research
∙
08/31/2023
Context Aware Query Rewriting for Text Rankers using LLM
Query rewriting refers to an established family of approaches that are a...
share
research
∙
06/28/2023
Query Understanding in the Age of Large Language Models
Querying, conversing, and controlling search and information-seeking int...
research
∙
06/12/2023
The Effect of Masking Strategies on Knowledge Retention by Language Models
Language models retain a significant amount of world knowledge from thei...
research
∙
11/09/2022
Distribution-Aligned Fine-Tuning for Efficient Neural Retrieval
Dual-encoder-based neural retrieval models achieve appreciable performan...
research
∙
11/04/2022
Explainable Information Retrieval: A Survey
Explainable information retrieval is an emerging research area aiming to...
research
∙
07/07/2022
Supervised Contrastive Learning Approach for Contextual Ranking
Contextual ranking models have delivered impressive performance improvem...
research
∙
06/28/2022
BAGEL: A Benchmark for Assessing Graph Neural Network Explanations
The problem of interpreting the decisions of machine learning is a well-...
research
∙
06/23/2022
BERT Rankers are Brittle: a Study using Adversarial Document Perturbations
Contextual ranking models based on BERT are now well established for a w...
research
∙
05/03/2022
SparCAssist: A Model Risk Assessment Assistant Based on Sparse Generated Counterfactuals
We introduce SparcAssist, a general-purpose risk assessment tool for the...
research
∙
10/12/2021
Fast Forward Indexes for Efficient Document Ranking
Neural approaches, specifically transformer models, for ranking document...
research
∙
06/23/2021
Learnt Sparsification for Interpretable Graph Neural Networks
Graph neural networks (GNNs) have achieved great success on various task...
research
∙
06/23/2021
Learnt Sparsity for Effective and Interpretable Document Ranking
Machine learning models for the ad-hoc retrieval of documents and passag...
research
∙
06/15/2021
Towards Axiomatic Explanations for Neural Ranking Models
Recently, neural networks have been successfully employed to improve upo...
research
∙
06/14/2021
Exploiting Sentence-Level Representations for Passage Ranking
Recently, pre-trained contextual models, such as BERT, have shown to per...
research
∙
05/18/2021
Zorro: Valid, Sparse, and Stable Explanations in Graph Neural Networks
With the ever-increasing popularity and applications of graph neural net...
research
∙
05/10/2021
Towards Benchmarking the Utility of Explanations for Model Debugging
Post-hoc explanation methods are an important class of approaches that h...
research
∙
03/30/2021
An In-depth Analysis of Passage-Level Label Transfer for Contextual Document Ranking
Recently introduced pre-trained contextualized autoregressive models lik...
research
∙
01/18/2021
Dissonance Between Human and Machine Understanding
Complex machine learning models are deployed in several critical domains...
research
∙
01/18/2021
Revisiting the Auction Algorithm for Weighted Bipartite Perfect Matchings
We study the classical weighted perfect matchings problem for bipartite ...
research
∙
01/11/2021
Explain and Predict, and then Predict again
A desirable property of learning systems is to be both effective and int...
research
∙
10/19/2020
BERTnesia: Investigating the capture and forgetting of knowledge in BERT
Probing complex language models has recently revealed several insights i...
research
∙
05/18/2020
Conversational Search – A Report from Dagstuhl Seminar 19461
Dagstuhl Seminar 19461 "Conversational Search" was held on 10-15 Novembe...
research
∙
04/29/2020
Valid Explanations for Learning to Rank Models
Learning-to-rank (LTR) is a class of supervised learning techniques that...
research
∙
04/24/2020
Question Answering over Curated and Open Web Sources
The last few years have seen an explosion of research on the topic of au...
research
∙
04/22/2020
Boilerplate Removal using a Neural Sequence Labeling Model
The extraction of main content from web pages is an important task for n...
research
∙
10/11/2019
Finding Interpretable Concept Spaces in Node Embeddings using Knowledge Bases
In this paper we propose and study the novel problem of explaining node ...
research
∙
07/15/2019
A study on the Interpretability of Neural Retrieval Models using DeepSHAP
A recent trend in IR has been the usage of neural networks to learn retr...
research
∙
06/20/2019
Understanding, Categorizing and Predicting Semantic Image-Text Relations
Two modalities are often used to convey information in a complementary a...
research
∙
03/19/2019
A Comprehensive Comparison of Unsupervised Network Representation Learning Methods
There has been appreciable progress in unsupervised network representati...
research
∙
02/05/2019
TableNet: An Approach for Determining Fine-grained Relations for Wikipedia Tables
Wikipedia tables represent an important resource, where information is o...
research
∙
12/07/2018
Asynchronous Training of Word Embeddings for Large Text Corpora
Word embeddings are a powerful approach for analyzing language and have ...
research
∙
10/25/2018
Expedition: A Time-Aware Exploratory Search System Designed for Scholars
Archives are an important source of study for various scholars. Digitiza...
research
∙
10/24/2018
Designing Search Tasks for Archive Search
Longitudinal corpora like legal, corporate and newspaper archives are of...
research
∙
10/24/2018
Discovering Entities with Just a Little Help from You
Linking entities like people, organizations, books, music groups and the...
research
∙
10/24/2018
History by Diversity: Helping Historians search News Archives
Longitudinal corpora like newspaper archives are of immense value to his...
research
∙
10/22/2018
Node Representation Learning for Directed Graphs
We propose a novel approach for learning node representations in directe...
research
∙
09/13/2018
Interpreting search result rankings through intent modeling
Given the recent interest in arguably accurate yet non-interpretable neu...
research
∙
09/11/2018
EXS: Explainable Search Using Local Model Agnostic Interpretability
Retrieval models in information retrieval are used to rank documents for...
research
∙
07/17/2018
User Fairness in Recommender Systems
Recent works in recommendation systems have focused on diversity in reco...
research
∙
06/29/2018
Posthoc Interpretability of Learning to Rank Models using Secondary Training Data
Predictive models are omnipresent in automated and assisted decision mak...
research
∙
07/23/2017
Fine Grained Citation Span for References in Wikipedia
Verifiability is one of the core editing principles in Wikipedia, editor...
research
∙
03/30/2017
Automated News Suggestions for Populating Wikipedia Entity Pages
Wikipedia entity pages are a valuable source of information for direct c...
research
∙
03/30/2017
Finding News Citations for Wikipedia
An important editing policy in Wikipedia is to provide citations for add...
research
∙
02/03/2017
The Dawn of Today's Popular Domains: A Study of the Archived German Web over 18 Years
The Web has been around and maturing for 25 years. The popular websites ...
research
∙
02/03/2017
ArchiveSpark: Efficient Web Archive Access, Extraction and Derivation
Web archives are a valuable resource for researchers of various discipli...
research
∙
01/14/2017