research
∙
05/23/2023
Dr.ICL: Demonstration-Retrieved In-context Learning
In-context learning (ICL), teaching a large language model (LLM) to perf...
share
research
∙
04/04/2023
Rethinking the Role of Token Retrieval in Multi-Vector Retrieval
Multi-vector retrieval models such as ColBERT [Khattab and Zaharia, 2020...
research
∙
11/02/2022
Multi-Vector Retrieval as Sparse Alignment
Multi-vector retrieval models improve over single-vector dual encoders o...
research
∙
10/17/2022
RARR: Researching and Revising What Language Models Say, Using Language Models
Language models (LMs) now excel at many tasks such as few-shot learning,...
research
∙
09/23/2022
Promptagator: Few-shot Dense Retrieval From 8 Examples
Much recent research on information retrieval has focused on how to tran...
research
∙
05/18/2022
Dialog Inpainting: Turning Documents into Dialogs
Many important questions (e.g. "How to eat healthier?") require conversa...
research
∙
12/15/2021
Large Dual Encoders Are Generalizable Retrievers
It has been shown that dual encoders trained on one domain often fail to...
research
∙
04/15/2021
COIL: Revisit Exact Lexical Match in Information Retrieval with Contextualized Inverted List
Classical information retrieval systems such as BM25 rely on exact lexic...
research
∙
01/21/2021
Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipeline
Pre-trained deep language models (LM) have advanced the state-of-the-art...
research
∙
01/20/2021
PGT: Pseudo Relevance Feedback Using a Graph-Based Transformer
Most research on pseudo relevance feedback (PRF) has been done in vector...
research
∙
11/03/2020
CMT in TREC-COVID Round 2: Mitigating the Generalization Gaps from Web to Special Domain Search
Neural rankers based on deep pretrained language models (LMs) have been ...
research
∙
07/21/2020
Understanding BERT Rankers Under Distillation
Deep language models such as BERT pre-trained on large corpus have given...
research
∙
05/23/2020
Summarizing and Exploring Tabular Data in Conversational Search
Tabular data provide answers to a significant portion of search queries....
research
∙
04/29/2020
Complementing Lexical Retrieval with Semantic Residual Embedding
Information retrieval traditionally has relied on lexical matching signa...
research
∙
04/28/2020
EARL: Speedup Transformer-based Rankers with Pre-computed Representation
Recent innovations in Transformer-based ranking models have advanced the...
research
∙
10/23/2019
Context-Aware Sentence/Passage Term Importance Estimation For First Stage Retrieval
Term frequency is a common method for identifying the importance of a te...
research
∙
05/22/2019
Deeper Text Understanding for IR with Contextual Neural Language Modeling
Neural networks provide new possibilities to automatically learn complex...
research
∙
10/22/2018
Where is this? Video geolocation based on neural network features
In this work we propose a method that geolocates videos within a delimit...
research
∙
09/27/2018
Consistency and Variation in Kernel Neural Ranking Model
This paper studies the consistency of the kernel-based neural ranking mo...
research
∙
06/20/2017