{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/few-shot-learning/papers/21","list_of":"/task/few-shot-learning","task":"Few-Shot Learning","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":21,"pages_in_order":30,"rows_per_page":100,"rows":[2001,2100],"of":2964,"counts":{"archive_papers_tagged":2964,"with_a_code_link":1297,"where_syntology_ran_a_sample":373,"not_listed_spam_title":0,"listed":2964,"listed_where_code_ran":373,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":306,"every_run_a_failure_of_syntologys_instrument":67,"listed_with_a_run_with_no_instrument_failure":306,"listed_every_run_a_failure_of_syntologys_instrument":67,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/few-shot-learning","prev":"/task/few-shot-learning/papers/20","next":"/task/few-shot-learning/papers/22","papers":[{"url":null,"slug":"meta-tuning-loss-functions-and-data","title":"Meta-tuning Loss Functions and Data Augmentation for Few-shot Object Detection","date":"2023-04-24","arxiv_id":"2304.12161","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-addressing-training-data-scarcity","title":"Towards Addressing Training Data Scarcity Challenge in Emerging Radio Access Networks: A Survey and Framework","date":"2023-04-24","arxiv_id":"2304.12480","repositories_listed":0,"syntology":null},{"url":null,"slug":"information-extraction-from-documents","title":"Information Extraction from Documents: Question Answering vs Token Classification in real-world setups","date":"2023-04-21","arxiv_id":"2304.10994","repositories_listed":0,"syntology":null},{"url":null,"slug":"rplkg-robust-prompt-learning-with-knowledge","title":"RPLKG: Robust Prompt Learning with Knowledge Graph","date":"2023-04-21","arxiv_id":"2304.10805","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-reference-transformer-for-few-shot","title":"Few-shot Medical Image Segmentation via Cross-Reference Transformer","date":"2023-04-19","arxiv_id":"2304.09630","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixpro-simple-yet-effective-data-augmentation","title":"MixPro: Simple yet Effective Data Augmentation for Prompt-based Learning","date":"2023-04-19","arxiv_id":"2304.09402","repositories_listed":0,"syntology":null},{"url":null,"slug":"cancergpt-few-shot-drug-pair-synergy","title":"CancerGPT: Few-shot Drug Pair Synergy Prediction using Large Pre-trained Language Models","date":"2023-04-18","arxiv_id":"2304.10946","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-few-shot-class-incremental","title":"A Survey on Few-Shot Class-Incremental Learning","date":"2023-04-17","arxiv_id":"2304.08130","repositories_listed":0,"syntology":null},{"url":null,"slug":"smae-few-shot-learning-for-hdr-deghosting","title":"SMAE: Few-shot Learning for HDR Deghosting with Saturation-Aware Masked Autoencoders","date":"2023-04-14","arxiv_id":"2304.06914","repositories_listed":0,"syntology":null},{"url":null,"slug":"lsfsl-leveraging-shape-information-in-few","title":"LSFSL: Leveraging Shape Information in Few-shot Learning","date":"2023-04-13","arxiv_id":"2304.06672","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-opportunities-and-challenges-of","title":"On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence","date":"2023-04-13","arxiv_id":"2304.06798","repositories_listed":0,"syntology":null},{"url":null,"slug":"out-of-distribution-few-shot-learning-for","title":"Out-of-distribution Few-shot Learning For Edge Devices without Model Fine-tuning","date":"2023-04-13","arxiv_id":"2304.06309","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-semantic-segmentation-a-review-of","title":"Few Shot Semantic Segmentation: a review of methodologies, benchmarks, and open challenges","date":"2023-04-12","arxiv_id":"2304.05832","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-learn-with-indispensable","title":"Learning to Learn with Indispensable