few shot - Robuta Search

https://openreview.net/forum?id=SyVuRiC5K7 LEARNING TO PROPAGATE LABELS: TRANSDUCTIVE PROPAGATION NETWORK FOR FEW-SHOT LEARNING | OpenReview We propose a novel meta-learning framework for transductive inference that classifies the entire test set at once to alleviate the low-data problem. few shot learning propagate labels https://few-shot-text-classification.fastforwardlabs.com/ Few-Shot Text Classification An online research report on few-shot text classification by Cloudera Fast Forward. few shot text classification https://arxiv.org/abs/2004.14884v3 [2004.14884v3] Few-Shot Learning for Opinion Summarization Abstract page for arXiv paper 2004.14884v3: Few-Shot Learning for Opinion Summarization few shot learning 2004 opinion summarization https://openreview.net/forum?id=wfLuiDjQ0u Making Text Embedders Few-Shot Learners | OpenReview Large language models (LLMs) with decoder-only architectures have demonstrated exceptional text-generation capabilities across a variety of tasks. Some... few shot making text embedders learners https://deepai.org/publication/trahgr-few-shot-learning-for-hand-gesture-recognition-via-electromyography TraHGR: Few-shot Learning for Hand Gesture Recognition via ElectroMyography | DeepAI Mar 28, 2022 - 03/28/22 - Deep learning-based Hand Gesture Recognition (HGR) via surface Electromyogram (sEMG) signals has recently shown significant potent... few shot learning hand gesture recognition https://deepai.org/publication/patchmix-augmentation-to-identify-causal-features-in-few-shot-learning PatchMix Augmentation to Identify Causal Features in Few-shot Learning | DeepAI Nov 29, 2022 - 11/29/22 - The task of Few-shot learning (FSL) aims to transfer the knowledge learned from base categories with sufficient labelled data to n... few shot learning augmentation identify causal https://deepai.org/publication/starnet-towards-weakly-supervised-few-shot-detection-and-explainable-few-shot-classification StarNet: towards weakly supervised few-shot detection and explainable few-shot classification |... Mar 15, 2020 - 03/15/20 - In this paper, we propose a new few-shot learning method called StarNet, which is an end-to-end trainable non-parametric star-mode... few shot starnet towards supervised detection https://aclanthology.org/2022.findings-naacl.31/ Few-Shot Self-Rationalization with Natural Language Prompts - ACL Anthology Ana Marasovic, Iz Beltagy, Doug Downey, Matthew Peters. Findings of the Association for Computational Linguistics: NAACL 2022. 2022. few shot natural language self rationalization prompts https://deepai.org/publication/the-unreasonable-effectiveness-of-few-shot-learning-for-machine-translation The unreasonable effectiveness of few-shot learning for machine translation | DeepAI Feb 2, 2023 - 02/02/23 - We demonstrate the potential of few-shot translation systems, trained with unpaired language data, for both high and low-resource ... few shot learning unreasonable effectiveness machine translation https://www.datacamp.com/zh/blog/what-is-few-shot-learning What is Few-Shot Learning? Unlocking Insights with Limited Data | DataCamp Unlock the power of few-shot learning and learn how to extract valuable insights from minimal data. Explore techniques, applications, and benefits. few shot learning what is limited data https://aclanthology.org/2022.acl-long.514/ Few-shot Controllable Style Transfer for Low-Resource Multilingual Settings - ACL Anthology Kalpesh Krishna, Deepak Nathani, Xavier Garcia, Bidisha Samanta, Partha Talukdar. Proceedings of the 60th Annual Meeting of the Association for Computational... few shot style transfer https://openreview.net/forum?id=RnBAclRKOC Vision Language Models Are Few-Shot Audio Spectrogram Classifiers | OpenReview We demonstrate that vision language models (VLMs) are capable of recognizing the content in audio recordings when given corresponding spectrogram images.... vision language models few shot audio spectrogram classifiers