Preprint2023
Orca 2
Unknown
Orca 2 introduces Cautious Reasoning to train smaller models to select effective solution strategies via task-specific system instructions.
0Nov 1, 2023ReasoningInstruction Tuning
AI Research
AI & ML Research Papers
A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
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9 papersConferenceInfoscience (Ecole Polytechnique Fédérale de Lausanne)2011Featured
Natural Language Processing (almost) from Scratch
Ronan Collobert, Jason Weston, Léon Bottou, et al.
A unified neural network architecture that learns internal representations from unlabelled data achieves state-of-the-art on multiple NLP tasks without task-specific feature engineering.
7.9kMar 2, 2011BenchmarksNeural Networks
arXiv
PreprintJournal of the American Medical Informatics Association2024
Improving large language models for clinical named entity recognition via prompt engineering
Yan Hu, Qingyu Chen, Jingcheng Du, et al.
This paper shows that task-specific prompt engineering, incorporating medical knowledge and few-shot examples, significantly improves GPT-3.5 and GPT-4 performance on clinical NER tasks, though still below BioClinicalBERT.
364Jan 27, 2024Large Language ModelsPrompting
PreprintarXiv.org2024
Jina Embeddings v3
Saba Sturua, Isabelle Mohr, Mohammad Kalim Akram, et al.
Jina Embeddings v3 is a 570M parameter multilingual embedding model supporting 8192-token contexts, task-specific LoRA adapters, and flexible dimension reduction via Matryoshka learning.
175Sep 1, 2024Retrieval Augmented Generation
arXiv
Preprint2019
CTRL
Unknown
A 1.63B parameter language model that uses control codes to explicitly govern style, content, and task-specific behavior during text generation.
0Sep 1, 2019
Preprint2024
Mtlora: Low-rank adaptation approach for efficient multi-task learning
Unknown
MtLoRA introduces task-agnostic and task-specific low-rank adaptation modules for efficient multi-task learning in vision.
0Jan 1, 2024Computer Vision
Preprint2022
Can foundation models wrangle your data?
A. Narayan, Ines Chami, Laurel J. Orr, et al.
Explores whether foundation models can perform data wrangling tasks without task-specific fine-tuning.
0May 1, 2022
arXiv
Preprint2026
Task-specific efficiency analysis: When small language models outperform large language models
Jinghan Cao, Yu Ma, Xinjin Li, et al.
This paper establishes a quantitative foundation showing that small language models can outperform large ones on task-specific efficiency metrics.
0Mar 1, 2026Large Language Models
arXiv
Preprint2023
Large language models in medicine
Unknown
This paper explores the potential and challenges of using large language models in healthcare, highlighting their ability to respond to free-text queries without task-specific training.
0Jan 1, 2023Large Language Models