Connections","date":"2023-04-06","arxiv_id":"2304.02862","repositories_listed":0,"syntology":null},{"url":null,"slug":"sociocultural-knowledge-is-needed-for","title":"Sociocultural knowledge is needed for selection of shots in hate speech detection tasks","date":"2023-04-04","arxiv_id":"2304.01890","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-cultural-transfer-learning-for-chinese","title":"Cross-Cultural Transfer Learning for Chinese Offensive Language Detection","date":"2023-03-31","arxiv_id":"2303.17927","repositories_listed":0,"syntology":null},{"url":null,"slug":"channel-phase-processing-in-wireless-networks","title":"Channel Phase Processing in Wireless Networks for Human Activity Recognition","date":"2023-03-29","arxiv_id":"2303.16873","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-3d-point-cloud-semantic-segmentation-1","title":"Few-Shot 3D Point Cloud Semantic Segmentation via Stratified Class-Specific Attention Based Transformer Network","date":"2023-03-28","arxiv_id":"2303.15654","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-codex-prompt-engineering-for-ocl","title":"On Codex Prompt Engineering for OCL Generation: An Empirical Study","date":"2023-03-28","arxiv_id":"2303.16244","repositories_listed":0,"syntology":null},{"url":null,"slug":"clidim-contrastive-learning-for-image","title":"Generalizable Denoising of Microscopy Images using Generative Adversarial Networks and Contrastive Learning","date":"2023-03-27","arxiv_id":"2303.15214","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-expressive-prompting-with-residuals","title":"Learning Expressive Prompting With Residuals for Vision Transformers","date":"2023-03-27","arxiv_id":"2303.15591","repositories_listed":0,"syntology":null},{"url":null,"slug":"spec-summary-preference-decomposition-for-low","title":"SPEC: Summary Preference Decomposition for Low-Resource Abstractive Summarization","date":"2023-03-24","arxiv_id":"2303.14011","repositories_listed":0,"syntology":null},{"url":null,"slug":"decomposed-prototype-learning-for-few-shot","title":"Decomposed Prototype Learning for Few-Shot Scene Graph Generation","date":"2023-03-20","arxiv_id":"2303.10863","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-general-purpose-ai-assistant-embedded-in-an","title":"A general-purpose AI assistant embedded in an open-source radiology information system","date":"2023-03-18","arxiv_id":"2303.10338","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-of-deep-visual-cross-domain-few-shot","title":"A Survey of Deep Visual Cross-Domain Few-Shot Learning","date":"2023-03-16","arxiv_id":"2303.09253","repositories_listed":0,"syntology":null},{"url":null,"slug":"instance-conditioned-gan-data-augmentation","title":"Instance-Conditioned GAN Data Augmentation for Representation Learning","date":"2023-03-16","arxiv_id":"2303.09677","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-cross-domain-few-shot","title":"Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey","date":"2023-03-15","arxiv_id":"2303.08557","repositories_listed":0,"syntology":null},{"url":null,"slug":"hazardnet-road-debris-detection-by","title":"HazardNet: Road Debris Detection by Augmentation of Synthetic Models","date":"2023-03-14","arxiv_id":"2303.07547","repositories_listed":0,"syntology":null},{"url":null,"slug":"meta-learning-approaches-for-few-shot","title":"Meta-learning approaches for few-shot learning: A survey of recent advances","date":"2023-03-13","arxiv_id":"2303.07502","repositories_listed":0,"syntology":null},{"url":null,"slug":"gradient-regulated-meta-prompt-learning-for","title":"Gradient-Regulated Meta-Prompt Learning for Generalizable Vision-Language Models","date":"2023-03-12","arxiv_id":"2303.06571","repositories_listed":0,"syntology":null},{"url":null,"slug":"consistency-analysis-of-chatgpt","title":"Consistency Analysis of