https://deepai.org/publication/instance-credibility-inference-for-few-shot-learning Instance Credibility Inference for Few-Shot Learning | DeepAI Mar 26, 2020 - 03/26/20 - Few-shot learning (FSL) aims to recognize new objects with extremely limited training data for each category. Previous efforts are... few shot learning instance credibility inference deepai https://www.fewshotlearning.co/ Few Shot Learning in Public | KBall | Substack This is where I am posting my learning in public about Machine Learning, LLMs, and the rest of this wild new wave of AI systems. Click to read Few Shot... few shot learning public kball substack https://openreview.net/forum?id=LWH-C1HoQG_ Few-Shot Segmentation via Cycle-Consistent Transformer | OpenReview We propose a cycle-consistent transformer (CyCTR) to aggregate the pixel-wise support features into the query ones for few-shot segmentation while avoiding... few shot segmentation via cycle consistent https://openreview.net/forum?id=JPk7pWtuow&referrer=%5Bthe%20profile%20of%20Adam%20Gaier%5D(%2Fprofile%3Fid%3D~Adam_Gaier1) Language Model Crossover: Variation through Few-Shot Prompting | OpenReview This article pursues the insight that language models naturally enable an intelligent variation operator similar in spirit to evolutionary crossover. In... few shot prompting language model crossover variation openreview https://deepai.org/publication/diversity-transfer-network-for-few-shot-learning Diversity Transfer Network for Few-Shot Learning | DeepAI Dec 31, 2019 - 12/31/19 - Few-shot learning is a challenging task that aims at training a classifier for unseen classes with only a few training examples. T... few shot learning diversity transfer network deepai https://arxiv.org/abs/2407.10910v2 [2407.10910v2] DataDream: Few-shot Guided Dataset Generation Abstract page for arXiv paper 2407.10910v2: DataDream: Few-shot Guided Dataset Generation few shot 2407 guided dataset generation https://arxiv.org/abs/2112.06538 [2112.06538] Hybrid Graph Neural Networks for Few-Shot Learning Abstract page for arXiv paper 2112.06538: Hybrid Graph Neural Networks for Few-Shot Learning graph neural networks few shot 2112 06538 hybrid https://arxiv.org/abs/2505.08260 [2505.08260] Few-shot Novel Category Discovery Abstract page for arXiv paper 2505.08260: Few-shot Novel Category Discovery few shot 2505 08260 novel category https://openreview.net/forum?id=odVhX3QDtO&referrer=%5Bthe%20profile%20of%20Qi%20Fan%5D(%2Fprofile%3Fid%3D~Qi_Fan2) Few-shot video object detection | OpenReview We introduce Few-Shot Video Object Detection (FSVOD) with three contributions to real-world visual learning challenge in our highly diverse and dynamic world:... few shot video object detection openreview https://openreview.net/forum?id=rrxDSvp-rWn&referrer=%5Bthe%20profile%20of%20Qi%20Fan%5D(%2Fprofile%3Fid%3D~Qi_Fan2) Self-Support Few-Shot Semantic Segmentation | OpenReview Existing few-shot segmentation methods have achieved great progress based on the support-query matching framework. But they still heavily suffer from the... self support few shot semantic segmentation openreview https://www.datacamp.com/tr/blog/what-is-few-shot-learning What is Few-Shot Learning? Unlocking Insights with Limited Data | DataCamp Unlock the power of few-shot learning and learn how to extract valuable insights from minimal data. Explore techniques, applications, and benefits. few shot learning what is limited data https://arxiv.org/abs/2207.05515v3 [2207.05515v3] Compound Prototype Matching for Few-shot Action Recognition Abstract page for arXiv paper 2207.05515v3: Compound Prototype Matching for Few-shot Action Recognition prototype matching few shot 2207 compound action https://deepai.org/publication/fewjoint-a-few-shot-learning-benchmark-for-joint-language-understanding FewJoint: A Few-shot Learning Benchmark for Joint Language Understanding | DeepAI Sep 17, 2020 - 09/17/20 - Few-learn learning (FSL) is one of the key future steps in machine learning and has raised a lot of attention. However, in