Vector-ICL: In-context Learning with Continuous Vector …
Oct 8, 2024 · This work highlights the potential of continuous representations in enhancing LLMs’ in-context learning capacities, pushing the boundaries of what these models can achieve beyond token …
Vector-ICL: In-context Learning with Continuous Vector …
Jan 22, 2025 · The paper studies the feasibility of vector-ICL, that extends the in-context learning capabilities of LLMs to continuous vectors. Authors use light-weight projectors to align embedding …
Table 1 from Vector-ICL: In-context Learning with Continuous Vector ...
Oct 8, 2024 · Table 1: Overview of the tasks, datasets, encoders, large language models, and prompts used in the experiments. Each task utilizes encoders and LLMs to perform functions across multiple …
Paper page - Vector-ICL: In-context Learning with Continuous Vector ...
Oct 12, 2024 · Large language models (LLMs) have shown remarkable in-context learning (ICL) capabilities on textual data. We explore whether these capabilities can be extended to continuous …
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Lifelong Learning royalty-free images - Shutterstock
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Continual learning for predictive maintenance: Overview and …
Sep 1, 2023 · We then discuss the current challenges of both predictive maintenance and continual learning, proposing future directions at the intersection of both areas. Finally, we propose a novel …
Building Feedback Loops in RAG for Continuous Learning
Mar 25, 2025 · Tools and frameworks for operationalizing continuous learning Why Feedback Loops Matter in RAG Even the most well-trained LLM or vector store can drift in accuracy, miss context, or …
Vector Quantization Prompting for Continual Learning
However, these prompts are continuous, which lack sufficient abstraction for task knowledge representation, making them less effective for continual learning. To address these challenges, we …
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