ChatGPT","date":"2023-03-11","arxiv_id":"2303.06273","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-augmented-few-shot-visual-relation","title":"Knowledge-augmented Few-shot Visual Relation Detection","date":"2023-03-09","arxiv_id":"2303.05342","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploring-data-augmentation-methods-on-social","title":"Exploring Data Augmentation Methods on Social Media Corpora","date":"2023-03-03","arxiv_id":"2303.02198","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-few-shot-attention-recurrent-residual-u-net","title":"A Few-Shot Attention Recurrent Residual U-Net for Crack Segmentation","date":"2023-03-02","arxiv_id":"2303.01582","repositories_listed":0,"syntology":null},{"url":null,"slug":"clr-gam-contrastive-point-cloud-learning-with","title":"CLR-GAM: Contrastive Point Cloud Learning with Guided Augmentation and Feature Mapping","date":"2023-02-28","arxiv_id":"2302.14306","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-transformers-and-language-models-for","title":"Language Models are Few-shot Learners for Prognostic Prediction","date":"2023-02-24","arxiv_id":"2302.12692","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-point-cloud-semantic-segmentation","title":"Few-Shot Point Cloud Semantic Segmentation via Contrastive Self-Supervision and Multi-Resolution Attention","date":"2023-02-21","arxiv_id":"2302.10501","repositories_listed":0,"syntology":null},{"url":null,"slug":"kg-eco-knowledge-graph-enhanced-entity","title":"KG-ECO: Knowledge Graph Enhanced Entity Correction for Query Rewriting","date":"2023-02-21","arxiv_id":"2302.10454","repositories_listed":0,"syntology":null},{"url":null,"slug":"mask-guided-bert-for-few-shot-text","title":"Mask-guided BERT for Few Shot Text Classification","date":"2023-02-21","arxiv_id":"2302.10447","repositories_listed":0,"syntology":null},{"url":null,"slug":"meta-world-conditional-neural-processes","title":"Meta-World Conditional Neural Processes","date":"2023-02-20","arxiv_id":"2302.10320","repositories_listed":0,"syntology":null},{"url":null,"slug":"dgp-net-dense-graph-prototype-network-for-few","title":"DGP-Net: Dense Graph Prototype Network for Few-Shot SAR Target Recognition","date":"2023-02-19","arxiv_id":"2302.09584","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-multimodal-multitask-multilingual","title":"Few-shot Multimodal Multitask Multilingual Learning","date":"2023-02-19","arxiv_id":"2303.12489","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-adaptive-plug-and-play-network-for-few","title":"An Adaptive Plug-and-Play Network for Few-Shot Learning","date":"2023-02-18","arxiv_id":"2302.09326","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-attention-memory","title":"Neural Attention Memory","date":"2023-02-18","arxiv_id":"2302.09422","repositories_listed":0,"syntology":null},{"url":null,"slug":"scalable-prompt-generation-for-semi","title":"Scalable Prompt Generation for Semi-supervised Learning with Language Models","date":"2023-02-18","arxiv_id":"2302.09236","repositories_listed":0,"syntology":null},{"url":"/paper/covidexpert-a-triplet-siamese-neural-network","slug":"covidexpert-a-triplet-siamese-neural-network","title":"CovidExpert: A Triplet Siamese Neural Network framework for the detection of COVID-19","date":"2023-02-17","arxiv_id":"2302.09004","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-3d-lidar-semantic-segmentation-for","title":"Few-shot 3D LiDAR Semantic Segmentation for Autonomous Driving","date":"2023-02-17","arxiv_id":"2302.08785","repositories_listed":0,"syntology":null},{"url":null,"slug":"conversation-style-transfer-using-few-shot","title":"Conversation Style Transfer using Few-Shot Learning","date":"2023-02-16","arxiv_id":"2302.08362","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-initialize-can-meta-learning","title":"Learning to Initialize: Can Meta Learning Improve Cross-task Generalization