contras... few shot learning language understanding https://arxiv.org/abs/2603.21935v1?ref=aifeta.com [2603.21935v1] Chronological Contrastive Learning: Few-Shot Progression Assessment in Irreversible... Abstract page for arXiv paper 2603.21935v1: Chronological Contrastive Learning: Few-Shot Progression Assessment in Irreversible Diseases contrastive learning few shot 2603 chronological https://deepai.org/publication/training-few-shot-classification-via-the-perspective-of-minibatch-and-pretraining Training few-shot classification via the perspective of minibatch and pretraining | DeepAI Apr 10, 2020 - 04/10/20 - Few-shot classification is a challenging task which aims to formulate the ability of humans to learn concepts from limited prior d... few shot the perspective https://openreview.net/forum?id=ePH3xBFOiP Analyzing Few-Shot Neural Architecture Search in a Metric-Driven Framework | OpenReview While Neural Architecture Search (NAS) methods help find optimal neural network architectures for diverse tasks, they often come with unreasonable costs. To... neural architecture search few shot https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2024.1469032/full Frontiers | Few-shot SAR target classification via meta-learning with hybrid models Currently, in Synthetic Aperture Radar Automatic Target Recognition (SAR ATR), few-shot methods can save cost and resources while enhancing adaptability. How... few shot https://deepai.org/publication/unsupervised-meta-learning-via-few-shot-pseudo-supervised-contrastive-learning Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive Learning | DeepAI Mar 2, 2023 - 03/02/23 - Unsupervised meta-learning aims to learn generalizable knowledge across a distribution of tasks constructed from unlabeled data. H... meta learning few shot unsupervised via pseudo https://openreview.net/forum?id=7OmUSzlgd4a Shift and Scale is Detrimental To Few-Shot Transfer | OpenReview We demonstrate that removing the affine parameters of batchnorm yields large gains when transfering to distant few shot learning tasks shift and few shot scale detrimental transfer https://www.amazon.science/publications/domain-aligned-clip-for-few-shot-classification Domain aligned CLIP for few-shot classification - Amazon Science Large vision-language representation learning models like CLIP have demonstrated impressive performance for zero-shot transfer to downstream tasks while... clip for few shot domain aligned classification https://deepai.org/publication/an-efficient-framework-for-few-shot-skeleton-based-temporal-action-segmentation An Efficient Framework for Few-shot Skeleton-based Temporal Action Segmentation | DeepAI Jul 20, 2022 - 07/20/22 - Temporal action segmentation (TAS) aims to classify and locate actions in the long untrimmed action sequence. With the success of ... few shot https://www.datacamp.com/ru/blog/what-is-few-shot-learning What is Few-Shot Learning? Unlocking Insights with Limited Data | DataCamp Unlock the power of few-shot learning and learn how to extract valuable insights from minimal data. Explore techniques, applications, and benefits. few shot learning what is limited data https://arxiv.org/abs/2010.00511v3 [2010.00511v3] Fast Few-Shot Classification by Few-Iteration Meta-Learning Abstract page for arXiv paper 2010.00511v3: Fast Few-Shot Classification by Few-Iteration Meta-Learning few shot 2010 fast classification iteration https://openreview.net/forum?id=GCViBBoVru&referrer=%5Bthe%20profile%20of%20Chenxi%20Liu%5D(%2Fprofile%3Fid%3D~Chenxi_Liu2) Few-Shot Class Incremental Learning with Attention-Aware Self-Adaptive Prompt | OpenReview Few-Shot Class-Incremental Learning (FSCIL) models aim to incrementally learn new classes with scarce samples while preserving knowledge of old ones. Existing... few shot incremental learning https://openreview.net/forum?id=wCFB37bzud4 Bidirectional Language Models Are Also Few-shot Learners | OpenReview We present Sequential Autoregressive Prompting, a technique that enables