Model: noystl/recomb-pred-all-mpnet-base
Author: noystl
Pipeline: sentence-similarity
Library: sentence-transformers
Tags: sentence-transformers, safetensors, mpnet, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:784827, loss:ContrastiveLoss, en, dataset:noystl/Recombination-Pred, arxiv:2505.20779, arxiv:1908.10084, base_model:sentence-transformers/all-mpnet-base-v2, base_model:finetune:sentence-transformers/all-mpnet-base-v2, license:cc, endpoints_compatible, region:us
Base models (finetune): id: sentence-transformers/all-mpnet-base-v2
Card metadata: tags: sentence-transformers, sentence-similarity, feature-extraction, generated_from_trainer, dataset_size:784827, loss:ContrastiveLoss
base_model: sentence-transformers/all-mpnet-base-v2
widget: source_sentence: Background: The study addresses the need for effective tools that allow both novice and expert users to analyze the diversity of news coverage about events. It highlights the importance of tailoring the interface to accommodate non-expert users while also considering the insights of journalism-savvy users, indicating a gap in existing systems that cater to varying levels of expertise in news analysis.
Contribution: Combine 'a coordinated visualization interface tailored for visualization non-expert users' and 
sentences: a method considering lexical relationships, cross-modality self-supervised learning via masked visual language modeling, cognitive models of chaining, source_sentence: Background: Existing methods for anomaly detection on dynamic graphs struggle with capturing complex time information in graph structures and generating effective negative samples for unsupervised learning. These challenges highlight the need for improved methodologies that can address the limitations of current approaches in this field.
Contribution: Combine 'a message-passing framework' and 
sentences: the grouping task, a forecaster, the optimisation algorithm producing the learnable model, source_sentence: Background: The accuracy of pixel flows is crucial for achieving high-quality video enhancement, yet most prior works focus on estimating dense flows that are generally less robust and computationally expensive. This highlights a gap in existing methodologies that fail to prioritize accuracy over density, necessitating a more efficient approach to flow estimation for video enhancement tasks.
Contribution: Combine 'sparse point cloud data' and 
sentences: a deep CNN, a reinforcement learning view of the dialog generation task, graphical models, source_sentence: Background: The optimal robot assembly planning problem is challenging due to the necessity of finding the optimal solution amongst an exponentially vast number of possible plans while satisfying a selection of constraints. Traditional heuristic methods are limited as they are specific to a given objective structure or set of problem parameters, indicating a need for more versatile and effective approaches.
Contribution: 'pos[e] assembly sequencing' inspired by 
sentences: 3D geometric neural field representation, prompt learning, gestures, source_sentence: Background: Patients find it difficult to use dexterous prosthetic hands without a suitable control system, highlighting a need for improved grasp performance and ease of operation. Existing methods may not adequately address the challenges faced by users, particularly those with inferior myoelectric signals, in effectively controlling prosthetic devices.
Contribution: Combine 'myoelectric signal' and 
sentences: a unified framework for collaborative decoding between large and small language models (Large Language Models and small language models), image understanding, joint biomedical entity linking and event extraction
pipeline_tag: sentence-similarity
library_name: sentence-transformers
license: cc
datasets: noystl/Recombination-Pred
language: en
Likes: 0 | All-time downloads: 8
Created: 2025-04-13 09:55:51