Large language models know your contextual search intent: A prompting framework for conversational search
Precisely understanding users' contextual search intent has been an important challenge for
conversational search. As conversational search sessions are much more diverse and long …
conversational search. As conversational search sessions are much more diverse and long …
Towards accurate differential diagnosis with large language models
An accurate differential diagnosis (DDx) is a cornerstone of medical care, often reached
through an iterative process of interpretation that combines clinical history, physical …
through an iterative process of interpretation that combines clinical history, physical …
Query understanding in the age of large language models
Querying, conversing, and controlling search and information-seeking interfaces using
natural language are fast becoming ubiquitous with the rise and adoption of large-language …
natural language are fast becoming ubiquitous with the rise and adoption of large-language …
Generative query reformulation for effective adhoc search
Performing automatic reformulations of a user's query is a popular paradigm used in
information retrieval (IR) for improving effectiveness--as exemplified by the pseudo …
information retrieval (IR) for improving effectiveness--as exemplified by the pseudo …
Generative and pseudo-relevant feedback for sparse, dense and learned sparse retrieval
Pseudo-relevance feedback (PRF) is a classical approach to address lexical mismatch by
enriching the query using first-pass retrieval. Moreover, recent work on generative-relevance …
enriching the query using first-pass retrieval. Moreover, recent work on generative-relevance …
Gar-meets-rag paradigm for zero-shot information retrieval
Given a query and a document corpus, the information retrieval (IR) task is to output a
ranked list of relevant documents. Combining large language models (LLMs) with …
ranked list of relevant documents. Combining large language models (LLMs) with …
Enhancing Interactive Image Retrieval With Query Rewriting Using Large Language Models and Vision Language Models
Image search stands as a pivotal task in multimedia and computer vision, finding
applications across diverse domains, ranging from internet search to medical diagnostics …
applications across diverse domains, ranging from internet search to medical diagnostics …
GRM: generative relevance modeling using relevance-aware sample estimation for document retrieval
Recent studies show that Generative Relevance Feedback (GRF), using text generated by
Large Language Models (LLMs), can enhance the effectiveness of query expansion …
Large Language Models (LLMs), can enhance the effectiveness of query expansion …
USimAgent: Large Language Models for Simulating Search Users
Due to the advantages in the cost-efficiency and reproducibility, user simulation has become
a promising solution to the user-centric evaluation of information retrieval systems …
a promising solution to the user-centric evaluation of information retrieval systems …
Generative Information Retrieval Evaluation
In this chapter, we consider generative information retrieval evaluation from two distinct but
interrelated perspectives. First, large language models (LLMs) themselves are rapidly …
interrelated perspectives. First, large language models (LLMs) themselves are rapidly …