prompting of bidirectional models demonstrating prompt-based learning is an emergent... bidirectional language few shot models also learners https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2024.1349204/full Frontiers | In defense of local descriptor-based few-shot object detection State-of-the-art image object detection computational models require an intensive parameters fine-tuning stage (using Deep Convolution Network, etc.) with te... frontiers in few shot defense local https://openreview.net/forum?id=7qfkImn0dL ExPT: Synthetic Pretraining for Few-Shot Experimental Design | OpenReview Experimental design is a fundamental problem in many science and engineering fields. In this problem, sample efficiency is crucial due to the time, money, and... few shot experimental design synthetic openreview https://deepai.org/publication/big-model-driven-few-shot-continual-learning Big-model Driven Few-shot Continual Learning | DeepAI Sep 2, 2023 - 09/02/23 - Few-shot continual learning (FSCL) has attracted intensive attention and achieved some advances in recent years, but now it is dif... model driven few shot continual learning big deepai https://openreview.net/forum?id=p3nPHMpx04 A Surprisingly Simple Approach to Generalized Few-Shot Semantic Segmentation | OpenReview The goal of *generalized* few-shot semantic segmentation (GFSS) is to recognize *novel-class* objects through training with a few annotated examples and the... few shot semantic segmentation surprisingly simple approach https://www.mdpi.com/1424-8220/22/7/2648 Word Embedding Distribution Propagation Graph Network for Few-Shot Learning Few-shot learning (FSL) is of great significance to the field of machine learning. The ability to learn and generalize using a small number of samples is an... word embedding propagation graph few shot distribution network https://deepai.org/publication/few-shot-generative-model-adaption-via-relaxed-spatial-structural-alignment Few Shot Generative Model Adaption via Relaxed Spatial Structural Alignment | DeepAI Mar 6, 2022 - 03/06/22 - Training a generative adversarial network (GAN) with limited data has been a challenging task. A feasible solution is to start wit... few shot generative model structural alignment adaption https://www.a-star.edu.sg/cfar/research/publications/few-shot-adaptation-of-pre-trained-networks-for-domain-shift Few-Shot Adaptation of Pre-Trained Networks for Domain Shift few shot adaptation pre trained networks https://openreview.net/forum?id=7MXra1JSh8 Hierarchical Filtering and Refinement Classification for Few-Shot Class-Incremental Learning |... Few-shot class-incremental learning (FSCIL) aims at recognizing novel classes continually with limited novel class samples. A mainstream baseline for FSCIL is... few shot hierarchical filtering refinement classification https://openreview.net/forum?id=wEvO8BCqZcm POODLE: Improving Few-shot Learning via Penalizing Out-of-Distribution Samples | OpenReview We leverage samples from distractor classes or randomly generated noise to improve the generalization of few-shot learner few shot learning https://aclanthology.org/2023.nlrse-1.6/ Reasoning Circuits: Few-shot Multi-hop Question Generation with Structured Rationales - ACL... Saurabh Kulshreshtha, Anna Rumshisky. Proceedings of the 1st Workshop on Natural Language Reasoning and Structured Explanations (NLRSE). 2023. few shot https://oecd.ai/en/catalogue/metric-use-cases/a-bag-of-tricks-for-few-shot-class-incremental-learning-4 A Bag of Tricks for Few-Shot Class-Incremental Learning - OECD.AI Large language models (LLMs) have shown great potential in complex reasoning tasks, yet their performance is often hampered by the scarcity of high-quality and... bag of tricks few shot https://openreview.net/forum?id=GtnipgAomT&referrer=%5Bthe%20profile%20of%20Pradyumna%20Narayana%5D(%2Fprofile%3Fid%3D~Pradyumna_Narayana2) Discffusion: Discriminative Diffusion Models as Few-shot Vision and Language Learners | OpenReview Diffusion models, such as