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Gradually typed languages allow statically typed and dynamically typed code to interact while maintaining benefits of both styles. The key to reasoning about these mixed programs is Siek-Vitousek-Cimini-Boyland's (dynamic) gradual…

Programming Languages · Computer Science 2018-07-10 Max S. New , Amal Ahmed

Inferring topics from the overwhelming amount of short texts becomes a critical but challenging task for many content analysis tasks, such as content charactering, user interest profiling, and emerging topic detecting. Existing methods such…

Computation and Language · Computer Science 2016-09-28 Jipeng Qiang , Ping Chen , Tong Wang , Xindong Wu

Entity typing aims at predicting one or more words that describe the type(s) of a specific mention in a sentence. Due to shortcuts from surface patterns to annotated entity labels and biased training, existing entity typing models are…

Computation and Language · Computer Science 2022-10-27 Nan Xu , Fei Wang , Bangzheng Li , Mingtao Dong , Muhao Chen

This paper shows that the recent approach to quantitative typing systems for programming languages can be extended to pattern matching features. Indeed, we define two resource aware type systems, named U and E, for a lambda-calculus…

Logic in Computer Science · Computer Science 2019-12-05 Sandra Alves , Delia Kesner , Daniel Ventura

Recent models of intensional type theory have been constructed in algebraic weak factorization systems (AWFSs). AWFSs give rise to comprehension categories that feature non-trivial morphisms between types; these morphisms are not used in…

Programming Languages · Computer Science 2025-11-18 Niyousha Najmaei , Niels van der Weide , Benedikt Ahrens , Paige Randall North

Cross-lingual alignment in pretrained language models enables knowledge transfer across languages. Similar alignment has been reported in Whisper-style speech encoders, based on spoken translation retrieval using representational…

Computation and Language · Computer Science 2026-04-07 Ryan Soh-Eun Shim , Domenico De Cristofaro , Chengzhi Martin Hu , Alessandro Vietti , Barbara Plank

The acoustic-to-word model based on the Connectionist Temporal Classification (CTC) criterion is a natural end-to-end (E2E) system directly targeting word as output unit. Two issues exist in the system: first, the current output of the CTC…

Computation and Language · Computer Science 2019-09-06 Amit Das , Jinyu Li , Guoli Ye , Rui Zhao , Yifan Gong

This article presents a bidirectional type system for the Calculus of Inductive Constructions (CIC). It introduces a new judgement intermediate between the usual inference and checking, dubbed constrained inference, to handle the presence…

Programming Languages · Computer Science 2021-04-20 Meven Lennon-Bertrand

When we investigate a type system, it is helpful if we can establish the well-foundedness of types or terms with respect to a certain hierarchy, and the Extended Calculus of Constructions (called $ECC$, defined and studied comprehensively…

Logic in Computer Science · Computer Science 2021-05-12 Eitetsu Ken , Masaki Natori , Kenji Tojo , Kazuki Watanabe

Word embedding models offer continuous vector representations that can capture rich contextual semantics based on their word co-occurrence patterns. While these word vectors can provide very effective features used in many NLP tasks such as…

Computation and Language · Computer Science 2017-02-27 Cem Safak Sahin , Rajmonda S. Caceres , Brandon Oselio , William M. Campbell

Recent advancements in language representation learning primarily emphasize language modeling for deriving meaningful representations, often neglecting style-specific considerations. This study addresses this gap by creating generic,…

Machine Learning · Computer Science 2025-03-17 Phil Ostheimer , Marius Kloft , Sophie Fellenz

Classical Processes (CP) is a calculus where the proof theory of classical linear logic types communicating processes with mobile channels, a la pi-calculus. Its construction builds on a recent propositions as types correspondence between…

Logic in Computer Science · Computer Science 2018-02-09 Fabrizio Montesi

The words-as-classifiers model of grounded lexical semantics learns a semantic fitness score between physical entities and the words that are used to denote those entities. In this paper, we explore how such a model can incrementally…

Computation and Language · Computer Science 2019-11-11 Daniele Moro , Stacy Black , Casey Kennington

Learning high-quality embeddings for rare words is a hard problem because of sparse context information. Mimicking (Pinter et al., 2017) has been proposed as a solution: given embeddings learned by a standard algorithm, a model is first…

Computation and Language · Computer Science 2019-04-08 Timo Schick , Hinrich Schütze

Type soundness is an important property of modern programming languages. In this paper we explore the idea that "well-typed languages are sound": the idea that the appropriate typing discipline over language specifications guarantees that…

Programming Languages · Computer Science 2016-11-17 Matteo Cimini , Dale Miller , Jeremy G. Siek

A pattern p (i.e., a string of variables and terminals) matches a word w, if w can be obtained by uniformly replacing the variables of p by terminal words. The respective matching problem, i.e., deciding whether or not a given pattern…

Data Structures and Algorithms · Computer Science 2019-07-30 Florin Manea , Markus L. Schmid

We investigate, in the context of functional prototype-based lan- guages, a calculus of objects which might extend themselves upon receiving a message, a capability referred to by Cardelli as a self-inflicted operation. We present a sound…

Programming Languages · Computer Science 2018-08-14 Ciaffaglione Alberto , Di Gianantonio Pietro , Honsell Furio , Liquori Luigi

These lecture notes describe the design of a minimal dependently-typed language called "pi-forall" and walk through the implementation of its type checker. They are based on lectures given at the Oregon Programming Languages Summer School…

Programming Languages · Computer Science 2023-07-13 Stephanie Weirich

Correlated topic modeling has been limited to small model and problem sizes due to their high computational cost and poor scaling. In this paper, we propose a new model which learns compact topic embeddings and captures topic correlations…

Machine Learning · Computer Science 2017-07-04 Junxian He , Zhiting Hu , Taylor Berg-Kirkpatrick , Ying Huang , Eric P. Xing

Software synthesis - the process of generating complete, general-purpose programs from specifications - has become a hot research topic in the past few years. For decades the problem was thought to be insurmountable: the search space of…

Programming Languages · Computer Science 2015-10-29 Jonathan Frankle