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A rational framework is proposed to explain how we accommodate unbounded sensory input within bounded memory. According to this framework, memory is stored as a statistic-like representation that is repeatedly summarized and compressed to…

Neurons and Cognition · Quantitative Biology 2026-01-21 Alain de Cheveigné

Refactoring is an established technique from the object-oriented (OO) programming community to restructure code: it aims at improving software readability, maintainability and extensibility. Although refactoring is not tied to the…

Software Engineering · Computer Science 2007-05-23 Alexander Serebrenik , Tom Schrijvers , Bart Demoen

Most research on lifelong learning applies to images or games, but not language. We present LAMOL, a simple yet effective method for lifelong language learning (LLL) based on language modeling. LAMOL replays pseudo-samples of previous tasks…

Computation and Language · Computer Science 2019-12-24 Fan-Keng Sun , Cheng-Hao Ho , Hung-Yi Lee

Long-term memory is essential for natural, realistic dialogue. However, current large language model (LLM) memory systems rely on either brute-force context expansion or static retrieval pipelines that fail on edge-constrained devices. We…

Computation and Language · Computer Science 2025-10-13 Aneesh Jonelagadda , Christina Hahn , Haoze Zheng , Salvatore Penachio

In the past, the semantic issues raised by the non-monotonic nature of aggregates often prevented their use in the recursive statements of logic programs and deductive databases. However, the recently introduced notion of Pre-mappability…

Logic in Computer Science · Computer Science 2019-09-19 Ariyam Das , Youfu Li , Jin Wang , Mingda Li , Carlo Zaniolo

In lifelong learning, data are used to improve performance not only on the present task, but also on past and future (unencountered) tasks. While typical transfer learning algorithms can improve performance on future tasks, their…

Logic programming is a flexible programming paradigm due to the use of predicates without a fixed data flow. To extend logic languages with the compact notation of functional programming, there are various proposals to map evaluable…

Programming Languages · Computer Science 2022-05-17 Michael Hanus

Sequential programming and work-flow programming are two useful, but radically different, ways of describing computational processing. Of the two, it is sequential programming that we teach all programmers and support by programming…

Programming Languages · Computer Science 2011-08-24 William Harrison

Large Language Models are transforming software development by automatically generating code. Current prompting techniques such as Chain-of-Thought (CoT) suggest tasks step by step and the reasoning process follows a linear structure, which…

Software Engineering · Computer Science 2025-03-18 Ruwei Pan , Hongyu Zhang

Autoformalization aims to produce formal statements that compile and faithfully preserve the intended meaning of informal mathematics. Yet standard single-output evaluation protocols collapse a many-to-many problem into a single-output…

Artificial Intelligence · Computer Science 2026-05-29 Haijian Lu , Wei Wang , Jing Liu

This paper describes an efficient and robust implementation of a bi-directional, head-driven parser for constraint-based grammars. This parser is developed for the OVIS system: a Dutch spoken dialogue system in which information about…

cmp-lg · Computer Science 2008-02-03 Gertjan van Noord

Models trained on a new task typically degrade on prior tasks, a phenomenon known as forgetting. Traditionally, mitigating forgetting has required replaying stored exemplars from prior tasks, which is often impractical. By contrast,…

Machine Learning · Computer Science 2026-05-26 Martin Marek , Dongkyu Cho , Shikai Qiu , Rumi Chunara , Pavel Izmailov , Andrew Gordon Wilson

Fine-tuning Large Language Models (LLMs) on multi-turn reasoning datasets requires N (number of turns) separate forward passes per conversation due to reasoning token visibility constraints, as reasoning tokens for a turn are discarded in…

Computation and Language · Computer Science 2025-07-14 Ritesh Goru , Shanay Mehta , Prateek Jain

Refactoring is an established technique from the OO-community to restructure code: it aims at improving software readability, maintainability and extensibility. Although refactoring is not tied to the OO-paradigm in particular, its ideas…

Software Engineering · Computer Science 2007-05-23 Tom Schrijvers , Alexander Serebrenik

Forgetting - or variable elimination - is an operation that allows the removal, from a knowledge base, of middle variables no longer deemed relevant. In recent years, many different approaches for forgetting in Answer Set Programming have…

Artificial Intelligence · Computer Science 2021-12-08 Ricardo Gonçalves , Matthias Knorr , João Leite

Continual learning is an emerging paradigm in machine learning, wherein a model is exposed in an online fashion to data from multiple different distributions (i.e. environments), and is expected to adapt to the distribution change.…

Machine Learning · Computer Science 2022-03-29 Binghui Peng , Andrej Risteski

Spaced repetition is a technique for efficient memorization which uses repeated, spaced review of content to improve long-term retention. Can we find the optimal reviewing schedule to maximize the benefits of spaced repetition? In this…

A logic program is an executable specification. For example, merge sort in pure Prolog is a logical formula, yet shows creditable performance on long linked lists. But such executable specifications are a compromise: the logic is distorted…

Programming Languages · Computer Science 2015-09-29 M. H. van Emden

Jailbreak attacks on large language models (LLMs) aim to induce LLMs to produce content that they are expected to refuse. Automated black-box jailbreak generation is especially important for safety evaluation, where the attacker observes…

Cryptography and Security · Computer Science 2026-05-29 Junke Zhang , Jianwei Wang , Sishuo Chen , Yizhang He , Qingshuai Feng , Zhengyi Yang

Conversational recommender systems (CRSs) aim to capture user preferences and provide personalized recommendations through multi-round natural language dialogues. However, most existing CRS models mainly focus on dialogue comprehension and…

Information Retrieval · Computer Science 2024-07-09 Yunjia Xi , Weiwen Liu , Jianghao Lin , Bo Chen , Ruiming Tang , Weinan Zhang , Yong Yu