Stable Diffusion, have shown incredible performance on text-to-image generation. Since text-to-image generation often requires models... diffusion models few shot https://openreview.net/forum?id=Ix8o1xIX6y Online Prototype Alignment for Few-shot Policy Transfer | OpenReview Domain adaptation in RL mainly deals with the changes of observation when transferring the policy to a new environment. Many traditional approaches of domain... few shot policy transfer online prototype alignment https://openreview.net/forum?id=rJY0-Kcll¬eId=rJY0-Kcll Optimization as a Model for Few-Shot Learning | OpenReview We propose an LSTM-based meta-learner model to learn the exact optimization algorithm used to train another learner neural network in the few-shot regime few shot learning optimization model openreview https://www.amazon.science/publications/few-shot-acoustic-event-detection-via-meta-learning Few-Shot Acoustic Event Detection via Meta Learning - Amazon Science We study few-shot acoustic event detection (AED) in this paper. Few-shot learning enables detection of new events with very limited labeled data. Compared to... few shot event detection meta learning acoustic via https://aclanthology.org/2024.findings-eacl.82/ Clustering-based Sampling for Few-Shot Cross-Domain Keyphrase Extraction - ACL Anthology Prakamya Mishra, Lincy Pattanaik, Arunima Sundar, Nishant Yadav, Mayank Kulkarni. Findings of the Association for Computational Linguistics: EACL 2024. 2024. few shot https://www.datacamp.com/th/blog/what-is-few-shot-learning What is Few-Shot Learning? Unlocking Insights with Limited Data | DataCamp Unlock the power of few-shot learning and learn how to extract valuable insights from minimal data. Explore techniques, applications, and benefits. few shot learning what is limited data https://openreview.net/forum?id=I1y2bCibdQ ExPT: Synthetic Pretraining for Few-Shot Experimental Design | OpenReview Experimental design is a fundamental problem in many science and engineering fields. In this problem, sample efficiency is crucial due to the time, money, and... few shot experimental design synthetic openreview https://openreview.net/forum?id=3LvTtj0VYy ControlManip: Few-Shot Manipulation Fine-tuning via Object-centric Conditional Control | OpenReview Learning real-world robotic manipulation is challenging, particularly when limited demonstrations are available. Existing methods for few-shot manipulation... few shot fine tuning https://openreview.net/forum?id=MSr3u_FCRW Reinforced Few-Shot Acquisition Function Learning for Bayesian Optimization | OpenReview Present the first few-shot learning based acquisition function, which adapts effectively and demonstrates outstanding performance under a variety of black-box... few shot learning for bayesian optimization reinforced acquisition https://oecd.ai/en/catalogue/metric-use-cases/a-bag-of-tricks-for-few-shot-class-incremental-learning A Bag of Tricks for Few-Shot Class-Incremental Learning - OECD.AI Large language models (LLMs) have shown great potential in complex reasoning tasks, yet their performance is often hampered by the scarcity of high-quality and... bag of tricks few shot https://deepai.org/publication/fair-few-shot-learning-with-auxiliary-sets Fair Few-shot Learning with Auxiliary Sets | DeepAI Aug 28, 2023 - 08/28/23 - Recently, there has been a growing interest in developing machine learning (ML) models that can promote fairness, i.e., eliminatin... few shot learning fair auxiliary sets deepai https://openreview.net/forum?id=iYcrH9hLBs&referrer=%5Bthe%20profile%20of%20Qiannan%20Zhang%5D(%2Fprofile%3Fid%3D~Qiannan_Zhang1) Few-shot Heterogeneous Graph Learning via Cross-domain Knowledge Transfer | OpenReview few shot cross domain knowledge transfer heterogeneous graph https://robotap.github.io/ RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitation RoboTAP controls by tracking any desired point on a physical surface few shot tracking arbitrary points visual https://jmlr.org/papers/v24/21-1261.html