in Prompt Tuning?","date":"2023-02-16","arxiv_id":"2302.08143","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-learning-approaches-for-classifying","title":"Few-shot learning approaches for classifying low resource domain specific software requirements","date":"2023-02-14","arxiv_id":"2302.06951","repositories_listed":0,"syntology":null},{"url":null,"slug":"distillation-of-encoder-decoder-transformers","title":"Distillation of encoder-decoder transformers for sequence labelling","date":"2023-02-10","arxiv_id":"2302.05454","repositories_listed":0,"syntology":null},{"url":null,"slug":"re-vilm-retrieval-augmented-visual-language","title":"Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning","date":"2023-02-09","arxiv_id":"2302.04858","repositories_listed":0,"syntology":null},{"url":null,"slug":"crosscodebench-benchmarking-cross-task","title":"CrossCodeBench: Benchmarking Cross-Task Generalization of Source Code Models","date":"2023-02-08","arxiv_id":"2302.04030","repositories_listed":0,"syntology":null},{"url":null,"slug":"from-zero-shot-to-few-shot-learning-a-step-of","title":"A Systematic Evaluation and Benchmark for Embedding-Aware Generative Models: Features, Models, and Any-shot Scenarios","date":"2023-02-08","arxiv_id":"2302.04060","repositories_listed":0,"syntology":null},{"url":null,"slug":"autows-automated-weak-supervision-framework","title":"AutoWS: Automated Weak Supervision Framework for Text Classification","date":"2023-02-07","arxiv_id":"2302.03297","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-unreasonable-effectiveness-of-few-shot","title":"The unreasonable effectiveness of few-shot learning for machine translation","date":"2023-02-02","arxiv_id":"2302.01398","repositories_listed":0,"syntology":null},{"url":null,"slug":"differentiable-entailment-for-parameter","title":"Differentiable Entailment for Parameter Efficient Few Shot Learning","date":"2023-01-31","arxiv_id":"2301.13345","repositories_listed":0,"syntology":null},{"url":null,"slug":"alignment-with-human-representations-supports","title":"Alignment with human representations supports robust few-shot learning","date":"2023-01-27","arxiv_id":"2301.11990","repositories_listed":0,"syntology":null},{"url":null,"slug":"explore-the-power-of-dropout-on-few-shot","title":"Explore the Power of Dropout on Few-shot Learning","date":"2023-01-26","arxiv_id":"2301.11015","repositories_listed":0,"syntology":null},{"url":null,"slug":"fewshottextgcn-k-hop-neighborhood","title":"FewShotTextGCN: K-hop neighborhood regularization for few-shot learning on graphs","date":"2023-01-25","arxiv_id":"2301.10481","repositories_listed":0,"syntology":null},{"url":null,"slug":"odor-the-icpr2022-odeuropa-challenge-on","title":"ODOR: The ICPR2022 ODeuropa Challenge on Olfactory Object Recognition","date":"2023-01-24","arxiv_id":"2301.09878","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-of-brain-and-cognitive-sciences-from-the","title":"AI of Brain and Cognitive Sciences: From the Perspective of First Principles","date":"2023-01-20","arxiv_id":"2301.08382","repositories_listed":0,"syntology":null},{"url":null,"slug":"concept-discovery-for-fast-adapatation","title":"Concept Discovery for Fast Adapatation","date":"2023-01-19","arxiv_id":"2301.07850","repositories_listed":0,"syntology":null},{"url":null,"slug":"exploiting-style-transfer-based-task","title":"Exploiting Style Transfer-based Task Augmentation for Cross-Domain Few-Shot Learning","date":"2023-01-19","arxiv_id":"2301.07927","repositories_listed":0,"syntology":null},{"url":null,"slug":"continual-few-shot-learning-using","title":"Continual HyperTransformer: A Meta-Learner for Continual Few-Shot Learning","date":"2023-01-11","arxiv_id":"2301.04584","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-learning-for-cross-target-stance","title":"Few-shot Learning for Cross-Target Stance Detection