 Profir-Petru Pârţachi , Mahito Sugiyama

Semantic data fuels many different applications, but is still lacking proper integration into programming languages. Untyped access is error-prone while mapping approaches cannot fully capture the conceptualization of semantic data. In this…

Programming Languages · Computer Science 2016-10-25 Martin Leinberger , Ralf Lämmel , Steffen Staab

Because of their superior ability to preserve sequence information over time, Long Short-Term Memory (LSTM) networks, a type of recurrent neural network with a more complex computational unit, have obtained strong results on a variety of…

Computation and Language · Computer Science 2015-06-02 Kai Sheng Tai , Richard Socher , Christopher D. Manning

Context-Oriented programming languages provide us with primitive constructs to adapt program behaviour depending on the evolution of their operational environment, namely the context. In previous work we proposed ML_CoDa, a context-oriented…

Programming Languages · Computer Science 2015-12-25 Andrea Canciani , Pierpaolo Degano , Gian-Luigi Ferrari , Letterio Galletta

This paper presents Tree Notation, a new simple, universal syntax. Language designers can invent new programming languages, called Tree Languages, on top of Tree Notation. Tree Languages have a number of advantages over traditional…

Programming Languages · Computer Science 2017-10-25 Breck Yunits

Large language models (LLMs) are emerging as few-shot learners capable of handling a variety of tasks, including comprehension, planning, reasoning, question answering, arithmetic calculations, and more. At the core of these capabilities is…

Databases · Computer Science 2024-11-05 Yu Pan , Hongfeng Yu , Tianjiao Zhao , Jianxin Sun

Neural-symbolic methods have demonstrated efficiency in enhancing the reasoning abilities of large language models (LLMs). However, existing methods mainly rely on syntactically mapping natural languages to complete formal languages like…

Computation and Language · Computer Science 2024-06-04 Yiming Wang , Zhuosheng Zhang , Pei Zhang , Baosong Yang , Rui Wang