ProtoShotXAI: Using Prototypical Few-Shot Architecture for Explainable AI few shot using prototypical architecture ai https://www.amazon.science/publications/clustering-based-sampling-for-few-shot-cross-domain-keyphrase-extraction Clustering-based sampling for few-shot cross-domain keyphrase extraction - Amazon Science Keyphrase extraction is the task of identifying a set of keyphrases present in a document that captures its most salient topics. Scientific domain-specific... few shot https://deepai.org/publication/exploring-efficient-few-shot-adaptation-for-vision-transformers Exploring Efficient Few-shot Adaptation for Vision Transformers | DeepAI Jan 6, 2023 - 01/06/23 - The task of Few-shot Learning (FSL) aims to do the inference on novel categories containing only few labeled examples, with the he... few shot exploring efficient adaptation vision https://huggingface.co/papers/2312.05229 Paper page - Few-Shot Class-Incremental Learning via Training-Free Prototype Calibration Join the discussion on this paper page few shot incremental learning https://openreview.net/forum?id=WutpswD3ea Assisted Few-Shot Learning for Vision-Language Models in Agricultural Stress Phenotype... In the agricultural sector, labeled data for crop diseases and stresses are often scarce due to high annotation costs. We propose an Assisted Few-Shot Learning... few shot learning vision language models https://deepai.org/publication/hybrid-consistency-training-with-prototype-adaptation-for-few-shot-learning Hybrid Consistency Training with Prototype Adaptation for Few-Shot Learning | DeepAI Nov 19, 2020 - 11/19/20 - Few-Shot Learning (FSL) aims to improve a model's generalization capability in low data regimes. Recent FSL works have made steady... few shot learning consistency training hybrid prototype https://huggingface.co/papers/2309.12814 Paper page - Domain Adaptive Few-Shot Open-Set Learning Join the discussion on this paper page few shot open set paper domain adaptive https://aclanthology.org/2025.tacl-1.24/ Few-Shot Multilingual Open-Domain QA from Five Examples - ACL Anthology Fan Jiang, Tom Drummond, Trevor Cohn. Transactions of the Association for Computational Linguistics, Volume 13. 2025. few shot open domain from five multilingual https://oecd.ai/en/catalogue/metric-use-cases/instance-credibility-inference-for-few-shot-learning Instance Credibility Inference for Few-Shot Learning - OECD.AI Few-shot learning (FSL) aims to recognize new objects with extremely limited training data for each category. Previous efforts are made by either leveraging... few shot learning instance credibility inference oecd https://www.taskade.com/wiki/ai/few-shot-learning Few-Shot Learning - Learning from Examples | Taskade AI Discover few-shot learning, the AI capability that enables models to learn new tasks from just a handful of examples, powering adaptive AI agents. few shot learning examples taskade ai https://deepai.org/publication/orbit-a-real-world-few-shot-dataset-for-teachable-object-recognition ORBIT: A Real-World Few-Shot Dataset for Teachable Object Recognition | DeepAI Apr 8, 2021 - 04/08/21 - Object recognition has made great advances in the last decade, but predominately still relies on many high-quality training exampl... a real few shot https://openreview.net/forum?id=qY1hlv7gwg Selective Annotation Makes Language Models Better Few-Shot Learners | OpenReview We propose a select-then-annotate framework to make large language models better few-shot learners. Our method, vote-k, greatly improves the task performance... language models few shot selective annotation makes https://arxiv.org/html/2602.21854v1 FewMMBench: A Benchmark for Multimodal Few-Shot Learning few shot benchmark multimodal learning https://www.datacamp.com/pl/blog/what-is-few-shot-learning What is Few-Shot Learning? Unlocking Insights with Limited Data | DataCamp Unlock the power of few-shot learning and learn how to extract valuable insights from minimal data. Explore techniques, applications, and