by Aggregating Multimodal Embeddings","date":"2023-01-11","arxiv_id":"2301.04535","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-level-semantic-feature-matters-few-shot","title":"High-level semantic feature matters few-shot unsupervised domain adaptation","date":"2023-01-05","arxiv_id":"2301.01956","repositories_listed":0,"syntology":null},{"url":null,"slug":"task-weighting-in-meta-learning-with","title":"Task Weighting in Meta-learning with Trajectory Optimisation","date":"2023-01-04","arxiv_id":"2301.01400","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-survey-on-few-shot-knowledge-graph","title":"A Survey On Few-shot Knowledge Graph Completion with Structural and Commonsense Knowledge","date":"2023-01-03","arxiv_id":"2301.01172","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-theory-of-human-like-few-shot-learning","title":"A Theory of Human-Like Few-Shot Learning","date":"2023-01-03","arxiv_id":"2301.01047","repositories_listed":0,"syntology":null},{"url":null,"slug":"bi-level-meta-learning-for-few-shot-domain","title":"Bi-Level Meta-Learning for Few-Shot Domain Generalization","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-transductive-few-shot-fine-tuning","title":"Boosting Transductive Few-Shot Fine-Tuning With Margin-Based Uncertainty Weighting and Probability Regularization","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-continual-infomax-learning","title":"Few-shot Continual Infomax Learning","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"frequency-guidance-matters-in-few-shot","title":"Frequency Guidance Matters in Few-Shot Learning","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-label-semantics-improves-activity","title":"Unleashing the Power of Shared Label Structures for Human Activity Recognition","date":"2023-01-01","arxiv_id":"2301.03462","repositories_listed":0,"syntology":null},{"url":null,"slug":"task-aware-adaptive-learning-for-cross-domain","title":"Task-aware Adaptive Learning for Cross-domain Few-shot Learning","date":"2023-01-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"generalization-bounds-for-transfer-learning","title":"Generalization Bounds for Few-Shot Transfer Learning with Pretrained Classifiers","date":"2022-12-23","arxiv_id":"2212.12532","repositories_listed":0,"syntology":null},{"url":null,"slug":"contrastive-distillation-is-a-sample","title":"Contrastive Distillation Is a Sample-Efficient Self-Supervised Loss Policy for Transfer Learning","date":"2022-12-21","arxiv_id":"2212.11353","repositories_listed":0,"syntology":null},{"url":null,"slug":"jasmine-arabic-gpt-models-for-few-shot","title":"JASMINE: Arabic GPT Models for Few-Shot Learning","date":"2022-12-21","arxiv_id":"2212.10755","repositories_listed":0,"syntology":null},{"url":null,"slug":"opinesum-entailment-based-self-training-for","title":"OpineSum: Entailment-based self-training for abstractive opinion summarization","date":"2022-12-21","arxiv_id":"2212.10791","repositories_listed":0,"syntology":null},{"url":null,"slug":"in-context-learning-distillation-transferring","title":"In-context Learning Distillation: Transferring Few-shot Learning Ability of Pre-trained Language Models","date":"2022-12-20","arxiv_id":"2212.10670","repositories_listed":0,"syntology":null},{"url":null,"slug":"human-in-the-loop-how-to-effectively-create","title":"Human in the loop: How to effectively create coherent topics by manually labeling only a few documents per class","date":"2022-12-19","arxiv_id":"2212.09422","repositories_listed":0,"syntology":null},{"url":null,"slug":"alert-adapting-language-models-to-reasoning","title":"ALERT: Adapting Language Models to Reasoning Tasks","date":"2022-12-16","arxiv_id":"2212.08286","repositories_listed":0,"syntology":null},{"url":null,"slug":"check-worthy-claim-detection-across-topics","title":"Check-worthy Claim Detection across Topics for Automated