Large language models for information retrieval: A survey
As a primary means of information acquisition, information retrieval (IR) systems, such as
search engines, have integrated themselves into our daily lives. These systems also serve …
search engines, have integrated themselves into our daily lives. These systems also serve …
Towards open-ended visual quality comparison
Comparative settings (eg. pairwise choice, listwise ranking) have been adopted by a wide
range of subjective studies for image quality assessment (IQA), as it inherently standardizes …
range of subjective studies for image quality assessment (IQA), as it inherently standardizes …
A setwise approach for effective and highly efficient zero-shot ranking with large language models
We propose a novel zero-shot document ranking approach based on Large Language
Models (LLMs): the Setwise prompting approach. Our approach complements existing …
Models (LLMs): the Setwise prompting approach. Our approach complements existing …
Longrag: Enhancing retrieval-augmented generation with long-context llms
In traditional RAG framework, the basic retrieval units are normally short. The common
retrievers like DPR normally work with 100-word Wikipedia paragraphs. Such a design …
retrievers like DPR normally work with 100-word Wikipedia paragraphs. Such a design …
Bge m3-embedding: Multi-lingual, multi-functionality, multi-granularity text embeddings through self-knowledge distillation
In this paper, we present a new embedding model, called M3-Embedding, which is
distinguished for its versatility in Multi-Linguality, Multi-Functionality, and Multi-Granularity. It …
distinguished for its versatility in Multi-Linguality, Multi-Functionality, and Multi-Granularity. It …
[PDF][PDF] A comprehensive survey of small language models in the era of large language models: Techniques, enhancements, applications, collaboration with llms, and …
Large language models (LLM) have demonstrated emergent abilities in text generation,
question answering, and reasoning, facilitating various tasks and domains. Despite their …
question answering, and reasoning, facilitating various tasks and domains. Despite their …
Combining Semantic Matching, Word Embeddings, Transformers, and LLMs for Enhanced Document Ranking: Application in Systematic Reviews
The rapid increase in scientific publications has made it challenging to keep up with the
latest advancements. Conducting systematic reviews using traditional methods is both time …
latest advancements. Conducting systematic reviews using traditional methods is both time …
Real-time anomaly detection and reactive planning with large language models
Foundation models, eg, large language models (LLMs), trained on internet-scale data
possess zero-shot generalization capabilities that make them a promising technology …
possess zero-shot generalization capabilities that make them a promising technology …
mgte: Generalized long-context text representation and reranking models for multilingual text retrieval
We present systematic efforts in building long-context multilingual text representation model
(TRM) and reranker from scratch for text retrieval. We first introduce a text encoder (base …
(TRM) and reranker from scratch for text retrieval. We first introduce a text encoder (base …
Gender, race, and intersectional bias in resume screening via language model retrieval
Artificial intelligence (AI) hiring tools have revolutionized resume screening, and large
language models (LLMs) have the potential to do the same. However, given the biases …
language models (LLMs) have the potential to do the same. However, given the biases …