benefits. few shot learning what is limited data https://arxiv.org/abs/2602.21854v1 [2602.21854v1] FewMMBench: A Benchmark for Multimodal Few-Shot Learning Abstract page for arXiv paper 2602.21854v1: FewMMBench: A Benchmark for Multimodal Few-Shot Learning few shot 2602 benchmark multimodal learning https://deepai.org/publication/meta-generating-deep-attentive-metric-for-few-shot-classification Meta-Generating Deep Attentive Metric for Few-shot Classification | DeepAI Dec 3, 2020 - 12/03/20 - Learning to generate a task-aware base learner proves a promising direction to deal with few-shot learning (FSL) problem. Existing... few shot meta generating deep attentive https://openreview.net/forum?id=VBXRMnRBfRF Metric Based Few-Shot Graph Classification | OpenReview We provide an overview of few-shot graph classification approaches, releasing a public codebase. We then propose adapting a metric learning approach to tackle... few shot metric based graph classification https://openreview.net/forum?id=7xKIFaeEBG MEWL: Few-shot multimodal word learning with referential uncertainty | OpenReview Without explicit feedback, humans can rapidly learn the meaning of words. Children can acquire a new word after just a few passive exposures, a process known... few shot word learning mewl multimodal referential https://aclanthology.org/2022.flp-1.24/ Exploring Euphemism Detection in Few-Shot and Zero-Shot Settings - ACL Anthology Sedrick Scott Keh. Proceedings of the 3rd Workshop on Figurative Language Processing (FLP). 2022. few shot exploring euphemism detection https://openreview.net/forum?id=6ns5QTPQ_d Realistic evaluation of transductive few-shot learning | OpenReview A realistic evaluation of transductive few-shot methods via Dirichlet-distributed class marginals, and a generalization of the mutual information loss based on... few shot learning realistic evaluation openreview https://aclanthology.org/2024.findings-acl.602/ Designing Informative Metrics for Few-Shot Example Selection - ACL Anthology Rishabh Adiga, Lakshmi Subramanian, Varun Chandrasekaran. Findings of the Association for Computational Linguistics: ACL 2024. 2024. few shot designing informative metrics example https://arxiv.org/abs/2111.11656v2 [2111.11656v2] Few-Shot Object Detection via Association and DIscrimination Abstract page for arXiv paper 2111.11656v2: Few-Shot Object Detection via Association and DIscrimination few shot object detection 2111 via association https://deepai.org/publication/few-shot-action-recognition-with-compromised-metric-via-optimal-transport Few-Shot Action Recognition with Compromised Metric via Optimal Transport | DeepAI Apr 8, 2021 - 04/08/21 - Although vital to computer vision systems, few-shot action recognition is still not mature despite the wide research of few-shot i... few shot action recognition optimal transport https://www.datacamp.com/ro/blog/what-is-few-shot-learning What is Few-Shot Learning? Unlocking Insights with Limited Data | DataCamp Unlock the power of few-shot learning and learn how to extract valuable insights from minimal data. Explore techniques, applications, and benefits. few shot learning what is limited data https://arxiv.org/abs/2007.01496 [2007.01496] Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations Abstract page for arXiv paper 2007.01496: Few-Shot Semantic Segmentation Augmented with Image-Level Weak Annotations few shot semantic segmentation https://aclanthology.org/2021.findings-emnlp.177/ Few-Shot Novel Concept Learning for Semantic Parsing - ACL Anthology Soham Dan, Osbert Bastani, Dan Roth. Findings of the Association for Computational Linguistics: EMNLP 2021. 