ICICLE is an in-context indexing method for generative retrieval that uses source-aware docid generation with [COPY] routing and calibration to handle new documents without retraining.
Longqlora: Efficient and effective method to extend context length of large language models
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
citation-role summary
background 1
dataset 1
citation-polarity summary
representative citing papers
InternVL 2.5 is the first open-source MLLM to surpass 70% on the MMMU benchmark via model, data, and test-time scaling, with a 3.7-point gain from chain-of-thought reasoning.
A comprehensive survey of PEFT algorithms for large models, covering their performance, overhead, applications, and real-world system implementations.
citing papers explorer
-
ICICLE: Expanding Retrieval with In-Context Documents
ICICLE is an in-context indexing method for generative retrieval that uses source-aware docid generation with [COPY] routing and calibration to handle new documents without retraining.