Fact-checking","date":"2022-12-16","arxiv_id":"2212.08514","repositories_listed":0,"syntology":null},{"url":null,"slug":"fewfedweight-few-shot-federated-learning","title":"FewFedWeight: Few-shot Federated Learning Framework across Multiple NLP Tasks","date":"2022-12-16","arxiv_id":"2212.08354","repositories_listed":0,"syntology":null},{"url":null,"slug":"localized-latent-updates-for-fine-tuning","title":"Localized Latent Updates for Fine-Tuning Vision-Language Models","date":"2022-12-13","arxiv_id":"2212.06556","repositories_listed":0,"syntology":null},{"url":null,"slug":"technical-report-competition-solution-for","title":"Technical Report -- Competition Solution for Prompt Tuning using Pretrained Language Model","date":"2022-12-13","arxiv_id":"2212.06369","repositories_listed":0,"syntology":null},{"url":null,"slug":"diffalign-few-shot-learning-using-diffusion","title":"Cap2Aug: Caption guided Image to Image data Augmentation","date":"2022-12-11","arxiv_id":"2212.05404","repositories_listed":0,"syntology":null},{"url":null,"slug":"demystifying-prompts-in-language-models-via","title":"Demystifying Prompts in Language Models via Perplexity Estimation","date":"2022-12-08","arxiv_id":"2212.04037","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-medical-image-segmentation-with","title":"Few-shot Medical Image Segmentation with Cycle-resemblance Attention","date":"2022-12-07","arxiv_id":"2212.03967","repositories_listed":0,"syntology":null},{"url":"/paper/jampatoisnli-a-jamaican-patois-natural","slug":"jampatoisnli-a-jamaican-patois-natural","title":"JamPatoisNLI: A Jamaican Patois Natural Language Inference Dataset","date":"2022-12-07","arxiv_id":"2212.03419","repositories_listed":0,"syntology":null},{"url":null,"slug":"learn-to-explore-on-bootstrapping-interactive","title":"Learn to Explore: on Bootstrapping Interactive Data Exploration with Meta-learning","date":"2022-12-07","arxiv_id":"2212.03423","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-automatic-cetacean-photo","title":"Towards Automatic Cetacean Photo-Identification: A Framework for Fine-Grain, Few-Shot Learning in Marine Ecology","date":"2022-12-07","arxiv_id":"2212.03646","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-domain-few-shot-relation-extraction-via","title":"Cross-Domain Few-Shot Relation Extraction via Representation Learning and Domain Adaptation","date":"2022-12-05","arxiv_id":"2212.02560","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-few-shot-performance-of-language","title":"Improving Few-Shot Performance of Language Models via Nearest Neighbor Calibration","date":"2022-12-05","arxiv_id":"2212.02216","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-nested-named-entity-recognition","title":"Few-Shot Nested Named Entity Recognition","date":"2022-12-02","arxiv_id":"2212.00953","repositories_listed":0,"syntology":null},{"url":null,"slug":"aug-fedprompt-practical-few-shot-federated","title":"Towards Practical Few-shot Federated NLP","date":"2022-12-01","arxiv_id":"2212.00192","repositories_listed":0,"syntology":null},{"url":null,"slug":"explicit-knowledge-transfer-for-weakly","title":"Explicit Knowledge Transfer for Weakly-Supervised Code Generation","date":"2022-11-30","arxiv_id":"2211.16740","repositories_listed":0,"syntology":null},{"url":null,"slug":"disentangled-generation-with-information","title":"Disentangled Generation with Information Bottleneck for Few-Shot Learning","date":"2022-11-29","arxiv_id":"2211.16185","repositories_listed":0,"syntology":null},{"url":null,"slug":"few-shot-query-focused-summarization-with","title":"Few-shot Query-Focused Summarization with Prefix-Merging","date":"2022-11-29","arxiv_id":"2211.16164","repositories_listed":0,"syntology":null}],"record_sha256":"587c16ff51a6ca1a7fb7e48f9ec2e66dd84602e355ee150152de2dcf76d400a8","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}