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The missing modality issue is critical but non-trivial to be solved by multi-modal models. Current methods aiming to handle the missing modality problem in multi-modal tasks, either deal with missing modalities only during evaluation or…

Computer Vision and Pattern Recognition · Computer Science 2024-06-14 Hu Wang , Yuanhong Chen , Congbo Ma , Jodie Avery , Louise Hull , Gustavo Carneiro

The present work pursues the aim to draw attention to unique possibilities of the skew-symmetric differential forms. At present the theory of skew-symmetric exterior differential forms that possess invariant properties has been developed.…

General Mathematics · Mathematics 2007-05-23 L. I. Petrova

Recent efforts on combining deep models with probabilistic graphical models are promising in providing flexible models that are also easy to interpret. We propose a variational message-passing algorithm for variational inference in such…

Machine Learning · Statistics 2018-06-15 Wu Lin , Nicolas Hubacher , Mohammad Emtiyaz Khan

Segmental structure is a common pattern in many types of sequences such as phrases in human languages. In this paper, we present a probabilistic model for sequences via their segmentations. The probability of a segmented sequence is…

Machine Learning · Statistics 2018-07-20 Chong Wang , Yining Wang , Po-Sen Huang , Abdelrahman Mohamed , Dengyong Zhou , Li Deng

This article introduces a new symbolic regression algorithm based on the SPINEX (Similarity-based Predictions with Explainable Neighbors Exploration) family. This new algorithm (SPINEX_SymbolicRegression) adopts a similarity-based approach…

Machine Learning · Computer Science 2024-11-07 MZ Naser , Ahmed Z Naser

The representation space of pretrained Language Models (LMs) encodes rich information about words and their relationships (e.g., similarity, hypernymy, polysemy) as well as abstract semantic notions (e.g., intensity). In this paper, we…

Computation and Language · Computer Science 2023-06-02 Qing Lyu , Marianna Apidianaki , Chris Callison-Burch

Understanding training dynamics and feature evolution is crucial for the mechanistic interpretability of large language models (LLMs). Although sparse autoencoders (SAEs) have been used to identify features within LLMs, a clear picture of…

Machine Learning · Computer Science 2025-06-04 Yang Xu , Yi Wang , Hengguan Huang , Hao Wang

Probabilistic graphical models combine the graph theory and probability theory to give a multivariate statistical modeling. They provide a unified description of uncertainty using probability and complexity using the graphical model.…

Machine Learning · Statistics 2011-11-30 Yang Zhou

We explore inflectional morphology as an example of the relationship of the discrete and the continuous in linguistics. The grammar requests a form of a lexeme by specifying a set of feature values, which corresponds to a corner M of a…

Computation and Language · Computer Science 2017-03-14 John Goldsmith , Eric Rosen

The ramification method in Implicit Computational Complexity has been associated with functional programming, but adapting it to generic imperative programming is highly desirable, given the wider algorithmic applicability of imperative…

Logic in Computer Science · Computer Science 2020-02-20 Daniel Leivant

Type refinements combine the compositionality of typechecking with the expressivity of program logics, offering a synergistic approach to program verification. In this paper we apply dependent type refinements to SAX, a futures-based…

Programming Languages · Computer Science 2024-02-14 Siva Somayyajula , Frank Pfenning

This note is about using computational effects for scalability. With this method, the specification gets more and more complex while its semantics gets more and more correct. We show, from two fundamental examples, that it is possible to…

Logic in Computer Science · Computer Science 2013-07-02 Dominique Duval

The current advances in generative AI for learning large neural network models with the capability to produce essays, images, music and even 3D assets from text prompts create opportunities for a manifold of disciplines. In the present…

Computation and Language · Computer Science 2023-07-06 Thiago Rios , Stefan Menzel , Bernhard Sendhoff

We present a fully abstract model of a call-by-value language with higher-order functions, recursion and natural numbers, as an exponential ideal in a topos. Our model is inspired by the fully abstract models of O'Hearn, Riecke and…

Programming Languages · Computer Science 2021-07-07 Cristina Matache , Sean Moss , Sam Staton

Event Shape Sorting is a novel method which is devised to organise a sample of collision events in such a way, that events with similar final state distribution of hadrons end up sorted close to each other. Such events are likely to have…

Nuclear Theory · Physics 2020-06-24 Boris Tomasik , Jakub Cimerman

Generative language models define distributions over sequences of tokens that can represent essentially any combination of data modalities (e.g., any permutation of image tokens from VQ-VAEs, speech tokens from HuBERT, BPE tokens for…

A type system is introduced for a generic Object Oriented programming language in order to infer resource upper bounds. A sound andcomplete characterization of the set of polynomial time computable functions is obtained. As a consequence,…

Programming Languages · Computer Science 2018-02-20 Emmanuel Hainry , Romain Péchoux

Sequence labeling architectures use word embeddings for capturing similarity, but suffer when handling previously unseen or rare words. We investigate character-level extensions to such models and propose a novel architecture for combining…

Computation and Language · Computer Science 2016-11-15 Marek Rei , Gamal K. O. Crichton , Sampo Pyysalo

We introduce an invariant, associated to a coherent sheaf over a projective morphism of schemes, which controls when sheaf cohomology can be passed through the given morphism. We then use this invariant to estimate the stability indexes of…

Commutative Algebra · Mathematics 2019-01-15 Sankhaneel Bisui , Huy Tai Ha , Abu Chackalamannil Thomas

We propose a graph-based mechanism to extract rich-emotion bearing patterns, which fosters a deeper analysis of online emotional expressions, from a corpus. The patterns are then enriched with word embeddings and evaluated through several…

Computation and Language · Computer Science 2018-04-25 Elvis Saravia , Hsien-Chi Toby Liu , Yi-Shin Chen
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