From matching to generation: A survey on generative information retrieval
Information Retrieval (IR) systems are crucial tools for users to access information, widely
applied in scenarios like search engines, question answering, and recommendation …
applied in scenarios like search engines, question answering, and recommendation …
Generative retrieval as multi-vector dense retrieval
For a given query generative retrieval generates identifiers of relevant documents in an end-
to-end manner using a sequence-to-sequence architecture. The relation between …
to-end manner using a sequence-to-sequence architecture. The relation between …
Focused large language models are stable many-shot learners
In-Context Learning (ICL) enables large language models (LLMs) to achieve rapid task
adaptation by learning from demonstrations. With the increase in available context length of …
adaptation by learning from demonstrations. With the increase in available context length of …
Generative retrieval with preference optimization for e-commerce search
Generative retrieval introduces a groundbreaking paradigm to document retrieval by directly
generating the identifier of a pertinent document in response to a specific query. This …
generating the identifier of a pertinent document in response to a specific query. This …
Poor-supervised evaluation for superllm via mutual consistency
The guidance from capability evaluations has greatly propelled the progress of both human
society and Artificial Intelligence. However, as LLMs evolve, it becomes challenging to …
society and Artificial Intelligence. However, as LLMs evolve, it becomes challenging to …
Breaking the Hourglass Phenomenon of Residual Quantization: Enhancing the Upper Bound of Generative Retrieval
Generative retrieval (GR) has emerged as a transformative paradigm in search and
recommender systems, leveraging numeric-based identifier representations to enhance …
recommender systems, leveraging numeric-based identifier representations to enhance …