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Related papers: Tokenizing Loops of Antibodies

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In Simultaneous Localization and Mapping (SLAM), Loop Closure Detection (LCD) is essential to minimize drift when recognizing previously visited places. Visual Bag-of-Words (vBoW) has been an LCD algorithm of choice for many…

Computer Vision and Pattern Recognition · Computer Science 2022-09-27 Jonathan J. Y. Kim , Martin Urschler , Patricia J. Riddle , Jörg S. Wicker

Camouflaged Object Detection (COD) aims to segment objects that are highly integrated with the background in terms of color, texture, and structure, making it a highly challenging task in computer vision. Although existing methods introduce…

Computer Vision and Pattern Recognition · Computer Science 2026-03-26 Min Zhang

Discrete motion tokenization has recently enabled Large Language Models (LLMs) to serve as versatile backbones for motion understanding and motion-language reasoning. However, existing pipelines typically decouple motion quantization from…

Computer Vision and Pattern Recognition · Computer Science 2026-03-20 Zhankai Ye , Bofan Li , Yukai Jin , Shuoqiu Li , Wei Wang , Yanfu Zhang , Shangqian Gao , Xin Liu

Mathematical reasoning tasks pose significant challenges for large language models (LLMs) because they require precise logical deduction and sequence analysis. In this work, we introduce the concept of critical tokens -- elements within…

Computation and Language · Computer Science 2025-01-14 Zicheng Lin , Tian Liang , Jiahao Xu , Qiuzhi Lin , Xing Wang , Ruilin Luo , Chufan Shi , Siheng Li , Yujiu Yang , Zhaopeng Tu

This paper introduces a novel in-context learning (ICL) framework, inspired by large language models (LLMs), for soft-input soft-output channel equalization in coded multiple-input multiple-output (MIMO) systems. The proposed approach…

Signal Processing · Electrical Eng. & Systems 2025-05-12 Zihang Song , Matteo Zecchin , Bipin Rajendran , Osvaldo Simeone

Accurate prognosis for Glioblastoma (GBM) using deep learning (DL) is hindered by extreme spatial and structural heterogeneity. Moreover, inconsistent MRI acquisition protocols across institutions hinder generalizability of models.…

Machine Learning · Computer Science 2026-02-13 Ankita Paul , Wenyi Wang

We attempt to set a mathematical foundation of immunology and amino acid chains. To measure the similarities of these chains, a kernel on strings is defined using only the sequence of the chains and a good amino acid substitution matrix…

Machine Learning · Statistics 2012-06-26 Wen-Jun Shen , Hau-San Wong , Quan-Wu Xiao , Xin Guo , Stephen Smale

Iconicity, the resemblance between linguistic form and meaning, is pervasive in signed languages, offering a natural testbed for visual grounding. For vision-language models (VLMs), the challenge is to recover such essential mappings from…

Computer Vision and Pattern Recognition · Computer Science 2026-05-21 Onur Keleş , Aslı Özyürek , Gerardo Ortega , Kadir Gökgöz , Esam Ghaleb

Geometry and topology are the main factors that determine the functional properties of proteins. In this work, we show how to use the Gauss linking integral (GLN) in the form of a matrix diagram - for a pair of a loop and a tail - to study…

Biomolecules · Quantitative Biology 2020-05-12 Wanda Niemyska , Kenneth C. Millett , Joanna I. Sulkowska

Accurate segmentation of neuronal cells in fluorescence microscopy is a fundamental task for quantitative analysis in computational neuroscience. However, it is significantly impeded by challenges such as the coexistence of densely packed…

Computer Vision and Pattern Recognition · Computer Science 2026-01-21 Ujjwal Jain , Oshin Misra , Roshni Chakraborty , Mahua Bhattacharya

Understanding the relationship between antibody sequence, structure and function is essential for the design of antibody-based therapeutics and research tools. Recently, machine learning (ML) models mostly based on the application of large…

Quantitative Methods · Quantitative Biology 2025-10-29 Kevin Michalewicz , Mauricio Barahona , Barbara Bravi

In-context learning (ICL) emerges as a promising capability of large language models (LLMs) by providing them with demonstration examples to perform diverse tasks. However, the underlying mechanism of how LLMs learn from the provided…

Computation and Language · Computer Science 2023-12-20 Lean Wang , Lei Li , Damai Dai , Deli Chen , Hao Zhou , Fandong Meng , Jie Zhou , Xu Sun

Existing clustering methods for functional data often prioritize partitioning accuracy over interpretability, making it challenging to extract meaningful insights when the data-generating process follows a specific underlying structure and…

Human metapneumovirus (hMPV) poses serious risks to pediatric, elderly, and immunocompromised populations. Traditional antibody discovery pipelines require 10-12 months, limiting their applicability for rapid outbreak response. This project…

Quantitative Methods · Quantitative Biology 2025-09-01 Shawnak Shivakumar , Matthew Sandora

Existing methods for arbitrary-shaped text detection in natural scenes face two critical issues, i.e., 1) fracture detections at the gaps in a text instance; and 2) inaccurate detections of arbitrary-shaped text instances with diverse…

Computer Vision and Pattern Recognition · Computer Science 2022-04-21 Bo Du , Jian Ye , Jing Zhang , Juhua Liu , Dacheng Tao

Equivariant graph neural network (GNN) methods for antibody complementarity-determining region (CDR) design achieve the highest sequence recovery but suffer from severe vocabulary collapse. The current best GNN methods over-predict very few…

Machine Learning · Computer Science 2026-05-21 Mansoor Ahmed , Sujin Lee , Umar Khayaz , Murray Patterson

Somatic hypermutations of immunoglobulin (Ig) genes occuring during affinity maturation drive B-cell receptors' ability to evolve strong binding to their antigenic targets. The landscape of these mutations is highly heterogeneous, with…

Genomics · Quantitative Biology 2021-02-05 Natanael Spisak , Aleksandra M. Walczak , Thierry Mora

This paper proposes an introspective deep metric learning (IDML) framework for uncertainty-aware comparisons of images. Conventional deep metric learning methods focus on learning a discriminative embedding to describe the semantic features…

Computer Vision and Pattern Recognition · Computer Science 2023-09-20 Chengkun Wang , Wenzhao Zheng , Zheng Zhu , Jie Zhou , Jiwen Lu

Computational antibody CDR design methods condition on antigen structure to generate binding loops, yet existing architectures conflate two fundamentally distinct sub-problems: identifying which CDR positions will contact the antigen, and…

Machine Learning · Computer Science 2026-05-22 Mansoor Ahmed , Spencer VonBank , Nadeem Taj , Sujin Lee , Naila Jan , Murray Patterson

In-context learning (ICL) enables Large Vision-Language Models (LVLMs) to adapt to new tasks without parameter updates, using a few demonstrations from a large support set. However, selecting informative demonstrations leads to high…

Computer Vision and Pattern Recognition · Computer Science 2025-07-31 Huiyi Chen , Jiawei Peng , Kaihua Tang , Xin Geng , Xu Yang