2021. few shot concept learning semantic parsing novel acl https://deepai.org/publication/clustering-enabled-few-shot-load-forecasting Clustering Enabled Few-Shot Load Forecasting | DeepAI Feb 16, 2022 - 02/16/22 - While the advanced machine learning algorithms are effective in load forecasting, they often suffer from low data utilization, and... few shot load forecasting clustering enabled deepai https://openreview.net/forum?id=Kr6jWI4PSRd Generalized and Discriminative Few-Shot Object Detection via SVD-Dictionary Enhancement | OpenReview Few-shot object detection (FSOD) aims to detect new objects based on few annotated samples. To alleviate the impact of few samples, enhancing the... few shot object detection https://openreview.net/forum?id=kXXPLBEBVGH&referrer=%5Bthe%20profile%20of%20Johannes%20Schimunek%5D(%2Fprofile%3Fid%3D~Johannes_Schimunek1) Context-enriched molecule representations improve few-shot drug discovery | OpenReview We introduce a new architecture for few-shot learning in drug discovery that enriches molecule representations by retrieving from a large set of known... few shot drug discovery context enriched molecule https://openreview.net/forum?id=h924KUypsS&referrer=%5Bthe%20profile%20of%20Ji%20Xin%5D(%2Fprofile%3Fid%3D~Ji_Xin1) Few-Shot Non-Parametric Learning with Deep Latent Variable Model | OpenReview Most real-world problems that machine learning algorithms are expected to solve face the situation with 1) unknown data distribution; 2) little domain-specific... latent variable model few shot non parametric learning https://openreview.net/forum?id=FJo2lroF7R&referrer=%5Bthe%20profile%20of%20Shyam%20Upadhyay%5D(%2Fprofile%3Fid%3D~Shyam_Upadhyay1) AutoMix: Mixing Models with Few-shot Self and Meta Verification | OpenReview Large language models (LLMs) are now available in various sizes and configurations from cloud API providers. While this diversity offers a broad spectrum of... few shot automix mixing models https://arxiv.org/abs/2210.14124v1 [2210.14124v1] Lafite2: Few-shot Text-to-Image Generation Abstract page for arXiv paper 2210.14124v1: Lafite2: Few-shot Text-to-Image Generation text to image few shot 2210 generation https://www.datacamp.com/vi/blog/what-is-few-shot-learning What is Few-Shot Learning? Unlocking Insights with Limited Data | DataCamp Unlock the power of few-shot learning and learn how to extract valuable insights from minimal data. Explore techniques, applications, and benefits. few shot learning what is limited data https://research.google/pubs/learning-a-universal-template-for-few-shot-dataset-generalization/ Learning a Universal Template for Few-shot Dataset Generalization few shot learning universal template dataset https://openreview.net/forum?id=pW2Q2xLwIMD Few-Shot Learning via Learning the Representation, Provably | OpenReview This paper studies few-shot learning via representation learning, where one uses $T$ source tasks with $n_1$ data per task to learn a representation in order... few shot learning via representation openreview https://openreview.net/forum?id=6kCiVaoQdx9 Few-shot Learning via Dirichlet Tessellation Ensemble | OpenReview Few-shot learning (FSL) is the process of rapid generalization from abundant base samples to inadequate novel samples. Despite extensive research in recent... few shot learning dirichlet tessellation via ensemble openreview https://openreview.net/forum?id=uRz9GZN17X Bidirectional Reciprocative Information Communication for Few-Shot Semantic Segmentation |... Existing few-shot semantic segmentation methods typically rely on a one-way flow of category information from support to query, ignoring the impact of... information communication few shot bidirectional semantic segmentation https://www.datacamp.com/hi/blog/what-is-few-shot-learning What is Few-Shot Learning? Unlocking Insights with Limited Data | DataCamp Unlock the power of few-shot learning and learn how to extract valuable insights from minimal data. Explore techniques, applications, and benefits. few shot learning what is limited data https://www.datacamp.com/sv/blog/what-is-few-shot-learning What is Few-Shot Learning? Unlocking Insights with Limited Data | DataCamp Unlock the power of few-shot learning and learn how to extract valuable insights from minimal data. Explore techniques, applications, and benefits. few shot learning what is limited data